The governor of the Bank of England, Andrew Bailey, has warned recent events in US private credit markets have worrying echoes of the sub-prime mortgage crisis that kicked off the global financial crash of 2008.
Appearing before a House of Lords committee, the governor said it was important to have the “drains up” and analyse the collapse of two leveraged US firms, First Brands and Tricolor, in case they are not isolated events but “the canary in the coalmine”.
“Are they telling us something more fundamental about the private finance, private asset, private credit, private equity sector, or are they telling us that in any of these worlds there will be idiosyncratic cases that go wrong?” he asked.
The Bank of England governor, Andrew Bailey. Photograph: Alastair Grant/Reuters
“I think that is still a very open question; it’s an open question in the US.”
He added: “I don’t want to sound too foreboding, but the added reason this question is important is if you go back to before the financial crisis when we were having this debate about sub-prime mortgages in the US, people were telling us, ‘No it’s too small to be systemic, it’s idiosyncratic’… That was the wrong call.”
Bailey said the complex nature of some of the financial engineering in use in the private credit markets gave cause for concern.
“We certainly are beginning to see, for instance what used to be called slicing and dicing and tranching of loan structures going on, and if you were involved before the financial crisis and during it, alarm bells start going off at that point,” he told peers.
“That stuff was a feature of the financial crisis, so that’s another reason why we’ve got to use these cases as another reason to have more drains up, frankly.”
Deputy Bank governor Sarah Breeden, appearing alongside Bailey, said the Bank would be carrying out a war game exercise in these markets, to test the linkages between private credit and other sectors.
She underlined some of the concerns about the private credit sector. “It’s about high leverage, it’s about opacity, it’s about complexity and it’s about weak underwriting standards.
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“Those are things that we were talking about in the abstract as a source of vulnerability in this bit of the financial system, and those appear to have been at play in the context of these two defaults.”
The collapse of car parts firm First Brands and auto lender Tricolor prompted concern on Wall Street, with the JP Morgan chief executive, Jamie Dimon, comparing them to “cockroaches”, and saying that more could emerge.
The International Monetary Fund’s global financial stability review last week highlighted concerns about the close connections between private credit markets and mainstream banks – and the IMF’s managing director, Kristalina Georgieva, said it was the issue that kept her awake at night.
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Nine male patients were enrolled during January 2019 to September 2019. Due to the COVID-19 pandemic, study participation was incomplete. Pre-COVID pandemic onset (March 2020), 80.1% of the expected 171 visits were attended (including baseline visits). Post-COVID pandemic, 19.7% of the 458 scheduled visits were attended. The cognitive assessments DAS-II and VABS-3 were performed at baseline only. All other assessments had follow-up visits completed at varying time points (Supplementary Table 1).
Study population and genetic analysis results
We included eight pediatric males and one adult male from the USA, comprising eight families. The characteristics of the study population are summarized in Table 1. Nonsense mutations occurred in six patients (66%) and three patients (33%) had deletions (Table 2).
Table 1 Characteristics of the study cohort, n = 9
Table 2 Genetic screening results for the nine patients
Patient reported outcome measures
PCQLI
Patient responses
Seven of eight pediatric patients had baseline PCQLI responses (88%, n = 7), of which seven had follow-up responses (100%, n = 7). The baseline mean for the Disease Impact subscale was 25.6 ± 6.0. The mean follow-up time was 26.6 months for both patient and parent responses (see all responses in Supplementary Table 2). At last follow up, four patients (57%, n = 4) reported lower Disease Impact scores. For the Psychosocial Impact Score, the mean at baseline was 28.9 ± 7.5. At last follow-up, three patients (43%, n = 3) reported lower scores. For the Total Score, the mean was 54.5 ± 10.5 at baseline. At last follow-up, four patients (57%, n = 4) reported lower total scores.
Parent responses
For the parents, there were eight baseline responses (100%, n = 8), of which seven had follow-up responses (88%, n = 7). Mean follow-up time was 26.6 months. The baseline mean for Disease Impact was 23.8 ± 6.9, with three parents (43%, n = 3) reporting lower scores for their children at last follow up. Mean Psychosocial Impact score at baseline was 28.9 ± 9.6, with five parents (71%, n = 5) reporting lower scores at last follow-up. Finally, the mean Total Score was 52.8 ± 14.9 at baseline, and four parents (57%, n = 4) reported lower total scores for their children at last follow up. The mean scores can be visualized for children and parents in Fig. 1. Notably, average difference between patient and parent Total Scores were 9.1 ± 7.9 and concordance in longitudinal improvements or worsening of scores over time between patients and parents was 75% (n = 9).
Fig. 1
Average subscale and total scores for the Pediatric Cardiac Quality of Life Inventory (PCQLI) across the cohort. For Disease Impact and Psychosocial Impact subscales, 50 is the maximum score (100 for Total Score). The mean follow-up time is 26.6 months. The error bars are the mean and standard deviations for each subgroup
PQLQ
The average scores for the subscales of the PQLQ can be found in Table 3 (see all responses in Supplementary Table 3). Both patients and their parents responded to this. The max score for all subscales was 100. The mean follow-up time was 28.3 months. Figure 2 shows the scores for physical, emotional, social, and school functioning.
Table 3 Average subscale and total scores for the pediatric quality of life questionnaire
Fig. 2
Average scores for the dimensions of the Pediatric Quality of Life Questionnaire (PQLQ). The inventory is filled out by both patients and parents. The parents score their children as functioning worse than the patients personally score themselves. The composite scores total scores are not shown on this radar plot (Table 3). Error bars are not included here in order to maintain visibility. The mean follow-up time was 28.3 months
Patient responses
Six of eight pediatric patients had baseline responses (75%, n = 6), of which five patients had follow-up responses (83%, n = 5). For the physical health summary score, which is equal to the physical functioning score, the baseline mean was 50.0 ± 6.3; two patients (40%, n = 2) reported lower physical health summary scores at follow-up. For the psychosocial health summary score, the baseline mean was 55.3 ± 24.7; one patient (17%, n = 1) reported a lower psychosocial health summary score for themselves at follow-up. For emotional functioning, baseline mean was 66.7 ± 24.8, and two patients (40%, n = 2) reported worse functioning at follow-up (Fig. 2). For social functioning, baseline mean was 54.2 ± 32.9, and four patients (60%, n = 3) reported worse functioning at follow-up. For school functioning, baseline mean was 45.8 ± 30.1, and four patients (60%, n = 3) reported worse functioning at follow-up. Finally, for the total score, baseline mean was 53.4 ± 17.6, and one patient (20%, n = 1) reported a lower total score at follow-up.
Parent responses
Seven parents had baseline responses (88%, n = 7), of which six had follow-up responses (86%, n = 6) (Table 3). For the physical health summary score, the mean at baseline was 47.1 ± 8.4. At follow-up, all parents (100%, n = 7) reported worse functioning in their child. For the psychosocial health summary score, the baseline mean was 43.7 ± 16.0 and only one parent (17%, n = 1) reported a lower follow-up psychosocial health summary score. For emotional functioning, baseline mean was 52.9 ± 30.4, and four parents (67%, n = 4) reported worse functioning at follow-up. For social functioning, baseline mean was 44.6 ± 13.7, and four parents (67%, n = 4) reported worse functioning at follow-up. For school functioning, baseline mean was 33.6 ± 9.4, and three patients (50%, n = 3) reported worse functioning at follow-up. Finally, for the total score, baseline mean was 44.9 ± 8.6, and four parents (67%, n = 4) reported lower total scores at follow-up. Average difference between patient and parent total scores was 13.4 ± 9.1. Additionally, concordance in longitudinal changes in patient and parent total scores was 58% (n = 5). Parents were more likely to describe physical decline at follow up compared to the patients themselves. Although the remaining emotional, social and school functioning dimensions were more concordant between parents and patients, the total PQLQ parent scores were still lower at follow up compared to patients.
Cognitive and neuropsychological assessment
In our cohort, all patients (100%, n = 9) were affected by neuropsychological symptoms that included: learning difficulties (100%, n = 9), attention-deficit hyperactivity disorder (56%, n = 5), anxiety (44%, n = 4), depression (44%, n = 4), autism (22%, n = 2) and global developmental delay (11%, n = 1).
DAS-II
Six patients in the cohort completed the DAS-II at baseline. Figure 3a shows the average score for our cohort in each of the domains (see the scores for each domain for each patient in Supplementary Table 4). The mean at baseline for each domain in our cohort was: GCA, 67.0 ± 14.7; verbal, 66.3 ± 19.0; nonverbal, 70.5 ± 18.3; spatial, 68.7 ± 18.3.
Fig. 3
(a) Scores for patients for the DAS-II. Population mean and standard deviation for the domains tested are 100 (dashed line) ± 15 (dotted line). Patient 6, 8, 9 did not complete the DAS-II. Most DD patients lie below at least 1 standard deviation on both cognitive tests. (b) Scores for patients for the VABS-3. Population means and standard deviations for the domains tested are 100 (dashed line) ± 15 (dotted line). All patients completed this test at baseline only. The maximum score of the test is 170. Most of the patients scored below at least 1 standard deviation on all domains. DAS-II = Differential Ability Scales Second Edition, VABS-3 = Vineland Adaptive Behavior Scales Third Edition, GCA = General Conceptual Ability, ABC = Adaptive Behavior Composite, DLS = daily living skills
VABS-3
All patients completed the VABS-3 at baseline. The mean at baseline for each domain in our cohort was: ABC, 68.9 ± 11.4; communication, 66.2 ± 18.5; daily living skills 74.0 ± 11.7; socialization, 69.4 ± 10.9 (Fig. 3b; see the scores for each domain for each patient in Supplementary Table 5).
