Implementation and Assessment of the HIV Enhanced Access Testing in the Emergency Department (HEATED) Program in Nairobi, Kenya: A Quasi-Experimental Prospective Study.

Background: Persons seeking emergency injury care are often from underserved key populations (KPs) and priority populations (PPs) for HIV programming. While facility-based HIV Testing Services (HTS) in Kenya are effective, emergency department (ED) delivery is limited, despite the potential to reach underserved persons. Methods: This quasi-experimental prospective study evaluated implementation of the HIV Enhanced Access Testing in Emergency Departments (HEATED) at Kenyatta National Hospital ED in Nairobi, Kenya. The HEATED program was designed using setting specific data and utilizes resource reorganization, services integration and HIV sensitization to promote ED-HTS. KPs included sex workers, gay men, men who have sex with men, transgender persons and persons who inject drugs. PPs included young persons (18-24 years), victims of interpersonal violence, persons with hazardous alcohol use and those never previously HIV tested. Data were obtained from systems-level records, enrolled injured patient participants and healthcare providers. Systems and patient-level data were collected during a pre-implementation period (6 March - 16 April 2023) and post-implementation (period 1, 1 May - 26 June 2023). Additional, systems-level data were collected during a second post-implementation (period 2, 27 June - 20 August 2023). Evaluation analyses were completed across reach, effectiveness, adoption, implementation and maintenance framework domains. Results: All 151 clinical staff were reached through trainings and sensitizations on the HEATED program. Systems-level ED-HTS increased from 16.7% pre-implementation to 23.0% post-implementation periods 1 and 2 (RR=1.31, 95% CI:1.21-1.43; p<0.001) with a 62.9% relative increase in HIV self-test kit provision. Among 605 patient participants, facilities-based HTS increased from 5.7% pre-implementation to 62.3% post-implementation period 1 (RR=11.2, 95%CI:6.9-18.1; p<0.001). There were 440 (72.7%) patient participants identified as KPs (5.6%) and/or PPs (65.3%). For enrolled KPs/PPs, HTS increased from 4.6% pre-implementation to 72.3% post-implementation period 1 (RR=13.8, 95%CI:5.5-28.7, p<0.001). Systems and participant level data demonstrated successful adoption and implementation of the HEATED program. Through 16-weeks post-implementation a significant increase in ED-HTS delivery was maintained as compared to pre-implementation. Conclusions: The HEATED program increased ED-HTS and augmented delivery to KPs/PPs, suggesting that broader implementation could improve HIV services for underserved persons, already in contact with health systems.

Results of a cluster randomized trial testing the Systems Analysis and Improvement Approach to increase cervical cancer screening in family planning clinics in Mombasa County, Kenya.

BACKGROUND: Cervical cancer is the leading cause of cancer death in Kenyan women. Integrating cervical cancer screening into family planning (FP) clinics is a promising strategy to improve health for reproductive-aged women. The objective of this cluster randomized trial was to test the efficacy of an implementation strategy, the Systems Analysis and Improvement Approach (SAIA), as a tool to increase cervical cancer screening in FP clinics in Mombasa County, Kenya. METHODS: Twenty FP clinics in Mombasa County were randomized 1:1 to SAIA versus usual procedures. SAIA has five steps: (1) cascade analysis tool to understand the cascade and identify inefficiencies, (2) sequential process flow mapping to identify bottlenecks, (3) develop and implement workflow modifications (micro-interventions) to address identified bottlenecks, (4) assess the micro-intervention in the cascade analysis tool, and (5) repeat the cycle. Prevalence ratios were calculated using Poisson regression with robust standard errors to compare the proportion of visits where women were screened for cervical cancer in SAIA clinics compared to control clinics. RESULTS: In the primary intent-to-treat analysis in the last quarter of the trial, 2.5% (37/1507) of visits with eligible FP clients at intervention facilities included cervical cancer screening compared to 3.7% (66/1793) in control clinics (prevalence ratio [PR] 0.67, 95% CI 0.45-1.00). When adjusted for having at least one provider trained to perform cervical cancer screening at baseline, there was no significant difference between screening in intervention clinics compared to control clinics (adjusted PR 1.14, 95% CI 0.74-1.75). CONCLUSIONS: The primary analysis did not show an effect on cervical cancer screening. However, the COVID-19 pandemic and a healthcare worker strike likely impacted SAIA's implementation with significant disruptions in FP care delivery during the trial. While SAIA's data-informed decision-making and clinic-derived solutions are likely important, future work should directly study the mechanisms through which SAIA operates and the influence of contextual factors on implementation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03514459. Registered on April 19, 2018.

