Blog

  • Associations between fatigue and cardiovascular–kidney–metabolic s

    Associations between fatigue and cardiovascular–kidney–metabolic s

    1Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 2Department of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 3Sanjiang Street Community Health Service Centre, Jinhua City, Zhejiang, People’s Republic of China

    Correspondence: Liying Chen, Department of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Shangcheng District, Hangzhou, Zhejiang, 310016, People’s Republic of China, Email [email protected]

    Purpose: Fatigue is common in many chronic diseases. The aim of this cross-sectional study was to investigate the association between fatigue and cardiovascular–kidney–metabolic syndrome (CKM) in Chinese asymptomatic individuals undergoing routine health screenings and to explore the mediating role of inflammation.
    Patients and Methods: The data of 4349 individuals were included in this cross-sectional study. Fatigue was measured with the Fatigue Severity Scale (FSS). The association between fatigue and the severity of CKM syndrome was evaluated via logistic regression analysis. The mediating role of inflammation in fatigue and advanced CKM syndrome was explored using mediation analysis.
    Results: A total of 4349 participants were included in this study, and 2120 (48.7%) experienced fatigue. Fatigue was associated with a greater risk of developing advanced CKM syndrome (OR 2.597, 95% CI 1.323– 5.097, p < 0.05). However, there was no significant correlation with the risk of developing early CKM syndrome. Further analyses stratified by age revealed that the association between fatigue and advanced CKM syndrome was more pronounced in those aged < 60 years (OR 3.008, 95% CI 1.263– 7.163, p < 0.05). The white blood cell count and neutrophil count had a mediating effect in the association between fatigue and advanced CKM syndrome, with mediation rates of 7.2% and 6.3%, respectively.
    Conclusion: Fatigue is significantly associated with the increased risk of advanced CKM syndrome, especially in young and middle-aged adults. The cause of this association may be that white blood cell count and neutrophil count play a partial role in this relationship.

    Keywords: cardiovascular–kidney–metabolic syndrome, fatigue, inflammation, mediating effect

    Introduction

    Fatigue is a common chronic disease, manifesting itself as persistent fatigue and weakness accompanied by physical or mental impairment, and it can have a serious negative impact on patients’ quality of life.1,2 Approximately 45% of the United States population reports fatigue.3 The prevalence of fatigue is 30% for men and 33.9% for women over 45 years of age in China.4,5 Among perimenopausal and postmenopausal Chinese women, approximately 75.84% experienced fatigue.6 Fatigue is likely to be overlooked by health care professionals during patient visits if there is a lack of targeted questioning.7 Repeatedly ignoring fatigue tends to undermine the patient’s medical experience and exacerbate misunderstandings about the patient by those around them, thus further contributing to social isolation and depressive symptoms.2 Fatigue is associated with many diseases, including cancer, neurological disorders, psychiatric disorders, and metabolic disorders, and significantly increases the risk for developing negative health outcomes, but the mechanisms by which it occurs remain unclear.8–11 Fatigue significantly increases the risk for developing negative health outcomes. A meta-analysis of clinical trials reported fatigue increased all-cause mortality in patients with chronic kidney disease (CKD).12 A longitudinal study from Jerusalem residents reported that fatigue significantly increased the mortality among elderly people.13 A study from Italy reported that fatigued men and women have an increased risk for disabilities.14

    Obesity, diabetes, CKD and cardiovascular disease (CVD) continue to affect human health worldwide and are receiving increasing attention from researchers. The concept of cardiovascular–kidney–metabolic syndrome (CKM), proposed by the American Heart Association, is a systemic disease in which pathophysiological interactions between obesity, diabetes, chronic kidney disease, and cardiovascular disease lead to multiorgan dysfunction and adverse cardiovascular outcomes.15 As CKM syndrome is a progressive disease, it gradually progresses from excess adipose tissue and dysfunction to a condition with multiple metabolic risk factors and promotes chronic kidney disease, which contributes to an increased risk of clinical cardiovascular disease, renal failure, disability and even death.15 The CKM syndrome is classified into five stages: stage 0, no risk factors; stage 1, excess or dysfunctional adipose tissue; stage 2, metabolic risk factors and CKD; stage 3, subclinical CVD in CKM syndrome; stage 4, clinical CVD in CKM syndrome.15 In the United States, nearly 90% of adults had CKM syndrome and 15% had advanced CKM syndrome.16 Therefore, early detection and lifestyle intervention can help slow or even stop the progression of CKM.

    Inflammation was considered as a potential factor in the development of fatigue.17 A cohort study showed that inflammation may play a role in fatigue.18 And it is a common view that inflammation plays a role in the progression of chronic diseases. The study on the syndrome of cardiometabolic disease reported that excess and dysfunctional adipose tissue exhibited inflammation, and increased the risk of CVD.19 In addition, most previous research concentrated on a single disciplinary perspective and explored obesity, diabetes, CVD, and CKD separately. There has been insufficient co-operation between the different disciplines. And the links between the pathophysiological mechanisms of these diseases have been less well studied. Due to the lack of studies on pathophysiological mechanisms and the concept of CKM syndrome, the relationship between fatigue and CKM syndrome has not been adequately explored in prior studies. Therefore, on the basis of Chinese asymptomatic individuals undergoing routine health screenings at the Health Promotion Centre of Sir Run Run Shaw Hospital, this study assesses the correlation between fatigue and CKM syndrome and the potential mediating role of inflammatory markers between fatigue and advanced CKM syndrome, which may help promote early lifestyle management of CKM patients.

    Materials and Methods

    Study Population

    All subjects in this cross-sectional study completed a systematic health check-up and standardized questionnaires. Data were collected between September 2024 and December 2024 at Sir Run Run Shaw Hospital, Zhejiang University School of Medicine. The inclusion criterion was being over 18 years of age (n=5001). The exclusion criteria were participants who lacked data on past history, smoking history, alcohol consumption, height, weight, waist circumference, and blood pressure (n=416) or those with missing blood metabolism indicators and questionnaire data (n=225). Participants who submitted multiple health questionnaires (n=11) were excluded. A final total of 4349 participants were included in the analysis. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Sir Run Run Shaw Hospital, affiliated with Medical College of Zhejiang University (No. 2025–1033).

    Data Collection

    During the health screening, participants’ sex, age, history of previous illnesses and medications, smoking history, and alcohol consumption history were collected by trained general practitioners through face-to-face interviews. The participants completed an assessment of the Fatigue Severity Scale (FSS) via an online structured questionnaire. Nurses measured systolic blood pressure (SBP), and diastolic blood pressure (DBP), waist circumference (WC) from participants using calibrated standard instruments. Venous blood samples were taken in the morning after an overnight fast. Body mass index (BMI) was calculated by dividing body weight by the square of the elevation. The estimated glomerular filtration (eGFR) rate was calculated according to the race-free CKD-EPI 2021 creatinine formula.20

    Definition of Fatigue

    Fatigue was defined and assessed on the basis of the FSS score. The scale is validated in healthy individuals and patients with multiple medical conditions, including patients with multiple sclerosis, systemic lupus erythematosus, and chronic stroke.21–24 The scale is a 9-item self-report scale to assess the severity of fatigue. Respondents are asked to consider the previous week and rate each statement on a Likert scale from 1 (strongly disagree) to 7 (strongly agree).23 The FSS score was the total score divided by 9, where fatigue was defined as an FSS score ≥4.25 On the basis of the quartiles of the FSS scores, the participants were divided into four groups: Q1 (1.0–3.0), Q2 (3.0–3.9), Q3 (3.9–4.6), and Q4 (4.6–7.0). Q1 was used as the reference group.

    Definition of CKM Syndrome

    CKM syndrome is divided into 5 stages on the basis of the recommendations of the President of the American Heart Association.15 CKM Stage 0 is defined as the absence of excessive/dysfunctional obesity, metabolic risk factors and chronic kidney disease. CKM stage 1 is defined as overweight/obesity (BMI ≥24 kg/m2), abdominal obesity (WC ≥80 cm for women and ≥90 cm for men) or prediabetes (defined as a glycosylated haemoglobin [HbA1C] 5.7–6.4% or a fasting plasma glucose [FPG] between 5.6–6.9 mmol/L, without a self-reported diagnosis of diabetes). CKM stage 2 is defined as metabolic risk factors or intermediate to high risk of CKD (based on eGFR). Metabolic risk factors include hypertriglyceridaemia (triglyceride [TG] ≥1.53mmol/L), hypertension (SBP≥140mmHg or DBP≥90mmHg), type 2 diabetes mellitus (defined as HbA1C ≥6.5%, or FPG ≥7.0 mmol/L, or a past history of diabetes), or metabolic syndrome. CKM stage 3 is defined as combined subclinical cardiovascular disease on the basis of a predicted 10-year CVD risk of ≥20% in the AHA’s Predicting Risk of CVD EVENTs (PREVENT) equation (https://professional.heart.org/en/guidelines-and-statements/prevent-calculator). CKM stage 4 is defined as a combination of clinical cardiovascular disease based on a previous history of cardiovascular disease.