Ophthalmological assessment
DD patients very commonly have visual disturbances. In our cohort, eight patients had one or more ophthalmological changes (89%, n = 8): nyctalopia (11%, n = 1), photophobia (11%, n = 1), blurry vision (33%, n = 3), myopia (78%, n = 7), prescribed corrective lenses (78%, n = 7), and photophobia (89%, n = 8). The BCVA was within the normal range for all patients (100%, n = 9). Of note, hyperreflective foci were identified at the level of the outer nuclear layer (ONL) and the border of the outer plexiform layer in six patients (67%, n = 6) in SD-OCT (example in Fig. 4). These patients also had paler fundus pseudocolor images with what appeared to be a loss of retinal pigmentation. Fundus autofluorescence imaging demonstrated increased macular autofluorescence.
Fig. 4
Spectral Domain Optical Coherence Tomography (SD-OCT) of the left eye of patient 5 showing hyper-reflective foci on the border of the outer nuclear layer (ONL) foci and outer plexiform layer (OPL) (red circle and red arrows)
Cardiopulmonary assessment
Most patients in the cohort reported cardiac related symptoms (78%, n = 7): dyspnea (33%, n = 3), palpitations (44%, n = 4), and chest pain (56%, n = 5). All nine patients had baseline echocardiograms (100%, n = 9) and seven patients had follow-up echocardiograms (78%, n = 7). Regarding outcomes, one patient underwent transplantation during the study period at age 14. There were no deaths or ventricular assist device implantations. Two pediatric patients had baseline data only; one patient underwent cardiac transplantation and another patient stopped following up due to the COVID pandemic. Due to standardized z-score reporting in pediatric patients, we separated the pediatric patients (n = 8) from the adult patient (n = 1). The mean follow-up time was 24.5 months for the pediatric patients. Mean EF at baseline was 68.9 ± 4.8%. After the mean follow-up time, all six pediatric patients with follow-ups had lower EF values (100%, n = 6). The mean EF at last follow-up was 64.3 ± 8.5%, with an average paired difference of -5.9% which based on the Wilcoxon signed-rank test, was not statistically significant. The adult patient had a baseline EF of 47% and at last follow-up 41%.
For wall thickness, we utilized a maximum wall thickness (MWT) that measured the largest of the septal or posterior wall. The average MWT at baseline for the pediatric patients was 13.6 ± 7.1 mm (z-score = 6.9 ± 6.2; 75% [n = 6] of pediatric patients had a z-score > 2 at baseline). At last follow-up, wall thickness increased in all six pediatric patients (100%, n = 6). The mean MWT at last follow-up was 15.6 ± 6.8 mm (z-score = 9.4 ± 7.6), with an average paired difference of 3.8 mm, which based on the Wilcoxon signed-rank test, was not statistically signfiicant. For the young adult, his MWT was 30.4 mm at baseline and 28.2 mm at last follow-up after six months.
Mean LVEDD at baseline for the pediatric patients was 37.8 ± 5.7 mm (z-score = -1.6 ± 1.8). At last follow-up, four patients had a smaller LVEDD (67%, n = 4). Both patients with increased LVEDD, dilated in isolation of ventricular wall thinning, but did experience a drop in LVEF. The mean at last follow-up for the pediatric patients was 36.5 ± 6.7 mm (z-score = -2.1 ± 1.5), with an average paired difference of -0.5 mm. For the young adult, who had LV wall thinning and a drop in his LVEF during follow up, his LVEDD was 43.1 mm at baseline and 46.2 mm at last follow-up after six months.
Mean LV mass at baseline for the pediatric patients was 192.7 ± 133.1 g (z-score = 7.5 ± 6.6). Of the pediatric patients in the cohort (n = 8), 75% (n = 6) had a z-score >2 at baseline. At follow-up (n = 6), six patients had increased LV mass (100%, n = 6). Mean LV mass at last follow-up was 200.7 ± 88.9 g (z-score = 10.9 ± 12.0), with an average paired difference of + 66.2 g, which based on the Wilcoxon signed-rank test, was not statistically significant. For the young adult, he had an LV mass of 835.1 g at baseline and 789.1 g at follow-up after six months. Mean GLS at baseline for the pediatric patients was − 14.1% ± 2.9% which is lower than the − 20% measured in children without any cardiomyopathy [20]. Four pediatric patients (50%, n = 4) had follow-up GLS values, of which two had a GLS that was less negative (50%, n = 2). Mean GLS at last follow-up was − 14.7% ± 5.1%, with an average paired difference of + 0.14%. For the adult patient, the GLS at baseline was − 5.8% and at last follow-up was − 3.0%. Of note, this patient’s LVEF was already less than 50% base baseline. All echocardiogram data can be seen in Table 4; Fig. 5, and Supplementary Fig. 1.
Table 4 Summary table for cardiac measurements at baseline and at last follow-up, with a mean follow-up time of 24.5 months
Fig. 5
Echocardiogram findings for the pediatric patients in the cohort at their baseline and last follow-up visits. (a) LVEF plotted against age in our cohort. There is a downward trend (blue line) as age increases. (b) MWT z-scores plotted against age in our cohort. DD hearts thicken over time, as in this cohort. (c) LVEDD z-scores plotted against age. There is a downward trend in this age range. (d) LV mass z-scores plotted against age in our cohort. Despite the hearts having more mass, the scores remain relatively stable over time. The mean follow-up time for echocardiogram assessment was 24.5 months. MWT = maximum wall thickness, LVEDD = left ventricular end-diastolic dimension
Electrocardiogram findings
DD causes dysfunctional macroautophagy that results in accumulation of intracellular vacuoles, a mismatch between supply and demand of energy within cells and eventual cell death. The cardiac hypertrophy and fibrosis that occur result in significant electrophysiologic abnormalities including high voltage with repolarization abnormalities, conduction disorders, accessory pathways, and atrial and ventricular arrhythmias. Therefore, electrocardiogram (ECG) findings at baseline were also assessed in all nine patients. Baseline ECG findings included: Wolff-Parkinson-White (WPW) (56%, n = 5), LV hypertrophy (44%, n = 4), biventricular hypertrophy (22%, n = 1), sinus bradycardia (11%, n = 1), and 1st degree atrioventricular (AV) block (11%, n = 1).
Pulmonary function testing
Most of our patients (89%, n = 8) had respiratory related problems: wheezing (44%, n = 4), dyspnea (33%, n = 3), cough (22%, n = 2), asthma allergies (11%, n = 1), and sleep apnea (11%, n = 1). In our cohort, seven patients underwent PFTs at baseline (78%, n = 7) and five patients completed a follow-up visit (71%, n = 5). At baseline, the average percent of predicted seated upright FVC was 74.6% ± 8.5% (2.3 ± 1.3 L) (Table 5). After a mean follow-up time of 5.8 months, one patient had a lower upright FVC (20%, n = 1), one had no change (20%, n = 1), and three had an increase (60%, n = 3). The mean percent of predicted upright FVC at last follow-up was 74.0% ± 9.6% (2.4 ± 1.6 L).
Table 5 Pulmonary function testing results for the cohort
Mean percent of predicted supine FVC at baseline was 60.7% ± 12.6% (1.8 ± 1.2 L). After the mean follow-up time, from the five patients who completed a follow-up visit, one patient had a lower FVC (20%, n = 1), one had no change (20%, n = 1), and the rest had an increase (60%, n = 3). Last follow-up percent of predicted supine FVC was 64.4% ± 14.0% (2.0 ± 1.3 L).
The mean percent of predicted FEV1 was 53.6% ± 16.6% (1.6 ± 1.0 L). At follow-up, two patients had a lower percent of predicted FEV1 (40%, n = 2). The mean percent of predicted FEV1 at follow-up was 61.6% ± 16.8% (1.8 ± 1.3 L).
For the FEV1/FVC ratio, the mean percent of predicted was 103.4% ± 1.6% (0.89 ± 0.09). At follow-up, one patient had a lower percent of predicted FEV1/FVC (20%, n = 1), one had no change (20%, n = 1), and three had an increased (60%, n = 3). The mean at follow-up was 108.2% ± 7.7% (0.92 ± 0.05 L).
CPET
In this study, CPET was performed at baseline and at one follow-up visit, with a mean follow-up time of 5.2 months. Five patients performed CPET in our cohort (56%, n = 5) at baseline and at one follow-up, for a total of 10 visits. Our cohort had a baseline mean VO2 max of 17.2 ± 4.4 ml/kg/min (percent of predicted of 39.0 ± 9.0%) (Table 6; Fig. 6a, Supplementary Table 6). After a mean follow-up time of 5.2 months, three patients had a lower VO2 max (60%, n = 3). At last follow-up, the mean VO2 max was 17.6 ± 5.6 ml/kg/min (percent of predicted of 42.6 ± 13.0%). Out of the 10 total visits, six assessments reached an RQ of ≥ 1.0 (60%, n = 6). The baseline mean for ventilatory efficiency (VE/VCO2 slope) was 28.4 ± 2.5 (Table 6; Fig. 6b, Supplementary Table 6). After the mean follow-up time, two patients had a smaller VE/VCO2 slope (40%, n = 2). At last follow-up, the mean VE/VCO2 slope was 29.5 ± 3.2.
