Lymphatic filariasis, caused by filarial worms such as Wuchereria bancrofti, Brugia malayi, and Brugia timori, represents a significant public health burden in endemic regions. The disease primarily affects the lymphatic system, leading to lymphatic dysfunction and chronic morbidity. This abstract provides a comprehensive overview of lymphatic filariasis, including its transmission dynamics, pathogenesis, clinical manifestations, diagnostic approaches, and treatment options. Special attention is given to the socioeconomic impact of the disease and the challenges associated with its control and elimination. The patient in this particular case is a 58-year-old man who had lower limb swelling and pain, characteristic of chronic lymphatic obstruction. Additionally, the swelling tends to worsen during the evening hours often resulting in difficulty in walking and discomfort. Lymphatic filariasis was diagnosed based on clinical presentation.

BACKGROUND: This is a study protocol that tests and refines realist theories regarding the uptake and scale-up of the linked maternity waiting home (hereafter MWH) and facility birth intervention in the Mozambican context. The theories were developed through a realist review of MWH-facility birth literature from low-income and middle-income countries. The aim of the proposed study is to contribute to a contextually refined understanding of the causal chains underlying MWH-facility birth adoption by pregnant women and their families, communities, the health system and donors.
METHODS: The overarching methodology is mixed-methods realist evaluation. The study will adopt a comparative embedded case study design comparing three new masonry MWHs built by the Mozambique-Canada Maternal Health Project in Inhambane province with three older MWHs selected based on variation in the built environment. Baseline data on participating MWH-facility birth interventions will be collected through observations, reviews of routine data and analysis of statistics and reports from provincial and district health authorities and the Mozambique-Canada Maternal Health project. Realist interviews will be conducted with MWH users and non-users, companions of MWH users and non-users, partners of MWH users and non-users, and stakeholders within the health system and the non-governmental organisation sector. Realist focus groups will be used to collect data from community-level implementers. The analysis will be retroductive and use the context-mechanism-outcome configuration heuristic tool to represent generative causation. We will analyse data from intervention and comparator MWHs independently and compare the resulting refined programme theories. Data analysis will be done in NVivo 12.
BACKGROUND: Ethics approval for the project has been obtained from the Mozambique National Bioethics Committee (CNBS-Comité Nacional de Bioética para a Saúde) and the University of Saskatchewan Bioethical Research Ethics Board. The evaluation will adhere to the International Ethical Guidelines for Biomedical Research Involving Human Subjects and the African adaptation of evaluation ethics and principles. Evaluation results will be disseminated to stakeholders\' practice audiences through peer-reviewed publications, plain-language briefs, theory validation/feedback meetings and conference presentations.

Rheumatic heart disease (RHD) affects over 39 million people worldwide, the majority in low-income and middle-income countries. Secondary antibiotic prophylaxis (SAP), given every 3-4 weeks can improve outcomes, provided more than 80% of doses are received. Poor adherence is strongly correlated with the distance travelled to receive prophylaxis. Decentralising RHD care has the potential to bridge these gaps and at least maintain or potentially increase RHD prophylaxis uptake. A package of implementation strategies was developed with the aim of reducing barriers to optimum SAP uptake.
A hybrid implementation-effectiveness study type III was designed to evaluate the effectiveness of a package of implementation strategies including a digital, cloud-based application to support decentralised RHD care, integrated into the public healthcare system in Uganda. Our overarching hypothesis is that secondary prophylaxis adherence can be maintained or improved via a decentralisation strategy, compared with the centralised delivery strategy, by increasing retention in care. To evaluate this, eligible patients with RHD irrespective of their age enrolled at Lira and Gulu hospital registry sites will be consented for decentralised care at their nearest participating health centre. We estimated a sample size of 150-200 registrants. The primary outcome will be adherence to secondary prophylaxis while detailed implementation measures will be collected to understand barriers and facilitators to decentralisation, digital application tool adoption and ultimately its use and scale-up in the public healthcare system.
This study was approved by the Institutional Review Board (IRB) at Cincinnati Children\'s Hospital Medical Center (IRB 2021-0160) and Makerere University School of Medicine Research Ethics Committee (Mak-SOMREC-2021-61). Participation will be voluntary and informed consent or assent (>8 but <18) will be obtained prior to participation. At completion, study findings will be communicated to the public, key stakeholders and submitted for publication.

Osteoporosis is one of the major diseases worldwide but is often underdiagnosed and undertreated. The most common reasons for underdiagnosis and undertreatment in ambulatory settings are demonstrated and potential solutions are discussed.
UNASSIGNED: Die Osteoporose ist eine der häufigsten und gleichzeitig am wenigsten diagnostizierten oder therapierten Erkrankungen. Die häufigsten Gründe für Unterdiagnostizierung und Untertherapie sowie deren Lösungsmöglichkeiten im ambulanten und stationären Bereich werden aufgezeigt und diskutiert.

