Despite international efforts to address women’s long-term health and well-being, significant gaps in sexual and reproductive health (SRH) services and non-communicable diseases (NCDs) prevention remain, particularly in low-and-middle-income countries (LMICs).

We analysed data from 726 278 women aged 15–49 from six national surveys (2017–2021, Benin, Cameroon, Gabon, India, Madagascar and Mauritania) on unmet needs for NCD prevention (blood pressure, glucose, cervical cancer screening) and SRH services (contraception, antenatal, postnatal care). Unmet needs prevalence was calculated as the percentage of participants with specific unmet needs and estimated across demographics and socioeconomic groups using multivariable logistic regression models.

Unmet needs were strikingly high for NCD prevention: 36.6% for blood pressure, 70.0% for blood glucose and 98.5% for cervical cancer screening. In contrast, unmet needs for contraception, antenatal care and postnatal care were relatively lower: 7.5%, 14.5% and 14.5%, respectively. Significant variations were observed across countries. India had the lowest unmet needs for SRH services: 6.7% for contraception, 13.1% for antenatal care and 13.1% for postnatal care. Gabon had lower unmet needs for prenatal (16.8%) and postnatal care (14.8%) compared with other African countries and the lowest unmet need for cervical screening at 84.7% (95% confidential interval 83.1% to 86.2%), over 10 percentage points lower than others. Furthermore, socioeconomic factors like higher education, better economic status, healthcare access, insurance and internet use significantly lowered unmet needs, especially for antenatal and postnatal care. Employed women had higher unmet needs for antenatal (35.7%) and postnatal (37.3%) care than unemployed women (28.1%, 27.8%) but lower for NCDs prevention (98.9%, 71.8%) under two definitions than unemployed women (99.3%, 79.2%).

This study highlights the urgent need to address high unmet needs for NCD prevention among women in LMICs, particularly cervical cancer screening. Unmet SRH needs are also a major concern, given significant disparities across countries. Especially, governments should prioritise measures to focus on vulnerable groups.

To develop and validate a predictive model for assessing in-hospital mortality in patients with intra-abdominal sepsis (IAS), a leading cause of sepsis.

Secondary analysis of two retrospective critical care databases.

Data extracted from the Intensive Care Medicine Information Marketplace IV (MIMIC-IV) and the eICU Collaborative Research Database.

Patients with IAS from MIMIC-IV (2008–2019; 1300 patients, 264 deaths) for model training and internal validation, and eICU (2014–2015; 149 patients, 33 deaths) for external validation.

Clinical data were used for constructing a predictive model. Variable selection was performed using least absolute shrinkage and selection operator regression, followed by model development with multivariable logistic regression. The model was visualised as a nomogram.

The primary outcome was in-hospital mortality. Secondary outcomes were model performance metrics, including the area under the receiver operating characteristic curve (AUC), calibration curves, decision curve analysis and clinical impact curves.

Six predictors (lactate, age, activated partial thromboplastin time, blood urea nitrogen, total bilirubin and platelets) were identified. The predictive model showed good performance with an AUC of 0.795 (95% CI 0.758 to 0.831) in the training set (n=910) and 0.846 (95% CI 0.772 to 0.919) in the external validation set (n=149).

A robust predictive model was developed to estimate the risk of in-hospital mortality in patients with IAS. This tool may assist clinicians in enhancing patient management and decision-making.