BMJ Paediatrics Open
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Preprints posted in the last 7 days, ranked by how well they match BMJ Paediatrics Open's content profile, based on 24 papers previously published here. The average preprint has a 0.03% match score for this journal, so anything above that is already an above-average fit.
Leuenberger, L. M.; Shoman, Y.; Romero, F.; Sasaki, M.; Deligianni, X.; Goebel, N.; Mozun, R.; Bielicki, J. A.; Burckhardt, M.-A.; Saner, C.; Schwitzgebel, V.; Hauschild, M.; Righini Grunder, F.; Mueller, P.; Schlapbach, L. J.; Jenni, O.; Spycher, B. D.; Kuehni, C. E.; Belle, F. N.; SwissPedHealth consotrium,
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BACKGROUND: We used anthropometric data from electronic health records (EHRs) of Swiss childrens hospitals to evaluate growth references and estimate centile curves. METHODS: We received EHRs extracted from seven Swiss childrens hospitals and analysed two samples: all children with a height, weight, body mass index (BMI), or head circumference recording, and a subsample restricted to children without diseases potentially affecting growth, weighted to represent the general population. We calculated mean z-scores based on the World Health Organization growth references adopted for Switzerland in 2011 (CH-WHO 2011) and current Swiss growth references (Swiss 2026). We estimated sex-specific centile curves in the subsample using generalised additive models for location, scale, and shape. RESULTS: We included 213,868 children with height, 448,002 with weight, 209,244 with BMI, and 67,397 with head circumference recordings. Mean z-scores in the all children sample were (CH-WHO 2011; Swiss 2026): height (0.10; -0.19), weight (0.16; -0.09), BMI (0.04; -0.07), head circumference (-0.28, -0.28); and in the subsample: height (0.34; 0.00), weight (0.27; 0.01), BMI (0.18; 0.05), and head circumference (0.04; 0.01). The 50th height, weight, BMI, and head circumference centiles of girls and boys in the subsample closely followed those of Swiss 2026, with slightly wider 3rd and 97th centiles in infancy and adolescence. CONCLUSION: Height, weight, BMI, and head circumference centiles aligned well with the Swiss 2026 growth references in Switzerland, demonstrating that hospital EHRs could contribute to future growth references.
Masters, N. B.; Farrar, K. G.; Holler, E.; Lancaster, J. M.
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Background: Vitamin K prophylaxis is universally recommended for newborns to prevent life threatening vitamin K deficiency bleeding. Although not on the immunization schedule, vitamin K prophylaxis is often coadministered with hepatitis B birth dose and erythromycin ophthalmic ointment, and rising hesitancy around vaccines/preventive care may spill over into vitamin K administration. Methods: We conducted a retrospective cohort study using Truveta electronic health record data with linked mother-child dyads. Live births to mothers aged 15-49 from January 1, 2019 through June 30, 2026 were included. Vitamin K administration was defined as documentation on the birth date or following day. Logistic regression assessed sociodemographic predictors of non-receipt, and interrupted time series analysis evaluated changes after January 2026. Results: Among 1,026,375 infants, 995,628 (96.97%) had documented vitamin K administration. Non-receipt increased from an average of 2.1% during 2019-2022 to 4.3% in 2025 and 6.1% in 2026, reaching 8.10% in June 2026. Older maternal age, non-Hispanic or Latino ethnicity, Medicaid or unknown insurance, and year of delivery were associated with greater odds of non-receipt. After January 2026, there was no immediate step change, but the odds of vitamin K receipt declined an additional 10% per month (OR: 0.90; 95% CI, 0.88-0.91). Conclusions: Vitamin K non-receipt increased over the study period and accelerated after January 2026. Because vitamin K recommendations were not changed by the January vaccine schedule, this association may reflect broader impacts to confidence in newborn preventive care. Future studies should examine causal mechanisms, parental decision-making, and associated clinical outcomes.
Honore, A.; Rech, T.; Scrivens, A.; Binotto, I.; Zandvoort, C. S.; van der Staaij, H.; Peck, M.; Zivanovic, S.; Stanworth, S. J.; Hartley, C.; Dame, C.; Deschmann, E.; the Neonatal Transfusion Network,
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Background and Objectives: Preterm infants are commonly transfused, yet direct cardiorespiratory effects of red blood cell (RBC) transfusions remain poorly understood. We explored the feasibility of using multicentre electronic health data (EHD) to study such cardiorespiratory responses. Methods: Highly granular routine EHD were collected from preterm infants born <32 weeks gestational age at three European centres. Heart rate, oxygen saturation, and respiratory rate were evaluated 12 hours before and after the RBC transfusion. Results: A total of 321 transfusions in 164 infants were analysed. Overall, there was no significant change in the rate of bradycardia and apnoea following transfusion. Cardiorespiratory parameters varied substantially between infants; e.g. 20% of transfusions were associated with an unexpected, significant increase in heart rate. Respiratory rate and oxygen saturation exhibited similarly heterogenous patterns following transfusion. In sub-group analysis, the proportion of transfusions with increased heart rate was significantly higher within the first two weeks than later (32% vs 13%, p=0.0019). Conclusions: Multicentre EHD extraction allows to identify otherwise masked short-term effects of RBC transfusions on cardiorespiratory parameters, possibly indicating cardiac or pulmonary overload. Such effects may vary with adaptation to anaemia. Analysing EHD may ultimately enable personalized transfusion practice.