Table 6 Summary of CPET parameters and results of the 6MWT
Fig. 6
(a) VO2 max by age. There is a small positive correlation with age (blue line), likely due to lung maturity during puberty. (b) VE/VCO2 slope values plotted over time in the cohort. They remain stable over the 6 months. The mean follow-up time was 5.2 months
Neuromuscular assessment
Seven patients (78%) in our cohort reported neuromuscular symptoms at baseline: delay in motor milestones (67%, n = 6), difficulty running (67%, n = 6), difficulty walking (67%, n = 6), fatigue (67%, n = 6), weakness (67%, n = 6), joint pain (33%, n = 3), difficulty sitting (11%, n = 1), hypotonia (11%, n = 1), loss of range of motion (11%, n = 1), and abnormal gait (11%, n = 1). All limbs were found to be affected across the cohort: lower proximal limb (78%, n = 7), lower distal limb (67%, n = 6), upper proximal limb (56%, n = 5), upper distal limb (44%, n = 4).
For the 6MWT, all patients had baseline testing (100%, n = 9), but only seven patients had follow-up testing (78%, n = 7). At baseline, our cohort averaged 448.7 ± 64.7 m (Table 6; Fig. 7, Supplementary Table 7). After a mean follow-up time of 23.3 months, four patients walked shorter distances (57%, n = 4). The mean distance at last follow-up was 405.9 ± 136.1 m, with an average paired difference of -25.9 m.
Fig. 7
Longitudinal data for the 6-minute walk test (6MWT) at baseline and at follow-up for each patient in the cohort. The data is distance walked (meters) by age. Patients 6 and 7 only had baseline data. The mean follow-up time was 23.3 months
The results for the NSAA, 10MWT, time to rise from floor, and 4SC tests are shown in Fig. 8. For the NSAA, all patients completed the test at baseline (100%, n = 9). Seven patients completed follow-up visits (78%, n = 7), with a mean follow-up time of 23.1 months. The average NSAA total score at baseline was 28 ± 9 out of a max total of 34. After the follow-up time, one patient had a worse NSAA total score (14%, n = 1) and two patients had better scores (29%, n = 2) (Supplementary Table 8, Supplementary Fig. 4a). Out of the seven patients who had follow-up data, four (57%, n = 4) had no changes over 6-, 12-, 24-, and 36-month follow-ups. One of our patients, Patient 3, had markedly worse NSAA total score and 10MWT and 4SC times. Notably this patient had difficulty following instructions, which may have impacted these scores (Supplementary Fig. 4).
Fig. 8
(a) Baseline and last follow-up NSAA scores for the patients in the cohort. The maximum score is 34 (dashed line). The NSAA trended up with age (blue line). (b) Baseline and last follow-up speed during the 10MWT for our cohort. There is a positive correlation with age. (c) Baseline and last follow-up speed during the 4SC in our cohort. There is a positive correlation with age. The mean follow-up time for all these tests is 23.1 months. NSAA = North Star Ambulatory Assessment, 10MWT = 10-meter walk test, 4SC = 4-stair climb test
For the 10MWT, all nine patients (100%, n = 9) completed the test at baseline, but only seven (78%, n = 7) patients had follow-up testing done. The mean follow-up time was 19.4 months. In our cohort, ages 6–20, the baseline average speed was at 2.4 ± 0.6 m/s. At the end of study, two patients were slower (29%, n = 2). The average speed at follow-up was 2.2 ± 1.0 m/s.
For the time to rise from floor test, nine patients completed the test at baseline (100%, n = 9) and seven patients completed follow-up testing (78%, n = 7). The mean follow-up time was 23.3 months. The average time taken at baseline was 5.9 ± 4.1 s. At the end of the study, three patients took longer to rise from the floor (43%, n = 3). The mean time at last follow-up was 8.9 ± 11.8 s.
For the 4SC, we had nine patients complete the test at baseline (100%, n = 9), and seven patients with follow-up visits (78%, n = 7). The average speed at baseline was 1.1 ± 0.4 stairs/sec. After the mean follow-up time of 19.4 months, two patients were slower (29%, n = 2) (Fig. 8d).
Laboratory parameters
All patients completed the baseline laboratory measurements and follow-up with a mean follow-up time of 18.6 months. Of note, cardiac biomarkers including N-terminal pro brain natriuretic peptide (NT-proBNP) and high sensitivity cardiac troponin T (hs-cTnT) were elevated at both baseline and follow-up. Similarly, skeletal biomarkers including CPK and aldolase were similarly elevated at baseline and follow-up, as were AST, ALT and LDH (Table 7). Figure 9 shows the values for NT-proBNP and hs-cTnT for all patients at baseline and follow-up only, where mean paired difference was 971.3 pg/mL and 37.3 respectively, which based on Wilcoxon signed-rank test was a significant increase in NT-proBNP, but not hs-cTnT; Supplementary Fig. 5 shows the values at all visits.
Table 7 Lab values for the cohort, summarized at baseline and at last follow-up
Fig. 9
(a) Baseline and last follow-up NT-proBNP values for each patient. (b) Baseline and last follow-up hs-cTnT values for each patient. The mean follow-up time for all these tests is 18.7 months. NT-proBNP = N-terminal pro brain natriuretic peptide, hs-cTnT = high sensitivity cardiac troponin T
Establishment of T2DM rats fracture model and rats treatments
The work has been reported in line with the ARRIVE guidelines 2.0.
After adapting to feeding for three days, the Sprague Dawley (SD) rats were weighed and classified by cage (3 rats/cage), and 60 male SD rats of 3 weeks old were randomly distributed into 2 groups. Many studies have shown the procedures of establishing high-fat fed (HFD) and streptozotocin (STZ)-induced diabetic rat model which are a model of T2DM. According to the procedures of induction of the T2DM rat model in the existing study, after 3 weeks of feeding HFD (containing 60% fat), rats in the T2DM group were injected with STZ (40 mg/kg in citrate buffer). The control group fed with a normal pelleted diet received an equal volume of citrate buffer [21, 22].
The blood glucose (BG) levels were evaluated consecutively, and blood samples were collected from the tail vein. According to the procedures, rats with randomly blood glucose (RBG) samples > 16.7 mmol/L more than three times were identified to have T2DM after 7 weeks. During diabetes induction, animals were given free access to their original diets (received the high-fat or control diet and water ad libitum) for 12 weeks.
To assess the T2DM model, we measured the metabolic index, including body weight, food intake, water consumption and volume of excreted urine at several time points, including before being fed the HFD and 12 weeks after STZ injection. In addition, RBG was observed at several special time points, which included before fed HFD, before STZ injection, one week after STZ injection, 6 weeks after STZ injection and 12 weeks after STZ injection. At the end of the observation, IPGTT and ITT were evaluated. In detail, to execute IPGTT, animals were fasted for 12 h and injected with 1.5 g/kg glucose. BG was measured at 0, 30, 60 and 120 min after glucose injection. While ITT was carried out by injecting the rats with 0.75 IU/kg insulin, and then BG was obtained at 0, 30, 60 and 120 min after insulin administration. Animals with an RBG below 10 mmol/L at any time points were regarded as nondiabetic, and those with an RBG between 10 and 16.7 mmol/L were excluded. At 12 weeks after STZ injection, rats remaining in the T2DM group were evaluated as diabetic rats in a model of T2DM [23, 24].
After 15 weeks of treatment, all the successfully induced T2DM rats received general anesthesia with pentobarbital sodium intraperitoneal injection before surgery. A lateral incision was made along the proximal femur, followed by longitudinal dissection of the skin, subcutaneous tissue, and muscle along the femoral axis. The surrounding soft tissues were gently separated to expose the femur. A transverse osteotomy of the mid-diaphysis of the femur was performed by an oscillating mini-saw to establish a transverse femur shaft fracture model. The knee was bent 90 degrees, the lateral patellar incision was made, and the Kirschner needle was inserted femur intramedullary through the femoral intercondylar groove. The tip of the Kirschner needle was inserted through the top of the femoral greater trochanter to stabilize the fracture. Finally, all the incisions were closed using a 4-0 nylon suture. All the rats were kept in individual cages. Unprotected weight bearing was allowed immediately after the operation. After surgery, all the animals were given food and water ad libitum. At the end of the experiments, a sodium pentobarbital solution was administered intraperitoneally at a dose of 200 mg/kg. Following administration, animals were carefully monitored until the complete cessation of respiration and heartbeat, and a secondary physical method was applied when necessary to confirm death. All procedures were performed by personnel trained in rodent euthanasia.
Based on X-ray examinations, the fracture sites in the rats were located and marked on their skin. Then, 600 µL of ADSC-exosomes induced by mechanical stretch at a concentration of 200 µg/mL, as well as an equal volume of PBS, were locally injected into the fracture site every three days after surgery, with 200 µL administered each time. Finally, X-ray examination, micro-CT examination, histochemistry analysis, and Western blot analysis of the fractured femurs were performed 28 days after the operation.
Cells obtaining and culture
To obtain ADSCs, the subcutaneous fat in the groin of 3 weeks old male rats was cut into pieces as small as possible and centrifuged at 1500 rpm for 10 min to extract the sediment and glue enzyme was added in to digest at 37 °C for 40 min, then added the medium to terminate the reaction, and the mixture was filtered with a 70 μm filter. After centrifugating at 1500 rpm for 8 min, the cells were suspended in the medium and cultured in vitro for about 8 days. ADSCs (CD44+ CD90+ CD34-CD45-) were collected and certified by flow cytometry and the activity of ADSCs was determined by Calcein Acetoxymethyl Ester (Calcein AM) (Beyotime Biotechnology, Shanghai, China) staining assay.
Bone marrow cells were extracted from the femur and tibia of 3-week-old male rats, then isolated and cultured for 3 generations. BMSCs (CD44+ , CD34-) were identified by flow cytometry, and the cellular bioactivity of BMSCs was determined by Calcein AM staining assay.