Fertility Desire and Associations with Condomless Sex, Antiretroviral Adherence, and Transmission Potential in a Cohort of Kenyan Women Living with HIV in Sero-discordant Relationships: A Mixed Methods Study.

For women living with HIV (WLH) in serodiscordant partnerships, decisions about childbearing can challenge condom use and antiretroviral adherence. In a prospective cohort of 148 WLH in serodiscordant partnerships, 58 (39%) wanted more children in the future but were not currently trying to conceive (fertility desire), and 32 (22%) were currently trying to become pregnant (fertility intent). Detection of prostate specific antigen (PSA) in vaginal secretions, a marker for recent condomless sex, was lowest in women with fertility desire and highest in women with fertility intent. Detectable viral load followed a similar pattern. Risk of HIV transmission, when condomless sex and PSA detection occurred concurrently, was three to fourfold higher at visits with fertility intent compared to visits with fertility desire. Qualitative interviews underscored the importance women place on childbearing and suggested that they had limited information about the role of antiretroviral therapy in reducing sexual HIV transmission.

The Systems Analysis and Improvement Approach: specifying core components of an implementation strategy to optimize care cascades in public health.

BACKGROUND: Healthcare systems in low-resource settings need simple, low-cost interventions to improve services and address gaps in care. Though routine data provide opportunities to guide these efforts, frontline providers are rarely engaged in analyzing them for facility-level decision making. The Systems Analysis and Improvement Approach (SAIA) is an evidence-based, multi-component implementation strategy that engages providers in use of facility-level data to promote systems-level thinking and quality improvement (QI) efforts within multi-step care cascades. SAIA was originally developed to address HIV care in resource-limited settings but has since been adapted to a variety of clinical care systems including cervical cancer screening, mental health treatment, and hypertension management, among others; and across a variety of settings in sub-Saharan Africa and the USA. We aimed to extend the growing body of SAIA research by defining the core elements of SAIA using established specification approaches and thus improve reproducibility, guide future adaptations, and lay the groundwork to define its mechanisms of action. METHODS: Specification of the SAIA strategy was undertaken over 12 months by an expert panel of SAIA-researchers, implementing agents and stakeholders using a three-round, modified nominal group technique approach to match core SAIA components to the Expert Recommendations for Implementing Change (ERIC) list of distinct implementation strategies. Core implementation strategies were then specified according to Proctor's recommendations for specifying and reporting, followed by synthesis of data on related implementation outcomes linked to the SAIA strategy across projects. RESULTS: Based on this review and clarification of the operational definitions of the components of the SAIA, the four components of SAIA were mapped to 13 ERIC strategies. SAIA strategy meetings encompassed external facilitation, organization of provider implementation meetings, and provision of ongoing consultation. Cascade analysis mapped to three ERIC strategies: facilitating relay of clinical data to providers, use of audit and feedback of routine data with healthcare teams, and modeling and simulation of change. Process mapping matched to local needs assessment, local consensus discussions and assessment of readiness and identification of barriers and facilitators. Finally, continuous quality improvement encompassed tailoring strategies, developing a formal implementation blueprint, cyclical tests of change, and purposefully re-examining the implementation process. CONCLUSIONS: Specifying the components of SAIA provides improved conceptual clarity to enhance reproducibility for other researchers and practitioners interested in applying the SAIA across novel settings.

The cost of implementing the Systems Analysis and Improvement Approach for a cluster randomized trial integrating HIV testing into family planning services in Mombasa County, Kenya.