Witham, M.; Evison, F.; Bellass, S.; Cooper, R.; Gallier, S.; Pretorius, S.; Sapey, E.; Suklan, J.; Sayer, A. A.
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Study Objective Little is known about where in hospital care for multiple long-term conditions (MLTC) is delivered. We aimed to describe pathways of care (ward transfers) and outcomes for people admitted to hospital for unscheduled care by MLTC status and other key sociodemographic characteristics. Design and setting Analysis of routinely-collected electronic health records from a large acute UK hospital. Participants Adult unscheduled care admissions from 1st July 2018 to 30th June 2019. The presence of two or more of 59 long-term conditions was ascertained using ICD-10 codes from previous hospital discharges. Main outcome measures Markov state transition probabilities were derived for ward moves and compared for MLTC vs no MLTC, age, sex, ethnicity and neighbourhood deprivation. Outcomes (length of stay, death, readmission, move from definitive ward) and time spent in emergency and assessment departments were compared between subgroups. Results A total of 33,252 adults, mean age 56.0 (SD 21.9) years were analysed; 14,834 (42.4%) had MLTC. People with MLTC were more likely to die in hospital (4.2 vs 1.9%, p<0.001), transfer to internal medicine wards or older peoples medicine wards, were less likely to transfer to surgical wards, had longer median length of stay (1.83 vs 0.69 days, p<0.001), stayed longer in acute medical units (15.5 vs 9.6 hours, p<0.001), and were more likely to move from their definitive ward (18.2 vs 16.4%, p=0.002). Conclusion Unscheduled hospital care pathways are complex and differ for people with MLTC, who have worse outcomes and may be less likely to receive optimal care.
Misha, B.; Dassie, G. A.; Mohammad, I.
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Background: Early trophic feeding promotes gut maturation, feeding tolerance, and growth in preterm neonates. However, delays remain common despite recommendations for initiation within 24 hours of birth, especially in resource-limited settings. Evidence on feeding initiation timing and predictors among Ethiopian preterm neonates is limited. Objective: To determine time to trophic feeding initiation and identify predictors among preterm neonates admitted to Adama Hospital Medical College, Ethiopia. Methods: A hospital-based retrospective cohort study was performed on 436 randomly chosen preterm neonates admitted to NICU. Data extraction was performed using a structured checklist. Time to trophic feeding initiation was analyzed using Kaplan-Meier estimates, log-rank tests, and bivariable and multivariable Cox regression models . Adjusted hazard ratios with 95% CIs were reported. Results:The sample comprised 416 preterm neonates, of whom 311 (74.8%) started trophic feeding during follow-up, and 105 (25.2%) were censored. The rate of initiation of trophic feeding was 1.92 per 100 person-hours (95% CI 1.72 to 2.15). Median time to initiation was 42 hours (interquartile range 24 to 50). Independent predictors of feeding initiation were determined by multivariable analysis and included gestational age, birth weight, maternal anaemia, respiratory distress syndrome and necrotising enterocolitis. Neonates born at 34-36 weeks had earlier initiation than those born at <34 weeks (AHR 1.39; 95 % CI 1.09 to 1.78). Similarly, neonates with a birth weight of [≥]1500 g had an earlier initiation than those with a birth weight of <1500 g (AHR 1.41; 95% CI 1.04 to 1.91). Delayed initiation was associated with maternal anaemia (AHR 0.70; 95% CI 0.51-0.95), respiratory distress syndrome (AHR 0.67; 95% CI 0.51-0.88) and necrotising enterocolitis (AHR 0.48; 95% CI 0.33-0.69). Conclusions: Delayed trophic feeding remains common among preterm neonates. Standardized feeding protocols, strengthened maternal care, and individualized nutrition strategies are needed to improve neonatal outcomes in study area.
Li, D.; Xie, J.; Xue, J.; Chen, H.; Wang, X.; Shen, C.
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Background Respiratory infections remain the leading infectious cause of death among children and adolescents, yet the share of these deaths that could be averted with currently feasible care is not routinely quantified. Existing amenable-mortality frameworks rely on cause lists and population-level mortality benchmarks and do not exploit information on how many episodes occur. We propose an episode-fatality-ratio (EFR) frontier approach and apply it to lower respiratory infections (LRI), whooping cough (pertussis) and upper respiratory infections (URI) in 204 countries, 1990-2023. Methods For each cause, country and year we computed EFR = deaths/incident episodes using Global Burden of Disease (GBD) 2023 estimates for ages 0-19 years. The frontier was defined as the 10th-percentile country EFR within each GBD super-region, cause and year; avoidable deaths = max(0, deaths - episodes x frontier EFR). Primary estimates are deterministic; 95% uncertainty intervals (UIs) come from 2,000 Monte Carlo draws. Sensitivity analyses varied the frontier percentile, applied an aspirational global frontier, constructed pertussis counterfactuals, and recomputed all estimates within the single under-5 age band. Results In 2023, 333,803 childhood deaths from lower respiratory infections (95% UI 289,123-417,460; 46.9% of LRI deaths) were avoidable. Summing the three causes deterministically gives 391,034 avoidable deaths (46.5% of 840,444); the combined figure is a deterministic sum, and a UI is available for the LRI component only. The pertussis (43,958; 39.0%) and URI (13,273; 81.0%) estimates are secondary: their deterministic point values fall below their own Monte Carlo intervals and the underlying death estimates carry very wide uncertainty (global pertussis UI 12,545-321,874). Avoidable deaths fell from 1,050,468 (44.9%) in 1990, but between 2019 and 2023 the avoidable share for LRI+URI barely moved (48.7% to 47.7%) while absolute avoidable deaths fell 14.5%, a pattern consistent with stalled convergence to the frontier. Sub-Saharan Africa plus South Asia held 73.1% of avoidable deaths in 2023 versus 41.8% in 1990; ten countries accounted for 59.1%. Conclusion Nearly half of childhood respiratory-infection deaths remain avoidable relative to within-region best practice, and the residual burden is increasingly concentrated in low-income settings. In the pertussis counterfactual, most countries kept pace with their regional frontier, so further gains require advancing the frontier itself through quality-of-care improvements.
