Tag: nevin manimala

J Craniofac Surg. 2025 Nov 17. doi: 10.1097/SCS.0000000000012128. Online ahead of print.

ABSTRACT

Down syndrome (DS) is the most common chromosomal disorder worldwide, characterized by congenital anomalies, distinctive facial morphology, and developmental delays. Although phenotypic features vary, many individuals with DS exhibit consistent craniofacial traits. In this study, we evaluated the morphometric characteristics of the ears, nose, and the second-to-fourth digit ratio (2D:4D) in children with DS, and examined their relationship with age, sex, and lateralization. The sample included 40 children with DS (20 girls and 20 boys), aged 2 to 13 years, attending rehabilitation centers in Konya. Anthropometric and photogrammetric methods were used to measure nasal width, length, height, alare-pronasale and alare-subnasale distances, nasal root width, nasofrontal angle, and nasal tip angle. Ear dimensions, including width, length, earlobe size, and concha measurements, were recorded. The 2D:4D digit ratio was also calculated. Statistical analyses revealed that the 2D:4D ratio differed significantly between sexes (P < 0.05), while no significant lateral differences were observed. All parameters were positively correlated with age. These findings contribute to the understanding of craniofacial development in DS and may inform clinical applications such as early diagnosis, genetic counseling, surgical planning, and the customization of assistive devices like glasses and hearing aids.

PMID:41248432 | DOI:10.1097/SCS.0000000000012128

BMJ Open. 2025 Nov 4;15(11):e108220. doi: 10.1136/bmjopen-2025-108220.

ABSTRACT

INTRODUCTION: Detecting cancer earlier improves treatment options and long-term survival. A multicancer early detection test that reliably picks up early-stage cancer would potentially save lives and reduce the cost of treating cancer. One promising candidate is the Enlighten test, which applies machine learning to plasma amino acid concentrations to detect cancer. In a cohort of 77 patients recently diagnosed with breast, colorectal, pancreatic or prostate cancer, 60 (78%) were detected by the test (sensitivity), with no false positives in 20 healthy controls. The MODERNISED study will further develop the Enlighten test to detect 10 different cancers by adding bladder, lung, melanoma, oesophageal, ovarian and renal cancer to the test.

METHODS AND ANALYSIS: MODERNISED (ISRCTN17299125) is a multicentre prospective, non-interventional, case-control study. We aim to recruit 1000 adult participants with a recent cancer diagnosis, 250 adult participants with symptoms of cancer where a cancer diagnosis was ruled out by the National Health Service (NHS) standard of care and 100 healthy adult volunteers. Cancer tissue of origin (ToO) will include bladder, breast, colorectal, lung, melanoma, oesophageal, ovarian, pancreatic, prostate and renal. Participants in the two non-cancer cohorts who are later diagnosed with cancer will be moved to the cancer cases cohort. The primary aim is to train and validate a machine learning algorithm to detect cancer, which will be evaluated by AUROC. Secondary aims include training and validating an algorithm to predict ToO and stage of cancer, exploring differences in performance by demographics and estimating how sensitivity varies across specificity cut-offs of 95%, 99% and 99.9%. These results will provide a statistically powered estimate of how well the Enlighten test can discriminate between individuals with and without cancer, which can then be validated for clinical use in further research.

ETHICS AND DISSEMINATION: This study is sponsored by University Hospital Southampton NHS Foundation Trust and has been approved by the Health Research Authority and Health and Care Research West Midlands (24/WM/0234). Results will be presented at scientific meetings and published in international peer-reviewed journals. Lay summaries of study progress and findings will be published on the Southampton Clinical Trial Unit’s website.

TRIAL REGISTRATION NUMBER: ISRCTN17299125.

PMID:41248417 | DOI:10.1136/bmjopen-2025-108220

BMJ Open. 2025 Nov 4;15(11):e105455. doi: 10.1136/bmjopen-2025-105455.

ABSTRACT

OBJECTIVE: To ascertain the clinical impact, prevalence and associated determinants of delayed treatment intensification, defined as delaying the escalation of treatment plans for individuals with type 2 diabetes mellitus who fail to attain ideal glycaemic control, at the University of Gondar Comprehensive Specialised Hospital in Northwest Ethiopia.

DESIGN: A mixed-methods study.

SETTING: University of Gondar Comprehensive Specialised Hospital.