BACKGROUND: Although HIV testing in family planning (FP) clinics is a promising approach for engaging women in HIV treatment and prevention services, HIV testing rates are low in FP clinics in Kenya. In 2018, a cluster randomized trial was implemented in Mombasa, Kenya applying the Systems Analysis and Improvement Approach (SAIA) to integrate HIV testing into FP services (1K24HD088229-01). We estimated the incremental costs and explored cost drivers of the FP HIV SAIA implementation in Mombasa, Kenya. METHODS: We conducted a costing evaluation from the payer perspective for the FP HIV SAIA randomized control trial. We identified relevant activities for the intervention including start-up, training, research and FP HIV SAIA. We estimated activity time burden using a time-and motion study. We derived unit costs through staff interviews and programmatic budgets. We present cost estimates for two different scenarios: as-implemented including research and projected costs for a Ministry of Health-supported intervention. All costs are reported in 2018 USD. RESULTS: For an annual program output of 36,086 HIV tests administered to new FP clients, we estimated the total annual program cost to be $91,994 with an average cost per new FP client served of $2.55. Personnel and HIV rapid testing kits comprised 55% and 21% of programmatic costs, respectively. Assuming no changes to program outputs and with efficiency gains under the MOH scenario, the estimated cost per new FP client served decreased to $1.30 with a programmatic cost reduction of 49%. CONCLUSION: FP HIV SAIA is a low-cost and flexible implementation strategy for facilitating integrated delivery of HIV testing alongside FP services. Although cost implications of the FP HIV SAIA intervention must continue to be evaluated over time, these findings provide context-specific cost data useful for budget planning and decision-making regarding intervention delivery and expansion. TRIAL REGISTRATION: The trial was registered on December 15, 2016, with clinicaltrials.gov (NCT02994355).

A cross-sectional study of the prevalence, barriers, and facilitators of cervical cancer screening in family planning clinics in Mombasa County, Kenya.

BACKGROUND: Cervical cancer is the most common cancer in sub-Saharan Africa. With appropriate screening and treatment, cervical cancer can be prevented. In Kenya, cervical cancer screening is recommended for all women of reproductive age who visit a health facility. In particular, the Kenyan Ministry of Health has tasked family planning clinics and HIV clinics with implementing cervical cancer screening as part of the overall cervical cancer screening strategy. A cross-sectional survey was conducted to understand cervical cancer screening practices and explore clinic-level barriers and facilitators to screening in family planning clinics (FP) in Mombasa County, Kenya. METHODS: Structured interviews were conducted with randomly sampled FP clinic managers to collect information about clinic size, location, type, management support, infrastructure, screening practices, and availability of screening commodities. Data were abstracted from FP registers for a 15-month period from October 1, 2017 until December 31, 2018 to understand cervical cancer screening prevalence. Generalized linear models were used to calculate prevalence ratios (PR) and identify clinic-level correlates of reporting any cervical cancer screening. RESULTS: A total of 70 clinics were sampled, 54% (38) were urban and 27% (19) were public facilities. The median number of staff in a clinic was 4 (interquartile range [IQR] 2-6) with a median of 1 provider trained to perform screening (IQR 0-3). Fifty-four percent (38/70) of clinic managers reported that their clinics performed cervical cancer screening. Of these, only 87% (33) and 71% (27) had dependable access to speculums and acetic acid, respectively. Being a public FP clinic was associated with higher prevalence of reported screening (14/38 [37%] vs 6/32 [16%]; prevalence rate ratio [PR] 1.57, 95%CI 1.05-2.33). Clinics that reported cervical cancer screening were much more likely to have at least one provider trained to perform cervical cancer screening (84%, 32/38) compared to clinics that did not report screening (28%, 9/32; PR 3.77, 95%CI 1.82-7.83). CONCLUSION: Integration of cervical cancer screening into FP clinics offers great potential to reach large numbers of reproductive-aged women. Increasing training of healthcare providers and ensuring adequate commodity supplies in FP clinics offer concrete solutions to increase screening in a largely unscreened population.

Assessing the sustainability of the Systems Analysis and Improvement Approach to increase HIV testing in family planning clinics in Mombasa, Kenya: results of a cluster randomized trial.