    Metabolic syndrome is defined by the presence of 3 or more of the following: WC ≥80 cm for women and ≥90 cm for men; High-density lipoprotein cholesterol (HDL-C) <1.04 mmol/L for men and <1.30 mmol/L for women; TG ≥1.70 mmol/L; SBP ≥130 mmHg or DBP ≥80 mmHg or use of antihypertensive medications; FPG ≥5.6 mmol/L.15

    In accordance with AHA recommendations, in this study, CKM stages 1 and 2 were combined as early CKM syndrome, and stages 3 or 4 were combined as advanced CKM syndrome.16 Advanced CKM syndrome staging identifies people who have CVD or are at high risk of CVD.16

    Definition of Inflammation

    Fasting venous blood samples were selected to collect systemic immunoinflammatory index (SII), neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR). The SII is the platelet count multiplied by the neutrophil count divided by the lymphocyte count. All indicators of inflammation were converted to natural logarithmically transformed values.

    Assessment of Variables

    Categorical variables consisted of sex, smoking and alcohol consumption, previous history of diabetes, and previous history of hypertension. Age, BMI, WC, SBP, DBP, total cholesterol (TC), TG, FPG, HbA1c, blood urea nitrogen (BUN), creatinine (Cr), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), serum uric acid (SUA), and eGFR were analysed as continuous variables.

    Statistical Analysis

    Analyses were performed using SPSS version 25 software and R version 4.4.2. In this study, quantitative variables are expressed as the means±standard deviations or medians (interquartile ranges). Differences were assessed using an independent samples t test or Mann‒Whitney U-test and ANOVA or K independent samples test. Qualitative variables were expressed as percentages and were assessed using the chi-square test. The normality test was assessed by Kolmogorov–Smirnov test. Correlation analysis between fatigue and CKM syndrome was assessed using logistic regression. Multicollinearity was assessed using the Pearson’s correlation coefficient and the Variance Inflation Factor. The model fit was assessed by the Hosmer–Lemeshow goodness-of-fit Chi-square test. And the result was presented as the odds ratio (OR) and the 95% confidence interval (CI). Model 1 was not adjusted. Model 2 was adjusted for age, sex, smoking status, drinking status, BMI, WC, SBP, and DBP. Further analyses were stratified by age. Excluding participants with cancer history, sensitivity analysis was conducted to test the robustness of the results. Mediation analysis was used by causal steps approach, to assess the impact of inflammatory markers on the development of advanced CKM syndrome in fatigued patients. The level of statistical significance was set at p < 0.05.

    Results

    The baseline characteristics of the included participants are summarized in Table 1. There were 4349 participants, including 2683 (61.7%) men and 1666 (38.3%) women. A total of 2120 (48.7%) patients had fatigue. There were no significant differences between the fatigued and nonfatigued populations in terms of BMI, WC, smoking status, or TC, TG, LDL-c, FPG, HbA1c, or SUA levels. The data indicate that those with fatigue had a lower average age, SBP, DBP, HDL-c, Cr, and BUN and had a higher eGFR (p values less than 0.05). The prevalence of CKM syndrome with respect to fatigue status across different age groups is shown in Table 2. We found a greater prevalence of advanced CKM syndrome among fatigued patients aged <60 years.

    Table 1 The Baseline Characteristics of Included Participants

    Table 2 The Prevalence of CKM Syndrome in Fatigue Statues in Different Age Levels

    The associations between fatigue and CKM syndrome stages are displayed in Table 3. After adjustment for confounders in Model 2, fatigued patients had an increased risk of advanced CKM syndrome compared with patients without fatigue (OR 2.597, 95% CI 1.323–5.097, p=0.006), while there was no significant correlation with the risk of developing early CKM syndrome (OR 0.994, 95% CI 0.831–1.190, p=0.952). The FSS score was positively correlated with the risk of advanced stages (OR 1.405, 95% CI 1.081–1.827, p=0.011), but not with the risk of early CKM syndrome (OR 1.033, 95% CI 0.959–1.112, p=0.390). Compared with patients with FSS scores ≤3.0, patients with FSS scores of 3.9–4.6 had an increased risk of advanced stages (OR 3.328, 95% CI 1.407–7.870, p=0.006). Further analysis stratified by age revealed that the association between fatigue and advanced stages was more significant in those aged <60 years (OR 3.008, 95% CI 1.263–7.163, p=0.013), although the results of the interaction test were not distinct (p for interaction>0.05), as shown in Figures 1 and 2. Sensitivity analyses are displayed in Table 4. After excluding participants with cancer history, the relationship between fatigue and CKM syndrome stages showed similar results.

    Table 3 The Association Between Fatigue and CKM Syndrome Stages

    Table 4 The Association Between Fatigue and CKM Syndrome Stages Excluding Patients with Cancer History

    Figure 1 Adjusted odd ratios for CKM syndrome Stage 1–2 with fatigue by using model 2. The quartiles of FSS scores were calculated respectively (FSS-Q1 1.0–3.0, FSS-Q2 3.0–3.9, FSS-Q3 3.9–4.6, and FSS-Q4 4.6–7.0). Model 2 was adjusted for age, sex, smoking status, drinking status, BMI, WC, SBP, and DBP.

    Figure 2 Adjusted odd ratios for CKM syndrome Stage 3–4 with fatigue by using model 2. The quartiles of FSS scores were calculated respectively (FSS-Q1 1.0–3.0, FSS-Q2 3.0–3.9, FSS-Q3 3.9–4.6, and FSS-Q4 4.6–7.0). Model 2 was adjusted for age, sex, smoking status, drinking status, BMI, WC, SBP, and DBP.

    The mediating effects of inflammatory indicators in fatigue and advanced CKM syndrome is shown in Figure 3. After adjusting for Model 2, white blood cell count and neutrophil count had a mediating effect on the association between fatigue and advanced stages, with mediating proportions of 7.2% and 6.3%, respectively.

    Figure 3 The mediating effects of inflammatory indicators in fatigue and advanced CKM syndrome with adjusting for Model 2.

    Abbreviations: SII, systemic immunoinflammatory index; NLR, neutrophil/lymphocyte ratio; PLR; platelet/lymphocyte ratio.

    Discussion

    This study investigated the correlation between fatigue and CKM syndrome in Chinese asymptomatic individuals undergoing routine health screenings. Fatigue was found to be positively correlated with advanced CKM syndrome but not with early CKM syndrome. FSS scores were positively correlated with advanced stages but not with early CKM syndrome. This correlation was significant in the young and middle-aged populations. In addition, mediation effect analysis further demonstrated that blood cell count and neutrophil count mediated the association between fatigue and advanced stages (7.2% and 6.3%, respectively).

    Few previous studies have focused on the correlation between fatigue and CKM syndrome. Keyu Bian et al reported that fatigue was associated with an increased risk of stroke, coronary artery disease, type 2 diabetes and heart failure.9 Yasuyuki Honda et al reported that fatigue was associated with an increased risk of peripheral arterial disease.26 Studies by Charlotte Winwards et al, Peter Appelros, Eva-Lotta Glader and others revealed a significant positive correlation between fatigue and stroke.27–29 Amber J. Guest et al reported that fatigue is negatively correlated with systolic and diastolic blood pressure.30 L. Parker Gregg et al reported that fatigue in dialysis-dependent kidney disease patients was independently associated with the progression of end-stage renal disease.31 However, there are still no uniform conclusions in studies on the correlation between fatigue and diabetes. Some studies have shown increased levels of fatigue in diabetic patients.32,33 A review revealed that acute hypoglycaemia or chronic hyperglycaemia or fluctuations in blood glucose due to abnormal glucose metabolism in patients with diabetes may affect fatigue symptoms.34 Julie Lasselin et al reported no correlation between fatigue and glycated haemoglobin in diabetic patients.35

    We found that fatigue was positively correlated with advanced CKM syndrome but was not correlated with early CKM syndrome and that this correlation was significant in young and middle-aged individuals. The possible mechanism is the involvement of fatigue in the common pathophysiological effects of advanced stages. Fatigue production is associated with activated immunoinflammatory pathways, elevated levels of oxidative stress and mitochondrial dysfunction.36–38 Fatigue may be involved in sympathetic overactivity, the renin‒angiotensin‒aldosterone system, and oxidative stress in CKM syndrome.39 Early CKM syndrome is associated mainly with metabolic risk factors, including BMI, WC, fasting glucose, glycation, blood pressure, triglycerides and renal disease, and the probable reason for this result is that the present study population consisted mainly of young and middle-aged individuals. In addition, work and economic stress are more common in middle-aged individuals with chronic diseases, which may further contribute to the development of fatigue.40 This prompts the early introduction of targeted lifestyle changes to improve symptoms of fatigue in young and middle-aged people.

    Furthermore, we investigated the mediating role of white blood cell count and neutrophil count in the association of CKM syndrome and fatigue. Inflammation has been suggested as a possible mechanism influencing the development of fatigue, and studies have shown that fatigue is associated with chronic inflammation, which affects the peripheral and central nervous systems.41 In advanced stages, endothelial dysfunction is further exacerbated by increased oxidative stress, increasing the risk of CVD.39 In addition, dysfunction of the autonomic nervous system and dysregulation of the hypothalamic‒pituitary‒adrenal axis also increase the risk of CVD.42 The role of inflammatory mediators is further supported by a study showing that an elevated systemic inflammatory response index was associated with an increased risk of cardiovascular disease mortality, which was evident in people under 60 years of age.43

    As a cross-sectional study, the results of this study preclude causal inferences. We could not explore the causal relationship between fatigue and CKM syndrome. Second, our assessment of fatigue was based on the content of the questionnaire, which may be affected by self-report bias. Furthermore, as a single-dimensional scale, the FSS can not systematically evaluate different dimensions of fatigue, and it cannot capture multiple features of fatigue and its impact on function. Finally, the study population was mainly the health check-up population in Zhejiang Province, China, and may not reflect other populations. The Fatigue Severity Scale should be included in the early screening of CKM syndrome, which may contribute to identifying and mitigating the progression of the disease. In the future prospective cohort study, we can further study the role of inflammatory indicators such as C-reactive protein in fatigue and CKM syndrome in different CKM stages.