PARTICIPANTS: 420 patients with type 2 diabetes mellitus with poor glycaemic control after the index date were included in this study. A simple random sampling technique was employed to select the required sample size. Data were collected retrospectively and entered into EpiData V.4.6 and exported to Stata V.14.2 for analysis.

METHOD: Multivariable logistic regression was used to identify factors associated with delayed treatment intensification. A p value of 0.05 in the multivariable analysis was considered statistically significant. Qualitative data were collected through in-depth interviews with eight selected healthcare providers, and thematic analysis was undertaken to identify the underlying barriers to timely treatment intensification.

PRIMARY OUTCOME: Delayed treatment intensification.

RESULTS: The prevalence of delayed treatment intensification was 51.4% (95% CI 46.6% to 56.2%), with a median delay of 14 months (IQR: 7.5-42 months) from the index date. Among those experiencing delayed treatment intensification, 43.1% developed new chronic diabetic complications, including retinopathy (18.1%), neuropathy (14.4%) and nephropathy (6.0%). Other complications (hypertension, stroke, heart failure and diabetic foot ulcer) accounted for 4.64% of the cases. Significant predictors of delayed treatment intensification included longer duration of diabetes (adjusted ORs (AOR) 1.68; 95% CI 1.13 to 2.5), presence of comorbidities (AOR 1.83; 95% CI 1.04 to 3.2) and use of cardioprotective medications (AOR 1.59; 95% CI: 1.04 to 2.43). The qualitative findings revealed additional barriers contributing to delayed treatment intensification, including financial limitations, insufficient patient awareness and non-adherence among patients. Additionally, healthcare provider-related factors, including professional fatigue and knowledge gaps, as well as health institution-related factors such as inadequate healthcare infrastructure.

CONCLUSIONS: This study found a high prevalence of delayed treatment intensification (51.4%), associated with comorbidities, longer disease duration, low patient awareness, cardioprotective drug use and barriers related to the system and providers. To address these gaps, priorities should include strengthening patient education, scheduling regular reviews for high-risk patients and improving clinical decision support tools for timely treatment intensification. Enhancing healthcare infrastructure, such as medication supply and diagnostic services, and offering refresher training to reduce provider fatigue, are also crucial for improving the delivery of diabetes care.

PMID:41248414 | DOI:10.1136/bmjopen-2025-105455

BMJ Open. 2025 Nov 16;15(11):e106013. doi: 10.1136/bmjopen-2025-106013.

ABSTRACT

OBJECTIVES: This study examined factors associated with the use of Indonesia’s National Health Insurance (NHI) among its beneficiaries in Maluku province.

DESIGN: Cross-sectional study.

SETTING: The individual-level data were derived from the 2021 Social Health Insurance Sample Data. National health reports of Indonesia were used to provide the district-level variables. We performed multivariable logistic regression analyses to identify factors associated with NHI use among its beneficiaries in Maluku province.

PARTICIPANT: Data were collected from 31 517 NHI beneficiaries registered in Maluku.

PRIMARY OUTCOME: The primary outcome was the use of NHI insurance when accessing healthcare services (yes/no).

RESULTS: Only 14.79% of NHI beneficiaries in Maluku had ever used their insurance for healthcare services. Individual factors associated with higher NHI use included being under 60 years, females (adjusted OR (aOR)=1.29, p<0.001), married (aOR=1.83, p<0.001) and having non-subsidised insurance (aOR=1.12, p<0.001). At the district level, higher usage was associated with increased rates of joint diseases (aOR=1.19, p<0.001), hypertension (aOR=1.81, p<0.001), diarrhoea (aOR=1.24, p<0.001) and a higher doctor-to-population ratio (aOR=1.01, p<0.001). A reduced likelihood of NHI use was found in beneficiaries living in the districts with high rates of acute respiratory infections (aOR=0.86, p<0.001) and with a high fiscal capacity (aOR=0.14, p<0.001).

CONCLUSION: Strengthening primary healthcare accessibility, improving the distribution of healthcare workers and addressing socioeconomic and geographical disparities are essential to ensure that the NHI scheme achieves equitable use across all regions in Maluku and other areas with similar settings.

PMID:41248413 | DOI:10.1136/bmjopen-2025-106013

BMJ Open. 2025 Nov 13;15(11):e105355. doi: 10.1136/bmjopen-2025-105355.

