PLOS Medicine

Background Perioperative stroke is a serious and potentially fatal complication following non-cardiac surgery. Thus, it is important to identify the risk factors and develop an effective prognostic model to predict the incidence of perioperative stroke following non-cardiac surgery. Methods and findings We identified potential risk factors and built a model to predict the incidence of perioperative stroke using logistic regression derived from hospital registry data of adult patients that underwent non-cardiac surgery from 2008 to 2019 at The First Medical Center of Chinese PLA General Hospital. Our model was then validated using the records of two additional hospitals to demonstrate its clinical applicability. In our hospital cohorts, 223,415 patients undergoing non-cardiac surgery were included in this study with 525 (0.23%) patients experiencing a perioperative stroke. Thirty-three indicators including several intraoperative variables had been identified as potential risk factors. After multi-variate analysis and stepwise elimination (P < 0.05), 13 variables including age, American Society of Anesthesiologists (ASA) classification, hypertension, previous stroke, valvular heart disease, preoperative steroid hormones, preoperative β-blockers, preoperative mean arterial pressure, preoperative fibrinogen to albumin ratio, preoperative fasting plasma glucose, emergency surgery, surgery type and surgery length were screened as independent risk factors and incorporated to construct the final prediction model. Areas under the curve were 0.893 (95% confidence interval (CI) [0.879, 0.908]; P < 0.001) and 0.878 (95% CI [0.848, 0.909]; P < 0.001) in the development and internal validation cohorts. In the external validation cohorts derived from two other independent hospitals, the areas under the curve were 0.897 and 0.895. In addition, our model outperformed currently available prediction tools in discriminative power and positive net benefits. To increase the accessibility of our predictive model to doctors and patients evaluating perioperative stroke, we published an online prognostic software platform, 301 Perioperative Stroke Risk Calculator (301PSRC). The main limitations of this study included that we excluded surgical patients with an operation duration of less than one hour and that the construction and external validation of our model were from three independent retrospective databases without validation from prospective databases and non-Chinese databases. Conclusions In this work, we identified 13 independent risk factors for perioperative stroke and constructed an effective prediction model with well-supported external validation in Chinese patients undergoing non-cardiac surgery. The model may provide potential intervention targets and help to screen high-risk patients for perioperative stroke prevention.

Background In late March 2020, the Mexican government announced an updated norm to include front-of-pack warning labels for packaged foods and non-alcoholic beverages. Warning labels came into effect in October 2020. To avoid displaying warning labels, producers can reformulate their products by reducing the content of calories or critical nutrients targeted by the policy (added sugars, saturated fat, and sodium) or removing non-caloric sweeteners or added caffeine. The objective of this study is to assess changes in the percentage of products above warning-label cutoffs for calories and critical nutrients and changes in the content of calories and critical nutrients associated with warning labels in Mexico. Methods and findings We used nutritional panel data collected by the Mexican National Institute of Public Health from ≈1,000 top-purchased products, which represented ≥60% of the market share for each of the included food groups according to household purchases in the Nielsen Consumer Panel commercial dataset for Mexico in 2016. Nutritional panel data is available for three periods: 2016−2017, T0 (pre-policy); Jul–Sep 2020, T1 (post-warning-label announcement); and Feb–Apr 2021, T2 (post-warning-label implementation). We assessed changes in T1 versus T0 (potential anticipatory reformulation before the warning-label implementation) and T2 versus T0 (reformulation after the warning-label implementation) by food group using generalized estimating equations for the percentage of products above warning-label cutoffs or containing non-caloric sweeteners or added caffeine, and fixed-effects linear models and quantile regressions for the content of calories and critical nutrients. Included food groups were cereal-based desserts, bread and other cereals, salty snacks, sweetened beverages, solid dairy, liquid dairy, instant food, and candies. At T0, the food group level with the lowest percentage of products with at least one calorie/nutrient content above warning-label cutoffs was instant food (77.8%); at T2, this fell to 52.6%. Based on our statistical models, we found that all food groups showed reductions in at least one type of warning label. The most common reductions in the percentage of products exceeding warning-label cutoffs were for sodium (up to −63.1 percentage points for bread and other cereals; 95% CI: −77.5, −48.6; p-value < 0.001), saturated fat (up to −26.3 percentage points for salty snacks; 95% CI: −35.8, −16.8; p-value < 0.001), and products containing non-caloric sweeteners (up to −29.0 percentage points for solid dairy; 95% CI: −40.7, −17.2; p-value < 0.001). The reductions in products above warning-label cutoffs were coupled with reductions in products’ content of calories and critical nutrients. According to quantile regressions, these reductions mostly occurred at the 50th–75th percentiles. Product reformulation mainly occurred in T2. Conclusion Our findings show product reformulation due to reductions in critical nutrients/calories after the warning-label policy implementation, which entails improving the nutritional profile of the packaged food and beverage supply in Mexico.

Background The direct and indirect impacts of the COVID-19 pandemic on life expectancy (LE) and years of life lost with and without disability remain unclear. Accounting for pre-pandemic trends in morbidity and mortality, we assessed these impacts in 18 European countries, for the years 2020–2022. Methods and Findings We used multi-state Markov modeling based on several data sources to track transitions of the population aged 35 or older between eight health states from disease-free, combinations of cardiovascular disease, cognitive impairment, dementia, and disability, through to death. We quantified separately numbers and rates of deaths attributable to COVID-19 from those related to mortality from other causes during 2020–2022, and estimated the proportion of loss of life expectancy and years of life with and without disability that could have been avoided if the pandemic had not occurred. Estimates were disaggregated by COVID-19 versus non-COVID causes of deaths, calendar year, age, sex, disability status, and country. We generated the 95% uncertainty intervals (UIs) using Monte Carlo simulations with 500 iterations. Among the 289 million adult population in the 18 countries, person-years of life lost (PYLL) in millions were 4.7 (95% UI 3.4–6.0) in 2020, 7.1 (95% UI 6.6–7.9) in 2021, and 5.0 (95% UI 4.1–6.2) in 2022, totaling 16.8 (95% UI 12.0–21.8) million. PYLL per capita varied considerably between the 18 countries ranging between 20 and 109 per 1,000 population. About 60% of the total PYLL occurred among persons aged over 80, and 30% in those aged 65–80. If the pandemic were avoided, over half (9.8 million (95% UI 4.7–15.1)) of the 16.8 million PYLL were estimated to have been lived without disability. Of the total PYLL, 11.6–13.2 million were due to registered COVID-19 deaths and 3.6–5.3 million due to non-COVID mortality. Despite a decrease in PYLL attributable to COVID-19 after 2021, PYLL associated with other causes of death continued to increase from 2020 to 2022 in most countries. Lower income countries had higher PYLL per capita as well as a greater proportion of disability-free PYLL during 2020–2022. Similar patterns were observed for life expectancy. In 2021, LE at age 35 (LE-35) declined by up to 2.8 (95% UI 2.3–3.3) years, with over two-thirds being disability-free. With the exception of Sweden, LE-35 in the studied countries did not recover to 2019 levels by 2022. Conclusions The considerable loss of life without disability and the rise in premature mortality not directly linked to COVID-19 deaths during 2020–2022 suggest a potential broader, longer-term and partially indirect impact of the pandemic, possibly resulting from disruptions in healthcare delivery and services for non-COVID conditions and unintended consequences of COVID-19 containment measures. These findings highlight a need for better pandemic preparedness in Europe, ideally, as part of a more comprehensive global public health agenda.