    Conclusion

    In the asymptomatic individuals undergoing routine health screenings, people with fatigue are correlated with a greater risk of developing advanced CKM syndrome, especially young and middle-aged people. It is clear that while inflammation appears to play a role, it only partially explains the observed association. In the early screening of CKM syndrome, the implementation of fatigue assessment should be emphasized. Individuals with fatigue should accept interdisciplinary care early and address adverse social determinants of health actively.

    Data Sharing Statement

    The datasets analysed during the current study are not publicly available because the data of this study was retrospective and informed consent could not be obtained, so the exemption of informed consent was applied. In order to respect the study subjects, this research data cannot be shared with others.

    Ethics Approval and Consent to Participate

    The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Sir Run Run Shaw Hospital, affiliated with Medical College of Zhejiang University (No. 2025-1033). Patient consent was waived due to the research using the data obtained in the previous clinical diagnosis and treatment, without using the medical records that the patient has clearly refused to use. The study will not adversely affect the rights and health of the subjects, and the privacy and personal identity of the subjects will be protected.

    Author Contributions

    All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

    Funding

    This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

    Disclosure

    Yunxia Xie and Keqing Shen are co-first authors for this study. The authors report no conflicts of interest in this work.

    References

    1. PROMIS Cooperative Group; Cella D, Yount S, Rothrock N, et al. The Patient-Reported Outcomes Measurement Information System (PROMIS): progress of an NIH roadmap cooperative group during its first two years. Med Care. 2007;45(5 Suppl 1):S3–S11. doi:10.1097/01.mlr.0000258615.42478.55

    2. Jaime-Lara RB, Koons BC, Matura LA, Hodgson NA, Riegel B. A qualitative metasynthesis of the experience of fatigue across five chronic conditions. J Pain Symptom Manage. 2020;59(6):1320–1343. doi:10.1016/j.jpainsymman.2019.12.358

    3. Ricci JA, Chee E, Lorandeau AL, Berger J. Fatigue in the U.S. workforce: prevalence and implications for lost productive work time. J Occup Environ Med. 2007;49(1):1–10. doi:10.1097/01.jom.0000249782.60321.2a

    4. Jing MJ, Wang JJ, Lin WQ, Lei YX, Wang PX. A community-based cross-sectional study of fatigue in middle-aged and elderly women. J Psychosom Res. 2015;79(4):288–294. doi:10.1016/j.jpsychores.2015.05.009

    5. Lin WQ, Jing MJ, Tang J, et al. Factors associated with fatigue among men aged 45 and older: a cross-sectional study. Int J Environ Res Public Health. 2015;12(9):10897–10909. doi:10.3390/ijerph120910897

    6. Ruan X, Cui Y, Du J, Jin F, Mueck AO. Prevalence of climacteric symptoms comparing perimenopausal and postmenopausal Chinese women. J Psychosom Obstet Gynaecol. 2017;38(3):161–169. doi:10.1080/0167482X.2016.1244181

    7. Katz P. Fatigue in rheumatoid arthritis. Curr Rheumatol Rep. 2017;19(5):25. doi:10.1007/s11926-017-0649-5

    8. Matura LA, Malone S, Jaime-Lara R, Riegel B. A systematic review of biological mechanisms of fatigue in chronic illness. Biol Res Nurs. 2018;20(4):410–421. doi:10.1177/1099800418764326

    9. Bian K, Zhang P, Xu G, Sun W. The association between fatigue and cardiometabolic diseases: insights from the UK biobank study. J Affect Disord. 2025;371:261–267. doi:10.1016/j.jad.2024.11.040

    10. Kralik D, Telford K, Price K, Koch T. Women’s experiences of fatigue in chronic illness. J Adv Nurs. 2005;52(4):372–380. doi:10.1111/j.1365-2648.2005.03602.x

    11. Jhamb M, Liang K, Yabes J, et al. Prevalence and correlates of fatigue in chronic kidney disease and end-stage renal disease: are sleep disorders a key to understanding fatigue? Am J Nephrol. 2013;38(6):489–495. doi:10.1159/000356939

    12. Yang XH, Zhang BL, Gu YH, Zhan XL, Guo LL, Jin HM. Association of sleep disorders, chronic pain, and fatigue with survival in patients with chronic kidney disease: a meta-analysis of clinical trials. Sleep Med. 2018;51:59–65. doi:10.1016/j.sleep.2018.06.020

    13. Moreh E, Jacobs JM, Stessman J. Fatigue, function, and mortality in older adults. J Gerontol a Biol Sci Med Sci. 2010;65(8):887–895. doi:10.1093/gerona/glq064

    14. Vestergaard S, Nayfield SG, Patel KV, et al. Fatigue in a representative population of older persons and its association with functional impairment, functional limitation, and disability. J Gerontol a Biol Sci Med Sci. 2009;64(1):76–82. doi:10.1093/gerona/gln017

    15. American Heart Association; Ndumele CE, Rangaswami J, Chow SL, et al. Cardiovascular-kidney-metabolic health: a presidential advisory from the American heart association. Circulation. 2023;148(20):1606–1635. Erratum in: Circulation. 2024 Mar 26;149(13):e1023. doi: 10.1161/CIR.0000000000001241. doi:10.1161/CIR.0000000000001184

    16. Aggarwal R, Ostrominski JW, Vaduganathan M. Prevalence of cardiovascular-kidney-metabolic syndrome stages in US adults, 2011-2020. JAMA. 2024;331(21):1858–1860. doi:10.1001/jama.2024.6892

    17. Karshikoff B, Sundelin T, Lasselin J. Role of inflammation in human fatigue: relevance of multidimensional assessments and potential neuronal mechanisms. Front Immunol. 2017;8:21. doi:10.3389/fimmu.2017.00021

    18. Querido NR, Kenkhuis MF, van Roekel EH, et al. Longitudinal associations between inflammatory markers and fatigue up to two years after colorectal cancer treatment. Cancer Epidemiol Biomarkers Prev. 2022;31(8):1638–1649. doi:10.1158/1055-9965.EPI-22-0077

    19. Rangaswami J, Bhalla V, Blair JEA, et al. American heart association council on the kidney in cardiovascular disease and council on clinical cardiology. cardiorenal syndrome: classification, pathophysiology, diagnosis, and treatment strategies: a scientific statement from the American Heart Association. Circulation. 2019;139(16):e840–e878. doi:10.1161/CIR.0000000000000664

    20. Inker LA, Eneanya ND, Coresh J, et al. Chronic kidney disease epidemiology collaboration. new creatinine- and cystatin C-based equations to estimate GFR without race. N Engl J Med. 2021;385(19):1737–1749. doi:10.1056/NEJMoa2102953

    21. Impellizzeri FM, Agosti F, De Col A, Sartorio A. Psychometric properties of the fatigue severity scale in obese patients. Health Qual Life Outcomes. 2013;11:32. doi:10.1186/1477-7525-11-32

    22. Whitehead L. The measurement of fatigue in chronic illness: a systematic review of unidimensional and multidimensional fatigue measures. J Pain Symptom Manage. 2009;37(1):107–128. doi:10.1016/j.jpainsymman.2007.08.019

    23. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46(10):1121–1123. doi:10.1001/archneur.1989.00520460115022

    24. Taghizadeh G, Sarlak N, Fallah S, Sharabiani PTA, Cheraghifard M. Minimal clinically important differenceof fatigue severity scale in patients with chronic stroke. J Stroke Cerebrovasc Dis. 2024;33(4):107577. doi:10.1016/j.jstrokecerebrovasdis.2024.107577

    25. Weinges-Evers N, Brandt AU, Bock M, et al. Correlation of self-assessed fatigue and alertness in multiple sclerosis. Mult Scler. 2010;16(9):1134–1140. doi:10.1177/1352458510374202

    26. Honda Y, Mok Y, Mathews L, et al. Psychosocial factors and subsequent risk of hospitalizations with peripheral artery disease: the Atherosclerosis Risk in Communities (ARIC) Study. Atherosclerosis. 2021;329:36–43. doi:10.1016/j.atherosclerosis.2021.04.020

    27. Winward C, Sackley C, Metha Z, Rothwell PM. A population-based study of the prevalence of fatigue after transient ischemic attack and minor stroke. Stroke. 2009;40(3):757–761. doi:10.1161/STROKEAHA.108.527101

    28. Appelros P. Prevalence and predictors of pain and fatigue after stroke: a population-based study. Int J Rehabil Res. 2006;29(4):329–333. doi:10.1097/MRR.0b013e328010c7b8

    29. Glader EL, Stegmayr B, Asplund K. Poststroke fatigue: a 2-year follow-up study of stroke patients in Sweden. Stroke. 2002;33(5):1327–1333. doi:10.1161/01.str.0000014248.28711.d6

    30. Guest AJ, Clemes SA, King JA, et al. Attenuated cardiovascular reactivity is related to higher anxiety and fatigue symptoms in truck drivers. Psychophysiology. 2021;58(9):e13872. doi:10.1111/psyp.13872

    31. Gregg LP, Jain N, Carmody T, et al. Fatigue in nondialysis chronic kidney disease: correlates and association with kidney outcomes. Am J Nephrol. 2019;50(1):37–47. doi:10.1159/000500668

