Virologic Failure and Drug Resistance After Programmatic Switching to Dolutegravir-based First-line Antiretroviral Therapy in Malawi and Zambia.

BACKGROUND: People with human immunodeficiency virus (PWH) on first-line, nonnucleoside reverse-transcriptase inhibitor-based antiretroviral therapy (ART) were routinely switched to tenofovir-lamivudine-dolutegravir. We examined virologic outcomes and drug resistance in ART programs in Malawi, where switching was irrespective of viral load, and Zambia, where switching depended on a viral load <1000 copies/mL in the past year. METHODS: We compared the risk of viremia (≥400 copies/mL) at 1 and 2 years by viral load at switch and between countries using exact methods and logistic regression adjusted for age and sex. We performed HIV-1 pol Sanger sequencing on plasma samples with viral load ≥1000 copies/mL. RESULTS: A total of 2832 PWH were eligible (Malawi 1422, Zambia 1410); the median age was 37 years, and 2578 (91.0%) were women. At switch, 77 (5.4%) were viremic in Malawi and 42 (3.0%) in Zambia (P = .001). Viremia at switch was associated with viremia at 1 year (adjusted odds ratio (OR), 6.15; 95% confidence interval [CI], 3.13-11.4) and 2 years (7.0; 95% CI, 3.73-12.6). Viremia was less likely in Zambia than in Malawi at 1 year (OR, 0.55; 0.32-0.94) and 2 years (OR, 0.33; 0.18-0.57). Integrase sequencing was successful for 79 of 113 eligible samples. Drug resistance mutations were found in 5 PWH (Malawi 4, Zambia 1); 2 had major mutations (G118R, E138K, T66A and G118R, E138K) leading to high-level dolutegravir resistance. CONCLUSIONS: Restricting switching to dolutegravir-based ART to PWH with a viral load <1000 copies/mL may reduce subsequent viremia and, consequently, the emergence of dolutegravir drug resistance mutations. CLINICAL TRIALS REGISTRATION: Clinicaltrials.gov (NCT04612452).

Health of singleton neonates in Switzerland through time and crises: a cross-sectional study at the population level, 2007-2022.

BACKGROUND: Being exposed to crises during pregnancy can affect maternal health through stress exposure, which can in return impact neonatal health. We investigated temporal trends in neonatal outcomes in Switzerland between 2007 and 2022 and their variations depending on exposure to the economic crisis of 2008, the flu pandemic of 2009, heatwaves (2015 and 2018) and the COVID-19 pandemic. METHODS: Using individual cross-sectional data encompassing all births occurring in Switzerland at the monthly level (2007-2022), we analysed changes in birth weight and in the rates of preterm birth (PTB) and stillbirth through time with generalized additive models. We assessed whether the intensity or length of crisis exposure was associated with variations in these outcomes. Furthermore, we explored effects of exposure depending on trimesters of pregnancy. RESULTS: Over 1.2 million singleton births were included in our analyses. While birth weight and the rate of stillbirth have remained stable since 2007, the rate of PTB has declined by one percentage point. Exposure to the crises led to different results, but effect sizes were overall small. Exposure to COVID-19, irrespective of the pregnancy trimester, was associated with a higher birth weight (+12 grams [95% confidence interval (CI) 5.5 to 17.9 grams]). Being exposed to COVID-19 during the last trimester was associated with an increased risk of stillbirth (odds ratio 1.24 [95%CI 1.02 to 1.50]). Exposure to the 2008 economic crisis during pregnancy was not associated with any changes in neonatal health outcomes, while heatwave effect was difficult to interpret. CONCLUSION: Overall, maternal and neonatal health demonstrated resilience to the economic crisis and to the COVID-19 pandemic in a high-income country like Switzerland. However, the effect of exposure to the COVID-19 pandemic is dual, and the negative impact of maternal infection on pregnancy is well-documented. Stress exposure and economic constraint may also have had adverse effects among the most vulnerable subgroups of Switzerland. To investigate better the impact of heatwave exposure on neonatal health, weekly or daily-level data is needed, instead of monthly-level data.

Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement.

Importance: Mendelian randomization (MR) studies use genetic variation associated with modifiable exposures to assess their possible causal relationship with outcomes and aim to reduce potential bias from confounding and reverse causation. Objective: To develop the STROBE-MR Statement as a stand-alone extension to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guideline for the reporting of MR studies. Design, Setting, and Participants: The development of the STROBE-MR Statement followed the Enhancing the Quality and Transparency of Health Research (EQUATOR) framework guidance and used the STROBE Statement as a starting point to draft a checklist tailored to MR studies. The project was initiated in 2018 by reviewing the literature on the reporting of instrumental variable and MR studies. A group of 17 experts, including MR methodologists, MR study design users, developers of previous reporting guidelines, and journal editors, participated in a workshop in May 2019 to define the scope of the Statement and draft the checklist. The draft checklist was published as a preprint in July 2019 and discussed on the preprint platform, in social media, and at the 4th Mendelian Randomization Conference. The checklist was then revised based on comments, further refined through 2020, and finalized in July 2021. Findings: The STROBE-MR checklist is organized into 6 sections (Title and Abstract, Introduction, Methods, Results, Discussion, and Other Information) and includes 20 main items and 30 subitems. It covers both 1-sample and 2-sample MR studies that assess 1 or multiple exposures and outcomes, and addresses MR studies that follow a genome-wide association study and are reported in the same article. The checklist asks authors to justify why MR is a helpful method to address the study question and state prespecified causal hypotheses. The measurement, quality, and selection of genetic variants must be described and attempts to assess validity of MR-specific assumptions should be well reported. An item on data sharing includes reporting when the data and statistical code required to replicate the analyses can be accessed. Conclusions and Relevance: STROBE-MR provides guidelines for reporting MR studies. Improved reporting of these studies could facilitate their evaluation by editors, peer reviewers, researchers, clinicians, and other readers, and enhance the interpretation of their results.

Development and temporal validation of a prognostic model for 1-year clinical outcome after decompression surgery for lumbar disc herniation.

PURPOSE: Surgeons need tools to provide individualised estimates of surgical outcomes and the uncertainty surrounding these, to convey realistic expectations to the patient. This study developed and validated prognostic models for patients undergoing surgical treatment of lumbar disc herniation, to predict outcomes 1 year after surgery, and implemented these models in an online prediction tool. METHODS: Using the data of 1244 patients from a large spine unit, LASSO and linear regression models were fitted with 90% upper prediction limits, to predict scores on the Core Outcome Measures Index, and back and leg pain. Candidate predictors included sociodemographic factors, baseline symptoms, medical history, and surgeon characteristics. Temporal validation was conducted on 364 more recent patients at the same unit, by examining the proportion of observed outcomes exceeding the threshold of the 90% upper prediction limit (UPL), and by calculating mean bias and other calibration measures. RESULTS: Poorer outcome was predicted by obesity, previous spine surgery, and having basic obligatory (rather than private) insurance. In the validation data, fewer than 12% of outcomes were above the 90% UPL. Calibration plots for the model validation showed values for mean bias < 0.5 score points and regression slopes close to 1. CONCLUSION: While the model accuracy was good overall, the prediction intervals indicated considerable predictive uncertainty on the individual level. Implementation studies will assess the clinical usefulness of the online tool. Updating the models with additional predictors may improve the accuracy and precision of outcome predictions. These slides can be retrieved under Electronic Supplementary Material.

Single index methods for evaluation of marker-guided treatment rules based on multivariate marker panels.

Clinical practice may be enhanced by use of person-level information that could guide treatment choice and lead to better outcomes for both treated individuals and for the population. The scientific challenge is to identify and validate those factors that can reliably be used to target treatment, and to accurately quantify the expected treatment benefit as a function of candidate markers. Our proposal is to explicitly focus on smooth non-parametric evaluation of a canonical single index score that estimates the expected treatment benefit associated with patient characteristics. Our methods intentionally decouple the model used to generate the treatment benefit score from the methods that are adopted to evaluate the performance of the resulting single index score. We are motivated by the practical issue that model performance can not realistically be evaluated for every specific covariate value due to intrinsic sparseness. However, direct validation of a scalar treatment benefit score obtained through model-based dimension reduction is feasible, and we believe should be the focus of validation efforts. We also show that the canonical single index treatment benefit score can be used for selecting subsets of patients with enriched expected treatment response since patients can be easily ordered and grouped based on the scalar score. Our biomedical motivation comes from a recent randomized trial of steroid injections for low back pain where baseline clinical and imaging data are candidate measures for guiding therapeutic choice.

