莫希比利大学卫生与联合科学学院

Abstract Background Low 5-minute Apgar scores remain an important indicator of compromised neonatal status and may assist in identifying high-risk newborns in resource-constrained or high-volume labour ward settings. Accurate prediction of newborns at risk could guide timely intrapartum and immediate postpartum interventions. Because risk factors vary by maternal parity, prediction models may benefit from a parity-specific approach. This study aimed to develop and internally validate two prognostic models for predicting low 5-minute Apgar scores, stratified by parity. Methods The analysis used data from 124,376 singleton births at or beyond 28 weeks of gestation, recorded between July 2021 and December 2023 across 16 hospitals in Benin, Malawi, Tanzania and Uganda. Model predictors were selected using a knowledge-based approach, and multivariable logistic regression was performed. Model performance was assessed through calibration and discrimination with internal validation conducted using bootstrapping. The predicted outcome was the 5-minute Apgar score, categorised as low (< 7) or normal (≥ 7). Results In the overall study population, 6.3% of newborns received a low Apgar score. The final nulliparous and parous models included 14 and 19 predictor parameters, respectively, with country included as an additional fixed effect. The models demonstrated moderate optimism-adjusted performance, with C-statistics of 0.663 for the nulliparous model (95% CI: 0.654–0.675) and 0.732 for the multiparous model (95% CI: 0.724–0.740). Calibration was excellent in both models, with calibration-in-the-large (CITL) values of 0.000–0.001 and calibration slopes of 0.989–0.995. Antepartum haemorrhage and severe anaemia were the strongest contributors in both models. Conclusions Two prediction models for low 5-minute Apgar scores, one for nulliparous and one for parous women, demonstrated moderate predictive ability. External validation and further testing are necessary to assess the generalisability and clinical utility of these models.

Introduction: Achieving viral suppression is central to HIV epidemic control; however, routine viral load (VL) testing in many low- and middle-income countries is constrained by laboratory capacity, logistics, and cost. In Tanzania, disparities in VL coverage persist across age groups and geographical regions, limiting the timely detection of treatment failure. Pharmacy refill adherence is a low-cost, routinely collected objective indicator of treatment behavior. This study assessed whether pharmacy refill adherence, enhanced using machine learning (ML) models, can reliably predict viral suppression among people living with HIV (PLHIV) in Tanzania. Methods: We conducted a retrospective analysis using nationally representative patient-level data from the Care and Treatment Center (CTC-2) database, collected between 2017 and 2021. A random sample of 40,000 records was drawn, of which 28,044 patients met the inclusion criteria. Pharmacy refill adherence was calculated as the proportion of days covered and capped at 100%. Viral suppression was defined as a VL of <1,000 copies/mL. Logistic regression, Random Forest, Gradient Boosting Machine (GBM), and XGBoost models were trained using an 80/20 training-testing split, and the model performance was evaluated using the area under the receiver operating characteristic curve (AUC). Youden's Index was used to determine the optimal adherence threshold. Results: Among the 28,044 patients included in the analysis, the median age at ART initiation was 38 years, and 64.9% were female. The median pharmacy refill adherence was 90.64% (mean, 87.37%). Viral load (VL) measurements were available for 21,572 patients, of whom 88.7% achieved viral suppression. Higher pharmacy refill adherence was strongly associated with viral suppression, whereas lower adherence was observed among adolescents, young adults, and individuals who were lost to follow-up. Marked geographic variation was observed, with higher adherence in regions such as Dar es Salaam and lower adherence in more remote regions, including Rukwa and Singida. Among machine learning models, XGBoost demonstrated the highest predictive performance (AUC >0.85), followed by Gradient Boosting Machines and Random Forest, while logistic regression provided stable baseline estimates. Pharmacy refill adherence, duration of follow-up, clinic visit frequency, and patient age were the strongest predictors of viral suppression. Conclusion: Pharmacy refill adherence is a strong predictor of viral suppression and provides a feasible and cost-effective tool for monitoring ART outcomes in settings with limited VL testing. Machine learning approaches further enhance the predictive value of routine program data and can support the early identification of patients at risk of virological failure. Integrating adherence-based predictive analytics into national HIV program monitoring systems may strengthen differentiated service delivery, improve treatment outcomes, and accelerate progress toward the UNAIDS 95-95-95 targets in Tanzania and similar resource-limited settings. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Meshack D. Lugoba received a small Sida-supported grant administered through Muhimbili University of Health and Allied Sciences (MUHAS), which contributed to capacity building but did not influence the study design, data analysis, interpretation of results, or the decision to publish. Data access and institutional support were provided by the National AIDS and Sexually Transmitted Infections Control Programme (NASHCOP) and MUHAS. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical clearance for this study was obtained from the Directorate of Research and Publication of the Muhimbili University of Health and Allied Sciences (MUHAS) with reference number DA.282/298/01.C/. The NASHCOP administration granted permission to collect the data. Strict privacy and confidentiality were maintained throughout the study. Only de-identified data were used, and patient IDs, names, or other personally identifiable information were not collected from the patients. Data collection adhered to national and international ethical standards, particularly regarding the handling of sensitive health information. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The Government of Tanzania owns the data used in this study through NASHCOP, and they are not publicly available. The de-identified analytical code and derived output can be made available from the corresponding author upon reasonable request and subject to NASHCOP approval.

