The prevalence of mental disorders among intimate partner violence exposed and non-exposed Rwandans: Findings from a national cross-sectional survey.

Despite mounting evidence indicating an increased risk of long-term mental disorders in Rwanda's general population, little is still known about the national prevalence of mental disorders among victims of intimate partner violence (IPV) in a post-conflict setting. The aim of this study was to compare the prevalence of mental disorders among IPV exposed and non-exposed individuals in Rwanda. This was a cross-sectional study based on secondary data from the 2018 Rwanda Mental Health Survey. The sample consisted 20,381 participants selected nationwide, from 7,124 households (age range: 14-65 years), of which 3,759 Rwandans were exposed to IPV (18.4%) and 16,622 were non-exposed to IPV (81.6%). Participants were screened for IPV exposure and common mental disorders, and data was analyzed using the SPSS version 25 software. The results showed that the rate of any mental disorder was substantially higher in the group exposed to IPV than the non-exposed, at 32.4% and 11.7% respectively. These results highlight that among Rwandans diagnosed with severe mental disorders, participants with a history of IPV exposure present with increased odds of mental disorders prevalence and severity. Therefore, people seeking mental health care should also be screened for their IPV exposure and offered appropriate interventions.

The Use of Mobile Thermal Imaging and Deep Learning for Prediction of Surgical Site Infection.

The ability to detect surgical site infections (SSI) is a critical need for healthcare worldwide, but is especially important in low-income countries, where there is limited access to health facilities and trained clinical staff. In this paper, we present a new method of predicting SSI using a thermal image collected with a smart phone. Machine learning algorithms were developed using images collected as part of a clinical study that included 530 women in rural Rwanda who underwent cesarean section surgery. Thermal images were collected approximately 10 days after surgery, in conjunction with an examination by a trained doctor to determine the status of the wound (infected or not). Of the 530 women, 30 were found to have infected wounds. The data were used to develop two Convolutional Neural Net (CNN) models, with special care taken to avoid overfitting and address the problem of class imbalance in binary classification. The first model, a 6-layer naïve CNN model, demonstrated a median accuracy of AUC=0.84 with sensitivity=71% and specificity=87%. The transfer learning CNN model demonstrated a median accuracy of AUC=0.90 with sensitivity =95% and specificity=84%. To our knowledge, this is the first successful demonstration of a machine learning algorithm to predict surgical infection using thermal images alone.Clinical Relevance- This work establishes a promising new method for automated detection of surgical site infection.

Surgical Site Infections and Antimicrobial Resistance After Cesarean Section Delivery in Rural Rwanda.

Background: As the volume of surgical cases in low- and middle-income countries (LMICs) increases, surgical-site infections (SSIs) are becoming more prevalent with anecdotal evidence of antimicrobial resistance (AMR), despite a paucity of data on resistance patterns. Objectives: As a primary objective, this prospective study aimed to describe the epidemiology of SSIs and the associated AMR among women who delivered by cesarean at a rural Rwandan hospital. As secondary objectives, this study also assessed patient demographics, pre- and post-operative antibiotic use, and SSI treatment. Methods: Women who underwent cesarean deliveries at Kirehe District Hospital between September 23rd, 2019, and March 16th, 2020, were enrolled prospectively. On postoperative day (POD) 11 (+/- 3 days), their wounds were examined. When an SSI was diagnosed, a wound swab was collected and sent to the Rwandan National Reference Laboratory for culturing and antibiotic susceptibility testing. Findings: Nine hundred thirty women were enrolled, of whom 795 (85.5%) returned for the POD 11 clinic visit. 45 (5.7%) of the 795 were diagnosed with SSI and swabs were collected from 44 of these 45 women. From these 44 swabs, 57 potential pathogens were isolated. The most prevalent bacteria were coagulase-negative staphylococci (n = 12/57, 20.3% of all isolates), and Acinetobacter baumannii complex (n = 9/57, 15.2%). 68.4% (n = 39) of isolates were gram negative; 86.7% if excluding coagulase-negative staphylococci. No gram-negative pathogens isolated were susceptible to ampicillin, and the vast majority demonstrated intermediate susceptibility or resistance to ceftriaxone (92.1%) and cefepime (84.6%). Conclusions: Bacterial isolates from SSI swab cultures in rural Rwanda predominantly consisted of gram-negative pathogens and were largely resistant to commonly used antibiotics. This raises concerns about the effectiveness of antibiotics currently used for surgical prophylaxis and treatment and may guide the appropriate selection of treatment of SSIs in rural Rwanda and comparable settings.

Strengthening Antimicrobial Resistance Diagnostic Capacity in Rural Rwanda: A Feasibility Assessment.