The HUVECs (PUMC-HUVEC-T1; Cat NO: CL-0675) used in our experiments were originally purchased from a commercial vendor (Wuhan Pricella Biotechnology Co., Ltd.). To mimic the true condition and environment of Type 2 Diabetes Mellitus. All cells used in cellular function experiments were cultured with a complete culture medium consisting of high-concentration glucose (30 mM).
Tensile strain treatments of cells
Cell’s mechanical stimulation device has become a well-established method to apply mechanical strain to cultured cells; numerous similar devices for cell stimulation have been developed. In this study, external tensile strain was applied to ADSCs using a cell tension culture system. The special elastic membrane or well of the cell tension culture system was precoated with Matrigel (Corning, Bedford, MA, USA), incubated overnight, and kept moist with PBS for later use. ADSCs were cultured on the coated membrane or well. Cyclic tensile strain was applied using a uniaxial elongation model either 24 h post-seeding or upon reaching 90–100% confluence to simulate mechanical stimulation. In the selected uniaxial elongation model, cyclic sinusoidal tensile strain at a fixed frequency was applied to the cells according to a predefined protocol. All the ADSCs were divided into 3 groups, in which ADSCs were given of 1.0 Hz 6% (lower magnitude mechanical stretch ADSCs, LMS), 1.0 Hz 18% (higher magnitude mechanical stretch ADSCs, HMS) tensile strain, 2 h per day separately, and a total of 3 days. In the non-stress group (non-mechanical stretch ADSCs, NMS), 0% tensile strain was applied to ADSCs for 3 days in succession [25,26,27].
Isolation and identification of ADSC exosomes
After exposure to the corresponding tensile strain, ADSCs were washed three times with PBS and then cultured in exosome-free, FBS-free basal medium for an additional 24 h. Exosomes were isolated using the technique of differential centrifugation. In detail, the supernatant was collected and centrifuged at 1000×g at 4 °C for 10 min, 2000×g at 4 °C for 10 min, then centrifuged at 10000×g at 4 °C for 30 min, and centrifuged at 140000×g at 4 °C for 90 min in turn using a Beckman Coulter ultracentrifuge (Beckman Coulter, USA). Discard supernatant PBS washing sample, 140000×g centrifuge for 90 min at 4 °C. The precipitated exosomes were collected and re-suspended in 0.5 mL PBS and conserved at − 80 °C [28]. Then the volume of exosomes was concentrated to 200 μL. The morphology of exosomes was observed by transmission electron microscope (TEM; HITACHI, HT7700, JAPAN) and the diameter distribution was analyzed by Nanoparticles Tracking Analysis (NTA; ZetaView, Particle Metrix, Meerbusch, Germany). Western blot analysis identified its specific biomarkers (CD9, CD63, TSG101).
Flow cytometry (FCM) assay
ADSCs were analyzed by flow cytometry. ADSCs were detected with specific biomarker antibodies CD44 (Affinity), CD90 (Abcam), CD34, and CD45 (Abcam). BMSCs were certified by specific biomarkers CD44 (Affinity) and CD34 (Abcam). Results were analyzed using Flowjo software (version 10.0; BD Biosciences).
Exosome uptake assay
Based mainly on the manufacturer’s standard procedure, PKH26 was used as a dye to label the exosomes in the exosome uptake assay. In short, exosomes were obtained with differential centrifugation (140,000×g, 20 min, 4 °C) dyed with PKH26 (mixed solution was incubated for 20 min at room temperature). While BMSCs were seeded onto a 35 mm confocal dish at the proper density and labeled with DAPI dye. Then, exosomes labeled with PKH26 were mixed and co-cultured with BMSCs labeled with DAPI for 12 h and finally observed via a confocal laser scanning microscopy (CLSM, Leica Microsystems, Germany).
ALP activity and mineralization assessment of osteogenic differentiation
Following three passages of culture, BMSCs were seeded into 6-well plates (2 × 105 cells per well) that had been pre-coated with a 0.1% gelatin solution. The plates were then incubated for 14 days using a specific osteogenic induction medium (Cyagen Biosciences). To evaluate the effect of ADSCs-Exos on osteogenic differentiation, 200 µL of ADSCs-Exos (LMS-Exos, NMS-Exos, HMS-Exos derived from ADSCs) with a concentration of 200 µg/mL and equal volumes of PBS were added into every well severally with the osteogenic induction medium, and the medium was refreshed every three days. To evaluate the level of osteogenic differentiation, the cells were stained with alizarin red staining (ARS) dye and alkaline phosphatase (ALP) staining, and were collected for Western Blotting analysis on day 14. In detail, BMSCs were osteogenic induced for 14 days with different treatments, then cells were washed two times via PBS, then fixed with 4% paraformaldehyde for 30 min at room temperature prepare for ALP and ARS staining. A BCIP/NBT ALP kit (Beyotime, China) was used for ALP staining. After the stained cells were washed using PBS three times, the BCIP/NBT substrate was utilized to stain osteogenic-induced BMSCs. The results were observed and imaged via optical microscopy and then calculated and evaluated by the Image J software processing system (NIH, USA), and GraphPad Prism 10.0 (GraphPad Software, CA, USA) was used for the data analysis.
Tube formation assay of ADSC-Exos
HUVECs were cultured in Matrigel (Corning, USA) precoated 24-well plates (1 × 105 cells per well). 200 µL of ADSCs-Exos (LMS-Exos, NMS-Exos, HMS-Exos derived from ADSCs) with a concentration of 200 µg/mL and equal volumes of PBS were added into every well with the medium, respectively. 6 h later, tube formation was observed with a fluorescence microscope. The Image J software processing system (NIH, USA) and GraphPad Prism 10.0 (GraphPad Software, CA, USA) were used for quantification and data analysis.
Scratch test and migration test
HUVECs were cultured in 6-well plates (2 × 105 cells per well). 200 µL of ADSCs-Exos (LMS-Exos, NMS-Exos, HMS-Exos derived from ADSCs) with a concentration of 200 µg/mL and equal volumes of PBS were added into every well with the medium without serum. 24 h later when cultured HUVEC cells reached 100% confluence, a straight scratch was made with a 200 µL pipette in every well. 0 h, scratched wounds were observed with a fluorescence microscope and recorded. 12 h later, Scratch wound healing results were observed with a fluorescence microscope and photos were taken. Before observation, all samples were stained with calcein AM dye (Beyotime Biotechnology, Shanghai, China). The Image J software processing system (NIH, USA) and GraphPad Prism 10.0 (GraphPad Software, CA, USA) were used for quantification and data analysis.
Transwell assay
HUVECs treated with 200 µL of ADSCs-Exos (LMS-Exos, NMS-Exos, HMS-Exos derived from ADSCs) with a concentration of 200 µg/mL and equal volumes of PBS were seeded into 24-well transwell of 8 µm pore diameter cell culture plate (Corning, USA). 12 h later, HUVECs were stained with crystal violet for 20 min, and then observed by an optical microscope. The Image J software processing system (NIH, USA) and GraphPad Prism 10.0 (GraphPad Software, CA, USA) were used for quantification and the data analysis.
Cell alive/dead assays
All cells, including ADSCs, HUVECs, and BMSCs, were stained before use via calcein AM and Propidium iodide (PI) dye (Beyotime Biotechnology, Shanghai, China) to evaluate cell vitality.
Western blot analysis
Western blotting was performed following previously described protocols. First, after the concentrations of protein were measured via BCA (Aspen), the protein was separated into equal amounts via SDS-PAGE (Beyotime, China), transferred into the PVDF membrane (Millipore, Burlington, MA, USA) and then incubated with 5% bovine serum albumin for 1 h at 25 °C. Next, the membranes were incubated overnight with primary antibodies specific for CD9 (Abcam), CD63 (Abcam), TSG101 (Abcam), Runx2 (Abcam), OCN (Santa), and GAPDH (Abcam). HRP-labeled secondary antibody (Abcam, USA) was added, and then, the membrane was visualized using a T5200 Multi Chemiluminescence Detection System (Tanon, China) as recommended of the manufacturer. The membranes were incubated with Immobilon ECL reagent (Thermo Fisher Scientific, Waltham, MA, USA), and the bands were quantified via Image J software (NIH, USA). GAPDH protein level was used as an internal control for MACF1. The Image J software processing system (NIH, USA) and GraphPad Prism 10.0 (GraphPad Software, CA, USA) were used for quantification of protein level and the data analysis. The significance level was set to a 95% confidence interval, and statistical significance was declared as * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 and nsp > 0.05.
Micro-CT analysis
The animals were euthanized 4 weeks postoperatively, the internal fixations were removed and their femurs were fixed in 4% paraformaldehyde for 24 h at 4 °C. Then, tissue specimens were scanned via a micro-CT system (SkyScan1276, Bruker, Belgium) at a resolution of 9.054604 μm with 85 kV and 200 µA. After scanning, 3D structures of femurs were performed (Reconstruction was accomplished by NRecon (version 1.7.4.2)), and the new bone volume/total volume (BV/TV) were calculated to assess bone regeneration in the fracture site to assess the morphology of the reconstructed femurs (3D and 2D analysis were performed using software CT Analyser (version 1.20.3.0)).
qRT‑PCR analysis
Total RNA was isolated from exosomes using TRIZOL Extraction Reagent (G3013, Servicebio). The cDNA was reverse transcribed using RevertAid First Strand cDNA Synthesis Kit (Invitrogen, CA, USA) following the manufacturer’s instructions. And the qRT-PCR for mRNAs was performed on a StepOne™ Real-Time PCR System (Life technologies) using EnTurboSYBR Green PCR SuperMix (EQ001, ELK Biotechnology) or HieffTM qPCR SYBR™ Green Master Mix (No Rox Plus) (11201ES, Shanghai Yeasen BioTechnologies). The relative expression levels of mRNA or miRNA were normalized to those of GAPDH or U6 and evaluated using the 2−ΔΔCT method. The primers used for qRT-PCR are listed in Table 1.