Invertebrates are increasingly consumed and kept as pets, research models, and in zoological exhibits, creating a growing need to better understand their clinical management and welfare. However, the knowledge regarding nociception, pain perception, and euthanasia in invertebrates remains limited, and standardized protocols are largely absent. Current guidelines are incomplete, often anecdotal, and omit several major invertebrate phyla. To address this gap, we conducted a narrative review of the literature, aiming to critically evaluate existing euthanasia methods, associated welfare implications, and opportunities for refinement. The amount of peer-reviewed species-specific literature is limited and scattered. In addition, most described methods are insufficiently studied and/or do not align with our definition of euthanasia. Based on the available literature, and to provide practical guidance despite these limitations, we propose a two-step approach to invertebrate euthanasia. The first step consists of inducing anesthesia to achieve loss of responsiveness, followed by a second step; a terminal procedure involving physical or chemical destruction of the brain or major ganglia. Our review focuses on the application of this two-step approach. The effectiveness and humaneness of euthanasia techniques vary considerably across taxa and life stages. Substantial further research is required to validate and optimize humane end-of-life procedures for diverse invertebrate species.

Postpartum haemorrhage (PPH) is a leading cause of maternal death. Preventing PPH can spare women from experiencing the trauma and risks of PPH, reduce the strain on overstretched health systems, and probably produce better outcomes than a strategy solely focused on PPH treatment. Prevention of PPH is often interpreted as provision of uterotonic drugs to contract the uterus at the time of childbirth. Although uterotonics are a central strategy for PPH prevention, several other approaches can prevent PPH or ameliorate its severity. These approaches include addressing the unmet need for contraception, remedying anaemia and other modifiable risk factors for PPH, optimising medical conditions that predispose to PPH, and tackling the rise in caesarean births in many countries. Effective delivery of preventive care requires early and regular antenatal care and planned birth at appropriately resourced health facilities. Social and behavioural change interventions for improving contraceptive provision and uptake, targeting adolescents, postpartum women, geographically remote communities, and families on low income, are a priority. Effective interventions to tackle anaemia include the management of heavy menstrual bleeding, pre-pregnancy or antenatal haemoglobin testing and oral or intravenous iron treatment, dietary improvements, and-on rare occasions-blood transfusion. Risk factors for PPH that need attention include high BMI, multiple pregnancy, gestational diabetes, pre-eclampsia, macrosomia, and several medical conditions. Caesarean births are associated with a substantial increase in PPH risk and should therefore only be done when medically indicated. A Cochrane network meta-analysis of 122 trials, with 121 931 women, found that the combinations of oxytocin plus misoprostol, or oxytocin plus ergometrine, were the most effective prophylaxis for PPH when given at the time of childbirth; however, these combinations had a higher risk of side-effects compared with single-drug prophylaxis. Oxytocin and carbetocin were the most effective single drugs for PPH prophylaxis, with minimal side-effects. Single uterotonic prophylaxis with either oxytocin or carbetocin is, therefore, recommended for routine prophylaxis. However, if oxytocin or carbetocin is not accessible, misoprostol is an alternative. Combination prophylaxis with oxytocin plus misoprostol can be considered for women at high risk of PPH. Ergometrine alone and oxytocin plus ergometrine combination are no longer recommended due to hypertension-related safety concerns. A robust implementation approach that engages various stakeholders to promote change, ensures the supply of quality-assured medicines and devices, provides training and support, and secures ongoing political and financial commitment is necessary to translate evidence into global impact.

Introduction Sub-Saharan Africa (SSA) bears the highest global burden of neonatal mortality, a problem continued by the widespread ‘know-do gap’, the failure to translate evidence-based guidelines into practice. Tanzania’s 2019 national neonatal care guideline illustrates this challenge, as its impact remains unevaluated despite stagnant mortality rates. A systematic mapping of implementation evidence, including its rates, determinants and improvement strategies, is urgently needed to identify gaps and inform actionable policies across SSA.Methods and analysis This scoping review will be conducted in accordance with the Joanna Briggs Institute methodology. We will systematically search six electronic databases (MEDLINE (PubMed), Embase, CINAHL (EBSCOhost), Web of Science, Cochrane Library and African Journals Online) and the grey literature from 1 January 2000 to 31 December 2025. Two reviewers will independently screen records using PCC criteria (Population: healthcare workers/systems; Concept: guideline implementation; Context: SSA/Tanzania). Data will be charted and analysed using descriptive statistics and deductive thematic analysis guided by the Consolidated Framework for Implementation Research and the Expert Recommendations for Implementing Change taxonomy.Ethics and dissemination Ethical approval is not required as this synthesis uses published data. Findings will be disseminated through a peer-reviewed journal manuscript, conference presentations, integration into a PhD thesis and tailored outputs for policymakers (policy brief) and frontline workers (clinical implementation brief) in Tanzania.Trial registration This protocol is registered with the Open Science Framework (https://doi.org/10.17605/OSF.IO/3FMBG).