Background Diarrhea and growth faltering in early childhood reduce survival and impair neurodevelopment. We assessed whether a national program combining (i) funds for latrine and water upgrades; (ii) institutional strengthening; and (iii) behavior change campaigns reduced diarrhea and stunting, and strengthened local institutions. Methods and Findings We collaborated with program implementers to conduct a cluster-randomized controlled trial in four provinces of the Democratic Republic of Congo (DRC). Three hundred thirty-two rural villages were grouped into 121 clusters to minimize geographic spillovers. Between 15 March and 30 June 2018, we randomly assigned, after stratifying by province and cluster size, 50 intervention and 71 control clusters. Masking of participants and interviewers was not possible. Primary outcomes were length-for-age Z-score among children under 5 years of age, caregiver-reported diarrhea in last 7 days among children under 5 years of age, and an index of community WASH institutions. The primary analysis was on an intention-to-treat basis, using a binary variable indicating whether the participant was in an intervention or control cluster. Three thousand two hundred eighty-three households were interviewed between November 2022 and April 2023, median 3.6 years post-intervention. The intervention had no effect on diarrhea (adjusted mean difference −0.01 [95% −0.05 to 0.03]). Diarrhea prevalence was high overall, at 38% in the treatment group and 42% in the control group. The intervention had no effect on length-for-age Z-scores in children (adjusted mean difference −0.01 [95% CI −0.15 to 0.12]). In the control group, the mean length-for-age Z-score was −2.18 (1.60 SD). Villages in the intervention group had a 0.40 higher score on the WASH institutions index (95% CI 0.16–0.65). The percentage of villages in the intervention group with an active water, sanitation, and hygiene (or just water) committee was 21 pp higher than the control group. Households in the intervention group were 24 pp (95% CI 12–36) more likely to report using an improved water source, 18 pp (95% CI 10–25) more likely to report using an improved sanitation facility, and reported more positive perceptions of water governance (adjusted difference 0.19 SD [95% CI 0.04–0.34]). The trial had several limitations, including incomplete (86%) adherence in the implementation group, the absence of baseline measures, and the reliance on self-reported outcomes for some measures. Conclusions The DRC’s national rural WASH program increased access to improved water and sanitation infrastructure, and created new WASH institutions, all of which persisted for at least 3.6 years. However, these effects were not sufficient to reduce diarrhea or growth faltering. Trial registration The Pan African Clinical Trials Registry PACTR202102616421588 (https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=14670). The American Economics Association RCT registry AEARCTR-0004648 (https://www.socialscienceregistry.org/trials/4648).

Background Malaria in pregnancy detected by microscopy is associated with maternal anaemia, reduced fetal growth, and preterm birth, but the effects of lower density (i.e., submicroscopic) malaria infections are poorly characterised. This analysis was undertaken to investigate associations between submicroscopic malaria at the first antenatal care (ANC) visit and these adverse pregnancy events on the Thailand–Myanmar border. Methods Blood samples taken from refugee and migrant pregnant women presenting for their first ANC visit were analysed retrospectively for malaria using ultrasensitive PCR (uPCR, limit of detection 22 parasites/mL). The relationships between submicroscopic malaria and subsequent microscopically detectable malaria, anaemia, birth weight, and preterm birth were evaluated using inverse probability weighting for stratified random sampling. Results First ANC visit samples from 4,352 asymptomatic women (median gestational age 16.5 weeks) attending between October 1st 2012 and December 31st 2015 were analysed. The weighted proportion of women with submicroscopic malaria infection was 4.6% (95% CI 3.9–5.6), comprising 59.8% (49.5–69.4) Plasmodium vivax, 6.5% (4.0–10.5) Plasmodium falciparum, 1.8% (0.9–3.6) mixed, and 31.9% (22.2–43.5) infections which could not be speciated. Submicroscopic parasitaemia at first ANC visit was associated with subsequent microscopically detected malaria (adjusted hazard ratio [HR] 12.9, 95% CI 8.8–18.8, p < 0.001) and lower birth weight (adjusted predicted mean difference −275 g, 95% CI −510 to −40, p = 0.022). There was no association with preterm birth. Submicroscopic P. falciparum mono-infection (adjusted HR 2.8, 95% CI 1.2–6.6, p = 0.023) and coinfection with P. falciparum and P. vivax (adjusted HR 10.3, 95% CI 2.6–40.4, p = 0.001) was associated with increased risk of maternal anaemia, but submicroscopic P. vivax mono-infection was not. That uPCR was conducted for only a part of the cohort due to cost constraints is a limitation. Conclusions In low transmission settings, uPCR identifies substantially more malaria infections at antenatal screening than conventional diagnostic methods. On the Thailand–Myanmar border, submicroscopic malaria at first antenatal consultation was associated with higher risks of microscopically diagnosed malaria later in pregnancy, anaemia, and reduced birth weight.

Background Polygenic risk scores (PRSs) have been extensively developed for cancer risk prediction in European populations, but their effectiveness in the Chinese population remains uncertain. Methods and findings We constructed 80 PRSs for the 13 most common cancers using seven schemes and evaluated these PRSs in 100,219 participants from the China Kadoorie Biobank (CKB). The optimal PRSs with the highest discriminatory ability were used to define genetic risk, and their site-specific and cross-cancer associations were assessed. We modeled 10-year absolute risk trajectories for each cancer across risk strata defined by PRSs and modifiable risk scores and quantified the explained relative risk (ERR) of PRSs with modifiable risk factors for different cancers. More than 60% (50/80) of the PRSs demonstrated significant associations with the corresponding cancer outcomes. Optimal PRSs for nine common cancers were identified, with each standard deviation increase significantly associated with corresponding cancer risk (hazard ratios (HRs) ranging from 1.20 to 1.76). Compared with participants at low genetic risk and reduced modifiable risk scores, those with high genetic risk and elevated modifiable risk scores had the highest risk of incident cancer, with HRs ranging from 1.97 (95% confidence interval (CI): 1.11–3.48 for cervical cancer, P = 0.020) to 8.26 (95% CI: 1.92–35.46 for prostate cancer, P = 0.005). We observed nine significant cross-cancer associations for PRSs and found the integration of PRSs significantly increased the prediction accuracy for most cancers. The PRSs contributed 2.6%–20.3%, while modifiable risk factors explained 2.3%–16.7% of the ERR in the Chinese population. Conclusions The integration of existing evidence has facilitated the development of PRSs associated with nine common cancer risks in the Chinese population, potentially improving clinical risk assessment.