Table 1 The sequences of primers used for PCR studies
Transfection
Following manufacturer’s protocols, miR-877 mimics or inhibitors and their NCs (Generalbiol, HeFei, China) were transfected into BMSCs and HUVECs to evaluate miR-877 function. After 48 h of transfection, the expression level of miR-877 was measured by qRT-PCR.
RNA sequencing and bioinformatics analysis
All the samples were processed as description previously. All the experiment procedures were according manufacture’s protocols and recommendations. Briefly, Total RNA was extracted from exosomes using TRIzol reagent (Invitrogen, CA, USA) according to the manufacturer’s protocol. Purity, concentration and integrity of RNA sample were examined by NanoDrop, Qubit 2.0, Agilent 2100, etc. RNA concentration and purity was measured using NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, DE). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Only RNA with good quality could move on to following procedures. Total RNA from each sample was used to prepare miRNA library using NEB Next Ultra small RNA Sample Library Prep Kit (NEB, Boston, MA, USA) according to the Illumina small RNA sample preparation protocol. Sequencing was then performed on the Illumina novaseq6000 platform (Illumina, San Diego, CA). A total amount of 1.5 μg RNA per sample was used as input material for the RNA sample preparations. Briefly, first of all, ligated the 3′SR Adaptor. Mixed 3′SR Adaptor for Illumina, RNA and Nuclease-Free Water, after mixture system incubation for 2 min at 70 °C in a preheated thermal cycler, the Tube was transfer to ice. Then, add 3′ Ligation Reaction Buffer (2X) and 3′Ligation Enzyme Mix ligate the 3′SR Adaptor. Incubated for 1 h at 25 °C in a thermal cycler. To prevent adaptor-dimer formation, the SR RT Primer hybridizes to the excess of 3′SR Adaptor (that remains free after the 3′ligation reaction) and transforms the single stranded DNA adaptor into a double-stranded DNA molecule. And dsDNAs are not substrates for ligation mediated. The second, ligated the 5′SR Adaptor. Then, reverse transcription synthetic first chain. Last, PCR amplification and Size Selection. PAGE gel was used for electrophoresis fragment screening purposes, rubber cutting recycling as the pieces to get small RNA libraries. At last, PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v4-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq 2500 platform and paired-end reads were generated. Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter, ploy-N and low-quality reads from raw data. And reads were trimmed and cleaned by removing the sequences smaller than 18 nt or longer than 30 nt. Differential expression analysis of two groups was performed using the DESeq R package (1.10.1). DESeq provide statistical routines for determining differential expression in digital miRNA expression data using a model based on the negative binomial distribution. The resulting P values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate. miRNA with an adjusted p < 0.05 found by DESeq were assigned as differentially expressed. Target gene function was annotated based on the following databases:Nr (NCBI non-redundant protein sequences); Nt (NCBI non-redundant nucleotide sequences); Pfam (Protein family); KOG/COG (Clusters of Orthologous Groups of proteins); Swiss-Prot (A manually annotated and reviewed protein sequence database); KO (KEGG Ortholog database); GO (Gene Ontology).
Histological and immunofluorescence analysis
The collected femurs of rats from different groups were fixed in 4% paraformaldehyde solution for 48 h, decalcified with 20% EDTA at 25 °C for 28 days, embedded in paraffin, and sectioned along the longitudinal axis. Sections from the fracture region were stained with hematoxylin and eosin (H&E), safranin O-fast green, Masson, RUNX2, OCN for immunohistochemical analysis. Immunofluorescence staining with α-SMA, CD31, RUNX2, OCN for immunofluorescence analysis. The sections were imaged and observed by a microscope.
Statistical analysis
All the experiments were performed at least three replicates per group. Values were presented as mean ± SD, and were analyzed with GraphPad Prism 10.0 (Graph-Pad Software, CA, USA). Variances between groups were assessed by the two-sided Student’s t-test (for two-group comparisons) or the one-way analysis of variance (ANOVA) with Tukey’s test (for more than two-group comparisons). And statistical significance was declared as* p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001; nsp > 0.05, not significant.
Company to Spotlight Comprehensive Hip & Knee Portfolios and Latest Advancements in Robotics, Including the mBôs™ System Following Recent Acquisition of Monogram Technologies
WARSAW, Ind., Oct. 21, 2025 /PRNewswire/ — Zimmer Biomet Holdings, Inc. (NYSE and SIX: ZBH), a global medical technology leader, today announced that it is highlighting bold innovations across its broad robotics and musculoskeletal portfolio at the 2025 annual meeting of the American Association of Hip and Knee Surgeons (AAHKS).
During the meeting, the company’s booth will prominently feature its broad knee and hip portfolio of customer-centric solutions and infection solutions, along with the latest robotic technologies and data solutions to meet a vast array of surgeon techniques and preferences. Zimmer Biomet will also showcase the surgeon-guided robotic technology recently acquired through the Monogram Technologies Inc. acquisition.
“Orthopedics is at a pivotal moment,” said Ivan Tornos, Chairman, President and Chief Executive Officer of Zimmer Biomet. “As the population ages and expectations rise, patients are demanding more: less disruption, faster recovery and care that fits their lives. Surgeons need solutions that match this urgency, and that’s why we’ve engineered next-generation hip and knee implants and curated an ecosystem of robotics, digital platforms and AI. This isn’t incremental innovation — it’s the most ambitious innovation cycle in our company’s history, positioning Zimmer Biomet to deliver the industry’s most comprehensive and adaptable suite of orthopedic robotics and navigation technologies designed to elevate surgical precision and transform patient outcomes.”
The highlights at the Zimmer Biomet booth (#1206) include:
Digital and Technology Solutions
mBôs™ TKA System: a CT-based, semi-autonomous, total knee arthroplasty (TKA) robotic technology that received U.S. Food and Drug Administration (FDA) 510(k) clearance. A surgeon-guided fully autonomous version of this technology is currently in clinical trials.
ROSA® Knee with OptimiZe™: the newest version of the ROSA® Knee System that customizes and looks to enhance the surgeon’s experience with personalized and intelligent surgical planning, new positioning, tracking and alignment features to improve accuracy1 and reduce user variability,2 pending U.S. FDA 510(k) clearance.
TMINI® Miniature Robotic System: a state-of-the-art miniature, handheld, wireless CT-based robotic system designed to enable accurate and precise implant placement.
ZBEdge® Analytics : a data platform that delivers intra-operative, mobility and outcome insights directly on a smartphone application, enabling surgeons to objectively assess performance and understand the potential impact of clinical decisions on patient recovery.
mymobility® Care Management Platform : a digital care management platform that delivers continuous data and patient-reported feedback to facilitate care, outcomes and satisfaction about patients’ surgical preparation and recovery.
Knee Reconstruction Technologies
Oxford® Cementless Partial Knee : the only FDA-approved mobile cementless partial knee implant in the U.S. that has been shown to be efficient3,4 in the operating room and has been proven to have excellent survivorship5,6 worldwide.
Persona® OsseoTi® Keel Tibia : a cementless tibia for TKA with a 3D printed porous tray that provides stable initial and biological fixation and intra-operative versatility.7
Persona® SoluTion™ PPS® Femur : a knee implant component designed to serve as an alternative metal for patients with certain metal sensitivities like nickel and cobalt-chrome (Co, Cr, Ni) and bone cement that features a porous coating for cementless fixation and leverages a proprietary surface treatment designed to enhance wear performance.8,9
Persona IQ® The Smart Knee® : a first-to-world smart knee implant that captures patient-specific gait and range of motion metrics directly from the knee during patient monitoring to provide post-operative recovery insights10,11 and trends, allowing care teams to monitor and personalize the TKA patient experience.10-12
Hip Reconstruction Technologies
Z1® Femoral Hip System : offers an expansive size range and three distinct neck options designed to address a variety of patient anatomies and reconstructive needs.
OrthoGrid Hip AI® : an AI-powered, fluoroscopy-based technology that provides direct anterior hip surgeons with intuitive and instantaneous intra-operative tools to assist surgeons in achieving the desired surgical outcomes for component positioning.13
HAMMR® Automated Hip Impaction System : designed to address surgeon strain, fatigue and repetitive motion associated with the traditional mallet.
For more information about Zimmer Biomet events at 2025 AAHKS, visit https://www.zimmerbiomet.com/en/aahks2025.html.
About Zimmer Biomet
Zimmer Biomet is a global medical technology leader with a comprehensive portfolio designed to maximize mobility and improve health. We seamlessly transform the patient experience through our innovative products and suite of integrated digital and robotic technologies that leverage data, data analytics and artificial intelligence.
With 90+ years of trusted leadership and proven expertise, Zimmer Biomet is positioned to deliver the highest quality solutions to patients and providers. Our legacy continues to come to life today through our progressive culture of evolution and innovation.
For more information about our product portfolio, our operations in 25+ countries and sales in 100+ countries or about joining our team, visit www.zimmerbiomet.com or follow on LinkedIn at www.linkedin.com/company/zimmerbiomet or X at www.x.com/zimmerbiomet.