Humphries, C.; Brett, J.; Gruber, F.; James, E.; McKendrick, T. I.; McNairn, K. C.; Miell, A.; O'Brien, R.; Rahman, F.; Schölin, L.; Stewart, M.; Casey, A.
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Objective To measure the accuracy of clinical coding, clinician review, and a locally deployed large language model (LLM) in identifying alcohol, drug, and self-harm involvement in emergency department (ED) attendances, and quantify prevalence. Design Two-phase diagnostic accuracy study. In a validation week, the identification strategies were assessed against a conflict-adjudicated reference standard (n=2,256); the LLM was then applied to n=105,096 annual attendances at the same site. Setting UK Type 1 Emergency Department treating patients [≥]16yrs. Main outcome measures Prevalence quantification compared with the reference standard; sensitivity, specificity, and balanced accuracy of each strategy; monthly identification rates and adjusted annual prevalence. Results The reference standard identified 12.1% of attendances as involving alcohol, drugs, or self-harm (coding 6.0%; clinician 10.0%, LLM 15.6%). LLM balanced accuracy matched or outperformed clinician review in all three domains (alcohol 0.942 v 0.930, p=0.635; drug 0.959 v 0.791, p<0.001; self-harm 0.982 v 0.908, p=0.004). Coding recorded 1.07 domains per identified patient against 1.32 in the reference standard. Adjusted annual prevalence corresponded to 12,890 domain involvements per year not identifiable in coded data. Subdomain classification found at least 81.6% of self-harm attendances required medical assessment for injury or overdose before psychiatric review. Conclusions Clinical coding identified fewer than half of presentations involving alcohol, drugs, and self-harm and rarely captured co-occurring domains; under-recording was present across a full year. A locally deployed LLM generated more complete structured data from existing clinical text within NHS infrastructure, at a scale which is not feasible for manual review.
Rabbani, N.; Mettner, J.; Lee, K.; Soto-Rivera, C. L.; Windberger, A.; Santiago, K.; Hatoun, J.; Correa, E. T.; Vernacchio, L.; Kohane, I.
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Routine childhood growth surveillance is a cornerstone of pediatric care. Growth pattern abnormalities are often early manifestations of chronic disease. Yet subtle abnormalities are frequently underrecognized, leading to diagnostic delays and avoidable morbidity. We introduce SPROUT (System for Pediatric Recognition Of Undiagnosed Trajectories), a generalized, multi-agent large language model (LLM) reasoning system designed to identify a broad spectrum of pediatric growth-related conditions from longitudinal electronic health records (EHRs) earlier than standard clinical practice. Using a large pediatric primary care EHR dataset, we developed and validated SPROUT as a two-stage system. First, a highly specific LLM screener flags concerning longitudinal growth patterns. Second, an Orchestrator module coordinates a multidisciplinary panel of LLM agents to generate a ranked differential diagnosis. To correct systemic reasoning errors, a Trainer module injects meta-knowledge into the panel via a dedicated "Learner" agent. Diagnostic capability was evaluated using a walk-forward, visit-by-visit simulation leading up to the diagnosis date. The SPROUT screener model achieved 98% (83/85) specificity and 28% (9/32) sensitivity on a gold-standard dataset of pediatric primary care patients when evaluated one year before the index date, and 100% specificity and 47% sensitivity when evaluated using longitudinal data up to the day of diagnosis. When applied to 300 control patients (i.e., healthy or undiagnosed), the screener flagged 15. Subsequent expert panel review confirmed high suspicion for undiagnosed pathology in 33% (5/15) of these cases. In chronological walk-forward validation on disease cases, the diagnostic engine identified conditions well before standard-of-care documentation. One year prior to clinical diagnosis, the system achieved sensitivities of 81% for type 1 diabetes mellitus, 56% for pituitary disorders, and 44% for celiac disease. The SPROUT multi-agent system demonstrates the ability to detect a significant portion of latent growth-related pediatric conditions months to years before current clinical standards while minimizing false positives. These results support its potential as a decision support tool for reducing diagnostic delays in pediatric care.
Chowdhury, A. R.; Chowdhury, B.