Background Electronic health records (EHRs) are increasingly used to investigate health inequalities across ethnic groups. While there are some studies showing that the recording of ethnicity in EHR is imperfect, there is no robust evidence on the accuracy between the ethnicity information recorded in various real-world sources and census data. Methods and findings We linked primary and secondary care NHS England data sources with Census 2021 data and compared individual-level agreement of ethnicity recording in General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR), Hospital Episode Statistics (HES), Ethnic Category Information Asset (ECIA), and Talking Therapies for anxiety and depression (TT) with ethnicity reported in the census. Census ethnicity is self-reported and, therefore, regarded as the most reliable population-level source of ethnicity recording. We further assessed the impact of multiple approaches to assigning a person an ethnic category. The number of people that could be linked to census from ECIA, GDPPR, HES, and TT were 47.4m, 43.5m, 47.8m, and 6.3m, respectively. Across all 4 data sources, the White British category had the highest level of agreement with census (≥96%), followed by the Bangladeshi category (≥93%). Levels of agreement for Pakistani, Indian, and Chinese categories were ≥87%, ≥83%, and ≥80% across all sources. Agreement was lower for Mixed (≤75%) and Other (≤71%) categories across all data sources. The categories with the lowest agreement were Gypsy or Irish Traveller (≤6%), Other Black (≤19%), and Any Other Ethnic Group (≤25%) categories. Conclusions Certain ethnic categories across all data sources have high discordance with census ethnic categories. These differences may lead to biased estimates of differences in health outcomes between ethnic groups, a critical data point used when making health policy and planning decisions.

In June 2024, Gavi, the Vaccine Alliance, launched a preventive vaccination program against Ebola virus disease (EVD). This marks a historic shift in the management of EVD, allowing at-risk countries across sub-Saharan Africa to request support in implementing preventive vaccination campaigns. This perspective piece shares considerations that can inform how countries approach preventive EVD vaccination and potential unintended consequences. It also provides insights into strategies for vaccines against other epidemic-prone pathogens.

Background An accurate prognostic tool is essential to aid clinical decision-making (e.g., patient triage) and to advance personalized medicine. However, such a prognostic tool is lacking for acute pancreatitis (AP). Increasingly machine learning (ML) techniques are being used to develop high-performing prognostic models in AP. However, methodologic and reporting quality has received little attention. High-quality reporting and study methodology are critical for model validity, reproducibility, and clinical implementation. In collaboration with content experts in ML methodology, we performed a systematic review critically appraising the quality of methodology and reporting of recently published ML AP prognostic models. Methods/findings Using a validated search strategy, we identified ML AP studies from the databases MEDLINE and EMBASE published between January 2021 and December 2023. We also searched pre-print servers medRxiv, bioRxiv, and arXiv for pre-prints registered between January 2021 and December 2023. Eligibility criteria included all retrospective or prospective studies that developed or validated new or existing ML models in patients with AP that predicted an outcome following an episode of AP. Meta-analysis was considered if there was homogeneity in the study design and in the type of outcome predicted. For risk of bias (ROB) assessment, we used the Prediction Model Risk of Bias Assessment Tool. Quality of reporting was assessed using the Transparent Reporting of a Multivariable Prediction Model of Individual Prognosis or Diagnosis—Artificial Intelligence (TRIPOD+AI) statement that defines standards for 27 items that should be reported in publications using ML prognostic models. The search strategy identified 6,480 publications of which 30 met the eligibility criteria. Studies originated from China (22), the United States (4), and other (4). All 30 studies developed a new ML model and none sought to validate an existing ML model, producing a total of 39 new ML models. AP severity (23/39) or mortality (6/39) were the most common outcomes predicted. The mean area under the curve for all models and endpoints was 0.91 (SD 0.08). The ROB was high for at least one domain in all 39 models, particularly for the analysis domain (37/39 models). Steps were not taken to minimize over-optimistic model performance in 27/39 models. Due to heterogeneity in the study design and in how the outcomes were defined and determined, meta-analysis was not performed. Studies reported on only 15/27 items from TRIPOD+AI standards, with only 7/30 justifying sample size and 13/30 assessing data quality. Other reporting deficiencies included omissions regarding human–AI interaction (28/30), handling low-quality or incomplete data in practice (27/30), sharing analytical codes (25/30), study protocols (25/30), and reporting source data (19/30). Conclusions There are significant deficiencies in the methodology and reporting of recently published ML based prognostic models in AP patients. These undermine the validity, reproducibility, and implementation of these prognostic models despite their promise of superior predictive accuracy. Registration Research Registry (reviewregistry1727)

Background Pregnant women with twins and a short cervical length (CL) are at greater risk of preterm birth (PTB). The comparative efficacy of cervical cerclage and cervical pessary with or without additional progesterone to prevent PTB is unknown. We aimed to assess, in women with twin pregnancies and a short CL, the effectiveness of cerclage versus pessary and the additional treatment with 400 mg vaginal progesterone versus no progesterone in preventing PTB. Methods and findings This multicenter, two-by-two factorial randomised trial was conducted in 2 hospitals in Ho Chi Minh City, Vietnam. Asymptomatic women with twin pregnancies and a CL ≤28 mm at 16 to 22 gestational weeks were recruited. Between March 2019 and July 2023, we randomised 219 participants (64.4% of the planned sample size) to cerclage plus progesterone (n = 55), Arabin pessary plus progesterone (n = 56), cerclage alone (n = 54) or Arabin pessary alone (n = 54). Primary outcome was any PTB <34 weeks. Following the second interim analysis, the study was terminated due to significantly lower rates of perinatal deaths and deliveries <28 weeks in the cerclage group. The primary outcome occurred in 20 (19.8%) participants receiving cerclage versus 20 (19%) participants receiving pessary (relative risk [RR] 1.04; 95% confidence interval [CI], 0.60 to 1.8). Delivery <28 weeks occurred in 1% versus 8.6% (RR 0.12; 95% CI, 0.01 to 0.52) and perinatal death occurred in 1% versus 5.8% (RR 0.17; 95% CI, 0.05 to 0.62) in the cerclage group and the pessary group, respectively. However, PTB <24 weeks, <32 weeks, and other neonatal outcomes were not significantly different between the 2 groups. For maternal side effects, vaginal discharge was significantly less frequent in the cerclage group. In participants allocated to progesterone, PTB <34 weeks occurred in 19 (18.4%) versus 21 (20.4%) participants who did not have progesterone (RR 0.90; 95% CI, 0.52 to 1.6). Conclusions In this prematurely halted study on pregnant women with twins and a CL ≤28 mm, cerclage and cervical pessary were comparably effective on PTB <34 weeks prevention. However, compared to pessary, cerclage was associated with significantly lower rates of PTB <28 weeks and perinatal mortality. ClinicalTrials.gov Registration: NCT03863613 (https://clinicaltrials.gov/study/NCT03863613)