Important Safety Information for Oxford Cementless Partial Knee:
The Oxford® Cementless Partial Knee System is indicated for use in unilateral knee procedures with osteoarthritis or avascular necrosis limited to the medial compartment of the knee. It is intended to be implanted without the application of bone cement for patients whose clinical condition would benefit from a shorter surgical time compared to the cemented implant. The Oxford Partial Knee is not indicated for use in the lateral compartment or for patients with ligament deficiency, or for use in simultaneous bilateral surgery or planned staged bilateral procedures. Potential risks include, but are not limited to, loosening, dislocation, fracture, wear and infection, any of which can require additional surgery. For a full list of product indications, contraindications and warnings, please see the associated product Instructions For Use (IFU).
This news release contains forward-looking statements within the meaning of the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. Forward-looking statements include, but are not limited to, statements concerning Zimmer Biomet’s expectations, plans, prospects, and product and service offerings, including new product launches and potential clinical successes. Such statements are based upon the current beliefs and expectations of management and are subject to significant risks, uncertainties and changes in circumstances that could cause actual outcomes and results to differ materially. For a list and description of some of such risks and uncertainties, see Zimmer Biomet’s periodic reports filed with the U.S. Securities and Exchange Commission (SEC). These factors should not be construed as exhaustive and should be read in conjunction with the other cautionary statements that are included in Zimmer Biomet’s filings with the SEC. Forward-looking statements speak only as of the date they are made, and Zimmer Biomet disclaims any intention or obligation to update or revise any forward-looking statements, whether as a result of new information, future events or otherwise. Readers of this news release are cautioned not to rely on these forward-looking statements, since there can be no assurance that these forward-looking statements will prove to be accurate. This cautionary statement is applicable to all forward-looking statements contained in this news release.
Laboratory and animal studies are not necessarily indicative of clinical performance.
THINK Surgical and TMINI are trademarks of THINK Surgical, Inc.
Persona IQ: The objective kinematic data generated by the CSE with CHIRP System are not intended to support clinical decision-making and have not been shown to provide any clinical benefit
References:
1 Data on File. DVaR-DS250106-01 ROSA Knee System v1.5 Validation Report. 2 Data on File. FER-EMS230714-01 Formative Evaluation Report – July Lab 2023. 3 Pandit, H., et al. “Improved fixation in cementless unicompartmental knee replacement: five-year results of a randomized controlled trial.” JBJS 95.15 (2013): 1365-1372. 4 Stempin R, Kaczmarek W, Stempin K, Dutka J. Midterm Results of Cementless and Cemented Unicondylar Knee Arthroplasty with Mobile Meniscal Bearing: A Prospective Cohort Study. Open Orthop J. 2017 Oct 31;11:1173-1178. doi: 10.2174/1874325001711011173. PMID: 29290853; PMCID: PMC5721307. 5 NJR- UK . The National Joint Registry 22st Annual Report 2025 London, 2024 [Available from: https://reports.njrcentre.org.uk/Portals/0/PDFdownloads/NJR%2022nd%20Annual%20Report%202025_Knees.pdf. 6 AOANJRR. Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR). Hip, Knee & Shoulder Arthroplasty: 2023 Annual Report Adelaide, AOA2024 [updated 2024. Available from: https://aoanjrr.sahmri.com/documents/10180/1798900/AOANJRR+2024+Annual+Report.pdf/9d0bfe03-2282-8fc8-a424-b8d9abb82b1f?t=1727666185313. 7 Mueller J.K., et al. Persona OsseoTi Keel Tibia Provides Stable Initial Fixation 4027.2-GLBL-en. November 2022. 8 Improved Abrasion Resistance of Nitrogen-Hardened Titanium Alloy Surfaces. Current Topics in Orthopaedic Technology. Zimmer. Vol. 3, No. 6 (1991). 9 Zimmer ZRR_WA_2537_12. 10 Cushner FD, Yergler J, ElashoffB, Aubin PM, VertaP, Scuderi GR. Staying Ahead of the Curve: The Case for Recovery Curves in Total Knee Arthroplasty. The Journal of Arthroplasty. 2024;doi:10.1016/j.arth.2024.07.039 11 Cushner FD, Sculco PK, Long WJ. The Talking Knee Is a Reality: What Your Knee Can Tell You After Total Knee Arthroplasty. J OrthopaedicExperience and Innovation. 2022;2022 12 Cushner FD, Schiller P, Gross J, Mueller JK, Hunter W. A Total Knee Arthroplasty Prosthesis Capable of Remote Patient Monitoring. OrthopaedicProceedings. 2021/06/01 2021;103-B(SUPP_9):18-18 doi:10.1302/1358-992X.2021.9.018 13 Cardenas JM, Gordon D, Waddell BS, Kitziger KJ, Peters PC Jr, Gladnick BP. Does Artificial Intelligence Outperform Humans Using Fluoroscopic-Assisted Computer Navigation for Total Hip Arthroplasty? Arthroplasty Today. 2024 May 27;27:101410. doi: 10.1016/j.artd.2024.101410. PMID: 38840694; PMCID: PMC11150909.
This study was conducted as a longitudinal cohort study through a retrospective review of medical records at NHO Fukuoka National Hospital. We reviewed 288 patients aged ≥ 20 years who met the American Thoracic Society/Infectious Diseases Society of America (ATS/IDSA) diagnostic criteria for MAC lung disease between April 1, 1996, and December 31, 2021 [6]. Of these, we excluded 42 patients with no available data of chest computed tomography (CT) scans between June 1, 2017, and December 31, 2021, 4 patients whose CT image data were unable to be processed for the present analysis by the software, 2 patients without any follow-up medical records after the date of CT scanning, 1 patient with no information concerning smoking history, and 7 patients without body mass index (BMI) data. Hence, the remaining 232 subjects with MAC lung disease were enrolled in the present study (Fig. 1). When multiple CT scans were available during the 2017–2021 period, the earliest scan was used for analysis. The follow-up period was defined as the time from the CT scan to either July 2023 or a maximum of 5 years.
Fig. 1
Quantitative CT image analysis
CT examinations were performed with a 160-slice multidetector CT scanner (Aquilion Lightning, Canon Medical Systems, Otawara, Japan) with a slice thickness of 5 mm. Quantitative CT image analyses were performed using dedicated software (AZE Virtual Place, Canon Medical Systems, Otawara, Japan) by a radiologic technologist without prior knowledge of the clinical data. For each patient, the lung field areas (LFAs) were evaluated separately in six domains using three axial CT slices in accordance with the Goddard score assessment protocols—the levels of the upper margin of the aortic arch (right and left upper lung field), the carina (right and left middle lung field), and 1–3 cm above the top of the diaphragm (right and left lower lung field) [13]. To identify the extent of cavitary destruction of the lung, the low-attenuation areas (LAAs) were defined as lung areas below − 950 Hounsfield units (HU), as in previous literature [14], and were also semiautomatically estimated using the same images (see Fig. S1 in Additional file 1) [15]. Mean values of LFA and LAA were calculated and used for the present analyses. The LFA/LAA ratio was computed for each of the six lung fields, and the average of these six values was used in the analysis. When dividing the study subjects into three groups based on the tertile distribution of the mean LFA, the cutoff values were as follows: lowest, ≤ 69.54 cm2 (N = 78); middle, 69.55–85.59 cm2 (N = 77); and highest, ≥ 85.60 cm2 (N = 77). For validation analysis between the mean values of LFA and lung volume (LV), a total of 9 subjects were randomly selected in order to assess LV. LV was calculated with the following 3 steps: at first, the lung plus bronchus volume (LBV) was identified by extracting the area less than − 500 HU. Next, the bronchus volume (BV) was measured by extracting the area less than − 920 HU and by ensuring the continuity of connection to other bronchi. Lastly, the LV was calculated by subtracting the BV from the LBV.
Clinical evaluations
For each case, respiratory physicians reviewed the patient’s medical records and assessed the demographic and clinical characteristics: age, gender, height, weight, smoking history, medical history, and results of mycobacterial cultures. BMI (kg/m2) was calculated as weight divided by squared height. Smoking habit was dichotomized as never smokers and smokers, considering that smoking could have affected emphysematous changes of the lung, appearing as low-attenuation areas (< −950 HU). Antibiotic treatment for MAC disease was defined as the prescription of clarithromycin and/or rifampicin and/or ethambutol. MAC species were categorized into three groups: M. avium group, Mycobacterium intracellulare (M. intracellulare) group, and co-infection group (subjects with both M. avium and M. intracellulare detected).
Statistical analysis
R software version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria) was used to perform all statistical analyses. A two-sided P < 0.05 was considered to indicate statistical significance. For baseline characteristics, the heterogeneity in each variable among the levels of mean LFA was evaluated using the analysis of variance (ANOVA), chi-square test, or Kruskal–Wallis test. Pearson’s correlation coefficient was calculated to assess the correlation between the mean values of LFA and those of LV. Kaplan–Meier curves were constructed to show the survival rate over the follow-up period. The unadjusted and multivariable-adjusted hazard ratios (HRs) with their 95% confidence intervals (95% CIs) according to the levels of mean LFA for all-cause mortality were estimated using a Cox proportional hazards model. Adjustments were made for age, gender, BMI, smoking history, MAC treatment, MAC species, co-infection with NTM other than MAC, and mean LAA, which has been reported as a potential prognostic factor in patients with NTM lung disease [16, 17]. Relevant models were used to evaluate the linear trends in the risk of all-cause death across the tertile classification of mean LFA. We evaluated the ability of mean LFA and mean LAA to predict mortality using receiver operating characteristic curves and estimated the area under the curve (AUC) for each. The AUCs were compared using the DeLong method. The robustness of the main results was tested through sensitivity analyses limiting the subjects to M. avium-positive or M. intracellulare-positive cases individually. Since smoking exposure can accelerate emphysematous change and increase the value of LAA in the lung, stratified analysis was performed by smoking status.