Predictive diagnostics for Escherichia coli infections based on the clonal association of antimicrobial resistance and clinical outcome.

The ability to identify bacterial pathogens at the subspecies level in clinical diagnostics is currently limited. We investigated whether splitting Escherichia coli species into clonal groups (clonotypes) predicts antimicrobial susceptibility or clinical outcome. A total of 1,679 extraintestinal E. coli isolates (collected from 2010 to 2012) were collected from one German and 5 U.S. clinical microbiology laboratories. Clonotype identity was determined by fumC and fimH (CH) sequencing. The associations of clonotype with antimicrobial susceptibility and clinical variables were evaluated. CH typing divided the isolates into >200 CH clonotypes, with 93% of the isolates belonging to clonotypes with ≥ 2 isolates. Antimicrobial susceptibility varied substantially among clonotypes but was consistent across different locations. Clonotype-guided antimicrobial selection significantly reduced "drug-bug" mismatch compared to that which occurs with the use of conventional empirical therapy. With trimethoprim-sulfamethoxazole and fluoroquinolones, the drug-bug mismatch was predicted to decrease 62% and 78%, respectively. Recurrent or persistent urinary tract infection and clinical sepsis were significantly correlated with specific clonotypes, especially with CH40-30 (also known as H30), a recently described clonotype within sequence type 131 (ST131). We were able to clonotype directly from patient urine samples within 1 to 3 h of obtaining the specimen. In E. coli, subspecies-level identification by clonotyping can be used to significantly improve empirical predictions of antimicrobial susceptibility and clinical outcomes in a timely manner.

Authorship inequalities in global health research: the IeDEA Southern Africa collaboration.

BACKGROUND: The International epidemiology Databases to Evaluate AIDS conducts research in several regions, including in Southern Africa. We assessed authorship inequalities for the Southern African region, which is led by South African and Swiss investigators. METHODS: We analysed authorships of publications from 2007 to 2020 by gender, country income group, time and citation impact. We used 2020 World Bank categories to define income groups and the relative citation ratio (RCR) to assess citation impact. Authorship parasitism was defined as articles without authors from the countries where the study was conducted. A regression model examined the probability of different authorship positions. RESULTS: We included 313 articles. Of the 1064 contributing authors, 547 (51.4%) were women, and 223 (21.0%) were from 32 low-income/lower middle-income countries (LLMICs), 269 (25.3%) were from 13 upper middle-income countries and 572 (53.8%) were from 25 high-income countries (HICs). Most articles (150/157, 95.5%) reporting data from Southern Africa included authors from all participating countries. Women were more likely to be the first author than men (OR 1.74; 95% CI 1.06 to 2.83) but less likely to be last authors (OR 0.63; 95% CI 0.40 to 0.99). Compared with HIC, LLMIC authors were less likely to publish as first (OR 0.21; 95% CI 0.11 to 0.41) or last author (OR 0.20; 95% CI 0.09 to 0.42). The proportion of women and LLMIC first and last authors increased over time. The RCR tended to be higher, indicating greater impact, if first or last authors were from HIC (p=0.06). CONCLUSIONS: This analysis of a global health collaboration co-led by South African and Swiss investigators showed little evidence of authorship parasitism. There were stark inequalities in authorship position, with women occupying more first and men more last author positions and researchers from LLMIC being 'stuck in the middle' on the byline. Global health research collaborations should monitor, analyse and address authorship inequalities.

Investigating the transparency of reporting in two-sample summary data Mendelian randomization studies using the MR-Base platform.