Background Depression is associated with a range of adverse physical health outcomes. We aimed to quantify the association between depression and the subsequent rate of accrual of long-term physical health conditions in middle and older age. Methods and findings We included 172,556 participants from the UK Biobank (UKB) cohort study, aged 40–71 years old at baseline assessment (2006–2010), who had linked primary care data available. Using self-report, primary care, hospital admission, cancer registry, and death records, we ascertained 69 long-term physical health conditions at both UKB baseline assessment and during a mean follow-up of 6.9 years. We used quasi-Poisson models to estimate associations between history of depression at baseline and subsequent rate of physical condition accrual. Within our cohort, 30,770 (17.8%) had a history of depression. Compared to those without depression, participants with depression had more physical conditions at baseline (mean 2.9 [SD 2.3] versus 2.1 [SD 1.9]) and accrued additional physical conditions at a faster rate (mean 0.20 versus 0.16 additional conditions/year during follow-up). After adjustment for age and sex, participants with depression accrued physical morbidities at a faster rate than those without depression (RR 1.32, 95% confidence interval [CI] [1.31, 1.34]). After adjustment for all sociodemographic characteristics, the rate of condition accrual remained higher in those with versus without depression (RR 1.30, 95% CI [1.28, 1.32]). This association attenuated but remained statistically significant after additional adjustment for baseline condition count and social/lifestyle factors (RR 1.10, 95% CI [1.09, 1.12]). The main limitation of this study is healthy volunteer selection bias, which may limit generalisability of findings to the wider population. Conclusions Middle-aged and older adults with a history of depression have more long-term physical health conditions at baseline and accrue additional physical conditions at a faster rate than those without a history of depression. Our findings highlight the importance of integrated approaches to managing both mental and physical health outcomes.

Background The high cost of prescription drugs in the United States is maintained by brand-name manufacturers’ competition-free period made possible in part through patent protection, which generic competitors must challenge to enter the market early. Understanding the predictors of these challenges can inform policy development to encourage timely generic competition. Identifying categories of drugs systematically overlooked by challengers, such as those with low market size, highlights gaps where unchecked patent quality and high prices persist, and can help design policy interventions to help promote timely patient access to generic drugs including enhanced patent scrutiny or incentives for challenges. Our objective was to characterize and assess the extent to which market size and other drug characteristics can predict patent challenges for brand-name drugs. Methods and findings This cross-sectional study included new patented small-molecule drugs approved by the FDA from 2007 to 2018. Market size, patent, and patent challenge data came from IQVIA MIDAS pharmaceutical quarterly sales data, the FDA’s Orange Book database, and the FDA’s Paragraph IV list. Predictive models were constructed using random forest and elastic net classification. The primary outcome was the occurrence of a patent challenge within the first year of eligibility. Of the 210 new small-molecule drugs included in the sample, 55% experienced initiation of patent challenge within the first year of eligibility. Market value was the most important predictor variable, with larger markets being more likely to be associated with patent challenges. Drugs in the anti-infective therapeutic class or those with fast-track approval were less likely to be challenged. The limitations of this work arise from the exclusion of variables that were not readily available publicly, will be the target of future research, or were deemed beyond the scope of this project. Conclusions Generic competition does not occur with the same timeliness across all drug markets, which can leave granted patents of questionable merit in place and sustain high brand-name drug prices. Predictive models may help direct limited resources for post-grant patent validity review and adjust policy when generic competition is lacking.

Background Rwandan individuals bordering the Democratic Republic of the Congo (DRC) are at-risk of Ebola virus disease. A 2019 to 2021 vaccination campaign called UMURINZI offered a Janssen Vaccines & Prevention B.V. 2-dose heterologous Ebola vaccine regimen (Ad26.ZEBOV, MVA-BN-Filo) to Rwandan individuals aged ≥2 years and not pregnant. In this region with high rates of pregnancy, preventing pregnancy until their second dose of the Ebola vaccine is essential to ensure full protection. This analysis describes contraceptive use, pregnancy incidence, serious adverse events (SAE), and the effect of pregnancy and SAE on receipt of the second dose among women in the UMURINZI vaccination campaign. Methods and findings During the vaccination campaign, women who were fertile and sexually active were counseled as part of the campaign by trained UMURINZI nursing staff about preventing pregnancy until dose two (56 days post-dose one) and offered contraception. Women were followed up to their second dose appointment. Contraception, pregnancy incidence, and SAE were recorded. Of the 47,585 fertile and sexually active women, the mean age was 28·0 years (standard deviation 9·9 years), 54·7% (n = 26,051) were from Rubavu and 45·3% (n = 21,534) were from Rusizi, and 71·9% (n = 34,158) had not crossed the DRC border in the last year. Sixty-six percent (66·6%, n = 31,675) were not using modern contraception at baseline and 19·1% (n = 9,082) were using hormonal implants, 10·9% (n = 5,204) injectables, 2·9% (n = 1,393) oral contraceptive pills (OCPs), and 0·5% (n = 231) intrauterine devices. After contraceptive counseling, 8·0% (n = 2,549) of non-users initiated a method of contraception and 3·6% (n = 50) of OCP users switched to a more effective method. Of the 969 incident pregnancies detected after dose one, 18·8% (n = 182) resulted in an obstetric SAE, primarily due to spontaneous abortion which occurred in 16·0% (n = 155) of all incident pregnancies. Other obstetric SAE included 14 blighted ova, 9 stillbirths, 1 termination due to hydrops fetalis, 1 cleft palate, and 2 threatened abortions resulting in normal deliveries. Six pregnant women had a non-obstetric SAE (0·6%), including 1 postpartum death from COVID-19 and 5 hospitalizations. Among the 74,002 women without an incident pregnancy detected after dose one, 0·01% (n = 4) had an SAE; 2 were fatalities due to hypertension and diabetes in one case and seizures in the other, and the other 2 were hospitalizations. No SAE were determined to be related to the vaccine by the program physicians. Among the 74,002 women without an incident pregnancy detected after dose one, 94·6% (n = 69,986) received dose two; in contrast, among the 969 women with an incident pregnancy detected after dose one, 34·5% (n = 334) received dose two after pregnancy completion. Conclusions Many fertile and sexually active women who sought vaccination during UMURINZI were not using contraception prior to vaccination, and contraceptive method uptake after family planning counseling and method provision was low. Most women who became pregnant after the first vaccination dose did not receive the second dose, thus potentially reducing protection against Ebola. Family planning messaging for this context should be developed and pilot-tested. The estimated risk of spontaneous abortion was similar to previous estimates from Rwanda and other African countries.