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Background: Consumer use of AI chatbots for health advice is rising, yet triage safety relative to established services remains unclear. Australia's Healthdirect, a government-backed symptom checker with 2.4 million uses in FY2024-25, remains unevaluated against frontier large language models (LLMs), and whether premium subscriptions improve triage safety remains unexplored. This study compared the triage accuracy and safety of Healthdirect against six LLM configurations across ChatGPT, Claude, and Gemini, assessed whether paid subscriptions improve triage safety, and characterised each system's error patterns. Methods: Forty-five clinical vignettes from the Semigran et al. benchmark spanning emergency, non-emergent, and self-care categories (15 each) were evaluated across seven systems. Healthdirect was tested following a seven-rule interaction protocol. LLMs were evaluated using first-person patient-language prompts under free-tier and paid-tier conditions. Outcomes were triage accuracy, emergency sensitivity, under-triage, and critical misses, analysed using Cochran's Q, Bonferroni-corrected McNemar tests, Cohen's kappa, and Wilson intervals. Findings: Triage accuracy differed significantly (Cochran's Q = 36.79, p < 0.001). Healthdirect achieved 48.9% accuracy (95% CI 35.0% to 63.0%; kappa = 0.233) versus 73.3% to 86.7% for LLMs (kappa = 0.600 to 0.800). Healthdirect operated under conservative interactive defaults while LLMs received complete information in a single prompt, which may have disadvantaged Healthdirect. Emergency sensitivity was 46.7% versus 80.0% to 86.7% for LLMs. Healthdirect produced two critical misses; no LLM produced any across 270 evaluations (95% CI 0% to 1.4%). When LLMs undertriaged, they recommended GP care rather than self-care. No tier differences were significant (all p > 0.05), and most systems over-triaged self-care cases. Interpretation: Frontier LLMs demonstrated higher triage accuracy and safer error profiles than Healthdirect. All LLMs avoided critical misses; Healthdirect did not. Premium subscriptions did not significantly improve triage safety. These findings support clinical governance decisions about whether LLMs warrant formal evaluation alongside government-backed symptom checkers.
Siddiq, A. I.; Saafu, I.; Borkor, E. T.; Vondee, E.; Sampana, F. T.; Okine, B.
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Background: Exclusive breastfeeding may protect infants against common infections and support healthy growth and development. Working mothers may face constraints on exclusive breastfeeding arising from work schedules, separation from their infants, and inadequate breastfeeding support. National evidence on the individual, healthcare-related, and contextual factors associated with exclusive breastfeeding among working Ghanaian mothers appears to remain limited. Design: Cross-sectional secondary analysis. Setting: Nationally representative survey covering urban and rural communities across all 16 administrative regions of Ghana. Participants: The analysis included 620 currently working mothers whose youngest living infants were aged 0-5 completed months and lived with them. The complete-case multivariable analysis included 619 mother-infant pairs. Primary outcome measure: Current exclusive breastfeeding, defined using the standard 24-hour infant-feeding indicator. Infants were classified as exclusively breastfed when they received breast milk without water, formula, animal milk, other liquids, or solid or semi-solid foods during the preceding day or night. Oral rehydration solution, vitamins, minerals and prescribed medicines were permitted. Aim: To estimate the prevalence of exclusive breastfeeding and examine its individual, healthcare-related and contextual correlates among working mothers of infants aged 0-5 months in Ghana. Methods: Birth Recode data from the 2022 Ghana Demographic and Health Survey were analysed. Unweighted frequencies and survey-weighted percentages described the study population. Design-adjusted Wald tests assessed bivariate associations. Survey-weighted binary logistic regression estimated adjusted odds ratios (AORs) and 95% confidence intervals (CIs), accounting for sampling weights, primary sampling units, and strata. Results: The survey-weighted prevalence of exclusive breastfeeding was 54.3% (95% CI: 49.2-59.3). Ethnicity, mode of delivery, region, and community poverty appeared to be statistically significant in the bivariate analyses. In the adjusted model, region was jointly associated with exclusive breastfeeding (p = 0.004). Mothers in the Northern (AOR = 4.93; 95% CI: 1.5-16.17) and Savannah (AOR = 4.22; 95% CI: 1.08-16.41) regions had higher odds than mothers in the Western Region. Mothers in low-education communities had lower odds than those in high-education communities (AOR = 0.54; 95% CI: 0.30-0.98). Although Guan mothers had higher odds than Akan mothers, the overall association with ethnicity was non-significant, and the estimate appeared imprecise. Maternal age, individual education, religion, parity, wealth, infant sex, antenatal care, postnatal care, and residence were not independently associated with exclusive breastfeeding. Conclusion: The prevalence estimate suggests that slightly more than half of working mothers exclusively breastfed their infants. Regional and community differences appeared more pronounced than those associated with most measured individual characteristics. Regionally responsive breastfeeding support and practical community education may contribute to improved coverage. Workplace recommendations require further evidence because employment conditions were not measured directly. Keywords: Exclusive breastfeeding; working mothers; infant feeding; maternal employment; regional inequalities; community education; Ghana; 2022 Ghana Demographic and Health Survey; survey-weighted analysis.
Yazdani, N. S.; Oakley, E.; Khan, A.; Qazi, M. F.; Khakwani, S.; Sheikh, A.; Mazhar, A.; Iqbal, U. M.; Marquis, J.; Liaqat, B.; Kumari, K.; Caniglia, E. C.; Hotwani, A.; Nisar, I.; Jehan, F.; Smith, E. R.; Hoodbhoy, Z.