Introduction: Antimicrobial resistance (AMR) is a global public health threat. Worse still, there is a paucity of data from low- and middle-income countries to inform rational antibiotic use. Objective: Assess the feasibility of setting up microbiology capacity for AMR testing and estimate the cost of setting up microbiology testing capacity at rural district hospitals in Rwanda. Methods: Laboratory needs assessments were conducted, and based on identified equipment gaps, appropriate requisitions were processed. Laboratory technicians were trained on microbiology testing processes and open wound samples were collected and cultured at the district hospital (DH) laboratories before being transported to the National Reference Laboratory (NRL) for bacterial identification and antibiotic susceptibility testing. Quality control (QC) assessments were performed at the DHs and NRL. We then estimated the cost of three scenarios for implementing a decentralized microbiology diagnostic testing system. Results: There was an eight-month delay from the completion of the laboratory needs assessments to the initiation of sample collection due to the regional unavailability of appropriate supplies and equipment. When comparing study samples processed by study laboratory technicians and QC samples processed by other laboratory staff, there was 85.0% test result concordance for samples testing at the DHs and 90.0% concordance at the NRL. The cost for essential equipment and supplies for the three DHs was $245,871. The estimated costs for processing 600 samples ranged from $29,500 to $92,590. Conclusion: There are major gaps in equipment and supply availability needed to conduct basic microbiology assays at rural DHs. Despite these challenges, we demonstrated that it is feasible to establish microbiological testing capacity in Rwandan DHs. Building microbiological testing capacity is essential for improving clinical care, informing rational antibiotics use, and ultimately, contributing to the establishment of robust national antimicrobial stewardship programs in rural Rwanda and comparable settings.

Factors Associated with Loss to Follow-up among Cervical Cancer Patients in Rwanda.

Background: Cervical cancer is among the most common cancers affecting women globally. Where treatment is available in low- and middle-income countries, many women become lost to follow-up (LTFU) at various points of care. Objective: This study assessed predictors of LTFU among cervical cancer patients in rural Rwanda. Methods: We conducted a retrospective study of cervical cancer patients enrolled at Butaro Cancer Center of Excellence (BCCOE) between 2012 and 2017 who were either alive and in care or LTFU at 12 months after enrollment. Patients are considered early LTFU if they did not return to clinic after the first visit and late LTFU if they did not return to clinic after the second visit. We conducted two multivariable logistic regressions to determine predictors of early and late LTFU. Findings: Of 652 patients in the program, 312 women met inclusion criteria, of whom 47 (15.1%) were early LTFU, 78 (25.0%) were late LTFU and 187 (59.9%) were alive and in care. In adjusted analyses, patients with no documented disease stage at presentation were more likely to be early LTFU vs. patients with stage 1 and 2 when controlling for other factors (aOR: 14.93, 95% CI 6.12-36.43). Patients who travel long distances (aOR: 2.25, 95% CI 1.11, 4.53), with palliative care as type of treatment received (aOR: 6.65, CI 2.28, 19.40) and patients with missing treatment (aOR: 7.99, CI 3.56, 17.97) were more likely to be late LTFU when controlling for other factors. Patients with ECOG status of 2 and higher were less likely to be late LTFU (aOR: 0.26, 95% CI 0.08, 0.85). Conclusion: Different factors were associated with early and later LTFU. Enhanced patient education, mechanisms to facilitate diagnosis at early stages of disease, and strategies that improve patient tracking and follow-up may reduce LTFU and improve patient retention.

Postoperative Rheumatic Heart Disease Follow-Up: Creating a National Registry and First Results from Rwanda.

Background: In many developing countries, rheumatic heart disease (RHD) is diagnosed at an advanced stage and requires surgery for patient survival. However, access to cardiac surgery in this context is limited and often provided through partnerships, requiring centralized patient data systems for monitoring and follow-up. Objectives: This study used data from a national postoperative RHD registry to analyze clinical outcomes of Rwandan patients who received surgery between 2006 and 2017. Methods: The RHD registry was created in 2017 using data compiled from Rwanda Ministry of Health and RHD surgery partners. We extracted pre- and post-operative data on patients who were alive and in care. We excluded patients who died or were lost to follow-up, as their data was not collected in the registry. We evaluated the association between demographic, surgical, and follow-up characteristics and most recent patient symptoms, categorized by New York Heart Association (NYHA) class. Findings: Among the 191 patients eligible for inclusion in this study, 107(56.0%) were female, 110(57.6%) were adults at the time of surgery (>15 years), and 128(67.4%) had surgery in Rwanda. Most patients (n = 166, 86.9%) were on penicillin prophylaxis. Of the patients with mechanical valves, 47(29.9%) had therapeutic International Normalized Ratio values. 90% of patients were asymptomatic (NYHA I) at the time of most recent visit. NYHA class was not significantly associated with any of the considered variables. The median length of follow-up for patients was four years (IQR: 2, 5 years). Conclusion: This study shows both the feasibility and challenges of creating a RHD registry 11 years after the national initiation of RHD surgeries. Most patients captured in the registry are asymptomatic; however, collecting details on patients who had died or were lost to follow-up has proven difficult. Implementing strategies to maintain a complete and up-to-date registry will facilitate follow-up for pre- and postoperative patients.