This Perspective article from Rebecca Grais and colleagues places a recently published study in PLOS Medicine in the context of the evolving landscape of vaccines and pregnancy.

Background Gonorrhea is the second most common sexually transmitted disease notified in Singapore in 2023. Evidence suggests that the 4CMenB vaccine designed to protect against Neisseria meningitidis infection may offer partial cross-protection against gonorrhea. This generated interest in using 4CMenB for the purpose of staving gonorrhea transmission. We explored the efficacy of potential gonorrhea vaccination strategies in the context of historically declining gonorrhea incidence. Methods and findings We employed an integrated transmission-dynamic model, calibrated using Bayesian methods to local surveillance data to understand the potential public health impact of 4CMenB in reducing gonorrhea acquisition and transmission in men who have sex with men (MSM) in Singapore. We explored the efficacy of implementing six vaccination programmes: (1) offering vaccination to all male adolescents in schools (vaccination before entry [VbE]), (2) offering vaccination to individuals attending sexual health clinics for testing (vaccination on attendance [VoA]), (3) offering vaccination to individuals attending sexual health clinics and who were diagnosed with gonorrhea (vaccination on diagnosis [VoD]), or (4) vaccination according to risk (VaR), by offering vaccination to patients who were diagnosed with gonorrhea plus individuals who tested negative, but report having more than five sexual partners per year. We further examined how altering (5) VoA and (6) VoD strategies changed if the strategies only targeted high risk groups (VoA(H),VoD(H)). We assessed efficacy by examining vaccination impact relative to no vaccination and when behavioral parameters were held constant. We further ascertained the effects of varying vaccine uptake (10%, 33%, 100%), vaccine efficacy (22%, 31%, 47%), and duration of protection (1.5, 4, 7.5 years) on the effectiveness of each vaccination strategy. For a hypothetical 10-year vaccination programme, VbE had 14.18% of MSM gonorrhea cases averted over the time the programme was implemented. VoA had the highest protective impact on the MSM population with 40.26% averted cases (95% credible interval (CrI): 18.32%−52.57%), but required more vaccine doses than any other strategy. VoD had a smaller impact (12.04% averted cases (95% CrI: 7.12%−15.00%)), but was three times more efficient than VoA in terms of averted cases per dose. VoA(H) and VoD(H) improved the efficiency of VoA and VoD strategies by increasing averted cases per dose to 0.22 and 0.24 respectively, but conferred similar protective effects as VoA (VoA(H): 40.10% averted cases (95% CrI: 18.14%−52.55%)) and VoD (VoD(H): 12.04% averted cases (95% CrI: 7.12%−15.00%)), respectively. VaR (40.10% averted cases (95% CrI: 18.14%−52.55%)) had almost the same impact as VoA, but was more efficient by requiring administration of fewer doses than VoA, with 0.21 (95% CrI: 0.12–0.27) averted cases per dose. Sensitivity analyses indicated that VaR had the greatest public health impact with the highest number of averted cases per dose for vaccines of any efficacy or duration of protection (or both), although VoD and VoD(H) saved more vaccine resource and had the highest number averted MSM cases per dose for highly protective vaccines of long protection. Conclusions Vaccination of MSM against gonorrhea, according to risk in sexual health clinics in Singapore, can be considered to reduce gonorrhea acquisition and transmission. Development of gonorrhea-specific vaccines which focuses on protective efficacy and the implementation of efficient vaccination programmes can maximize public health impact.

Background Pressure injuries (PIs) pose a substantial healthcare burden and incur significant costs worldwide. Several risk prediction tools to allow timely implementation of preventive measures and a subsequent reduction in healthcare system burden are available and in use. The ability of risk prediction tools to correctly identify those at high risk of PI (prognostic accuracy) and to have a clinically significant impact on patient management and outcomes (effectiveness) is not clear. We aimed to evaluate the prognostic accuracy and clinical effectiveness of risk prediction tools for PI and to identify gaps in the literature. Methods and findings The umbrella review was conducted according to Cochrane guidance. Systematic reviews (SRs) evaluating the accuracy or clinical effectiveness of adult PI risk prediction tools in any clinical settings were eligible. Studies on paediatric tools, sensor-only tools, or staging/diagnosis of existing PIs were excluded. MEDLINE, Embase, CINAHL, and EPISTEMONIKOS were searched (inception to June 2024) to identify relevant SRs, as well as Google Scholar (2013 to 2024) and reference lists. Methodological quality was assessed using adapted AMSTAR-2 criteria. Results were described narratively. We identified 26 SRs meeting all eligibility criteria with 19 SRs assessing prognostic accuracy and 11 assessing clinical effectiveness of risk prediction tools for PI (4 SRs assessed both aspects). The 19 SRs of prognostic accuracy evaluated 70 tools (39 scales and 31 machine learning (ML) models), with the Braden, Norton, Waterlow, Cubbin-Jackson scales (and modifications thereof) the most evaluated tools. Meta-analyses from a focused set of included SRs showed that the scales had sensitivities and specificities ranging from 53% to 97% and 46% to 84%, respectively. Only 2/19 (11%) SRs performed appropriate statistical synthesis and quality assessment. Two SRs assessing machine learning-based algorithms reported high prognostic accuracy estimates, but some of which were sourced from the same data within which the models were developed, leading to potentially overoptimistic results. Two randomised trials assessing the effect of PI risk assessment tools (within the full test-intervention-outcome pathway) on the incidence of PIs were identified from the 11 SRs of clinical effectiveness; both were included in a Cochrane SR and assessed as high risk of bias. Both trials found no evidence of an effect on PI incidence. Limitations included the use of the AMSTAR-2 criteria, which may have overly focused on reporting quality rather than methodological quality, compounded by the poor reporting quality of included SRs and that SRs were not excluded based on low AMSTAR-2 ratings (in order to provide a comprehensive overview). Additionally, diagnostic test accuracy principles, rather than prognostic modelling approaches were heavily relied upon, which do not account for the temporal nature of prediction. Conclusions Available systematic reviews suggest a lack of high-quality evidence for the accuracy of risk prediction tools for PI and limited reliable evidence for their use leading to a reduction in incidence of PI. Further research is needed to establish the clinical effectiveness of appropriately developed and validated risk prediction tools for PI.

