Stage of HIV presentation at initial clinic visit following a community-based HIV testing campaign in rural Kenya

Background: The Kenyan Ministry of Health and partners implemented a community-based integrated prevention campaign (IPC) in Western Kenya in 2008. The aim of this study was to determine whether the IPC, compared to Voluntary Counselling and Testing (VCT) services, was able to identify HIV positive individuals earlier in the clinical course of HIV infection following testing

Physical examination tests of the shoulder: a systematic review and meta-analysis of diagnostic test performance

Background: Physical examination tests of the shoulder (PETS) are clinical examination maneuvers designed to aid the assessment of shoulder complaints. Despite more than 180 PETS described in the literature, evidence of their validity and usefulness in diagnosing the shoulder is questioned. Methods: This meta-analysis aims to use diagnostic odds ratio (DOR) to evaluate how much PETS shift overall probability and to rank the test performance of single PETS in order to aid the clinician’s choice of which tests to use. This study adheres to the principles outlined in the Cochrane guidelines and the PRISMA statement. A fixed effect model was used to assess the overall diagnostic validity of PETS by pooling DOR for different PETS with similar biomechanical rationale when possible. Single PETS were assessed and ranked by DOR. Clinical performance was assessed by sensitivity, specificity, accuracy and likelihood ratio. Results: Six thousand nine-hundred abstracts and 202 full-text articles were assessed for eligibility; 20 articles were eligible and data from 11 articles could be included in the meta-analysis. All PETS for SLAP (superior labral anterior posterior) lesions pooled gave a DOR of 1.38 [1.13, 1.69]. The Supraspinatus test for any full thickness rotator cuff tear obtained the highest DOR of 9.24 (sensitivity was 0.74, specificity 0.77). Compression-Rotation test obtained the highest DOR (6.36) among single PETS for SLAP lesions (sensitivity 0.43, specificity 0.89) and Hawkins test obtained the highest DOR (2.86) for impingement syndrome (sensitivity 0.58, specificity 0.67). No single PETS showed superior clinical test performance. Conclusions: The clinical performance of single PETS is limited. However, when the different PETS for SLAP lesions were pooled, we found a statistical significant change in post-test probability indicating an overall statistical validity. We suggest that clinicians choose their PETS among those with the highest pooled DOR and to assess validity to their own specific clinical settings, review the inclusion criteria of the included primary studies. We further propose that future studies on the validity of PETS use randomized research designs rather than the accuracy design relying less on well-established gold standard reference tests and efficient treatment options

Childhood trauma and outcome trajectories in patients with longstanding eating disorders across 17 years

Background: A large proportion of patients with eating disorders (ED) report experiences of childhood trauma. Latent trajectory analysis in ED samples reveals the complexities in course and outcome and can explore the long-term impact of adverse experiences in childhood. Method: A total of 84 patients with longstanding ED were included. ED symptoms were assessed by the Eating Disorder Examination interview at discharge from inpatient treatment, and at 1-, 2-, 5-, and 17-year follow-up, respectively. Change over time was examined using growth mixture modeling, allowing the number of trajectories to emerge through the data. Prevalence of childhood trauma was assessed, and its relation to class membership was tested. Results: We identified four distinct classes: patients with (a) a continuous improvement in the entire follow-up period, and scores within normal range at the end, “continuous improvement” (54.8%); (b) a high symptom level at baseline and moderate decrease over time, “high and declining” (22.6%); (c) initial ED scores below clinical cut-off and stable symptoms throughout the course, “consistently low” (14.3%); and (d) with high scores initially, and a significant increase in symptoms over time, “high and increasing” (8.3%). A history of childhood sexual abuse (CSA) was overrepresented in classes with persistently high symptom levels and poor long-term outcome Discussion: Patients with longstanding ED displayed considerable diversity in trajectories of symptom change across 17 years. To improve long-term outcome, enhanced treatment of sequelae from CSA seems essential. Public Significance: Patients with longstanding eating disorders displayed four different trajectories of change in a 17-year follow-up study. Although there were significant changes over time, the majority of patients remained within similar symptom levels as they presented with at discharge from inpatient treatment. Exposure to childhood maltreatment was common within the sample. Childhood sexual abuse predicted poor long-term outcome, which highlights the importance of trauma informed care

Implementation of a cloud-based electronic medical record for maternal and child health in rural Kenya