BACKGROUND: Two-sample Mendelian randomization (2SMR) is an increasingly popular epidemiological method that uses genetic variants as instruments for making causal inferences. Clear reporting of methods employed in such studies is important for evaluating their underlying quality. However, the quality of methodological reporting of 2SMR studies is currently unclear. We aimed to assess the reporting quality of studies that used MR-Base, one of the most popular platforms for implementing 2SMR analysis. METHODS: We created a bespoke reporting checklist to evaluate reporting quality of 2SMR studies. We then searched Web of Science Core Collection, PsycInfo, MEDLINE, EMBASE and Google Scholar citations of the MR-Base descriptor paper to identify published MR studies that used MR-Base for any component of the MR analysis. Study screening and data extraction were performed by at least two independent reviewers. RESULTS: In the primary analysis, 87 studies were included. Reporting quality was generally poor across studies, with a mean of 53% (SD = 14%) of items reported in each study. Many items required for evaluating the validity of key assumptions made in MR were poorly reported: only 44% of studies provided sufficient details for assessing if the genetic variant associates with the exposure ('relevance' assumption), 31% for assessing if there are any variant-outcome confounders ('independence' assumption), 89% for the assessing if the variant causes the outcome independently of the exposure ('exclusion restriction' assumption) and 32% for assumptions of falsification tests. We did not find evidence of a change in reporting quality over time or a difference in reporting quality between studies that used MR-Base and a random sample of MR studies that did not use this platform. CONCLUSIONS: The quality of reporting of two-sample Mendelian randomization studies in our sample was generally poor. Journals and researchers should consider using the STROBE-MR guidelines to improve reporting quality.

The effect of the COVID-19 lockdown on mental health care use in South Africa: an interrupted time-series analysis.

AIMS: The coronavirus disease 2019 (COVID-19) pandemic and ensuing restrictions have negatively affected the mental health and well-being of the general population, and there is increasing evidence suggesting that lockdowns have led to a disruption of health services. In March 2020, South Africa introduced a lockdown in response to the COVID-19 pandemic, entailing the suspension of all non-essential activities and a complete ban of tobacco and alcohol sales. We studied the effect of the lockdown on mental health care utilisation rates in private-sector care in South Africa. METHODS: We conducted an interrupted time-series analysis using insurance claims from 1 January 2017 to 1 June 2020 of beneficiaries 18 years or older from a large private sector medical insurance scheme. We calculated weekly outpatient consultation and hospital admission rates for organic mental disorders, substance use disorders, serious mental disorders, depression, anxiety, other mental disorders, any mental disorder and alcohol withdrawal syndrome. We calculated adjusted odds ratios (OR) for the effect of the lockdown on weekly outpatient consultation and hospital admission rates and the weekly change in rates during the lockdown until 1 June 2020. RESULTS: 710 367 persons were followed up for a median of 153 weeks. Hospital admission rates (OR 0.38; 95% confidence interval (CI) 0.33-0.44) and outpatient consultation rates (OR 0.74; 95% CI 0.63-0.87) for any mental disorder decreased substantially after the introduction of the lockdown and did not recover to pre-lockdown levels by 1 June 2020. Health care utilisation rates for alcohol withdrawal syndrome doubled after the introduction of the lockdown, but the statistical uncertainty around the estimates was large (OR 2.24; 95% CI 0.69-7.24). CONCLUSIONS: Mental health care utilisation rates for inpatient and outpatient services decreased substantially after the introduction of the lockdown. Hospital admissions and outpatient consultations for alcohol withdrawal syndrome increased after the introduction of the lockdown, but statistical uncertainty precludes strong conclusions about a potential unintended effect of the alcohol sales ban. Governments should integrate strategies for ensuring access and continuity of essential mental health services during lockdowns in pandemic preparedness planning.

Mortality from drug-resistant tuberculosis in high-burden countries comparing routine drug susceptibility testing with whole-genome sequencing: a multicentre cohort study.