Background Although X-rays are not recommended for routine diagnosis of osteoarthritis (OA), clinicians and patients often use or expect X-rays. We evaluated whether: (i) a radiographic diagnosis and explanation of knee OA influences patient beliefs about management, compared to a clinical diagnosis and explanation that does not involve X-rays; and (ii) showing the patient their X-ray images when explaining radiographic report findings influences beliefs, compared to not showing X-ray images. Methods and findings This was a 3-arm randomised controlled trial conducted between May 23, 2024 and May 28, 2024 as a single exposure (no follow-up) online survey. A total of 617 people aged ≥45 years, with and without chronic knee pain, were recruited from the Australian-wide community. Participants were presented with a hypothetical scenario where their knee was painful for 6 months and they had made an appointment with a general practitioner (primary care physician). Participants were randomly allocated to one of 3 groups where they watched a 2-min video of the general practitioner providing them with either: (i) clinical explanation of knee OA (no X-rays); (ii) radiographic explanation (not showing X-ray images); or (iii) radiographic explanation (showing X-ray images). Primary comparisons were: (i) clinical explanation (no X-rays) versus radiographic explanation (showing X-ray images); and (ii) radiographic explanation (not showing X-ray images) versus radiographic explanation (showing X-ray images). Primary outcomes were perceived (i) necessity of joint replacement surgery; and (ii) helpfulness of exercise and physical activity, both measured on 11-point numeric rating scales (NRS) ranging 0 to 10. Compared to clinical explanation (no X-rays), those who received radiographic explanation (showing X-ray images) believed surgery was more necessary (mean 3.3 [standard deviation: 2.7] versus 4.5 [2.7], respectively; mean difference 1.1 [Bonferroni-adjusted 95% confidence interval: 0.5, 1.8]), but there were no differences in beliefs about the helpfulness of exercise and physical activity (mean 7.9 [standard deviation: 1.9] versus 7.5 [2.2], respectively; mean difference −0.4 [Bonferroni-adjusted 95% confidence interval: −0.9, 0.1]). There were no differences in beliefs between radiographic explanation with and without showing X-ray images (for beliefs about necessity of surgery: mean 4.5 [standard deviation: 2.7] versus 3.9 [2.6], respectively; mean difference 0.5 [Bonferroni-adjusted 95% confidence interval: −0.1, 1.2]; for beliefs about helpfulness of exercise and physical activity: mean 7.5 [standard deviation: 2.2] versus 7.7 [2.0], respectively; mean difference −0.2 [Bonferroni-adjusted 95% confidence interval: −0.7, 0.3]). Limitations of our study included the fact that participants were responding to a hypothetical scenario, and so findings may not necessarily translate to real-world clinical situations, and that it is unclear whether effects would impact subsequent OA management behaviours. Conclusions An X-ray–based diagnosis and explanation of knee OA may have potentially undesirable effects on people’s beliefs about management. Trial registration ACTRN12624000622505.

Background Preeclampsia is a potentially life-threatening pregnancy complication. Among women whose pregnancies are complicated by preeclampsia, the Preeclampsia Integrated Estimate of RiSk (PIERS) models (i.e., the PIERS Machine Learning [PIERS-ML] model, and the logistic regression-based fullPIERS model) accurately identify individuals at greatest or least risk of adverse maternal outcomes within 48 h following admission. Both models were developed and validated to be used as part of initial assessment. In the United Kingdom, the National Institute for Health and Care Excellence (NICE) recommends repeated use of such static models for ongoing assessment beyond the first 48 h. This study evaluated the models’ performance during such consecutive prediction. Methods and findings This multicountry prospective study used data of 8,843 women (32% white, 30% black, and 26% Asian) with a median age of 31 years. These women, admitted to maternity units in the Americas, sub-Saharan Africa, South Asia, Europe, and Oceania, were diagnosed with preeclampsia at a median gestational age of 35.79 weeks between year 2003 and 2016. The risk differentiation performance of the PIERS-ML and fullPIERS models were assessed for each day within a 2-week post-admission window. The PIERS adverse maternal outcome includes one or more of: death, end-organ complication (cardiorespiratory, renal, hepatic, etc.), or uteroplacental dysfunction (e.g., placental abruption). The main outcome measures were: trajectories of mean risk of each of the uncomplicated course and adverse outcome groups; daily area under the precision-recall curve (AUC-PRC); potential clinical impact (i.e., net benefit in decision curve analysis); dynamic shifts of multiple risk groups; and daily likelihood ratios. In the 2 weeks window, the number of daily outcome events decreased from over 200 to around 10. For both PIERS-ML and fullPIERS models, we observed consistently higher mean risk in the adverse outcome (versus uncomplicated course) group. The AUC-PRC values (0.2–0.4) of the fullPIERS model remained low (i.e., close to the daily fraction of adverse outcomes, indicating low discriminative capacity). The PIERS-ML model’s AUC-PRC peaked on day 0 (0.65), and notably decreased thereafter. When categorizing women into multiple risk groups, the PIERS-ML model generally showed good rule-in capacity for the “very high” risk group, with positive likelihood ratio values ranging from 70.99 to infinity, and good rule-out capacity for the “very low” risk group where most negative likelihood ratio values were 0. However, performance declined notably for other risk groups beyond 48 h. Decision curve analysis revealed a diminishing advantage for treatment guided by both models over time. The main limitation of this study is that the baseline performance of the PIERS-ML model was assessed on its development data; however, its baseline performance has also undergone external evaluation. Conclusions In this study, we have evaluated the performance of the fullPIERS and PIERS-ML models for consecutive prediction. We observed deteriorating performance of both models over time. We recommend using the models for consecutive prediction with greater caution and interpreting predictions with increasing uncertainty as the pregnancy progresses. For clinical practice, models should be adapted to retain accuracy when deployed serially. The performance of future models can be compared with the results of this study to quantify their added value.