ABSTRACT

INTRODUCTION: Mistreatment and obstetric violence constitute significant human rights violations with profound implications for maternal mental health. These detrimental practices persist globally, particularly in contexts where underfunded health systems, workforce shortages and entrenched gender inequalities intersect, depriving women of adequate psychosocial support and culturally sensitive mental healthcare. Although awareness of the immediate harms of mistreatment is increasing, its cumulative effects throughout the maternal care continuum remain insufficiently understood. This review will synthesise evidence on the impact of mistreatment on perinatal mental health, identify critical gaps and advocate for systemic change.

METHODS AND ANALYSIS: This systematic review and meta-analysis protocol complies with the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols. A thorough literature search will be executed across multiple electronic databases, including CINAHL-Cumulative Index to Nursing and Allied Health Literature, Embase via Ovid, MEDLINE, PsycInfo, PubMed, Scopus, as well as other significant or specialised databases and grey literature. The review will incorporate only non-randomised study types and observational studies (cohort, cross-sectional, case-control), along with mixed-method and qualitative studies. Abstract and full-text screening will be performed by two reviewers using Covidence. The methodological quality of the included studies will be assessed using the Newcastle-Ottawa Scale for observational studies, the Risk of Bias in Non-Randomised Studies of Interventions, the Critical Appraisal Skills Programme and the Mixed Methods Appraisal Tool. Statistical heterogeneity will be evaluated using the Higgins test. Meta-analysis will be conducted using R statistical software V.4.4.4, employing random effects models to determine the weights. The study results will be reported sequentially, beginning with primary outcomes, followed by secondary outcomes and significant subgroup outcome analyses.

ETHICS AND DISSEMINATION: Ethical approval is not required as no original data will be collected. The findings of this review will be disseminated through publication and conference presentations.

PROSPERO REGISTRATION NUMBER: CRD420251044379.

PMID:41248398 | DOI:10.1136/bmjopen-2025-105355

BMJ Open. 2025 Nov 4;15(11):e105026. doi: 10.1136/bmjopen-2025-105026.

ABSTRACT

OBJECTIVES: Current prediction models for disease progression to AIDS in people living with HIV primarily rely on traditional statistical methods. This study aimed to develop and compare four machine learning models and to create a clinically applicable nomogram for identifying risk factors associated with AIDS progression.

DESIGN: A retrospective cohort study conducted from January 2013 to December 2022.

SETTING: Yining City, Xinjiang, China.

PARTICIPANTS: Newly diagnosed HIV-infected patients (aged 18-60 years) who received antiretroviral therapy and had not progressed to AIDS at baseline.

PRIMARY OUTCOME MEASURES: Progression from HIV infection to AIDS, as defined by the Chinese Center for Disease Control and Prevention criteria.

RESULTS: Among the 2305 patients included, 652 progressed to AIDS. The cohort was predominantly male, with a mean baseline CD4 cell count of 384 cells/μL. Four machine learning models-Support Vector Machine, Random Forest, Logistic Regression and Extreme Gradient Boosting (XGBoost)-were developed. The XGBoost model demonstrated the best predictive performance (area under the curve, AUC: 0.877). Univariate and multivariate analyses identified WHO clinical stages, CD4 cell count, HIV transmission route, platelet count and haemoglobin level as significant predictors. The developed nomogram achieved an AUC of 0.840. Its calibration curve, after bias correction, showed good agreement with the ideal curve, and decision curve analysis indicated potential clinical utility.

CONCLUSIONS: In this cohort, the XGBoost model showed superior performance for predicting AIDS progression. The proposed nomogram may serve as a practical tool to facilitate rapid risk assessment in similar clinical settings. These findings suggest that enhanced monitoring and regular follow-up might be beneficial for patients with low CD4 counts for timely intervention and to improve outcomes.

PMID:41248391 | DOI:10.1136/bmjopen-2025-105026

BMJ Open. 2025 Nov 16;15(11):e102980. doi: 10.1136/bmjopen-2025-102980.

ABSTRACT

OBJECTIVE: The under-5 mortality rate (U5MR) is a crucial global health metric for evaluating public health interventions, and further reductions in U5MR are essential for achieving the Sustainable Development Goals (SDGs). This study analyses the trends of U5MR globally from 2000 to 2021 and explores the quantitative impact of health resources on U5MR reduction.

DESIGN AND PARTICIPANTS: This study used WHO public data from 2000 to 2021 to investigate the temporal trend of U5MR through Joinpoint regression analysis. A two-way fixed-effect model was used to investigate the relationship between U5MR and health resources.