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Background: Despite several trials on the hematological outcomes of intravenous (IV) iron in pregnancy, only few have examined its effect on birth outcomes. We estimated the causal effect of IV-iron on moderate or severe anaemia and birth outcomes. Methods: Women presenting to routine antenatal care in Pakistan with haemoglobin <10 g/dL were eligible for treatment. We used target trial emulation (TTE) methodology to estimate the effect of IV-iron treatment within 14 days of anaemia identification, compared to no treatment, on anaemia status at follow-up. A modified TTE analysis examined birth outcomes at delivery for singleton pregnancies, including birthweight, size-for-gestational-age, and mortality. We conducted a separate TTE for each of five gestational-age periods and pooled the results of each TTE. Results: We screened 3115 pregnancies of which 1715 were eligible for IV-iron; 1043 participants were treated during pregnancy. Those who received IV-iron had half the risk of moderate or severe anaemia in pregnancy compared with no treatment (pooled relative risk (RR) 0.40; 95% confidence interval (CI): 0.27, 0.59). The pooled effect of IV-iron on stillbirth suggested an 83% risk reduction (95% CI 55-94%), and trends were similar for perinatal and neonatal mortality. Conclusion: IV-iron treatment improved haematological status in pregnant women and was associated with a large reduction in stillbirth. Given limited data from randomised trials regarding fetal death and treatment earlier in pregnancy, this study contributes important information to the potential benefit of IV-iron in contexts where anaemia and its sequelae are a major public health problem.
Manikam, L.; Fatima, A.; Patil, P.; Mayadewi, C. A.; El Khatib, T.; Drazdzewska, J.; Oyebode, O.; Llewellyn, C. H.; Webb-Martin, K.; Irish, C.; Archibong, M.; Gilmour, J.; Kalungi, P.; Batura, N.; Shringarpure, K.; Lakhanpaul, M.; Heys, M.; NEON Steering Team,
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South Asian communities in the UK experience disproportionate maternal and child health inequalities linked to non-recommended infant feeding practices, limited health literacy, and socioeconomic constraints. Participatory learning and action (PLA) is effective in low- and middle-income countries, but high-income evidence is scarce. This pilot assessed the feasibility of a community facilitator-led PLA intervention to improve infant feeding among South Asian families in East London. A three-arm pilot feasibility cluster randomised controlled trial (ISRCTN10234623) was conducted in Tower Hamlets and Newham, East London (May-September 2022), with 12 wards randomised 1:1:1 to face-to-face PLA, online PLA, or usual care. Multilingual community facilitators delivered eight biweekly sessions over 14 weeks. Feasibility outcomes were assessed against prespecified Go/Stop criteria; exploratory outcomes included child feeding behaviours (Children's Eating Behaviour Questionnaire, CEBQ), parental feeding style (Parental Feeding Style Questionnaire, PFSQ), and child BMI Z-scores. Of 263 enrolled participants, 261 had a recorded trial arm allocation; consent to the pilot feasibility study was 70.7% (186/263; 95% CI 65.0-75.9%) meeting the [≥]50% Go criterion. Attendance was 37% (Tower Hamlets 59%, Newham 29%), below the [≥]80% Go threshold. Six-month retention was 54.8% (Tower Hamlets 78%, Newham 48.5%; 95% CI 41.8-55.3%), triggering the Definite Stop criterion. Significant baseline imbalances included BMI Z-score (p = 0.005), ethnicity, borough, and education; no between-arm BMI differences were observed at follow-up (p = 0.249). CEBQ and PFSQ baseline completion was 24.5% and 23.0%, with no usable follow-up data. PLA Phases 3 and 4 were not completed by any group; all participants providing feedback reported it acceptable. Recruitment was feasible and the intervention acceptable, but a Definite Stop criterion was triggered in Newham, no group completed the full PLA cycle, and outcome data were insufficient for evaluation. A definitive trial requires stratified randomisation, digitised multilingual data collection, participant reimbursement, and explicit PLA phase-completion criteria.
Hickman, R.; Joyce, D. W.; Gray, N.; Hampshire, A.; Hellyer, P. J.; Cai, Z.; Shergill, S.; D'Oliveira, T. C.
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Background Sleep, mood, and affective states are mutually connected. There is a paucity of studies, however, that have considered bidirectional relationships between daily sleep-affective dyads in naturalistic settings, particularly for shift workers. Objective To evaluate the dynamic and temporal interplay of daily smartphone-based self-reported sleep measurements, dimensions of affective experience and cognitive processing in UK shift working nurses. Methods The EClocker Study prospectively monitored 102 National Health Service (NHS) nurses (aged 25-61 years, 83.3% female) working standard (day shift) and non-standard (fast rotating shifts) schedules over a two-week period. Smartphone-based Experience Sampling Methodology (ESM) recorded daily sleep, mood, momentary affect and cognitive attentional functioning. Self-reported burnout, emotional dysregulation, emotion reactivity and affective dimensions (positive and negative) were also collected. Findings Overall, NHS nurses reported a high prevalence of depressive symptoms, stress, burnout and sleep-circadian rhythm disturbances. Generalised Additive Modelling (GAMs) revealed that NHS nurses higher perceived sleep quality predicted better next-day mood state, while better daytime mood was associated with reduced sleep onset latency, such that participants reported falling asleep faster. In contrast, daytime mood or affect (positive and negative) had no substantial, direct impact on nurses subjective sleep parameters (sleep quality, sleep duration, sleep efficiency). Exposure to fast rotating night shifts across the two-week study was associated with more frequent response errors on a Choice Reaction Time (CRT) cognitive task, while daytime somnolence did not adversely influence nurses momentary reaction time speeds or attentional function. Conclusions Clinically relevant sleep impairments, insomnia-related symptoms, elevated stress, and poor mood were pervasive in a sample of UK NHS nurses, regardless of shift type. Sleep quality impacted next-day mood and daytime mood impacted sleep latency, while rotating shifts led to an increase in cognitive errors. Recognising the impact of shiftwork and designing interventions to promote better sleep quality offer potential to enhance mood and performance in healthcare professionals. Clinical implications We need to implement and evaluate interventions that regularise sleep patterns and promote sleep quality to alleviate mood symptoms among frontline NHS shift workers.