Background Accelerating improvements in maternal and newborn health (MNH) care is a major public health priority in Kenya. While use of formal health care has increased, many pregnant and postpartum women do not receive the recommended number of maternal care visits. Even when they do, visits are often short with many providers not offering important elements of evaluation and counseling, leaving gaps in women’s knowledge and preparedness. Digital health tools have been proposed as a complement to care that is provided by maternity care facilities, but there is limited evidence of the impact of digital health tools at scale on women’s knowledge, preparedness, and the content of care they receive. We evaluated a digital health platform (PROMPTS (Promoting Mothers in Pregnancy and Postpartum Through SMS)) composed of informational messages, appointment reminders, and a two-way clinical helpdesk, which had enrolled over 750,000 women across Kenya at the time of our study, on 6 domains across the pregnancy-postpartum care continuum. Methods and findings We conducted an unmasked, 1:1 parallel arm cluster randomized controlled trial in 40 health facilities (clusters) across 8 counties in Kenya. A total of 6,139 pregnant individuals were consented at baseline and followed through pregnancy and postpartum. Individuals recruited from treatment facilities were invited to enroll in the PROMPTS platform, with roughly 85% (1,453/1,700) reporting take-up. Our outcomes were derived from phone surveys conducted with participants at 36 to 42 weeks of gestation and 7 to 8 weeks post-childbirth. Among eligible participants, 3,399/3,678 women completed antenatal follow-up and 5,509/6,128 women completed postpartum follow-up, with response rates of 92% and 90%, respectively. Outcomes were organized into 6 domains: knowledge, birth preparedness, routine care seeking, danger sign care seeking, newborn care, and postpartum care content. We generated standardized summary indices to account for multiple hypothesis testing but also analyzed individual index components. Intention-to-treat analyses were conducted for all outcomes at the individual level, with standard errors clustered by facility. Participants recruited from treatment facilities had a 0.08 standard deviation (SD) (95% CI [0.03, 0.12]; p = 0.002) higher knowledge index, a 0.08 SD (95% CI [0.02, 0.13]; p = 0.018) higher birth preparedness index, a 0.07 SD (95% CI [0.03, 0.11]; p = 0.003) higher routine care seeking index, a 0.09 SD (95% CI [0.07, 0.12]; p < 0.001) higher newborn care index, and a 0.06 SD (95% CI [0.01, 0.12]; p = 0.043) higher postpartum care content index than those recruited from control facilities. No significant effect on the danger sign care seeking index was found (95% CI [−0.01, 0.08]; p = 0.096). A limitation of our study was that outcomes were self-reported, and the study was not powered to detect effects on health outcomes. Conclusions Digital health tools indicate promise in addressing shortcomings in pregnant and postpartum women’s health care, amidst systems that do not reliably deliver a minimally adequate standard of care. Through providing women with critical information and empowering them to seek recommended care, such tools can improve individuals’ preparation for safe childbirth and receipt of more comprehensive postpartum care. Future work is needed to ascertain the impact of at-scale digital platforms like PROMPTS on health outcomes. Trial Registration ClinicalTrials.gov ID: NCT05110521; AEA RCT Registry ID: R-0008449

Background Understanding the effects of balanced energy and protein (BEP) supplements on gestational weight gain (GWG) and how the effects differ depending on maternal characteristics and the nutritional composition of the supplements will inform the implementation of prenatal BEP interventions. Methods and findings Individual participant data from 11 randomized controlled trials of prenatal BEP supplements (N = 12,549, with 5,693 in the BEP arm and 6,856 in the comparison arm) in low- and middle-income countries were used. The primary outcomes included GWG adequacy (%) and the estimated total GWG at delivery as continuous outcomes, and severely inadequate (<70% adequacy), inadequate GWG (<90% adequacy), and excessive GWG (>125% adequacy) as binary outcomes; all variables were calculated based on the Institute of Medicine recommendations. Linear and log-binomial models were used to estimate study-specific mean differences or risk ratios (RRs), respectively, with 95% confidence intervals (CIs) of the effects of prenatal BEP on the GWG outcomes. The study-specific estimates were pooled using meta-analyses. Subgroup analyses were conducted by individual characteristics. Subgroup analyses and meta-regression were conducted for study-level characteristics. Compared to the comparison group, prenatal BEP led to a 6% greater GWG percent adequacy (95% CI: 2.18, 9.56; p = 0.002), a 0.59 kg greater estimated total GWG at delivery (95% CI, 0.12, 1.05; p = 0.014), a 10% lower risk of severely inadequate GWG (RR: 0.90; 95% CI: 0.83, 0.99; p = 0.025), and a 7% lower risk of inadequate GWG (RR: 0.93; 95% CI: 0.89, 0.97; p = 0.001). The effects of prenatal BEP on GWG outcomes were stronger in studies with a targeted approach, where BEP supplements were provided to participants in the intervention arm under specific criteria such as low body mass index or low GWG, compared to studies with an untargeted approach, where BEP supplements were provided to all participants allocated to the intervention arm. Conclusions Prenatal BEP supplements are effective in increasing GWG and reducing the risk of inadequate weight gain during pregnancy. BEP supplementation targeted toward pregnant women with undernutrition may be a promising approach to delivering the supplements.