PRIMARY OUTCOME MEASURES: Data on U5MR and health resources (including six vaccine-related indicators and eight health expenditure-related indicators) were obtained from the WHO Global Health Observatory, encompassing 200 countries and regions from 2000 to 2021.

RESULTS: Globally, U5MR declined, though at a slower pace (annual average percentage change: -3.259, p<0.001), while vaccination coverage and health expenditures increased (p<0.05). We found a significant negative correlation of global polio vaccination coverage (β=-0.489, p<0.05) and current health expenditure (CHE) as percentage of gross domestic product and U5MR (β=-0.762, p<0.05) with U5MR. In G20 countries, domestic general government health expenditure as percentage of CHE was negatively correlated with U5MR (β=-0.553, p<0.05). Health resources contributed to 65.01% of U5MR reduction in G20 countries, with vaccines accounting for 23.86%. Globally, health resources contributed 37.26% to U5MR reduction, with vaccines accounting for 72.69%.

CONCLUSION: Global U5MR has declined from 2000 to 2021, but progress remains insufficient to fully achieve the SDGs. Immunisation played a dominant role in the global reduction of U5MR, underscoring the critical need to prioritise vaccination in health resource allocation strategies.

PMID:41248390 | DOI:10.1136/bmjopen-2025-102980

BMJ Open. 2025 Nov 4;15(11):e101586. doi: 10.1136/bmjopen-2025-101586.

ABSTRACT

OBJECTIVES: To investigate patterns of sustainable working life, defined as a few or no interruptions from paid work due to sickness absence, unemployment or disability pension among Swedish twins with and without common mental disorders (CMDs). We also sought to examine the role of baseline sociodemographic factors for the identified patterns.

DESIGN: Prospective cohort study.

SETTING: Population-based sample of twins born in Sweden.

PARTICIPANTS: The sample of 5529 CMDs, discordant twin pairs between ages 18 and 59 years at baseline in 1998 (50% women) were followed annually for working life statuses using data obtained from national registers until 2020.

PRIMARY OUTCOME: Sustainable working life.

MEASURES: Group-based trajectory modelling was applied to identify distinct trajectory groups. Multinomial logistic regression models estimating ORs were performed.

RESULTS: For those with CMDs, a three-trajectory solution was the best-fitting model, while for those without CMDs, a two-trajectory solution had best fit; in both groups, sustainable working life constituted the largest trajectory group (71% and 83%, respectively). No sustainable working life yielded 14.5% and 17% in those with CMDs and those without CMDs, respectively, whereas, among those with CMDs, another 14.5% had a trajectory with decreasing sustainable working life. Higher education was associated with a lower likelihood (OR 0.12-0.47) and being single (with or without children, OR 2.23-2.51) with a higher likelihood of belonging to those trajectories characterised by no sustainable working life.

CONCLUSION: A small cluster among those with CMDs tended to follow a decreasing sustainable working life pattern, while a minority with or without CMDs had no sustainable working life. Although a sustainable working life seems common, those with CMDs should be identified early for preventive actions and support to remain in paid work.

PMID:41248389 | DOI:10.1136/bmjopen-2025-101586

BMJ Open. 2025 Nov 4;15(11):e099209. doi: 10.1136/bmjopen-2025-099209.

ABSTRACT

OBJECTIVES: To assess the relationship of infant growth, feeding practices and tummy time to their motor development at 12 months, with a special focus on how maternal physical activity during late pregnancy relates to infants’ motor skills.

DESIGN: Longitudinal study.

SETTING: Rural city in the Mid-Southern USA.

PARTICIPANTS: 16 singleton pregnant women in the third trimester and their term infants were recruited, excluding mother-infant pairs with health issues that impact infants’ motor development and restrict mothers’ physical activity.

PRIMARY AND SECONDARY OUTCOME MEASURES: Maternal physical activity and sedentary time during the third trimester were measured using Actigraph activity monitors. Labour nurses measured neonatal birth weight and length using standard procedures. Infants’ motor percentiles at 4 and 12 months were measured respectively using the Alberta Infant Motor Scale and Peabody Developmental Motor Scales II test by a licensed paediatric physical therapist. Feeding practices, infants’ time spent in different positions and family composition were evaluated separately at 4 and 12 months using a study-specific survey.