BACKGROUND: In Kenya, HIV incidence is highest among reproductive-age women. A key HIV mitigation strategy is the integration of HIV testing and counseling (HTC) into family planning services, but successful integration remains problematic. We conducted a cluster-randomized trial using the Systems Analysis and Improvement Approach (SAIA) to identify and address bottlenecks in HTC integration in family planning clinics in Mombasa County, Kenya. This trial (1) assessed the efficacy of this approach and (2) examined if SAIA could be sustainably incorporated into the Department of Health Services (DOHS) programmatic activities. In Stage 1, SAIA was effective at increasing HTC uptake. Here, we present Stage 2, which assessed if SAIA delivery would be sustained when implemented by the Mombasa County DOHS and if high HTC performance would continue to be observed. METHODS: Twenty-four family planning clinics in Mombasa County were randomized to either the SAIA implementation strategy or standard care. In Stage 1, the study staff conducted all study activities. In Stage 2, we transitioned SAIA implementation to DOHS staff and compared HTC in the intervention versus control clinics 1-year post-transition. Study staff provided training and minimal support to DOHS implementers and collected quarterly HTC outcome data. Interviews were conducted with family planning clinic staff to assess barriers and facilitators to sustaining HTC delivery. RESULTS: Only 39% (56/144) of planned SAIA visits were completed, largely due to the COVID-19 pandemic and a prolonged healthcare worker strike. In the final study quarter, 81.6% (160/196) of new clients at intervention facilities received HIV counseling, compared to 22.4% (55/245) in control facilities (prevalence rate ratio [PRR]=3.64, 95% confidence interval [CI]=2.68-4.94). HIV testing was conducted with 60.5% (118/195) of new family planning clients in intervention clinics, compared to 18.8% (45/240) in control clinics (PRR=3.23, 95% CI=2.29-4.55). Interviews with family planning clinic staff suggested institutionalization contributed to sustained HTC delivery, facilitated by low implementation strategy complexity and continued oversight. CONCLUSIONS: Intervention clinics demonstrated sustained improvement in HTC after SAIA was transitioned to DOHS leadership despite wide-scale healthcare disruptions and incomplete delivery of the implementation strategy. These findings suggest that system interventions may be sustained when integrated into DOHS programmatic activities. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02994355) registered on 16 December 2016.

Qualitative evaluation of the Systems Analysis and Improvement Approach as a strategy to increase HIV testing in family planning clinics using the Consolidated Framework for Implementation Research and the Implementation Outcomes Framework.

BACKGROUND: Significant gaps remain in HIV testing and counseling (HTC) in family planning (FP) clinics. To address these gaps, our group tested an implementation strategy called the Systems Analysis and Improvement Approach (SAIA), an evidenced-based multi-component implementation strategy focused on improving entire care cascades. In a cluster randomized trial of 24 FP clinics in Mombasa County, Kenya, SAIA led to a significant increase in HTC in intervention clinics compared to control clinics. The objective of this manuscript was to evaluate SAIA using the Consolidated Framework for Implementation Research (CFIR) and assess the Implementation Outcomes Framework outcomes of acceptability, appropriateness, and feasibility. METHODS: This qualitative assessment was nested within the cluster-randomized trial. Data collection included questionnaires to assess modifiable and non-modifiable health system factors related to HTC and in-depth interviews to query clinic norms, priorities, communication strategies, and readiness for change. The primary outcomes of interest were feasibility, appropriateness, and acceptability of SAIA. Data on inner setting and structural characteristics of FP clinics were collected to inform how context may impact outcomes. All interviews were recorded and analyzed using a rapid assessment approach. RESULTS: Of the 12 intervention clinics, 6 (50%) were public facilities. Availability of resources varied by clinic. Most clinics had a positive implementation climate, engaged leadership, and access to resources and information. While not all clinics identified HTC as a clinic priority, most reported a strong culture of embracing change and recognition of the importance of HIV testing within FP clinics. Interviews highlighted very high acceptability, appropriateness, and feasibility of SAIA. The implementation strategy was not complicated and fit well into existing clinic processes. In particular, staff appreciated that SAIA allowed clinic staff to generate contextually relevant solutions that they implemented. CONCLUSIONS: SAIA was implemented in FP clinics of varying sizes, capacity, and management support and was found to be acceptable, appropriate, and feasible. The agency that clinic staff felt in proposing and implementing their own solutions was likely part of SAIA's success. We anticipate this will continue to be a mechanism of SAIA's success when it is scaled up to more clinics in future trials. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02994355) registered 16 December 2016.

Cervical cancer screening, abnormal results, and follow-up in women with substance use-related diagnoses.