    32. Ba J, Chen Y, Liu D. Fatigue in adults with type 2 diabetes: a systematic review and meta-analysis. West J Nurs Res. 2021;43(2):172–181. doi:10.1177/0193945920938636

    33. Bhatt PP, Sheth MS. Comparison of fatigue and functional status in elderly type 2 diabetes patients versus age and gender matched individuals. Aging Med. 2024;7(1):84–89. doi:10.1002/agm2.12289

    34. Fritschi C, Quinn L. Fatigue in patients with diabetes: a review. J Psychosom Res. 2010;69(1):33–41. doi:10.1016/j.jpsychores.2010.01.021

    35. Lasselin J, Layé S, Barreau JB, et al. Fatigue and cognitive symptoms in patients with diabetes: relationship with disease phenotype and insulin treatment. Psychoneuroendocrinology. 2012;37(9):1468–1478. doi:10.1016/j.psyneuen.2012.01.016

    36. Morris G, Maes M. Mitochondrial dysfunctions in myalgic encephalomyelitis/chronic fatigue syndrome explained by activated immuno-inflammatory, oxidative and nitrosative stress pathways. Metab Brain Dis. 2014;29(1):19–36. doi:10.1007/s11011-013-9435-x

    37. Morris G, Berk M, Galecki P, Walder K, Maes M. The neuro-immune pathophysiology of central and peripheral fatigue in systemic immune-inflammatory and neuro-immune diseases. Mol Neurobiol. 2016;53(2):1195–1219. doi:10.1007/s12035-015-9090-9

    38. Gregg LP, Bossola M, Ostrosky-Frid M, Hedayati SS. Fatigue in CKD: epidemiology, pathophysiology, and treatment. Clin J Am Soc Nephrol. 2021;16(9):1445–1455. doi:10.2215/CJN.19891220

    39. Sebastian SA, Padda I, Johal G. Cardiovascular-Kidney-Metabolic (CKM) syndrome: a state-of-the-art review. Curr Probl Cardiol. 2024;49(2):102344. doi:10.1016/j.cpcardiol.2023.102344

    40. Madva EN, Gomez-Bernal F, Millstein RA, et al. Magnitude and sources of distress in mid-life adults with chronic medical illness: an exploratory mixed-methods analysis. Psychol Health Med. 2018;23(5):555–566. doi:10.1080/13548506.2017.1384554

    41. Lee CH, Giuliani F. The role of inflammation in depression and fatigue. Front Immunol. 2019;10:1696. doi:10.3389/fimmu.2019.01696

    42. Strike PC, Steptoe A. Psychosocial factors in the development of coronary artery disease. Prog Cardiovasc Dis. 2004;46(4):337–347. doi:10.1016/j.pcad.2003.09.001

    43. Cao Y, Wang W, Xie S, Xu Y, Lin Z. Joint association of the inflammatory marker and cardiovascular-kidney-metabolic syndrome stages with all-cause and cardiovascular disease mortality: a national prospective study. BMC Public Health. 2025;25(1):10. doi:10.1186/s12889-024-21131-2

    Continue Reading

  • CJP Afridi questions LHC’s ‘final observations’ in Imran’s May 9 bail cases – Pakistan

    CJP Afridi questions LHC’s ‘final observations’ in Imran’s May 9 bail cases – Pakistan

    Chief Justice of Pakistan (CJP) Yahya Afridi on Tuesday raised questions over some observations made by the Lahore High Court (LHC) on former premier Imran Khan’s bail pleas in eight May 9 cases.

    In November 2024, a Lahore anti-terrorism court had denied Imran bail in the cases related to the May 9, 2023 riots, including an attack on the house of the Lahore corps commander.

    The incarcerated PTI leader’s plea challenging that was also rejected by the LHC on June 24. Subsequently, days later, Imran moved the Supreme Court against the high court’s decision.

    A three-member bench led by CJP Afridi, which also included Justices Muhammad Shafi Siddiqui and Miangul Hassan Aurangzeb, resumed hearing the bail pleas today.

    Barrister Salman Safdar appeared on behalf of Imran, while Punjab Special Prosecutor Zulfiqar Naqvi was representing the state.

    During the hearing, CJP Afridi took note of some “findings” issued by the LHC in its detailed verdict of dismissing Imran’s bail pleas.

    “Can final observations be given in a case for bail?” the chief justice questioned rhetorically.

    Based on the same principle, he said, “For now, we will not touch upon whether the findings in this case are right or not. We will not go into the legal matters at the moment.

    “If we touch upon the legal findings, then the case for either [party] can be affected,” CJP Afridi explained.

    He directed the counsels of both respondents to assist the court with legal questions and complete their preparations by the next hearing.

    “The Supreme Court will not issue any such findings that may affect the case,” the top judge reiterated.

    At one point, Safdar requested the court to allow him to speak at the rostrum but CJP Afridi denied that plea.

    Subsequently, the bench issued notices to the Punjab government and adjourned the hearing till August 19.

    ‘Engineered and fabricated evidence’

    A two-member bench of the SC had taken up Imran’s bail pleas on June 29, but adjourned the hearing without issuing notices as Safdar could not appear.

    Imran’s appeal, filed through Safdar, claimed that the PTI founder has been accused of conspiring and abetting violence on May 9.

    However, at the time of the alleged offence, Imran was in the custody of the National Accountability Bureau. Therefore, his involvement in violence was “impossible”, the petition argued.

    On LHC’s rejection of the bail pleas, the fresh appeal claimed that the court relied on “engineered and fabricated evidence” which included “stale, discredited and delayed statements of police officials”.

    In its detailed verdict, the two-member LHC bench comprising Justice Syed Shahbaz Ali Rizvi and Tariq Mahmood Bajwa observed that the prosecution had evidence that reflected Imran’s role in the violence that broke out on May 9 following his arrest.

    The bench reproduced the statements of two police officials and prosecution witnesses, who claimed to have secretly attended PTI’s meetings wherein Imran allegedly gave instructions to other leaders to attack military installations in case of his imminent arrest from the Islamabad High Court (IHC).

    The meetings were allegedly held at a rest area of Chakri, Rawalpindi, on May 4 and at Imran’s Zaman Park residence in Lahore on May 7-9, 2023.

    Continue Reading

  • Intranasal Esketamine Premedication Reduces Sevoflurane Requirements d

    Intranasal Esketamine Premedication Reduces Sevoflurane Requirements d

    Introduction

    Pediatric anesthesia management requires balancing adequate anesthetic depth with minimal side effects. Sevoflurane remains the preferred inhalational agent in pediatric practice due to its favorable induction characteristics and low airway irritation potential. However, it may produce excitatory phenomena during the induction and emergence phases, particularly in younger children.1 The laryngeal mask airway (LMA) has become integral to pediatric anesthesia, facilitating spontaneous ventilation during general anesthesia for minor surgical procedures.2 When insufficient anesthetic depth, LMA insertion can trigger significant protective airway reflexes, including laryngospasm and coughing.3 While deepening anesthesia effectively prevents these airway responses, higher sevoflurane concentrations have been associated with adverse neurological effects in susceptible patients, including epileptiform activity and emergence agitation, though individual patient factors significantly influence risk.4–6 Successful LMA placement therefore requires careful optimization of anesthetic depth, quantified as the minimum alveolar concentration required for LMA insertion (MACLMA).

    Premedication offers several advantages in pediatric anesthesia, including anxiety reduction, improved induction cooperation, enhanced anesthetic potentiation, and decreased anesthetic requirements.7,8 Studies have shown that midazolam and dexmedetomidine effectively reduce sevoflurane requirements for LMA insertion.9,10 However, these agents present significant limitations: delayed onset, prolonged recovery times, and potential for paradoxical agitation or hemodynamic instability.

    Esketamine, the S (+) enantiomer of ketamine, has emerged as a promising alternative for pediatric premedication.11 This N-methyl-D-aspartate receptor (NMDA) antagonist exhibits approximately twice the analgesic potency of racemic ketamine with fewer psychological side effects, minimal secretions, rapid onset, and shorter recovery time.12 Unlike conventional agents, esketamine preserves airway reflexes without causing cardiovascular depression. Intranasal administration is particularly suitable for pediatric patients as it avoids injection-related distress while ensuring efficient mucosal absorption.13

    Despite these advantages, the effect of intranasal esketamine premedication on sevoflurane requirements for LMA insertion in pediatric patients has not been investigated. This randomized controlled trial, therefore, examines whether intranasal esketamine at doses of 0.5 mg/kg and 1.0 mg/kg reduces the minimum alveolar concentration of sevoflurane required for LMA insertion in children undergoing elective strabismus surgery. We hypothesize that intranasal esketamine premedication will produce dose-dependent reductions in sevoflurane requirements, enabling adequate anesthetic depth at lower sevoflurane concentrations, thereby reducing risks associated with inadequate anesthesia and excessive volatile exposure.