BACKGROUND: Drug resistance threatens global tuberculosis control. We aimed to examine mortality in patients with tuberculosis from high-burden countries, according to concordance or discordance of results from drug susceptibility testing done locally and whole-genome sequencing (WGS). METHODS: In this multicentre cohort study, we collected pulmonary Mycobacterium tuberculosis isolates and clinical data from individuals with tuberculosis from antiretroviral therapy programmes and tuberculosis clinics in Côte d'Ivoire, Democratic Republic of the Congo, Kenya, Nigeria, Peru, South Africa, and Thailand, stratified by HIV status and drug resistance. Sites tested drug susceptibility using routinely available methods. WGS was done on Illumina HiSeq 2500 in the USA and Switzerland, and TBprofiler was used to analyse the genomes. We included individuals aged 16 years or older with pulmonary tuberculosis (bacteriologically confirmed or clinically diagnosed). We analysed mortality in multivariable logistic regression models adjusted for sex, age, HIV status, history of tuberculosis, and sputum positivity. FINDINGS: Between Sept 1, 2014, and July 4, 2016, of 634 patients included in our previous analysis, we included 582 patients with tuberculosis (median age 33 years [IQR 27-43], 225 [39%] women, and 247 [42%] HIV-positive). Based on WGS, 339 (58%) isolates were pan-susceptible, 35 (6%) monoresistant, 146 (25%) multidrug-resistant, and 24 (4%) pre-extensively drug-resistant (pre-XDR) or XDR. The analysis of mortality was based on 530 patients; 63 (12%) died and 77 (15%) patients received inappropriate treatment. Mortality ranged from 6% (18 of 310) in patients with pan-susceptible tuberculosis to 39% (nine of 23) in patients with pre-XDR or XDR tuberculosis. The adjusted odds ratio for mortality was 4·92 (95% CI 2·47-9·78) among undertreated patients, compared with appropriately treated patients. INTERPRETATION: In seven countries with a high burden of tuberculosis, we observed discrepancies between drug resistance patterns obtained locally and WGS. The underdiagnosis of drug resistance resulted in inappropriate treatment and higher mortality. WGS can provide accurate and detailed drug resistance information required to improve the outcomes of drug-resistant tuberculosis in high-burden settings. Our results support WHO's call for point-of-care tests based on WGS. FUNDING: National Institutes of Allergy and Infectious Diseases, Swiss National Science Foundation, and Swiss National Center for Mycobacteria.

Spatial epidemiology of gestational age and birth weight in Switzerland: census-based linkage study.

BACKGROUND: Gestational age and birth weight are strong predictors of infant morbidity and mortality. Understanding spatial variation can inform policies to reduce health inequalities. We examined small-area variation in gestational age and birth weight in Switzerland. METHODS: All singleton live births recorded in the Swiss Live Birth Register 2011 to 2014 were eligible. We deterministically linked the Live Birth Register with census and survey data to create data sets including neonatal and pregnancy-related variables, parental characteristics and geographical variables. We produced maps of 705 areas and fitted linear mixed-effect models to assess to what extent spatial variation was explained by these variables. RESULTS: We analysed all 315 177 eligible live births. Area-level averages of gestational age varied between 272 and 279 days, and between 3138 and 3467 g for birth weight. The fully adjusted models explained 31% and 87% of spatial variation of gestational age and birth weight, respectively. Language region accounted for most of the explained variation (23% in gestational age and 62% in birth weight), with shorter gestational age (-0.6 days and -0.9 days) and lower birth weight (-1.1% and -1.8%) in French-speaking and Italian-speaking areas, respectively, compared with German-speaking areas. Other variables explaining variation were, for gestational age, the level of urbanisation (10%) and parental nationality (3%). For birth weight, they were gestational age (27%), parental nationality (27%), civil status (10%) and altitude (10%). In a random sample of 81 968 live births with data on parental education, levels of education were only weakly associated with gestational age (-0.9 days for compulsory vs tertiary maternal education) or birth weight (-0.7% for compulsory vs tertiary maternal education). CONCLUSIONS: In Switzerland, small area variation in birth weight is largely explained, and variation in gestational age partially explained, by geocultural, sociodemographic and pregnancy factors.