Background: Substance use-related diagnoses are common and associated with poor health outcomes. The objective of this analysis was to compare rates of cervical cancer screening, screening abnormalities, and follow-up care in women with and without a substance use-related diagnosis seen for primary care between January 1, 2016 and December 31, 2019 in the University of Washington healthcare system. Methods: This study included women aged 21-65 years of age who had at least one outpatient visit between January 1, 2016 and December 31, 2019 within one of 45 primary care or women's health clinics in the academic healthcare system. Exposure status was defined using ICD10 codes for substance-use related diagnoses or no substance-use related diagnoses. Only first cervical cancer screening was included. Generalized linear models with a binomial family and log link were used to estimate risk ratios. Results: 3845 women had a substance use-related diagnosis and 89214 did not. Women with a substance use-related diagnosis were less likely to be screened for cervical cancer (44%, 1675/3845) compared to women without a substance use-related diagnosis (49%, 43338/89214; relative risk [RR] 0.90, 95% CI 0.86-0.93). Women with a substance use-related diagnosis were also more likely to have an abnormal screening result (18%, 304/1675) compared to women without a substance use-related diagnosis (10%, 4528/43338; RR 1.74, 95% CI 1.56-1.93). Follow-up for abnormal screens did not differ significantly between groups (24 vs 25%; RR 0.80, 95% CI 0.55-1.17). Conclusion: To combat disparities in cervical cancer screening for women with substance use-related diagnoses, public health efforts should expand access to screening where women with substance use-related diagnoses are seen, including acute care, inpatient hospitalizations, and addiction treatment settings.

Association between duration of antimicrobial prophylaxis and postoperative outcomes after lumbar spine surgery.

OBJECTIVES: To describe the association between duration of antimicrobial prophylaxis (AMP) and 30-day surgical site infection (SSI), 7-day acute kidney injury (AKI), 90-day Clostridioides difficile infection (CDI), prolonged hospitalization, and 30-day reoperation after lumbar spine surgery for noninfectious indications, and to report adherence to current guidelines. DESIGN: Survey. PARTICIPANTS AND SETTING: The study cohort comprised 6,198 patients who underwent lumbar spine surgery for noninfectious indications across 137 Veterans' Health Administration surgery centers between 2016 and 2020. METHODS: Used univariate and multivariate logistic regression to determine the association between type and duration of AMP with 30-day SSI, 7-day AKI, 90-day CDI, prolonged hospitalization, and 30-day reoperation. RESULTS: Only 1,160 participants (18.7%) received the recommended duration of AMP. On multivariate analysis, the use of multiple prophylactic antimicrobials was associated with increased odds of 90-day CDI (adjusted odds ratio [aOR], 5.5; 95% confidence interval [CI], 1.1-28.2) and 30-day reoperation (aOR, 2.3; 95% CI, 1.2-4.4). Courses of antimicrobials ≥3 days were associated with increased odds of prolonged hospitalization (aOR,1.8; 95% CI, 1.4-2.3) and 30-day reoperation (aOR, 3.5; 95% CI, 2.2-5.7). In univariate analysis, increasing days of AMP was associated with a trend toward increasing odds of 90-day CDI (cOR, 1.4; 95% CI, 1.0-1.8 per additional day; P = .056). CONCLUSIONS: Longer courses of AMP after lumbar spine surgery were associated with higher odds of CDI, prolonged hospitalization, and reoperation, but not with lower odds of SSI. However, adherence to the recommended duration of AMP is very low, hinting at a wide evidence-to-practice gap that needs to be addressed by spine surgeons and antimicrobial stewardship programs.

Trends Over Time in the Risk of Adverse Outcomes Among Patients With Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

BACKGROUND: We aimed to describe trends in adverse outcomes among patients who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between February and September 2020 within a national healthcare system. METHODS: We identified enrollees in the national United States Veterans Affairs healthcare system who tested positive for SARS-CoV-2 between 28 February 2020 and 30 September 2020 (n = 55 952), with follow-up extending to 19 November 2020. We determined trends over time in incidence of the following outcomes that occurred within 30 days of testing positive: hospitalization, intensive care unit (ICU) admission, mechanical ventilation, and death. RESULTS: Between February and July 2020, there were marked downward trends in the 30-day incidence of hospitalization (44.2% to 15.8%), ICU admission (20.3% to 5.3%), mechanical ventilation (12.7% to 2.2%), and death (12.5% to 4.4%), which subsequently plateaued between July and September 2020. These trends persisted after adjustment for sociodemographic characteristics, comorbid conditions, documented symptoms, and laboratory tests, including among subgroups of patients hospitalized, admitted to the ICU, or treated with mechanical ventilation. From February to September, there were decreases in the use of hydroxychloroquine (56.5% to 0%), azithromycin (48.3% to 16.6%), vasopressors (20.6% to 8.7%), and dialysis (11.6% to 3.8%) and increases in the use of dexamethasone (3.4% to 53.1%), other corticosteroids (4.9% to 29.0%), and remdesivir (1.7% to 45.4%) among hospitalized patients. CONCLUSIONS: The risk of adverse outcomes in SARS-CoV-2-positive patients decreased markedly between February and July, with subsequent stabilization from July to September. These trends were not explained by changes in measured baseline patient characteristics and may reflect changing treatment practices or viral pathogenicity.