    Methods

    Study Design and Participants

    This randomized, double-blind, placebo-controlled trial was conducted at Fujian Provincial Hospital, China, from November 2023 through September 2024. The Institutional Review Board approved the study protocol (approval number K2023-01-003) on January 18, 2023, with trial registration at the Chinese Clinical Trials Registry (https://www.chictr.org.cn/showproj.html?proj=208297, ChiCTR2300076364) on October 7, 2023. Written informed consent was obtained from all parents or legal guardians before enrollment. The study adhered to the Declaration of Helsinki principles, Good Clinical Practice guidelines, and CONSORT 2025 reporting standards.14

    We enrolled healthy children aged 2–5 years, classified as American Society of Anesthesiologists, with physical status I or II and scheduled for elective strabismus surgery, who were eligible for participation. We excluded patients with suspected difficult airway, recent respiratory conditions (within two weeks), recent sedative or analgesic use (within 48 hours), neuropsychiatric disorders, obesity (body mass index > 30 kg/m²), known allergies to study medications, or significant life events within one month of surgery (parental divorce, bereavement, relocation, or school changes) that might affect behavioral assessments.

    Randomization and Allocation Concealment

    Participants were randomly assigned in equal proportions (1:1:1) to one of three treatment groups using computer-generated randomization: control (saline), esketamine 0.5 mg/kg, or esketamine 1.0 mg/kg. Allocation concealment was ensured using sequentially numbered, opaque, sealed envelopes. An independent research pharmacist, isolated from the clinical team, prepared identical syringes labeled only with study codes on the day of surgery. This double-blind design was maintained throughout the trial, with parents/guardians, healthcare providers, and outcome assessors all blinded to treatment assignments.

    Premedication Protocol

    All premedications were administered in a designated preoperative area with parents present to reduce anxiety. Twenty minutes before anesthetic induction, participants received one of three intranasal treatments according to their randomization: 0.9% saline solution (control), esketamine 0.5 mg/kg, or esketamine 1.0 mg/kg. Each formulation was delivered at a standardized volume of 0.04 mL/kg using a 1-mL syringe. An independent nurse administered the medication by instilling equal volumes into each nostril while the child remained supine.

    Anesthetic Management

    Children followed standard fasting guidelines (6–8 hours for solids, 2 hours for clear liquids) before anesthesia.15 Standard monitoring was established on arrival in the operating room, including pulse oximetry, electrocardiography, capnography, and noninvasive blood pressure measurement. We used a face mask with a semi-closed circuit system for anesthesia induction, delivering 5% sevoflurane in oxygen at 6 L/min. Ventilation progressed from initial spontaneous breathing to gentle manual assistance, maintaining end-tidal carbon dioxide between 35–45 mmHg throughout the procedure. We maintained the core temperature at 36.8 ± 0.4°C using a forced-air warming system (Bair Hugger 755; 3M Healthcare, USA). Sevoflurane concentration and end-tidal carbon dioxide were continuously monitored using a CARESCAPE Monitor B650 (GE Healthcare, USA).

    Sevoflurane MACLMA Determination

    We determined the minimum alveolar concentration of sevoflurane required for LMA insertion using Dixon’s sequential up-and-down method.16 Starting concentrations followed established protocols: 2.0% for the control group based on published data for unpremedicated children.10 The esketamine groups began at lower concentrations (1.6% for 0.5 mg/kg and 1.2% for 1.0 mg/kg) reflecting the expected dose-dependent anesthetic-sparing effect of NMDA receptor antagonists. All concentrations were equilibrated for 15 minutes before LMA insertion to ensure steady-state conditions.

    To ensure unbiased assessment, a single experienced pediatric anesthesiologist (with over 200 LMA insertions annually) performed all procedures while blinded to the premedication type and sevoflurane concentration. Following each insertion attempt, the sevoflurane concentration was adjusted by ± 0.2% for the next patient in that group. An unsuccessful insertion (intentional movement, coughing, or airway reaction within one minute of insertion) led to a 0.2% increase, while a successful insertion prompted a 0.2% decrease. Independent observers, also blinded to treatment allocation, documented all responses to maintain assessment objectivity.

    Anesthesia and Recovery Protocol

    Following LMA placement assessment, anesthesia was deepened with 2.0 mg/kg propofol, 0.2 μg/kg sufentanil, and 0.3 mg/kg rocuronium. Maintenance anesthesia consisted of 2% sevoflurane in a 50% oxygen-air mixture. Analgesia included 1 mg/kg intravenous flurbiprofen axetil and 0.4% oxybuprocaine eye drops administered perioperatively. Antiemetic prophylaxis comprised 0.15 mg/kg dexamethasone and 0.1 mg/kg ondansetron. Following surgery and LMA removal, children were transferred to the PACU, where parents provided emotional support during recovery.

    Outcome Measures

    The primary outcome was the MACLMA of sevoflurane, determined using Dixon’s up-and-down sequential allocation method.17 This method relies on identifying crossover events—instances where a patient’s response differed from the preceding patient’s response (either successful insertion followed by unsuccessful insertion or the reverse). We calculated each crossover value as the midpoint between the end-tidal sevoflurane concentrations. The final MACLMA for each group was derived by averaging all crossover values.

    For secondary outcomes, we assessed anesthesia induction quality using a validated 4-point scale (1 = uncooperative behavior requiring physical restraint; 4 = full cooperation or sleep state with mask acceptance).18 Emergence delirium was assessed during the first 30 minutes of recovery using the Pediatric Anesthesia Emergence Delirium scale, with scores ≥10 indicating clinically significant delirium.19 Emergence time was defined as the interval from sevoflurane discontinuation to purposeful movement in response to verbal commands. Discharge readiness from the PACU was evaluated using the modified Aldrete scoring system (threshold ≥9).20 Parental satisfaction was assessed 24 hours postoperatively using a 5-point Likert scale (1 = very dissatisfied; 5 = very satisfied).21 Finally, behavioral changes were evaluated three days after surgery via telephone interview using the Post-Hospitalization Behavior Questionnaire for Ambulatory Surgery.22

    Adverse events were systematically documented using standardized forms throughout the perioperative period. Monitored complications included bradycardia, hypotension, laryngospasm, hypoxemia, postoperative nausea and vomiting, and nightmares. All outcome assessments were performed by a single investigator blinded to treatment allocation to ensure consistency and minimize bias.

    Sample Size and Statistical Analysis

    Based on Dixon’s up-and-down methodology, dose-response studies typically require 24–26 participants to obtain six crossover points.23 Following recent methodological guidance,24 implemented a fixed prespecified sample size rather than a random stopping rule. We included 30 participants in each treatment group to enhance statistical reliability and account for potential withdrawals.

    Statistical analyses followed a predetermined plan. Data normality was assessed using the Shapiro–Wilk test. Continuous data are presented as mean ± standard deviation for normally distributed variables and median (interquartile range) for non-normally distributed variables. Categorical data are expressed as frequencies and percentages. We determined the sevoflurane MACLMA using Dixon’s method and verified it through probit regression analysis.

    Between-group comparisons employed appropriate parametric or non-parametric tests based on data distribution. One-way ANOVA with Bonferroni-adjusted post-hoc tests was applied to normally distributed variables, while the Kruskal–Wallis test, followed by Dunn’s test with Bonferroni adjustment, was used for non-normally distributed data. Categorical outcomes, including emergence delirium, behavioral changes, and adverse events, were analyzed using chi-square or Fisher’s exact tests as appropriate. All analyses were performed using IBM SPSS Statistics version 27 (IBM Corp., Armonk, NY, USA), with statistical significance set at p < 0.05 (two-tailed).

    Results

    Between November 2023 and September 2024, we screened 98 children for study participation, with 90 meeting the eligibility criteria for randomization. Following protocol exclusions, the final analysis included 28 patients in the control group, 28 in the esketamine 0.5 mg/kg group, and 29 in the esketamine 1.0 mg/kg group (Figure 1). Demographic and baseline characteristics were similar across all groups (Table 1).

    Table 1 Baseline Characteristics

    Figure 1 Consolidated Standards of Reporting Trials (CONSORT) flow diagram.

    Our primary finding showed that intranasal esketamine premedication reduced the MACLMA of sevoflurane in a dose-dependent manner. These concentrations were 2.16% ± 0.18% (control, Figure 2A), 1.87% ± 0.17% (esketamine 0.5 mg/kg, Figure 2B), and 1.50% ± 0.19% (esketamine 1.0 mg/kg, Figure 2C), representing reductions of 13.4% and 30.6% from the control value, respectively. Probit regression analysis validated these findings, yielding comparable values of 2.06% (95% confidence interval [CI]: 1.85–2.26%) for control, 1.77% (95% CI: 1.60–1.95%) for esketamine 0.5 mg/kg, and 1.42% (95% CI: 1.27–1.59%) for esketamine 1.0 mg/kg groups (Figure 3).

    Figure 2 Individual responses to laryngeal mask airway insertion determined by Dixon’s up-and-down method.

    Notes: Sequential plots showing patient responses to laryngeal mask airway insertion across three treatment groups: (A) control, (B) esketamine 0.5 mg/kg, and (C) esketamine 1.0 mg/kg. Hollow circles represent successful insertions, while solid circles indicate unsuccessful insertions (characterized by movement, coughing, or bucking within one minute of placement). The horizontal dashed lines indicate the calculated minimum alveolar concentration of sevoflurane required for laryngeal mask airway insertion: 2.16% ± 0.18% (control group), 1.87% ± 0.17% (esketamine 0.5 mg/kg group), and 1.50% ± 0.19% (esketamine 1.0 mg/kg group). These values demonstrate a dose-dependent reduction in sevoflurane requirements with intranasal esketamine premedication.

    Figure 3 Probability curves for successful laryngeal mask airway insertion.