BACKGROUND: Amidst growing consensus that stakeholder decision-making during drug development should be informed by an understanding of patient preferences, the Innovative Medicines Initiative project \'Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle\' (PREFER) is developing evidence-based recommendations about how and when patient preferences should be integrated into the drug life cycle. This protocol describes a PREFER clinical case study which compares two preference elicitation methodologies across several populations and provides information about benefit-risk trade-offs by those at risk of rheumatoid arthritis (RA) for preventive interventions.
METHODS: This mixed methods study will be conducted in three countries (UK, Germany, Romania) to assess preferences of (1) first-degree relatives (FDRs) of patients with RA and (2) members of the public. Focus groups using nominal group techniques (UK) and ranking surveys (Germany and Romania) will identify and rank key treatment attributes. Focus group transcripts will be analysed thematically using the framework method and average rank orders calculated. These results will inform the treatment attributes to be assessed in a survey including a discrete choice experiment (DCE) and a probabilistic threshold technique (PTT). The survey will also include measures of sociodemographic variables, health literacy, numeracy, illness perceptions and beliefs about medicines. The survey will be administered to (1) 400 FDRs of patients with RA (UK); (2) 100 FDRs of patients with RA (Germany); and (3) 1000 members of the public in each of UK, Germany and Romania. Logit-based approaches will be used to analyse the DCE and imputation and interval regression for the PTT.
BACKGROUND: This study has been approved by the London-Hampstead Research Ethics Committee (19/LO/0407) and the Ethics Committee of the Friedrich-Alexander-Universität Erlangen-Nürnberg (92_17 B). The protocol has been approved by the PREFER expert review board. The results will be disseminated widely and will inform the PREFER recommendations.

To evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections.
The US Department of Veterans Affairs has 130 medical centres. We created multivariate models from these data-339 772 patients with COVID-19-as of 30 September 2021.
The primary outcome for all models was death within 60 days of the diagnosis. Logistic regression was used to derive adjusted ORs for vaccination and infection with Delta versus earlier variants. Models were adjusted for confounding factors, including demographics, comorbidity indices and novel parameters representing prior diagnoses, vital signs/baseline laboratory tests and outpatient treatments. Patients with a Delta infection were divided into eight cohorts based on the time from vaccination to diagnosis. A common model was used to estimate the odds of death associated with vaccination for each cohort relative to that of unvaccinated patients.
9.1% of subjects were vaccinated. 21.5% had the Delta variant. 18 120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for a Delta infection was 1.87±0.05, which corresponds to a relative risk (RR) of 1.78. The overall adjusted OR for prior vaccination was 0.280±0.011 corresponding to an RR of 0.291. Raw CFR rose steadily after 10-14 weeks. The OR for vaccination remained stable for 10-34 weeks.
Our CFR model controls for the severity of confounding factors and priority of vaccination, rather than solely using the presence of comorbidities. Our results confirm that Delta was more lethal than earlier variants and that vaccination is an effective means of preventing death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks. We suggest that this model can be used to evaluate vaccines designed for emerging variants.

Heart failure (HF) is a commonly occurring health problem with high mortality and morbidity. If potential cases could be detected earlier, it may be possible to intervene earlier, which may slow progression in some patients. Preferably, it is desired to reuse already measured data for screening of all persons in an age group, such as general practitioner (GP) data. Furthermore, it is essential to evaluate the number of people needed to screen to find one patient using true incidence rates, as this indicates the generalisability in the true population. Therefore, we aim to create a machine learning model for the prediction of HF using GP data and evaluate the number needed to screen with true incidence rates.
GP data from 8543 patients (-2 to -1 year before diagnosis) and controls aged 70+ years were obtained retrospectively from 01 January 2012 to 31 December 2019 from the Nivel Primary Care Database. Codes about chronic illness, complaints, diagnostics and medication were obtained. Data were split in a train/test set. Datasets describing demographics, the presence of codes (non-sequential) and upon each other following codes (sequential) were created. Logistic regression, random forest and XGBoost models were trained. Predicted outcome was the presence of HF after 1 year. The ratio case:control in the test set matched true incidence rates (1:45).
Sole demographics performed average (area under the curve (AUC) 0.692, CI 0.677 to 0.706). Adding non-sequential information combined with a logistic regression model performed best and significantly improved performance (AUC 0.772, CI 0.759 to 0.785, p<0.001). Further adding sequential information did not alter performance significantly (AUC 0.767, CI 0.754 to 0.780, p=0.07). The number needed to screen dropped from 14.11 to 5.99 false positives per true positive.
This study created a model able to identify patients with pending HF a year before diagnosis.