Results of a cluster randomized trial testing the systems analysis and improvement approach to increase HIV testing in family planning clinics.

OBJECTIVE: The aim of this study was to test an implementation strategy, the Systems Analysis and Improvement Approach (SAIA), to increase rates of HIV testing and counseling (HTC) in family planning clinics in Mombasa, Kenya. DESIGN: A cluster randomized trial. METHODS: Twenty-four family planning clinics were randomized 1 : 1 to implementing SAIA versus usual procedures. Study staff implemented monthly SAIA cycles with family planning clinic staff for 12 months. SAIA has five steps. Step 1 uses a "cascade analysis' tool to quantify the number of individuals who complete each step of a process. Step 2 involves sequential process flow mapping to identify modifiable bottlenecks in the system. Step 3 develops and implements workflow modifications to address bottlenecks. Step 4 assesses impact of the modification by recalculating the cascade analysis. Step 5 repeats the cycle. The primary outcome was the proportion of new family planning clients tested for HIV during the last quarter of the trial. RESULTS: During the last 3 months of the trial, 85% (740/868) of new family planning clients were counseled for HIV in intervention clinics compared with 67% (1036/1542) in control clinics (prevalence rate ratio [PRR] 1.27, 95% confidence interval [CI] 1.15-1.30). Forty-two percent (364/859) of family planning clients were tested for HIV at intervention clinics compared with 32% (485/1521) at control clinics (PRR 1.33, 95% CI 1.16-1.52). CONCLUSION: SAIA led to a significant increase in HIV testing in family planning clinics in Mombasa. Integrating routine HTC into family planning clinics is a promising strategy to achieve the UNAIDS goal of 95% of people living with HIV being aware of their status.

Late antiretroviral refills and condomless sex in a cohort of HIV-seropositive pregnant and postpartum Kenyan women.

INTRODUCTION: The postpartum period can be challenging for women living with HIV. Understanding how the postpartum period impacts ART adherence and condomless sex could inform the development of comprehensive sexual and reproductive health and HIV services tailored to the needs of women living with HIV during this critical interval. METHODS: In a longitudinal cohort study of HIV-seropositive Kenyan women, late ART refills and self-reported condomless sex were compared between the woman's pregnancy and the postpartum period. Analyses were conducted using generalized estimating equations and adjusted for alcohol use, depressive symptoms, intimate partner violence (IPV), and having a recent regular partner. Effect modification was explored for selected variables. RESULTS AND DISCUSSION: 151 women contributed visits. Late ART refills occurred at 7% (32/439) of pregnancy visits compared to 18% (178/1016) during the postpartum period (adjusted relative risk [aRR] 2.44, 95% confidence interval [CI] 1.62-3.67). This association differed by women's education level. Women with ≥8 years of education had late ART refills more during the postpartum period than pregnancy (aRR 3.00, 95%CI 1.95-4.62). In contrast, in women with <8 years of education, late ART refills occurred similarly during pregnancy and the postpartum period (aRR 0.88, 95%CI 0.18-4.35). Women reported condomless sex at 10% (60/600) of pregnancy visits compared to 7% (72/1081) of postpartum visits (aRR 0.76, 95%CI 0.45-1.27). This association differed by whether women had experienced recent IPV. Women without recent IPV had a significant decline in condomless sex from pregnancy to postpartum (aRR 0.53, 95%CI 0.30-0.95) while women with recent IPV had no significant change in condomless sex from pregnancy to postpartum (aRR 1.76, 95%CI 0.87-3.55). CONCLUSION: Improved support for ART adherence during the postpartum period and addressing IPV to limit condomless sex could improve HIV treatment and prevention outcomes for HIV-seropositive women as well as their infants and sexual partners.

Development of COVIDVax Model to Estimate the Risk of SARS-CoV-2-Related Death Among 7.6 Million US Veterans for Use in Vaccination Prioritization.