    Notes: Probit regression analysis showing the probability of successful laryngeal mask airway insertion relative to sevoflurane concentration. Three treatment groups are represented: control (light red line), esketamine 0.5 mg/kg (medium blue line), and esketamine 1.0 mg/kg (dark blue line). The horizontal dashed line at 0.5 probability (50%) intersects with each curve at the minimum alveolar concentration value: 2.06% for control, 1.77% for esketamine 0.5 mg/kg, and 1.42% for esketamine 1.0 mg/kg. The progressive leftward shift of the curves with increasing esketamine dosage illustrates the dose-dependent reduction in sevoflurane requirements.

    The clinical benefits of esketamine extended beyond anesthetic reduction. Secondary outcomes revealed clear dose-dependent effects favoring the higher dose (Table 2). The 1.0 mg/kg group showed significantly improved cooperation during anesthesia induction compared to the control (p < 0.001), while the 0.5 mg/kg group showed no difference (p = 0.756). This dose-dependent pattern persisted through recovery: only the higher dose significantly reduced emergence delirium incidence (13.8% versus 46.4%, p = 0.007) and postoperative negative behavioral changes at day 3 (20.7% versus 53.6%, p = 0.010). Parents whose children received the higher dose reported significantly greater satisfaction (p = 0.022).

    Table 2 Secondary Outcomes

    Importantly, these benefits came without compromising safety or prolonging recovery. Emergence times and PACU discharge readiness were similar across all treatment groups (p = 0.331 and p = 0.589, respectively). The incidence of adverse events (including bradycardia, hypotension, laryngospasm, hypoxemia, postoperative nausea and vomiting, and nightmares) showed no significant differences between groups, and no serious complications occurred throughout the study.

    Discussion

    Our findings demonstrate that intranasal esketamine premedication significantly reduces sevoflurane requirements during LMA insertion in pediatric patients in a dose-dependent manner. Both tested dosages (0.5 mg/kg and 1.0 mg/kg) produced clinically meaningful reductions compared to the control, with the higher dose providing approximately twice the effect. The 1.0 mg/kg dose conferred additional clinical benefits beyond anesthetic sparing, including enhanced induction cooperation, decreased emergence delirium, and reduced postoperative negative behavioral changes at day 3 postoperatively. Crucially, these advantages were achieved without extending recovery time or increasing adverse events.

    These results build upon established research on NMDA in anesthesia practice. Chen et al showed that low-dose ketamine effectively reduces sevoflurane requirements for suppressing adrenergic responses during surgical procedures,25 while Hamp et al26 reported similar dose-dependent reductions with S-ketamine administration. Our findings advance this knowledge by demonstrating that the intranasal route achieves comparable anesthetic-sparing effects to intravenous administration while offering distinct advantages for pediatric patients, particularly avoiding injection-related distress. The observed dose-dependent relationship is consistent with known NMDA receptor antagonism pharmacological principles.

    Beyond anesthetic reduction, our study revealed important behavioral benefits. Intranasal esketamine at 1.0 mg/kg significantly reduced emergence delirium (13.8% versus 46.4%) and subsequent behavioral disturbances (20.7% versus 53.6%). These improvements align with Chen et al27 who demonstrated that intravenous ketamine infusion (1 mg/kg bolus followed by 1 mg/kg/h infusion) reduced emergence delirium from 46% to 22% in children. Several mechanisms may explain these findings. Esketamine’s anti-inflammatory properties could counteract surgery-induced neuroinflammation linked to postoperative behavioral changes.28,29 Furthermore, esketamine’s neuroprotective effects may reduce physiological stress responses to surgical and anesthetic stimuli, potentially protecting the developing brain from adverse changes.30,31

    Several factors limit the interpretation of our results. The absence of pharmacokinetic measurements precluded detailed characterization of intranasal esketamine absorption profiles. Although we selected a 20-minute premedication interval based on published data indicating peak sedative effects at approximately 16 minutes,11 this fixed timing may not have captured peak drug concentrations in all patients. Our single-center design involving a specific patient population undergoing eye muscle surgery may limit applicability to other pediatric surgical contexts. Testing only two doses provides incomplete information about the optimal dose across different age groups. Additionally, the varying sevoflurane concentrations required by the Dixon methodology could theoretically affect secondary outcomes, although the substantial separation between group values makes this unlikely. Finally, despite careful blinding protocols, esketamine’s recognizable clinical effects may have compromised blinding in some cases.

    Nevertheless, our study maintains high methodological standards. The randomized, double-blind, placebo-controlled design ensures robust internal validity. The Dixon sequential allocation method provided precise measurements of anesthetic requirement while protecting children from inappropriate depth. Our comprehensive pharmacodynamic and clinical outcomes assessment offers practitioners complete information about intranasal esketamine’s effects. This approach demonstrates the quantitative reduction in sevoflurane requirements and the meaningful clinical improvements in children’s perioperative experience.

    Conclusion

    Intranasal esketamine premedication significantly reduces sevoflurane requirements for LMA insertion in pediatric patients, with the 1.0 mg/kg dose achieving optimal results: 30.6% reduction in anesthetic requirements, improved induction cooperation, and decreased emergence agitation without prolonging recovery. These findings offer clinicians an evidence-based strategy to minimize volatile anesthetic exposure while maintaining airway safety. Although our single-center study involved a specific population undergoing strabismus surgery with one experienced operator, the results demonstrate clear clinical benefits. Future multicenter trials with diverse populations and practitioners should validate these findings and optimize dosing across age groups. Nevertheless, our data establish intranasal esketamine as a valuable tool for enhancing both safety and efficacy in pediatric anesthesia practice.

    Data Sharing Statement

    The corresponding author (Yanling Liao, Email: [email protected]) will make the deidentified participant data supporting this study’s findings available upon reasonable request with a methodologically sound proposal. Data will become accessible six months after publication and remain available for three years thereafter. Requestors will be required to sign a data access agreement.

    Acknowledgments

    We sincerely thank Professor Yusheng Yao for his valuable guidance, and all participating children and their families for their cooperation. Throughout this study, we also acknowledge the dedicated support provided by the anesthesiologists, surgeons, and nursing staff at Fujian Provincial Hospital.

    Author Contributions

    All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

    Funding

    This study was funded by the Science and Technology Program of Haicang District of Xiamen, China (No. 350205Z20232004), Natural Science Foundation of Xiamen, China (No. 3502Z202374068), the Fujian Provincial Health Technology Project (No. 2024CXA046), the Special Project of the National Natural Science Foundation Basic Research Enhancement Program (No. JCZX202404), and the Joint Funds for the Innovation of Science and Technology, Fujian Province (No. 2023Y9309).

    Disclosure

    The authors declare no conflicts of interest in this work.

    References

    1. Lerman J. Induction of anesthesia with sevoflurane in children: curiosities and controversies. Paediatr Anaesth. 2022;32(10):1100–1103. doi:10.1111/pan.14537

    2. Hsu G, von Ungern-Sternberg BS, Engelhardt T. Pediatric airway management. Curr Opin Anaesthesiol. 2021;34(3):276–283. doi:10.1097/ACO.0000000000000993

    3. Li L, Zhang Z, Yao Z, et al. The impact of laryngeal mask versus other airways on perioperative respiratory adverse events in children: a systematic review and meta-analysis of randomized controlled trials. Int J Surg. 2019;64:40–48. doi:10.1016/j.ijsu.2019.02.020

    4. Chao JY, Legatt AD, Yozawitz EG, et al. Electroencephalographic findings and clinical behavior during induction of anesthesia with sevoflurane in human infants: a prospective observational study. Anesth Analg. 2020;130(6):e161–e164. doi:10.1213/ANE

    5. Gibert S, Sabourdin N, Louvet N, et al. Epileptogenic effect of sevoflurane: determination of the minimal alveolar concentration of sevoflurane associated with major epileptoid signs in children. Anesthesiology. 2012;117(6):1253–1261. doi:10.1097/ALN.0b013e318273e272

    6. Aoyama K, Furuta M, Ameye L, et al. Risk factors for pediatric emergence delirium: a systematic review. Can J Anaesth. 2025;72(3):384–396. doi:10.1007/s12630-024-02889-w

    7. Dave NM. Premedication and induction of anesthesia in pediatric patients. Indian J Anaesth. 2019;63(9):713–720. doi:10.4103/ija.IJA_491_19

    8. Pereira EMM, Nascimento TSD, da Costa MG, et al. Comparison of intranasal dexmedetomidine versus oral midazolam for premedication in pediatric patients: an updated meta-analysis with trial-sequential analysis. Braz J Anesthesiol. 2024;74(5):844520. doi:10.1016/j.bjane.2024.844520

    9. Savla JR, Ghai B, Bansal D, et al. Effect of intranasal dexmedetomidine or oral midazolam premedication on sevoflurane EC 50 for successful laryngeal mask airway placement in children: a randomized, double-blind, placebo-controlled trial. Paediatr Anaesth. 2014;24(4):433–439. doi:10.1111/pan.12358

    10. Yao Y, Qian B, Lin Y, et al. Intranasal dexmedetomidine premedication reduces minimum alveolar concentration of sevoflurane for laryngeal mask airway insertion and emergence delirium in children: a prospective, randomized, double-blind, placebo-controlled trial. Paediatr Anaesth. 2015;25(5):492–498. doi:10.1111/pan.12574

    11. Huang J, Liu D, Bai J, et al. Median effective dose of esketamine for intranasal premedication in children with congenital heart disease. BMC Anesthesiol. 2023;23(1):129. doi:10.1186/s12871-023-02077-1