Excess weight and related health complications remain under diagnosed and poorly treated in general practice. We aimed to develop and validate a brief screening tool for determining the presence of unknown clinically significant weight-related health complications for potential application in general practice.
We considered 14 self-reported candidate predictors of clinically significant weight-related health complications according to the Edmonton Obesity Staging System (EOSS score of ≥2) and developed models using multivariate logistic regression across training and test data sets. The final model was chosen based on the area under the receiver operating characteristic curve and the Hosmer-Lemeshow statistic; and validated using sensitivity, specificity and positive predictive value.
We analysed cross-sectional data from the Australian Health Survey 2011-2013 sample aged between 18 and 65 years (n=7518) with at least overweight and obesity.
An EOSS≥2 classification was present in 78% of the sample. Of 14 candidate risk factors, 6 (family history of diabetes, hypertension, high sugar in blood/urine, high cholesterol and self-reported bodily pain and disability) were automatically included based on definitional or obvious correlational criteria. Three variables were retained in the final multivariate model (age, self-assessed health and history of depression/anxiety). The EOSS-2 Risk Tool (index test) classified 89% of those at \'extremely high risk\' (≥25 points), 67% of those at \'very high risk\' (7-24 points) and 42% of those at \'high risk\' (<7 points) of meeting diagnostic criteria for EOSS≥2 (reference).
The EOSS-2 Risk Tool is a simple, safe and accurate screening tool for diagnostic criteria for clinically significant weight-related complications for potential application in general practice. Research to determine the feasibility and applicability of the EOSS-2 Risk Tool for improving weight management approaches in general practice is warranted.

Population-wide interventions offer a pathway to tuberculosis (TB) and leprosy elimination, but \'real-world\' implementation in a high-burden setting using a combined approach has not been demonstrated. This implementation study aims to demonstrate the feasibility and evaluate the effect of population-wide screening, treatment and prevention on TB and leprosy incidence rates, as well as TB transmission.
A non-randomised \'screen-and-treat\' intervention conducted in the Pacific atoll of South Tarawa, Kiribati. Households are enumerated and all residents ≥3 years, as well as children <3 years with recent household exposure to TB or leprosy, invited for screening. Participants are screened using tuberculin skin testing, signs and symptoms of TB or leprosy, digital chest X-ray with computer-aided detection and sputum testing (Xpert MTB/RIF Ultra). Those diagnosed with disease are referred to the National TB and Leprosy Programme for management. Participants with TB infection are offered TB preventive treatment and those without TB disease or infection, or leprosy, are offered leprosy prophylaxis. The primary study outcome is the difference in the annual TB case notification rate before and after the intervention; a similar outcome is included for leprosy. The effect on TB transmission will be measured by comparing the estimated annual risk of TB infection in primary school children before and after the intervention, as a co-primary outcome used for power calculations. Comparison of TB and leprosy case notification rates in South Tarawa (the intervention group) and the rest of Kiribati (the control group) before, during and after the intervention is a secondary outcome.
Approval was obtained from the University of Sydney Human Research Ethics Committee (project no. 2021/127) and the Kiribati Ministry of Health and Medical Services (MHMS). Findings will be shared with the MHMS and local communities, published in peer-reviewed journals and presented at international conferences.

This study aimed to identify the risk factors associated with preterm birth, and to determine the prevalence of preterm births in the Dominican Republic.
Case-control study.
Seven National Reference Hospitals from different regions of the Dominican Republic.
A probabilistic sampling of both cases and controls was performed with a ratio of 2.92:1, and a power analysis was performed with α=0.05, P1 =0.5, P2 =0.6, and β=0.08, to yield a distribution of 394 cases and 1150 controls. Estimation of gestational age was based on neonatologist reports.
A protocol was created to obtain maternal and obstetric information.
The main risk factors were a family history of premature births (p<0.001, OR: 14.95, 95% CI 8.50 to 26.29), previous preterm birth (p=0.005, OR: 20.00; 95% CI 12.13 to 32.96), advanced maternal age (over 35 years; p<0.001, OR: 2.21; 95% CI 1.57 to 3.09), smoking (p<0.001, OR: 6.65, 95% CI 3.13 to 13.46), drug consumption (p=0.004, OR: 2.43, 95% CI 1.37 to 4.30), premature rupture of membranes (p<0.001, OR: 2.5) and reduced attendance at prenatal consultations (95% CI 6 to 7, Z=-10.294, p<0.001).
Maternal age greater than 35 years, previous preterm birth, family history of preterm births and prelabour rupture of membranes were independent risk factors for preterm birth. Adolescence, pregnancy weight gain and prenatal consultations, on the other hand, were protective factors for preterm birth. Although the prevalence of premature births in this study was 25%, this could have been biased.