Li, D.; Chen, H.; Xie, J.; Li, J.; Wang, X.; Shen, C.
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Background The historic decline in childhood pneumonia mortality was driven substantially by single-pathogen vaccines against Haemophilus influenzae type b (Hib) and Streptococcus pneumoniae. Yet the pathogen spectrum underlying child pneumonia deaths is diversifying: the effective number of pathogens rose from 5.57 in 1990 to 9.94 in 2023, and the residual burden is shifting toward opportunistic and hospital-associated pathogens for which no licensed childhood vaccines exist. This paper asks how resources should be sequenced between single-pathogen interventions and platform investments as this transition proceeds. Methods We analyzed Global Burden of Disease Study 2023 deaths from 29 pathogens in ages 0-19 years by super-region, combined with WHO/UNICEF Estimates of National Immunization Coverage (WUENIC) for PCV3 and Hib3. We quantified the spectrum transition under two denominators (26- and 29-pathogen calibers), constructed a share-by-intervenability matrix assigning each pathogen to a dominant intervention channel (vaccine-reachable, mixed, platform-sensitive) under explicit classification rules, compared platform-sensitive deaths with a transparently computed scenario of residual vaccine-preventable deaths, and cross-classified pathogens by age tropism and poverty lock. We anchored platform interventions to verified published evidence. Results The vaccine-preventable group share fell from 54.0% to 40.2% while the opportunistic/hospital group rose from 18.1% to 23.1% (29-pathogen caliber, 1990-2023). Super-region vaccine coverage showed no significant association with pathogen-share change (PCV3 Spearman rho = 0.108, p = 0.818; Hib3 rho = -0.036, p = 0.939), a null result we report as evidence that simple coverage-burden correlations do not hold at the regional level, not as evidence against vaccine value. In 2023, vaccine-reachable pathogens accounted for 441,410 deaths (45.7%, channel including COVID-19), mixed for 126,926 (13.1%), and platform-sensitive pathogens for 396,995 (41.1%). Platform-sensitive deaths were 2.9-5.1 times the scenario estimate of residual vaccine-preventable deaths (52,435-77,512). Nine of 14 classifiable pathogens fell into the poverty-locked, infant-tropic cell (480,922 deaths; Fisher OR = 9.0, p = 0.1758). Conclusions The marginal value of single-pathogen strategies declines as the spectrum diversifies and residual deaths concentrate in platform-sensitive, poverty-locked, infant-tropic pathogens. Vaccine scale-up remains a certain and sizeable opportunity; the next increment of marginal resources should increasingly fund platform capabilities (oxygen systems, antimicrobial access and stewardship, infection prevention and control, referral, and nutrition) delivered as a package to the populations where the residual burden is locked.
Marban-Castro, E.; Muhwava, L.; Girdwood, S.; Kemp, T.; Freitas, J.; Kamau, Y.; Otieno, M.; Akach, D.; Morato, A.; Sanz, S.; Fiechter, V.; Erkosar, B.; Watson, M.; Vetter, B.; Haldane, C.; Shilton, S.; Rheeder, P.; Dave, J. A.; Carrihill, M.; Karsas, M.
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Introduction: Continuous glucose monitoring (CGM) offers an advancement over traditional self-monitoring of blood glucose (SMBG) for people living with type 1 diabetes (T1D). However, evidence on the acceptability and feasibility of different CGM use cases in African populations remains limited. Methods: This was a pragmatic three-arm, randomised controlled trial on CGM conducted among people living with T1D in three public healthcare clinics in South Africa. Participants were assigned to Arm 1 (continuous CGM), Arm 2 (periodic CGM), or Arm 3 (SMBG). Diabetes education was provided at all study visits. Feasibility was assessed by adherence to CGM use and through the Glucose Monitoring Satisfaction Survey (GMSS). Diabetes distress was measured by the Diabetes Distress Scale (DDS), health-related quality of life (HRQoL) by the EQ-5D scales, and acceptability using the Theoretical Framework of Acceptability (TFA). Surveys were collected on paper and transferred to OpenClinica. Analyses were performed in R. The trial was registered in the Clinical Trials Registry (NCT05944718) on July 13, 2023. Results: A total of 83 participants were included in Arm 1, 85 in Arm 2, and 80 in Arm 3. CGM mean active time was 55% in Arm 1 versus 69% in Arm 2. The proportion of participants meeting the [≥]70% active time threshold was higher in Arm 2 (52%) than in Arm 1 (34%). Diabetes' distress declined across arms during the intervention period, with no significant difference between arms; distress increased slightly six months post-intervention but remained below baseline. At 6 months, glucose monitoring satisfaction was significantly higher in both CGM arms than in the SMBG arm, and satisfaction increased over time in CGM arms. Health-related quality of life remained stable across arms during the intervention period with no significant difference between arms. High acceptability was observed in both CGM arms, with higher ratings in the periodic arm. Conclusions: CGM was acceptable to people living with type 1 diabetes and feasible to use in public-sector clinics in South Africa, with high acceptability under continuous and periodic use. Health-related quality of life remained stable across arms, and diabetes-related distress declined, during the intervention period, across arms. Glucose monitoring satisfaction rose significantly in both CGM arms compared to SMBG. Periodic CGM might be a promising and potentially more scalable option than continuous use for public-sector care.