Importance: A strategy that prioritizes individuals for SARS-CoV-2 vaccination according to their risk of SARS-CoV-2-related mortality would help minimize deaths during vaccine rollout. Objective: To develop a model that estimates the risk of SARS-CoV-2-related mortality among all enrollees of the US Department of Veterans Affairs (VA) health care system. Design, Setting, and Participants: This prognostic study used data from 7 635 064 individuals enrolled in the VA health care system as of May 21, 2020, to develop and internally validate a logistic regression model (COVIDVax) that predicted SARS-CoV-2-related death (n = 2422) during the observation period (May 21 to November 2, 2020) using baseline characteristics known to be associated with SARS-CoV-2-related mortality, extracted from the VA electronic health records (EHRs). The cohort was split into a training period (May 21 to September 30) and testing period (October 1 to November 2). Main Outcomes and Measures: SARS-CoV-2-related death, defined as death within 30 days of testing positive for SARS-CoV-2. VA EHR data streams were imported on a data integration platform to demonstrate that the model could be executed in real-time to produce dashboards with risk scores for all current VA enrollees. Results: Of 7 635 064 individuals, the mean (SD) age was 66.2 (13.8) years, and most were men (7 051 912 [92.4%]) and White individuals (4 887 338 [64.0%]), with 1 116 435 (14.6%) Black individuals and 399 634 (5.2%) Hispanic individuals. From a starting pool of 16 potential predictors, 10 were included in the final COVIDVax model, as follows: sex, age, race, ethnicity, body mass index, Charlson Comorbidity Index, diabetes, chronic kidney disease, congestive heart failure, and Care Assessment Need score. The model exhibited excellent discrimination with area under the receiver operating characteristic curve (AUROC) of 85.3% (95% CI, 84.6%-86.1%), superior to the AUROC of using age alone to stratify risk (72.6%; 95% CI, 71.6%-73.6%). Assuming vaccination is 90% effective at preventing SARS-CoV-2-related death, using this model to prioritize vaccination was estimated to prevent 63.5% of deaths that would occur by the time 50% of VA enrollees are vaccinated, significantly higher than the estimate for prioritizing vaccination based on age (45.6%) or the US Centers for Disease Control and Prevention phases of vaccine allocation (41.1%). Conclusions and Relevance: In this prognostic study of all VA enrollees, prioritizing vaccination based on the COVIDVax model was estimated to prevent a large proportion of deaths expected to occur during vaccine rollout before sufficient herd immunity is achieved.

Association Between Vaginal Bacterial Microbiota and Vaginal Yeast Colonization.

BACKGROUND: Vaginal yeast is frequently found with Lactobacillus-dominant microbiota. The relationship between vaginal yeast and other bacteria has not been well characterized. METHODS: These analyses utilized data from the Preventing Vaginal Infections trial. Relative abundance of vaginal bacteria from 16S ribosomal ribonucleic acid gene amplicon sequencing and quantities of 10 vaginal bacteria using taxon-directed polymerase chain reaction assays were compared at visits with and without detection of yeast on microscopy, culture, or both. RESULTS: Higher relative abundances of Megasphaera species type 1 (risk ratio [RR], 0.70; 95% confidence interval [CI], 0.52-0.95), Megasphaera species type 2 (RR, 0.81; 95% CI, 0.67-0.98), and Mageeibacillus indolicus (RR, 0.46; 95% CI, 0.25-0.83) were associated with lower risk of detecting yeast. In contrast, higher relative abundances of Bifidobacterium bifidum, Aerococcus christensenii, Lactobacillus mucosae, Streptococcus equinus/infantarius/lutentiensis, Prevotella bivia, Dialister propionicifaciens, and Lactobacillus crispatus/helveticus were associated with yeast detection. Taxon-directed assays confirmed that increasing quantities of both Megasphaera species and M indolicus were associated with lower risk of detecting yeast, whereas increasing quantities of L crispatus were associated with higher risk of detecting yeast. CONCLUSIONS: Despite an analysis that examined associations between multiple vaginal bacteria and the presence of yeast, only a small number of vaginal bacteria were strongly and significantly associated with the presence or absence of yeast.

Risk Factors for Testing Positive for Severe Acute Respiratory Syndrome Coronavirus 2 in a National United States Healthcare System.