    12. Zhang BS, Zhang XJ, Wang CA. The efficacy and safety of esketamine in pediatric anesthesia: a systematic review and meta-analysis. Asian J Surg. 2023;46(12):5661–5663. doi:10.1016/j.asjsur.2023.08.073

    13. Hebbar KC, Reddy A, Luthra A, et al. Comparison of the efficacy of intranasal atomized dexmedetomidine versus intranasal atomized ketamine as a premedication for sedation and anxiolysis in children undergoing spinal dysraphism surgery: a randomized controlled trial. Eur J Anaesthesiol. 2024;41(4):288–295. doi:10.1097/EJA.0000000000001936

    14. Hopewell S, Chan AW, Collins GS, et al. CONSORT 2025 statement: updated guideline for reporting randomized trials. BMJ. 2025;389:e081123. doi:10.1136/bmj-2024-081123

    15. Joshi GP, Abdelmalak BB, Weigel WA, et al. American society of anesthesiologists practice guidelines for preoperative fasting: carbohydrate-containing clear liquids with or without protein, chewing gum, and pediatric fasting duration-A modular update of the 2017 American society of anesthesiologists practice guidelines for preoperative fasting. Anesthesiology. 2023;138(2):132–151. doi:10.1097/ALN.0000000000004381

    16. Pace NL, Stylianou MP, Warltier DC. Advances in and limitations of up-and-down methodology: a précis of clinical use, study design, and dose estimation in anesthesia research. Anesthesiology. 2007;107(1):144–152. doi:10.1097/01.anes.0000267514.42592.2a

    17. Yang C, Kang F, Meng W, et al. Minimum alveolar concentration-awake of sevoflurane is decreased in patients with Parkinson’s disease: an up-and-down sequential allocation trial. Clin Interv Aging. 2021;16:129–137. doi:10.2147/CIA.S291656

    18. Abukawa Y, Takano K, Hobo Y, et al. The use of a scented face mask in pediatric patients may facilitate mask acceptance before anesthesia induction. Front Med Lausanne. 2023;10:1190728. doi:10.3389/fmed.2023.1190728

    19. Sikich N, Lerman J. Development and psychometric evaluation of the pediatric anesthesia emergence delirium scale. Anesthesiology. 2004;100(5):1138–1145. doi:10.1097/00000542-200405000-00015

    20. Deshmukh PP, Chakole V. Post-anesthesia recovery: a comprehensive review of sampe, modified Aldrete, and white scoring systems. Cureus. 2024;16(10):e70935. doi:10.7759/cureus.70935

    21. Sam CJ, Arunachalam PA, Manivasagan S, et al. Parental satisfaction with pediatric day-care surgery and its determinants in a tertiary care hospital. J Indian Assoc Pediatr Surg. 2017;22(4):226–231. doi:10.4103/jiaps.JIAPS_212_16

    22. Jenkins BN, Kain ZN, Kaplan SH, et al. Revisiting a measure of child postoperative recovery: development of the post hospitalization behavior questionnaire for ambulatory surgery. Paediatr Anaesth. 2015;25(7):738–745. doi:10.1111/pan.12678

    23. Görges M, Zhou G, Brant R, et al. Sequential allocation trial design in anesthesia: an introduction to methods, modeling, and clinical applications. Paediatr Anaesth. 2017;27(3):240–247. doi:10.1111/pan.13088

    24. Oron AP, Souter MJ, Flournoy N. Understanding research methods: up-and-down designs for dose-finding. Anesthesiology. 2022;137(2):137–150. doi:10.1097/ALN.0000000000004282

    25. Chen C, Pang Q, Tu A, et al. Effect of low-dose ketamine on MAC BAR of sevoflurane in laparoscopic cholecystectomy: a randomized controlled trial. J Clin Pharm Ther. 2021;46(1):121–127. doi:10.1111/jcpt.13263

    26. Hamp T, Baron-Stefaniak J, Krammel M, et al. Effect of intravenous S-ketamine on the MAC of sevoflurane: a randomized, placebo-controlled, double-blinded clinical trial. Br J Anaesth. 2018;121(6):1242–1248. doi:10.1016/j.bja.2018.08.023

    27. Chen JY, Jia JE, Liu TJ, et al. Comparison of the effects of dexmedetomidine, ketamine, and placebo on emergence agitation after strabismus surgery in children. Can J Anaesth. 2013;60(4):385–392. doi:10.1007/s12630-013-9886-x

    28. Tu W, Yuan H, Zhang S, et al. Influence of anesthetic induction of propofol combined with esketamine on perioperative stress and inflammatory responses and postoperative cognition of elderly surgical patients. Am J Transl Res. 2021;13(3):1701–1709.

    29. Wang T, Weng H, Zhou H, et al. Esketamine alleviates postoperative depression-like behavior through anti-inflammatory actions in mouse prefrontal cortex. J Affect Disord. 2022;307:97–107. doi:10.1016/j.jad.2022.03.072

    30. Luo T, Deng Z, Ren Q, et al. Effects of esketamine on postoperative negative emotions and early cognitive disorders in patients undergoing non-cardiac thoracic surgery: a randomized controlled trial. J Clin Anesth. 2024;95:111447. doi:10.1016/j.jclinane.2024.111447

    31. Sah A, Singewald N. The (neuro) inflammatory system in anxiety disorders and PTSD: potential treatment targets. Pharmacol Ther. 2025;269:108825. doi:10.1016/j.pharmthera

    Continue Reading

  • Cambridge releases AS & A Level results amid paper leak

    Cambridge releases AS & A Level results amid paper leak

    Listen to article

    Cambridge Assessment International Education (CAIE) announced AS and A Level results for the May–June 2025 examination session in Pakistan on Tuesday, amid ongoing controversy over alleged paper leaks.

    “Congratulations to all our learners receiving their June 2025 results! Your hard work, dedication, and remarkable resilience – despite the uncertainty caused by regional tensions and alleged paper leaks – is truly inspiring,” said Uzma Yousuf, CAIE country director for Pakistan.

    CAIE said that it has launched an official investigation into the paper leaks in collaboration with the government of Pakistan. The organisation announced that students affected by the leaks would be offered free syllabus entry resits in the November 2025 exam series, applicable to those who sat one or more of the three affected papers.

    Over 100,000 students from over 700 schools sat for the June 2025 exam series for Cambridge International AS and A Level and Cambridge IGCSE and O Level this year in Pakistan.

    Cambridge received over 127,900 entries for Cambridge International AS and A Level in the June 2025 series from Pakistan.

     

     

    Continue Reading

  • Two Consecutive Holidays Announced in Islamabad

    Two Consecutive Holidays Announced in Islamabad

    The Islamabad Capital Territory (ICT) administration has declared Wednesday, August 13, 2025, as a local holiday within the revenue limits of the federal capital.

    The notification, issued by the Office of the District Magistrate on August 12, states that the holiday will apply to all offices except those providing essential services, including the Metropolitan Corporation Islamabad (MCI), Capital Development Authority (CDA), ICT Administration, ICT Police, Islamabad Electric Supply Company (IESCO), Sui Northern Gas Pipelines Limited (SNGPL), and hospitals.

    The District Magistrate has directed that the notification be circulated to relevant federal ministries, departments, and media outlets to ensure public awareness.

    It is worth noting that August 14, 2025, will also be observed as a public holiday to mark Pakistan’s Independence Day. This means residents of Islamabad will enjoy two consecutive days off on August 13 and 14.


    Continue Reading

  • Football transfer rumours: Real Madrid’s Rodrygo to join Manchester City? | Transfer window

    Football transfer rumours: Real Madrid’s Rodrygo to join Manchester City? | Transfer window

    Pep Guardiola is the foremost football genius of his generation, revolutionising the game with imaginative tactics such as having the best players and the most money. But he has a particular expertise when it comes to wingers: consider Jack Grealish, now binned to Everton; Savinho, in the process of being binned to Spurs; Jérémy Doku, once fun, now ineffective; Julián Alvarez, binned to be brilliant at Atlético Madrid; Ferran Torres, binned after two seasons; Nolito, binned to Sevilla after a season; all acquired for a combined total of roughly £234.4m.

    Consequently, one can only imagine Rodrygo’s excitement at the prospect of joining Manchester City from Real Madrid, who have decided that, though he offers goals, assists, energy, effort, experience, selflessness, variety, balance and big-game performances, he simply isn’t famous enough or attention-seeking enough to remain part of their squad. They value him at £87m – or, if he moves to the Etihad, £29.99 in two years’ time.

    None of this is to decry Guardiola’s expertise when it comes to midfielders: in other City news, James McAtee is the latest to be deemed sub-par, following Cole Palmer, Morgan Rogers and Roméo Lavia out of the club. Nottingham Forest are close to agreeing a deal for the 22-year-old and, having paid £52m for Anthony Elanga, expect the price to be somewhere in the region of £9067m; Matheus Nunes, Nico González and Matteo Kovacic are all expected to remain in situ.

    Elsewhere Chelsea are, of course, in the market. They are contemplating a bid for Piero Hincapié, the Bayer Leverkusen centre-back, but any move may be affected by their apparent antipathy towards Newcastle. Having already deprived them of João Pedro and Liam Delap, they are now trying to give Liverpool £43m for Ibrahima Konaté because, as last season proves, a frequently injured and inattentive defender is a mark of champions. Though this profile would need replacing, Arne Slot might well repurpose some loot for the acquisition of Alexander Isak, who will only contemplate reintegrating or signing a new contract if he is informed there is no prospect of a move to Anfield.