Ethical considerations
The study was approved by the NHO Fukuoka National Hospital Institutional Review Board for Clinical Research (#F5-34). For this study, informed consent has been waived by the NHO Fukuoka National Hospital Institutional Review Board due to the anonymity and retrospective nature of the study. This study was conducted according to the principles of the Declaration of Helsinki.
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The data for this study were sourced from the most recent Demographic and Health Survey (DHS) conducted in thirty-six (36) sub-Saharan African countries. The DHS is a nationally representative sample survey that collects data on demographic and health indicators, including measures of reproductive health such as ANC attendance among women of reproductive age (15–49 years). The data for the current study were drawn from DHS surveys conducted between 2007 and 2019 in the thirty-six countries involved in the study. The data were downloaded from the MEASURE DHS website at http://dhsprogram.com/data/available-datasets.cfm on February 1st, 2021. The list of countries by sub-region and the respective survey years and corresponding sample sizes are presented in Appendix 1 as part of the supplementary results.
Study sample and management of missing cases
The sample for this study was based on the last pregnancies completed by women aged 15–49 years within the 2 years preceding the DHS survey and who made at least one ANC visit during this index pregnancy. After pooling the data for the most recent surveys in the thirty-six countries, 377,112 pregnancies were identified within the preceding five years of the survey. Among them, 119,657 pregnancies that were not the most recent were excluded. Approximately 105,321 such pregnancies were completed more than two years before the survey and were excluded from the analysis as shown in Fig. 1.
Fig. 1
Flow diagram showing the inclusion and exclusion criteria for selecting the study sample
A total of 152,134 pregnancies were completed within the last two years, among which 16,373 pregnancies that did not receive any ANC were excluded. The percentage of missing data on related variables for the current study is low (less than 6% on single variable and less than 10% for the whole data set). The analyses were thus limited to cases with complete data employing listwise or case wise deletions. Excluding missing cases from the final sample does not pose a challenge for the analysis because it is generally accepted that if the presence of missing data on related variables are unrelated to any other variable, then the data are missing completely at random, and data missing completely at random with a small amount of missing data (less than 10% as in the case of the current study) still provide reliable and valid results as analysis of all cases with complete data [18, 19]. Thus, the final analysis was based on 123,134 completed pregnancies with valid data on all the variables included in the analysis. A table showing the percentage of missing cases per variable has been presented in the supplementary materials (see Appendix 2 in the supplementary materials).
Variables
Dependent variable
The outcome variable for this study was a time variable measured for each pregnancy (pregnant woman) subject to the risk of ANC initiation. The dependent variable equals the duration before the event of the first ANC attendance. The duration of the dependent variable was measured in months and ranged from 1 to 9 months.
Independent variables
The predictor variables for this study included factors associated with ANC according to the literature and available in the data sets. Previous studies have identified the factors associated with the utilization of ANC services in LMICs to include household wealth quintiles [12, 13, 17, 20,21,22,23,24,25], place of residence [9, 12, 24,25,26], female education [9, 12, 13, 22,23,24,25], desire for pregnancy [8, 12, 13, 23, 25], female occupation [9, 23], age [12, 24,25,26,27], pregnancy rank/parity [9, 23, 25, 26], mass media exposure [12, 23, 25], number of children under five [8, 9], sociocultural norms and practices [20, 25], women’s autonomy [9, 25], marital status [25], and husbands’ education [9]. Additionally, some studies provide evidence that the odds of ANC coverage are lower among women from households belonging to the poor wealth quintile, women who have no formal education or who are less educated [17, 20, 21, 25] and women living in rural areas [12, 20, 25, 26]. There is also empirical evidence showing the link between family/community involvement and utilization of ANC services [5], while others have noted the role of sociocultural factors [21, 25]. For example, in Ghana, women in predominantly Muslim areas appear to be more limited in their ability to participate in reproductive health decision-making [21]. Additionally, other factors, such as exposure to mass media, especially locally driven mass media, have been shown to strongly impact health service utilization [28]. Furthermore, there has been extensive research on barriers to ANC utilization in SSA. A systematic review of outcome measures and determinants of unmet reproductive health needs revealed that economic constraints, long-distance travel to access services and low education are among the key predictors of ANC utilization among women in some West African countries [22]. Again, the results of a systematic review and meta-analysis in Ethiopia showed that improving female education and women’s empowerment could reduce the magnitude of delayed ANC uptake [9]. The results of other studies also indicate that women with wanted pregnancies are more likely to receive antenatal care [8, 13, 23]. The results regarding place of residence show that while some studies [9, 20, 26] have found a strong relationship between ANC uptake and place of residence, others [13] have reported weak or no significant associations. Additionally, while some studies have shown a negative relationship between female age and ANC uptake [26], another study [13] has shown no such association.
The present study investigates variations in the first initiation of ANC over time during pregnancy and examines the influence of associated risk factors at the global SSA, controlling for covariates identified from previous research. Drawing on an adaptation of the Andersen behavioral model (1995), the various factors controlled for in this study were grouped into four categories consisting of environmental factors, predisposing characteristics, enabling factors and need factors, as shown in Fig. 2. The environmental/external factors included place of residence (urban or rural), country (all 36 countries included in the study) and sub-region (eastern, middle, southern or western Africa). Predisposing characteristics include respondent’s age at the birth of the child (in five-year age groups), highest level of education, type of occupation, marital status, mass media exposure (ranking variable from “very low” to “very high”)Footnote 1, and partner’s level of education. The enabling factors considered were household wealth quintile and women’s participation in the household’s decision-making processFootnote 2 (coded as involved in 0 – no decision; 1–1 decision; 2–2 decisions; 3–3 decisions; 4–4 decisions). Need factors included desire for pregnancy (wanted then, wanted later, wanted no more), number of births and ever had a pregnancy terminated. The list of independent variables and their categorization are shown in Table 1.
Table 1 Percentage distribution of study population by selected characteristics
Fig. 2
Conceptual Model Showing Factors Associated with initiation of antenatal care visits among women of reproductive age in sub-Saharan Africa
To ensure the reliability and accuracy of the regression models, a comprehensive multicollinearity test was conducted to assess correlation between all independent variables. Variables found to be highly correlated were systematically excluded. These variables were language, sub-region, and year of interview which were highly correlated with country of residence. However, due to the importance of these variables in the understanding of the context and to assess the variations in the chances of ANC initiation across the various sub-Saharan African regions, an alternative model excluding country was implemented. The alternate model accommodated the categorization of countries by sub-region and controlled for survey year. The results of the alternate model are included as supplementary results (see Appendix 4). These adjustments were made to enhance the clarity and interpretability of the models while addressing multicollinearity concerns.
Analytical strategy
The characteristics of the study sample were described using percentage distributions. All the independent variables, including survey year, were coded as categorical variables. The association between the timing of the first ANC visit and each independent variable was assessed using cross-tabulation with the Pearson chi-square test. Kaplan-Meier survivor curves were generated to examine the extent to which ANC initiation occurred over time according to the selected covariates. The Kaplan-Meier curves were generated to explore temporal trends in ANC initiation and to construct survival curves for participants stratified according to the selected covariates. The log-rank test was used to determine the significance of differences in survival distributions. At the multivariate level, a number of modeling techniques were explored, and model diagnostics and fitness tests were used to determine the best fit model for the data. The first modeling approach that was explored was multilevel modeling considering the nesting of respondents in countries, clusters and households. The intraclass coefficient (ICC) from the null model showed that only 0.6% (ICC = 0.0063) of the variation in ANC initiation was explained by between-cluster differences, indicating that a conventional one-level regression model fits the data better than a multilevel model [29]. After ruling out multilevel modeling, event history analysis was explored given the nature of the dependent variable. Discrete–time logit models were specified to examine the unadjusted and adjusted effects of each covariate on the dependent variable. The discrete-time survival analysis employed does not require an assumption of proportional hazards as piecewise exponentials [30]. In conducting the statistical analysis, the data were weighted to make the findings generalizable to women of reproductive age (15–49 years) within each country, and differences were tested for significance at the 5% level. All the statistical analyses were performed in R [31]. The analyses employed many R packages including survival [32], dplyr [33], knitr [34], haven [35], survey [36], gtools [37], numDervi [38], car [39], vim [40], summarytools [41], discsurv [42], survminer [43], flextable [44], officer [45], jtools [46], and finalfit [47].
Sixty-nine infants (49% female) meeting eligibility criteria were identified and included in the investigation. The majority received treatment after symptom onset (N = 52, 75%) and had two copies of SMN2 (pre-symptomatic N = 17, 100%; symptomatic N = 48, 92%) with others having three copies. All infants were treated with available disease modifying therapies (Risdiplam [Evrysdi®], Nusinersen [Spinraza®],Onasemnogene-abeparvovec [Zolgensma®]), with nearly half having received a combination of treatments (pre-symptomatic N = 10, 59%; symptomatic N = 28, 54%). Interestingly, ten (19%) of the infants who received treatment after symptom onset were identified as having SMA following SMA screening without symptoms triggering a referral and diagnosis. Upon initial neurology evaluation eight of those infants (80%) already exhibited clear symptoms of SMA (ex. Loss of reflexes) which were identified at an average age of 16 days. The other two did not exhibit symptoms at the time of their initial neurology consultation, though developed symptoms before their treatment was administered an average of 7 days later.