Background Complete and timely health information is essential to inform public health decision-making for maternal and child health, but is often lacking in resource-constrained settings. Electronic medical record (EMR) systems are increasingly being adopted to support the delivery of health care, and are particularly amenable to maternal and child health services. An EMR system could enable the mother and child to be tracked and monitored throughout maternity shared care, improve quality and completeness of data collected and enhance sharing of health information between outpatient clinic and the hospital, and between clinical and public health services to inform decision-making. Methods This study implemented a novel cloud-based electronic medical record system in a maternal and child health outpatient setting in Western Kenya between April and June 2013 and evaluated its impact on improving completeness of data collected by clinical and public health services. The impact of the system was assessed using a two-sample test of proportions pre- and post-implementation of EMR-based data verification. Results Significant improvements in completeness of the antenatal record were recorded through implementation of EMR-based data verification. A difference of 42.9% in missing data (including screening for hypertension, tuberculosis, malaria, HIV status or ART status of HIV positive women) was recorded pre- and post- implementation. Despite significant impact of EMR-based data verification on data completeness, overall screening rates in antenatal care were low. Conclusion This study has shown that EMR-based data verification can improve the completeness of data collected in the patient record for maternal and child health. A number of issues, including data management and patient confidentiality, must be considered but significant improvements in data quality are recorded through implementation of this EMR model

Surgery with disc prosthesis versus rehabilitation in patients with low back pain and degenerative disc: two year follow-up of randomised study

Objective To compare the efficacy of surgery with disc prosthesis versus non-surgical treatment for patients with chronic low back pain

Reduced risk of hospitalisation among reported COVID-19 cases infected with the SARS-CoV-2 Omicron BA.1 variant compared with the Delta variant, Norway, December 2021 to January 2022

We included 39,524 COVID-19 Omicron and 51,481 Delta cases reported in Norway from December 2021 to January 2022. We estimated a 73% reduced risk of hospitalisation (adjusted hazard ratio: 0.27; 95% confidence interval: 0.20–0.36) for Omicron compared with Delta. Compared with unvaccinated groups, Omicron cases who had completed primary two-dose vaccination 7–179 days before diagnosis had a lower reduced risk than Delta (66% vs 93%). People vaccinated with three doses had a similar risk reduction (86% vs 88%).publishedVersio

Modeling geographic vaccination strategies for COVID-19 in Norway.

Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient vaccine allocation to reduce infections and severe outcomes. This study explored alternative vaccination strategies to minimize health outcomes (infections, hospitalizations, ICU admissions, deaths) by varying regions prioritized, extra doses prioritized, and implementation start time. Using two models (individual-based and meta-population), we simulated COVID-19 transmission during the primary vaccination period in Norway, covering the first 7 months of 2021. We investigated alternative strategies to allocate more vaccine doses to regions with a higher force of infection. We also examined the robustness of our results and highlighted potential structural differences between the two models. Our findings suggest that early vaccine prioritization could reduce COVID-19 related health outcomes by 8% to 20% compared to a baseline strategy without geographic prioritization. For minimizing infections, hospitalizations, or ICU admissions, the best strategy was to initially allocate all available vaccine doses to fewer high-risk municipalities, comprising approximately one-fourth of the population. For minimizing deaths, a moderate level of geographic prioritization, with approximately one-third of the population receiving doubled doses, gave the best outcomes by balancing the trade-off between vaccinating younger people in high-risk areas and older people in low-risk areas. The actual strategy implemented in Norway was a two-step moderate level aimed at maintaining the balance and ensuring ethical considerations and public trust. However, it did not offer significant advantages over the baseline strategy without geographic prioritization. Earlier implementation of geographic prioritization could have more effectively addressed the main wave of infections, substantially reducing the national burden of the pandemic

A compelling demonstration of why traditional statistical regression models cannot be used to identify risk factors from case data on infectious diseases: a simulation study

Background Regression models are often used to explain the relative risk of infectious diseases among groups. For example, overrepresentation of immigrants among COVID-19 cases has been found in multiple countries. Several studies apply regression models to investigate whether different risk factors can explain this overrepresentation among immigrants without considering dependence between the cases. Methods We study the appropriateness of traditional statistical regression methods for identifying risk factors for infectious diseases, by a simulation study. We model infectious disease spread by a simple, population-structured version of an SIR (susceptible-infected-recovered)-model, which is one of the most famous and well-established models for infectious disease spread. The population is thus divided into different sub-groups. We vary the contact structure between the sub-groups of the population. We analyse the relation between individual-level risk of infection and group-level relative risk. We analyse whether Poisson regression estimators can capture the true, underlying parameters of transmission. We assess both the quantitative and qualitative accuracy of the estimated regression coefficients. Results We illustrate that there is no clear relationship between differences in individual characteristics and group-level overrepresentation —small differences on the individual level can result in arbitrarily high overrepresentation. We demonstrate that individual risk of infection cannot be properly defined without simultaneous specification of the infection level of the population. We argue that the estimated regression coefficients are not interpretable and show that it is not possible to adjust for other variables by standard regression methods. Finally, we illustrate that regression models can result in the significance of variables unrelated to infection risk in the constructed simulation example (e.g. ethnicity), particularly when a large proportion of contacts is within the same group. Conclusions Traditional regression models which are valid for modelling risk between groups for non-communicable diseases are not valid for infectious diseases. By applying such methods to identify risk factors of infectious diseases, one risks ending up with wrong conclusions. Output from such analyses should therefore be treated with great caution