Chakraborty, R.; Rosenberg, M.; Weigel, M. M.; Pettifor, A.; Kahn, K.; Gomez-Olive, F. X.
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Purpose Despite the high documented prevalence of hunger and poor mental health in adolescent girls and young women (AGYW) in South Africa, this relationship remains understudied, with existing studies limited by their cross-sectional designs. This longitudinal study aimed to identify the association of hunger trajectories with anxiety and depressive symptoms, and hope in AGYW. Methods We used secondary data from the HIV Prevention Trials Network (HPTN) -068 conducted in rural Agincourt, South Africa. Complete data from 1779 AGYW collected at baseline (2011/12) and three annual follow-up visits were used. Hunger trajectories, measured using the Household Hunger Scale, were estimated via Group-Based Trajectory Modelling. Self-reported incident anxiety and depressive symptoms and hope were assessed based on AGYWs last two follow-up visits. Covariate adjusted modified Poisson regression models estimated the association between hunger trajectories and incident anxiety symptoms, incident depressive symptoms, and hope. Results Moderate-severe hunger was prevalent in 11.0%, 10.8%, and 6.0% of the households at baseline, follow-up 1, and 2, respectively. Incident anxiety symptoms were reported by 4.5%, incident depressive symptoms by 20.0% and hopelessness by 52.8% of the AGYW. Two hunger trajectories were identified- no hunger (82%) and marginal hunger (18%). Hunger trajectories were not associated with incident anxiety symptoms [RR:1.09, 95% CI: 0.55, 2.18], incident depressive symptoms [RR: 0.97; 95% CI: 0.72, 1.33] nor hope [RR: 1.00; 95% CI: 0.81, 1.23] in AGYW. Conclusion Better understanding of the factors that promote resiliency and mental health of AGYW in this setting is warranted to inform the design of interventions.
Ji, J.; Sun, Z.; Ying, X.; Hao, J.; Fu, Z.; Shi, D.; Kong, X.; Xu, Y.; Zhang, X.; Du, X.; Zhang, Z.; Liu, X.; Lin, P.; Wang, H.
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Background. Routine service databases are attractive sources of training labels for clinical prediction models, but the processes that write those labels are rarely audited before the labels are used. In a deployed community cognitive-screening programme, we audited the routine cognitive-status label, built a matrix of twenty-four model arms over the same patients under a specialist reference standard, and measured what each supervision choice bought or cost. Methods. The study cohort is the 672 individuals whose cognitive status was recorded by a titled (attending-or-above) physician, that record being the reference standard; after holding out one institution entirely, a development panel of 642 individuals at 38 institutions. The routine cognitive-status label these individuals also carry was first audited at the operator level: for each data-entry account we counted diagnoses entered and the proportion recording any impairment, and tested a competing bulk-timestamp explanation. Twenty-four arms span the supervision choices such a programme faces: an incumbent 21-variable logistic regression; local language models (Qwen2.5-1.5B/3B, Qwen3-4B/8B) zero-shot, with chain-of-thought, fine-tuned on physician labels, on routine labels with and without decontamination, or on a proxy scale-band task; preference-optimised (DPO) and reinforcement-trained (GRPO) variants; a proprietary frontier model queried zero-shot; and knowledge distillation of that frontier model into the regression and into the local 4B, using 943 teacher-labelled records from the programme's unlabelled pool. All arms are scored out-of-fold under one five-fold split grouped on registry-resolved institution clusters (no cluster spans a fold); paired contrasts use a 2,000-draw cluster bootstrap. Results. 181 operator accounts (each entering at least 100 diagnoses with zero recorded impairments) account for 45,315 rows - 40.5% of the outcome column; recorded impairment falls monotonically with account volume (15.7% for 1-9 rows to 0.7% for 500-999); a bulk-timestamp explanation was tested and refuted, identifying the write-time column as a migration artefact. Under the specialist standard, no locally fine-tuned arm beat the incumbent regression (AUROC 0.926): physician-label SFT reached 0.924 (4B), DPO 0.881, and GRPO 0.789; the pre-registered two-stage proxy-then-RL recipe was worse than its single-stage contaminated baseline (-0.030, 95% CI -0.077 to -0.004). Chain-of-thought reduced discrimination at every size (-0.072, -0.080, -0.041 at 1.5B/3B/4B; -0.012, n.s., at 8B). The frontier model scored 0.932 (vs. regression +0.007, n.s.). The distilled 4B reached 0.940 - above the incumbent (+0.014, 0.004 to 0.031) and above its own teacher (+0.008, 0.001 to 0.017) - with near-teacher calibration; it reached the teacher's level by 50 teacher labels and changed little beyond 200. Conclusions. The audit and the arm matrix support one deployment recipe: audit the routine label at the operator level before training on it; do not expect fine-tuning, preference optimisation, or reinforcement learning on a few hundred specialist cases to beat a well-calibrated regression; and if a frontier model is available but undeployable, spend a bounded number of queries on it as a labelling instrument and distil. A companion paper uses these frozen predictions to quantify how evaluation design choices compare with model choice.