    Meantime, the feelgood story of the summer continues apace as Eddie Howe seeks a centre-forward, any centre-forward, prepared to play for him. As such, Newcastle are talking to Rennes about Arnaud Kalimuendo … but so too are Brentford, whose negotiations are the more advanced. Stay tuned for yet more heartwarming hilarity.

    Howe is also interested in Bilal El Khannouss, Leicester’s attacking midfielder, but so are Leeds, while Everton, having been rebuffed in various attempts to sign Tyler Dibling, will instead try for Tyler Durden. Should he fail to materialise, they too will contact the KP Stadium, with Abdul Fatawu the target.

    skip past newsletter promotion

    Down the East Lancs Road and to Old Trafford where, holding a placard reading “I AM THE TRUTH”, Rasmus Højlund has chained himself to the Manchester United team bus; shortly afterwards, Ruben Amorim ordered its sending to the breaker’s yard. However there is interest in the player from Italy, with Inter, Roma and Juventus joining Milan in the chase, but the smart money is on him joining his fellow reject Scott McTominay at Napoli and proving once again the old adage that when you leave United, the only way is stratospheric. Maybe they’ve got more in common with City than they think.

    Continue Reading

  • Pillar Two tax risk insurance – Irish market considerations

    Pillar Two tax risk insurance – Irish market considerations

    2. Pillar Two

    Pillar Two aims to create a fairer and more stable international tax system by protecting the tax base and curbing tax avoidance by multinational corporations. The publication of the Global Anti-Base Erosion Model Rules (Pillar Two) by the OECD in December 2021, outlined a global minimum taxation for international companies. It was implemented in Ireland in 2023 by way of Section 94 of the Finance (No.2) Act 2023’s insertion of (a new) Part 4A of the Taxes Consolidation Act (TCA) 1997.

    The regulatory framework of Pillar Two stipulates that in certain cases, a top-up tax must be levied on large multinational companies. To determine this tax, the tax base ‘GloBE Income’ is set in relation to the predefined recorded taxes ‘Adjusted Covered Taxes’. This allows for the identification of the states in which a multinational group of companies (MNE Group) is subject to an effective tax rate of less than 15%. When a group of companies has an effective tax rate of less than 15% in a certain country, a top-up tax is generally levied at the level of the ultimate group company within the framework of the ‘Income Inclusion Rule’ (IIR) and ‘Qualified Domestic Top Up Tax’ (QDTT). In the event that the low taxation is not (or is not fully) compensated for by the IIR, the ‘Undertaxed Profits Rule’ (UTPR) applies, the aim being to raise the effective tax rate of multinational groups to a minimum of 15%. However, the top-up tax is only calculated after deduction of a substance-related discount, so that ultimately only the ‘excess’ profit is subject to taxation.

    In the Irish context, Pillar Two’s target group and addressees are constituent entities located in Ireland that are part of an MNE Group. The prerequisite for designation as an MNE Group is that it achieves a turnover threshold of at least €750 million in the consolidated financial statements of the ‘Ultimate Parent Entity’ in at least two of the four previous financial years.

    Though simple in theory, in practice, there is considerable scope for uncertainty as by implementing these rules into Irish tax law, new laws have been introduced (which require interpretation), and ordinary accounting is interrupted by the increased administrative burden of the minimum tax assessment. The starting point for the calculation of GloBE Income is the result of the included group entity according to the annual financial statements (before consolidations of intra-group transactions). The result of the included company is generally to be calculated in accordance with the accounting standard used in the preparation of the consolidated financial statements of the group parent company. In addition, there are various adjustments and voting rights which must be carefully exercised. For example, uncapitalized tax deferrals on loss carryforwards can lead to an effective tax rate of less than 15% in the year of loss offsetting. This would trigger the application of Pillar Two provisions, and so the delta between the actual tax rate and the 15% minimum rate would be subject to tax.

    Some uncertainties can be preempted or clarified in Irish tax law by way of Revenue Opinions or Confirmations in accordance with Tax and Duty Manuals Part 37-00-40. However, the parameters for seeking a Revenue Opinion are relatively narrow. The question therefore arises as to whether Pillar Two risks can be insured.

    Pillar Two coverage: W&I insurance or tax insurance

    Two types of policies can be used to insure tax risks:

    • Warranty and indemnity (W&I) insurance, which is used to insure unknown tax risks that emanate from events in the past. Placed in the context of a corporate transaction, the provisions of W&I insurance are linked to the warranties and indemnities provided by a seller to a buyer in a sale and purchase agreement. A significant part of the cover is protection in the event that a seller has not disclosed relevant information to a buyer, or for risks which have not been discovered in due diligence.
    • Tax insurance is a form of standalone insurance that covers both known and unknown tax risks that have arisen in the past or may arise in the future. It has a much broader scope of application than W&I insurance and so can cover tax risks outside of an M&A transaction, e.g.  those risks for which a resolution might otherwise be sought by seeking a Revenue Opinion or Confirmation.

    Insurer appetite — W&I Insurance

    Approximately a third of insurers are willing to provide insurance cover for tax risks related to Pillar Two under a W&I insurance policy. Another third have clear reservations about providing coverage under W&I insurance, while the final third have yet to take a position. A list of reasons for the reluctance to offer tax cover under a W&I insurance policy includes:

    • Pillar Two being typically outside of the scope of tax due diligence
    • Lack of experience or lack of market consensus
    • The accounting standard may lead to risk allocation uncertainty (in the context of de-/first-time consolidation)
    • Liability for a third-party tax is difficult to assess without considering the position of both sides of a transaction
    • Certain issues are outside of the control of the parties (such as which countries have implemented the rules)
    • Uncertainty regarding political decision-making on Pillar Two implementation 

    Insurer appetite — Tax insurance

    The picture as relates to standalone tax insurance is clearer, and here there is a general willingness among insurers active in the Irish market to provide cover for Pillar Two risks. Insurers will consider areas such as:

    • Risks around inconsistency in implementation and interpretation in national law or tax authority commentary.
    • The Group’s use of Safe Harbor Rules.1
    • Risks related to the question of whether the non-consolidation of MNE Groups/units of companies is correct (this is likely to be particularly relevant at the time of first filing Pillar Two returns).

    The majority of insurers surveyed will consider covering known Pillar Two risks under a tax insurance policy.

    Continue Reading

  • Flood alert issued for Punjab rivers amid potential water discharge from India

    Flood alert issued for Punjab rivers amid potential water discharge from India



    A person stands on the shore near Chenab River near the Line of Control (LOC) on May 2, 2025. — AFP

    The Provincial Disaster Management Authority (PDMA) of Punjab on Tuesday warned of possible flooding in rivers due to rains in upper parts of the country along with possible water release by India in the coming days.

    “There is a fear of India releasing water into the Sutlej River in two days. There has been an unusual increase in water levels of Indian dams,” said a PDMA spokesperson.

    The Bhakra, Pong and Thein dams in India have reached 61%, 76% and 64% of their total capacity, respectively, he added.

    With a warning issued for medium to high level flood in the Chenab River, the PDMA director general (DG) has said that the situation of rivers and dams was being monitored round the clock.

    The official further warned that there is a chance of further increase in water flow in the Sutlej River.

    The development came a day after the authority issued a flood advisory as the province braces for a seventh spell of monsoon rains from August 13.

    A new monsoon spell is likely to cause rising water levels in major rivers, including the Sutlej, Ravi, Chenab and Jhelum, as well as their adjoining streams and tributaries.

    Commissioners, deputy commissioners, and all relevant departments have been instructed to remain on high alert, the advisory read.

    The recent monsoon spell wreaked havoc across Pakistan with scenes of urban flooding, flash floods and landslides resulting in over 300 deaths, while several others are still missing, along with damage to infrastructure.

    Gilgit Baltistan, which hosts several tourist hotspots, was also battered by flash floods and landslides, with Chief Minister Haji Gulbar Khan, last month, saying that at least 10 people were killed and four others were injured in the region in floods triggered by intense monsoon rains.

    Continue Reading

  • Man Utd reveal adidas third kit for 2025/26 season

    Man Utd reveal adidas third kit for 2025/26 season

    Reimagining one of the most storied kits in our history, the design focuses on the details, from the engineered devil-base fabric to the authentic three-stripe tape and flat-knit crew collar and cuffs.

    After last year’s celebrated reintroduction of the adidas Trefoil logo on our third jersey, its return honours the logo’s historic legacy in the sport, as well as acknowledging the rising role of fashion in today’s game. 

    The black engineered base fabric features a subtle, yet striking, club devil motif, woven directly into the design, a nod to one of the most iconic symbols in our history. The modern black-and-yellow shield crest further celebrates the club’s DNA, while yellow-and-blue accents on the collar and flat-knit cuffs add a fresh twist to a classic silhouette.

    Finished with the fabled three adidas stripes in bold yellow across the shoulders and the Trefoil logo in yellow on the chest, the jersey seamlessly blends heritage with timeless adidas Originals design.

    Continue Reading

  • Another holiday announced on August 13 – samaa tv

    1. Another holiday announced on August 13  samaa tv
    2. PSX to remain closed on August 14 for Independence Day  Profit by Pakistan Today
    3. Two Consecutive Holidays Announced in Islamabad  ProPakistani
    4. Banks to remain closed on Thursday  Associated Press of Pakistan
    5. Four-day school holiday announced in Sindh from Aug 15  nation.com.pk

    Continue Reading