RESULTS: Infant motor percentiles at 4 months were positively associated with their 12-month motor percentiles (r=0.649, p=0.009). For each additional percentile at 4 months, the mean 12-month percentile increased by 0.4. Motor percentiles at 12 months were also positively associated with infants’ birth weight (r=0.553, p=0.026) and length (r=0.637, p=0.008), but not significantly associated with tummy time (r=-0.069, p=0.840). Infant motor percentiles at 12 months were not associated with time spent sedentary (r=-0.134, p=0.634), light activity (r=0.213, p=0.447) or moderate activity (r=-0.050, p=0.858) during the third trimester. At 12 months, breastfeeding status (p=0.576) and having siblings (p=0.230) were not related to motor scores.

CONCLUSIONS: Motor percentiles at 4 months, birth weight and length correlated with motor skills at 12 months, whereas tummy time, siblings, and breastfeeding were not significant predictors. Physical activity during pregnancy did not significantly correlate to motor skills at 12 months.

PMID:41248387 | DOI:10.1136/bmjopen-2025-099209

BMJ Open. 2025 Nov 13;15(11):e105613. doi: 10.1136/bmjopen-2025-105613.

ABSTRACT

OBJECTIVE: Studying issues related to stroke medication non-adherence is essential for secondary prevention of stroke. This study aimed to identify the prevalence of medication non-adherence and risk factors among stroke survivors. The reasons behind this are that some patients may not follow stroke medication plans, and potential ways to help patients adhere better to medication plans.

DESIGN: This study employed a cross-sectional patient survey.

SETTING: The study was conducted in 20 public and private healthcare facilities in a resource-constrained setting, in Punjab, the largest province of Pakistan.

PARTICIPANTS: We included 6538 stroke survivors aged 21-75 years with at least a 6 month history of stroke who were prescribed one or more anti-stroke medications and met the inclusion criteria.

PRIMARY OUTCOME MEASURES: The main outcome was medication non-adherence, measured by the Self-Efficacy for Appropriate Medication Scale (SEAMS) and self-reported pill count. Descriptive statistics were used to summarise study variables. chi-square (χ²)/Fisher’s exact test and independent t-test/ANOVA were employed. A generalised linear model (logit model using multivariable logistic regression shows that several factors are associated with medication non-adherence and adherence. Odds ratio (OR) plots were generated using Seaborn and Matplotlib.

RESULTS: Non-adherence based on pill counts was 49.7%, while the mean SEAMS score (31.3±7.7) showed moderate self-reported adherence. After adjusting for age, gender, marital status, education, income, health insurance, smoking status, comorbidities, stroke type, disease duration, blood pressure control, number of medications, dosing frequency, physiotherapy continuation, perceived side effects and doctor-patient satisfaction, we found that female gender (vs male: AOR 0.31, 95% CI 0.27 to 0.35), lower income (10k-25k PKR vs >100k PKR: AOR 0.31, 95% CI 0.23 to 0.41; 26k-50k PKR vs >100k PKR: AOR 0.57, 95% CI 0.47 to 0.68), primary/secondary education (vs postgraduate: AOR 0.74, 95% CI 0.64 to 0.87), controlled BP (vs uncontrolled: AOR 0.66, 95% CI 0.59 to 0.73), longer disease duration (≥5 years vs <5 years: AOR 0.43, 95% CI 0.37 to 0.49), one time per day dosing (vs three times per day: AOR 0.25, 95% CI 0.21 to 0.29) and fewer medications (<5 vs 10+: AOR 0.50, 95% CI 0.43 to 0.58; 5-9 vs 10+: AOR 0.71, 95% CI 0.61 to 0.83) significantly reduced non-adherence odds (all p<0.001). Married status (vs other: AOR 1.22, 95% CI 1.02 to 1.45, p=0.028) and diabetes (vs obesity: AOR 1.29, 95% CI 1.09 to 1.53, p=0.003) increased non-adherence risk.

CONCLUSION: This study addresses the significant issue of medication non-adherence in stroke patients in Pakistan, reflecting global patterns yet remaining under-explored locally. It emphasises the critical role of adherence in managing chronic conditions such as stroke, where consistent use of preventive therapies is vital for reducing recurrence and improving outcomes. While the non-adherence rates are consistent with global trends, there is a notable lack of observational studies and epidemiological data in the Pakistani context. Our findings support a comprehensive approach to enhance medication adherence, taking into account the complex connections among social, behavioural and clinical factors. It also highlights the importance of maintaining detailed records to monitor adherence trends, identify high-risk groups and inform targeted public health interventions.

PMID:41248386 | DOI:10.1136/bmjopen-2025-105613