Yao, R.; Wi, C.-I.; Beenken, M. J.; Watson, D.; Wheeler, P. H.; Finch, M.; Kelleher, D. P.; Anil, G.; Anderson, T.; Madden, K.; Okuno, S. H.; Odedina, F. T.; Westfall, E. C.; Park, E. Y.; Sharma, P.; Dugani, S.; Foss, R. M.; Hidaka, B. H.; Sosso, J. L.; Sabarish, S.; Singh, G.; Lugo-Fagundo, N.; Howick, J.; Kim, W. R.; Calvin, A. D.; Walker-Mcgill, C. L.; Rennert, L.; Juhn, Y. J.; Cerhan, J. R.; Lynch, B. A.
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Purpose: This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods: We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings: Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion: Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.
Wantakisha, E. W. R.; Nyirenda, S.; Narayani, M.
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Background Rural-urban disparities in SARS-CoV-2 infection epidemiology remain poorly quantified and understood in Zambia despite differences in healthcare access, services and preventive interventions. This study examined the geographical distribution and associated factors of SARS-CoV-2 cases across selected rural and urban districts of Zambia. Methods A convergent mixed-methods study comprised of quantitative survey and qualitative interviews was conducted in; Ndola (Urban), Kafue (Peri-urban) and Lufwanyama (Rural). The proximate determinant framework guided variable selection and interpretation. Quantitative combined (Hospital-surveillance data with community survey), while qualitative included In-depth interviews. Participants were sampled using multistage sampling technique. Quantitative data were analysed using STATA version 17, while qualitative data were analysed thematically. Findings were integrated through triangulation. Results A total of 528 participants were included, with a median age 31 years (15-71). Overall SARS-CoV-2 positivity was 12.6%, varying across rural (16.5%), peri-urban (14.9%), and urban (9.9%) settings, though residence was not associated with infection (P<0.132). Participants aged [≥]49 years had significantly higher odds of infection (aOR=8.78; 95% CI:1.15-66.99), whereas secondary education (aOR=0.37; 95% CI:0.16-0.86) and hospital-based testing (aOR=0.37; 95% CI:0.15-0.92) were associated with lower odds of infection. Vaccine uptake was highest in urban areas but was not independently associated with infection. Qualitative findings revealed marked rural-urban differences in perceived susceptibility, testing access, vaccine decision-making, and adherence to preventive measures, explaining several quantitative observations. Conclusion SARS-CoV-2 infection across rural and urban settings in Zambia was influenced by demographic, behavioral, and health-system factors rather than geographic residence alone. These findings highlight the need for context-specific prevention strategies, equitable access to testing, strengthened community surveillance, and targeted risk communication to improve preparedness and response for future respiratory disease outbreaks.
Hickman, R.; Joyce, D. W.; Gray, N.; Shergill, S.; D'Oliveira, T. C.
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Background: Shiftwork disrupts natural sleep-wake cycles, alters light exposure patterns, and contributes to circadian misalignment. Detrimental health consequences associated with shift work include elevated risk for metabolic disorders, cardiovascular disease, cancer and all-cause mortality. Healthcare workers have one of the highest rates of shift work exposure, yet there are relatively few non-pharmacological interventions (with good evidence) developed to improve sleep outcomes in this population. Objective: A pre-post pilot interventional study assessed the acceptability and perceived effectiveness of commercial noise-masking earbuds on improving subjective sleep characteristics among National Health Service (NHS) healthcare staff working fast rotating shifts. Methods: Noise-masking sleep earbuds (Kokoon NightBuds) were worn for a pilot six-week intervention by twenty-seven NHS nurses (aged 26-43 years, 88.9% female) working fast rotating shifts from the EClocker Study. Sensors inside the earbuds were paired with a smartphone app to monitor sleep. An audio library in the smartphone app delivered personalised relaxation exercises and sleep techniques drawn from cognitive behavioural therapy for insomnia (CBT-I). A pre-post two-week monitoring period with daily smartphone-based Experience Sampling Methods (ESM) captured perceived daily sleep patterns. Acceptability and perceived effectiveness of the earbuds in promoting better sleep outcomes was assessed. Results: Use of the noise-masking sleep earbuds over a six-week period was associated with positive sleep improvement trends and elicited promising acceptability. Almost two thirds of NHS fast rotating shift nurses (63%) subjectively reported reductions in general sleep disturbance symptoms (PSQI Global), one in four experienced perceived sleep quality improvements (SQ; 25.9%), one in five reported sleeping longer (TST; 22.2%), and a third perceived falling asleep faster (SOL; 33.3%), had better sleep efficiency (SE; 33.3%) and improved daytime dysfunction (33.3%) (PSQI subcomponent scores). Sleep diaries (CSD) collected daily using smartphone-based ESM also demonstrated small improvements post-sleep earbud use; nurses reported sleeping an average 18 minutes longer (TST) and fell asleep more easily, on average 11 minutes faster (SOL). Sleep earbuds were generally well tolerated; 56% of nurses reported the earbuds as (somewhat to very) helpful, 52% reported (somewhat to strongly) falling asleep more easily (SOL), 44% felt (somewhat to strongly) their sleep quality was improved (SQ) and 30% agreed (somewhat to strongly) they slept longer (TST) and had less disturbed sleep. Conclusions: To our knowledge, this is the first study in Europe to pilot noise-masking earbuds as a potential non-pharmacological aid to improve sleep-wake behaviours or mitigate fatigue for healthcare staff. Preliminary results showed promising acceptability and (small) perceived sleep improvement trends following a targeted six-week earbud intervention in NHS fast rotating shift nurses.