Background A higher risk of placenta previa after assisted reproductive technology (ART) is well established. The underlying mechanisms are poorly understood, but may relate to embryo culture duration, cryopreservation, and cause of infertility. Within-mother analyses, where each woman is her own control (i.e., sibling design), help disentangle treatment contributions from maternal confounders that are stable between pregnancies. We aimed to investigate the risk of placenta previa in pregnancies achieved after ART according to embryo culture duration, cryopreservation, and infertility factors while accounting for stable maternal factors using within-mother analyses. Methods and findings We used linked nationwide registry data from Denmark (1994 to 2014), Finland (1990 to 2014), Norway (1988 to 2015), and Sweden (1988 to 2015). All women who gave their first birth during the study period at age 20 years or older were eligible and contributed up to 4 deliveries (singleton or multifetal) occurring between 22 and 44 weeks of gestation, excluding deliveries where maternal age exceeded 45 years. We used multilevel logistic regression to compare risk of placenta previa after ART (n = 139,694 deliveries) versus natural conception (n = 5,614,512 deliveries), both at the population level and within mothers, adjusting for year of delivery, maternal age, parity, and country. We categorized ART according to culture duration, embryo cryopreservation, and infertility factors. Population level risk of placenta previa was higher for ART versus natural conception (odds ratio [OR], 4.16; 95% confidence interval [CI], 3.96–4.37). Controlling for stable maternal factors, the association attenuated, but risk remained higher for ART versus natural conception (OR within mothers, 2.64; 95% CI, 2.31–3.02). Compared to naturally conceived, a larger difference in risk was seen for pregnancies from fresh embryos than for pregnancies from frozen embryos. Further categorization by culture duration showed the largest risk difference after fresh blastocyst transfer, and the smallest after frozen cleavage stage embryo transfer, which persisted in sensitivity analyses (including restriction to singletons). When stratified according to infertility factors at the population level, women with endometriosis conceiving by ART had the highest risk of placenta previa (OR, 9.35; 95% CI, 8.50–10.29), whereas women with polycystic ovary syndrome (PCOS) conceiving by ART had the lowest risk (OR, 1.52; 95% CI, 1.12–2.09), compared to natural conception. Within mothers, we found a higher risk of placenta previa after ART compared to natural conception for women with endometriosis (OR, 2.08; 95% CI, 1.50–2.90), but not for women with PCOS (OR, 0.88; 95% CI, 0.41–1.89 [unadjusted due to sparse data]). However, within-mother analyses are restricted to multiparous women with deliveries after different conception methods. Therefore, findings from these analyses might not generalize to all women undergoing ART. Conclusions The risk of placenta previa in pregnancies conceived by ART differed by embryo culture duration, cryopreservation, and underlying infertility. The highest risk was seen after fresh embryo transfer and especially fresh blastocyst transfer. Women with endometriosis had a higher risk than women with other infertility factors, and within mothers, their risk was higher after ART than after natural conception. Identifying the responsible mechanisms might provide opportunities for prevention.

Background As extreme events such as drought and flood are projected to increase in frequency and intensity under climate change, there is still large missing evidence on how drought exposure potentially impacts mortality among young children. This study aimed to investigate the association between drought and risk of infant mortality in Africa, a region highly vulnerable to climate change that bears the heaviest share of the global burden. Methods and findings In this cross-sectional study, we obtained data on infant mortality in 34 African countries during 1992–2019 from the Demographic and Health Surveys program. We measured drought by the standardized precipitation evapotranspiration index at a timescale of 24 months and a spatial resolution of 10 × 10 km, which was further dichotomized into mild and severe drought. The association between drought exposure and infant mortality risk was estimated using Cox regression models allowing time-dependent covariates. We further examined whether the association varied for neonatal and post-neonatal mortality and whether there was a delayed association with drought exposure during pregnancy or infancy. The mean (standard deviation) number of months in which children experienced any drought during pregnancy and survival period (from birth through death before 1 year of age) was 4.6 (5.2) and 7.3 (7.4) among cases and non-cases, respectively. Compared to children who did not experience drought, we did not find evidence that any drought exposure was associated with an increased risk of infant mortality (hazard ratio [HR]: 1.02, 95% confidence interval [CI] [1.00, 1.04], p = 0.072). When stratified by drought severity, we found a statistically significant association with severe drought (HR: 1.04; 95% CI [1.01, 1.07], p = 0.015), but no significant association with mild drought (HR: 1.01; 95% CI [0.99, 1.03], p = 0.353), compared to non-exposure to any drought. However, when excluding drought exposure during pregnancy, the association with severe drought was found to be non-significant. In addition, an increased risk of neonatal mortality was associated with severe drought (HR: 1.05; 95% CI [1.01, 1.10], p = 0.019), but not with mild drought (HR: 0.99; 95% CI [0.96, 1.02], p = 0.657). Conclusions Exposure to long-term severe drought was associated with increased infant mortality risk in Africa. Our findings urge more effective adaptation measures and alleviation strategies against the adverse impact of drought on child health.

Background There is indication that the fallopian tubes might be involved in ovarian cancer pathogenesis and their removal reduces cancer risk. Hence, bilateral salpingectomy during hysterectomy or sterilization, so called opportunistic salpingectomy (OS), is gaining wide acceptance as a preventive strategy. Recently, it was discussed whether implementation of OS at other gynecologic surgery, e.g., cesarean section, endometriosis excision or myomectomy and even at non-gynecologic abdominal surgery such as cholecystectomy or appendectomy for women with completed family could be feasible. This modeling analysis evaluated the clinical and economic potential of OS at gynecologic and abdominal surgeries. Methods and findings A state transition model representing all relevant health states (healthy, healthy with hysterectomy or tubal ligation, healthy with other gynecologic or non-gynecologic abdominal surgery, healthy with hysterectomy and salpingectomy, healthy with salpingectomy, healthy with hysterectomy and salpingo-oophorectomy, ovarian cancer and death) was developed and informed with transition probabilities based on inpatient case numbers in Germany (2019). Outcomes for women aged 20–85 years were simulated over annual cycles with 1,200,000 million individuals. We compared four strategies: (I) OS at any suitable abdominal surgery, (II) OS only at any suitable gynecologic surgery, (III) OS only at hysterectomy or sterilization, and (IV) no implementation of OS. Primary outcome measures were prevented ovarian cancer cases and deaths as well as the incremental cost-effectiveness ratio (ICER). Volume of eligible interventions in strategy I was 3.5 times greater than in strategy III (286,736 versus 82,319). With strategy IV as reference, ovarian cancer cases were reduced by 15.34% in strategy I, 9.78% in II, and 5.48% in III. Setting costs for OS to €216.19 (calculated from average OS duration and operating room minute costs), implementation of OS would lead to healthcare cost savings as indicated by an ICER of €−8,685.50 per quality-adjusted life year (QALY) gained for strategy I, €−8,270.55/QALY for II, and €−4,511.86/QALY for III. Sensitivity analyses demonstrated stable results over a wide range of input parameters with strategy I being the superior approach in the majority of simulations. However, the extent of cancer risk reduction after OS appeared as the critical factor for effectiveness. Preventable ovarian cancer cases dropped to 4.07% (I versus IV), 1.90% (II versus IV), and 0.37% (III versus IV) if risk reduction would be <27% (hazard ratio [HR] > 0.73). ICER of strategies I and II was lower than the 2× gross domestic product per capita (GDP/C) (€94,366/QALY, Germany 2022) within the range of all tested parameters, but strategy III exceeded this threshold in case-risk reduction was <35% (HR > 0.65). The study is limited to data from the inpatient sector and direct medical costs. Conclusions Based on our model, interdisciplinary implementation of OS in any suitable abdominal surgeries could contribute to prevention of ovarian cancer and reduction of healthcare costs. The broader implementation approach demonstrated substantially better clinical and economic effectiveness and higher robustness with parameter variation. Based on a lifetime cost saving of €20.89 per capita if OS was performed at any suitable abdominal surgery, the estimated total healthcare cost savings in Germany could be more than €10 million annually.