Infants treated pre-symptomatically received treatment at a younger age (median = 0.50, IQR 0.44 months), than those treated after symptom onset (2.81, IQR 3.56 months, t = 17.67, p < 0.001, δ = 0.89). Nine infants (13%) were born prematurely, with all but one being born in the late preterm period (median 36 weeks). Other comorbidities included laryngo or tracheomalacia (N = 3, 4%), biliary atresia (N = 1, 1%), craniosynostosis (N = 1, 1%), extralobar sequestration (N = 1, 1%), paraesophageal hernia (N = 1, 1%), and milk protein allergy (N = 1, 1%).
Median age of infants at the time of their last VFSS was 7.92 months (IQR 4.83), with infants who received pre-symptomatic treatment younger at the time of their last exam (6.8 IQR 5.77 months) than those who received treatment after symptoms (8.35, IQR 4.71; t = 2.96, p = 0.04, δ = 0.33). Although the majority (80%, N = 55) of infants underwent swallow studies due to clinical symptoms, 20% (N = 14) underwent the exam without symptoms as part of a routine, high-risk workup. Significantly more infants who received pre-symptomatic treatment underwent a routine, high-risk VFSS (59%, N = 10) than did those who received symptomatic treatment (8%, N = 4, p < 0.001, OR 0.06). Nearly all infants (86%, N = 59) were evaluated while consuming thin liquids, with other consistencies observed including mildly thick (43%, N = 30), moderately thick (22%, N = 15).
At the time of last VFSS, 50% (N = 26) of symptomatic treated infants were receiving noninvasive ventilation or mechanical ventilation via tracheostomy (22/26, 85% strictly nocturnal), while only one of those treated pre-symptomatic required these supports (strictly nocturnal) (χ2 = 9.43, p = 0.002, OR 17.28). CHOP INTEND scores were available for 66% of infants, with a median score of 46 [16] out of 64. Table 1 provides a full listing of infant demographics and clinical characteristics.
Table 1 Sample demographics and characteristics (N = 69)
Table 2 Swallowing Biomechanics by Treatment Group (N = 69)
Bolus Extraction: Though the majority (76%, N = 13) of infants who received pre-symptomatic treatment promptly initiated sucking when presented with the nipple, all but one had to suck > 3 times to express sufficient bolus to swallow. Prompt initiation of sucking tended to be less common in infants treated after symptom onset (40%, N = 21), with 55% (N = 28) of these infants not initiating sucking at all (χ2(1) = 3.59, p = 0.06, OR 0.28).
Table 3 Clinical Characteristics of Pre-Sympomatic Infants with Profound Swallowing Impairments
Airway Protection: Penetration occurred in almost all infants in both pre-symptomatic (95%, N = 16) and symptomatic (90%, N = 47) treatment groups (p = 1). Although aspiration occurred less frequently, it was still commonly observed; occurring more frequently in infants treated after symptom onset (71%, N = 36) than pre-symptomatic (35%. N = 6, χ2(1) = 5.31, p = 0.02, OR 4.4). Interestingly, among those infants who aspirated, 17% (N = 7) were not reported to be exhibiting feeding difficulties, with VFSS’ done as part of high-risk referral (pre-symptomatic 67%, N = 4; symptomatic 8%, N = 3).
Swallow function
Although all pre-symptomatic treated infants were managing secretions without suctioning, and nearly all were consuming full age-appropriate nutrition (N = 15, 88%), similar to biomechanics, some pre-symptomatic treated infants did exhibit profound functional impairments. Clinical deficits among those pre-symptomatic treated infants who required alternative nutrition appeared 11 days following treatment, with the reason for tube provision ranging from swallowing deficits impeding safe oral nutrition to impairments in consuming sufficient oral nutrition to meet caloric requirements. Table 3 provides further specifications pertaining to the clinical conditions of those pre-symptomatic infants who exhibited profound impairments. Significantly more infants treated after symptom onset required suctioning for secretion management (38% vs 0%; fisher’s p = 0.002, OR 0) and were not consuming age-appropriate oral nutrition (50% vs. 12%; χ2 (1) = 17.33, p < 0.001, OR 20.35) than those treated pre-symptomatic. Table 4 provides a full listing of CEDAS scores.
Table 4 Children’s Eating and Drinking Activity Scale (CEDAS)
Our study, which included pediatric patients with Angelman Syndrome (AS), did not demonstrate that the low-glycemic-index diet (LGID) produces clinical improvement in any of the neurodevelopmental domains assessed using the Bayley Scales of Infant and Toddler Development-III.
Although various publications explore the use of the ketogenic diet (KD) in patients with AS, most of these studies focus on its efficacy for epilepsy control. However, there are few studies where the primary objective is to analyze the potential effects of KD on neurocognitive and behavioral development in this population. Previous research has reported that KD has positive cognitive and behavioral effects in pediatric patients with epilepsy, regardless of seizure control or the number of concomitant antiepileptic drugs [11, 15,16,17]. These benefits include improvements in alertness, attention, reciprocal social interaction, mood, sustained attention, receptive vocabulary, and information processing speed. Furthermore, various reviews have reported subjective data from parents describing their children as “more awake” and “more attentive” after starting the diet [17].
In the specific population with AS, Grocott et al. [18] retrospectively reviewed 23 patients treated with LGID and found that most achieved improved seizure control: 22% remained seizure-free, 43% experienced seizures only in specific contexts such as illness or non-convulsive status, and 30% showed a significant reduction in seizure frequency. Additionally, Thibert et al. [13] conducted a prospective study on the efficacy and tolerability of LGID in AS patients, reporting a reduction in seizure frequency in all patients, a reduction greater than 80% in five of them, and generalized improvements in EEG patterns. This study also reported a subjective perception of neurodevelopmental improvement from parents, although only some of these improvements were statistically significant in neuropsychological assessments.
Our results align with these findings. In our study, we observed qualitative improvement in the EEGs of patients treated with LGID compared to the habitual diet group after 24 weeks of intervention (44% improvement in the LGID group versus 25% in the habitual diet group). Moreover, in the LGID group, only 11% of patients experienced clusters of epileptic seizures, compared to 25% in the habitual diet group, which included one case of non-convulsive status epilepticus.
Although no statistically significant cognitive differences were achieved, a trend toward improvement was observed in receptive language, expressive language, and communication domains in the LGID group. Similarly, subjective parental perception reflected a global improvement in neurodevelopment in most cases. This outcome aligns with previous observations and reinforces the hypothesis that LGID may have neurocognitive benefits in patients with AS. In fact, five of the nine patients in the LGID group chose to continue the diet after completing the study, suggesting a positive impact perceived by families.
Sleep plays a fundamental role in the development and maintenance of memory and learning. Improving sleep quality and structure can significantly enhance sustained attention and memory in children. In patients with Angelman Syndrome (AS), it is estimated that approximately 80% experience moderate to severe sleep disturbances. Pelc et al. [26] conducted a clinical review in a small group of AS patients and described specific sleep characteristics, such as reduced total sleep duration, increased sleep-onset latency, altered sleep architecture, frequent nighttime awakenings, and reduced REM phase. Similarly, Spruyt et al. [27] conducted a systematic review and meta-analysis of 14 heterogeneous studies, mostly observational, and concluded that characteristic sleep problems in AS include reduced total sleep time, increased latency, frequent awakenings, and reduced sleep efficiency.
Additionally, Miano et al. [29] evaluated 10 children with AS using polysomnography and compared them with a control group of patients with intellectual disabilities with or without epilepsy. The results showed a significant increase in sleep state transitions, four times more frequent awakenings, and a 50% reduction in time spent in the deepest stage of sleep (NREM). This suggests considerably reduced sleep quality and lower sleep efficiency in AS patients.
Our results are consistent with these observations, as patients in our series showed reduced total sleep time, increased latency, frequent awakenings, and decreased sleep efficiency.
Pasca et al. [30] reviewed the effects of the ketogenic diet (KD) on sleep in neurological conditions such as autism spectrum disorders, epilepsy, and migraines, finding improvements in overall sleep quality, sleep-onset latency, reduction of nighttime awakenings, improved daytime sleepiness, and increased REM sleep. In our study, although a trend toward improvement in sleep quality was observed in the LGID group compared to the habitual diet group, these data were not statistically significant, preventing the assertion that LGID alone improves sleep structure.
It is important to note the limitations of this study. These include the small sample size, inherent to rare diseases such as Angelman syndrome, which limits statistical power. Additionally, the 24-week follow-up may have been insufficient to detect clinically meaningful changes in neurodevelopmental parameters, which often require longer durations to reach statistical significance. Developmental age equivalents were used as the primary outcome measure instead of more sensitive psychometric scores such as the Person Ability Score (PAS). Although this choice aligned with standard practice in 2021, it may have limited the detection of subtle changes in this population. Similarly, the use of standard scores from the VABS-II may have lacked sensitivity to small variations over time, particularly in individuals with profound impairment. As with the Bayley-III, this approach was consistent with prevailing clinical guidelines and research practices in Angelman syndrome; however, more sensitive metrics such as PAS could not be derived due to the unavailability of item-level conversion tools. Finally, some missing data resulted from incomplete caregiver diaries, likely due to the emotional and time burden of caregiving, as well as issues with the use of the Actiwatch by some children, which limits the reliability of the data.
In conclusion, although a trend toward greater evolutionary improvement was observed in the LGID group compared to the habitual diet group, these differences were not statistically significant in the various domains evaluated using the Bayley Scales of Infant and Toddler Development-III and cannot be solely attributed to the low-glycemic-index ketogenic diet. However, global improvements were identified in several variables evaluated at six months in the LGID group, and no serious adverse reactions attributable to the diet were reported.
These preliminary results do not support recommending the low-glycemic-index ketogenic diet as a generalized treatment for cognitive improvement in AS patients. Further studies with larger sample sizes and robust designs are needed to evaluate the potential impact of this intervention in this population.