BACKGROUND: Identifying risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection could help health systems improve testing and screening strategies. The aim of this study was to identify demographic factors, comorbid conditions, and symptoms independently associated with testing positive for SARS-CoV-2. METHODS: This was an observational cross-sectional study at the Veterans Health Administration, including persons tested for SARS-CoV-2 nucleic acid by polymerase chain reaction (PCR) between 28 February and 14 May 2020. Associations between demographic characteristics, diagnosed comorbid conditions, and documented symptoms with testing positive for SARS-CoV-2 were measured. RESULTS: Of 88 747 persons tested, 10 131 (11.4%) were SARS-CoV-2 PCR positive. Positivity was associated with older age (≥80 vs <50 years: adjusted odds ratio [aOR], 2.16 [95% confidence interval {CI}, 1.97-2.37]), male sex (aOR, 1.45 [95% CI, 1.34-1.57]), regional SARS-CoV-2 burden (≥2000 vs <400 cases/million: aOR, 5.43 [95% CI, 4.97-5.93]), urban residence (aOR, 1.78 [95% CI, 1.70-1.87]), black (aOR, 2.15 [95% CI, 2.05-2.26]) or American Indian/Alaska Native Hawaiian/Pacific Islander (aOR, 1.26 [95% CI, 1.05-1.52]) vs white race, and Hispanic ethnicity (aOR, 1.52 [95% CI, 1.40-1.65]). Obesity and diabetes were the only 2 medical conditions associated with testing positive. Documented fevers, chills, cough, and diarrhea were also associated with testing positive. The population attributable fraction of positive tests was highest for geographic location (35.3%), followed by demographic variables (27.1%), symptoms (12.0%), obesity (10.5%), and diabetes (0.4%). CONCLUSIONS: The majority of positive SARS-CoV-2 tests were attributed to geographic location, demographic characteristics, and obesity, with a minor contribution of chronic comorbid conditions.

Cirrhosis and Severe Acute Respiratory Syndrome Coronavirus 2 Infection in US Veterans: Risk of Infection, Hospitalization, Ventilation, and Mortality.

BACKGROUND AND AIMS: Whether patients with cirrhosis have increased risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the extent to which infection and cirrhosis increase the risk of adverse patient outcomes remain unclear. APPROACH AND RESULTS: We identified 88,747 patients tested for SARS-CoV-2 between March 1, 2020, and May 14, 2020, in the Veterans Affairs (VA) national health care system, including 75,315 with no cirrhosis-SARS-CoV-2-negative (C0-S0), 9,826 with no cirrhosis-SARS-CoV-2-positive (C0-S1), 3,301 with cirrhosis-SARS-CoV-2-negative (C1-S0), and 305 with cirrhosis-SARS-CoV-2-positive (C1-S1). Patients were followed through June 22, 2020. Hospitalization, mechanical ventilation, and death were modeled in time-to-event analyses using Cox proportional hazards regression. Patients with cirrhosis were less likely to test positive than patients without cirrhosis (8.5% vs. 11.5%; adjusted odds ratio, 0.83; 95% CI, 0.69-0.99). Thirty-day mortality and ventilation rates increased progressively from C0-S0 (2.3% and 1.6%) to C1-S0 (5.2% and 3.6%) to C0-S1 (10.6% and 6.5%) and to C1-S1 (17.1% and 13.0%). Among patients with cirrhosis, those who tested positive for SARS-CoV-2 were 4.1 times more likely to undergo mechanical ventilation (adjusted hazard ratio [aHR], 4.12; 95% CI, 2.79-6.10) and 3.5 times more likely to die (aHR, 3.54; 95% CI, 2.55-4.90) than those who tested negative. Among patients with SARS-CoV-2 infection, those with cirrhosis were more likely to be hospitalized (aHR, 1.37; 95% CI, 1.12-1.66), undergo ventilation (aHR, 1.61; 95% CI, 1.05-2.46) or die (aHR, 1.65; 95% CI, 1.18-2.30) than patients without cirrhosis. Among patients with cirrhosis and SARS-CoV-2 infection, the most important predictors of mortality were advanced age, cirrhosis decompensation, and high Model for End-Stage Liver Disease score. CONCLUSIONS: SARS-CoV-2 infection was associated with a 3.5-fold increase in mortality in patients with cirrhosis. Cirrhosis was associated with a 1.7-fold increase in mortality in patients with SARS-CoV-2 infection.

BMI and Outcomes of SARS-CoV-2 Among US Veterans.

OBJECTIVE: The purpose of this study is to examine the associations of BMI with testing positive for severe acute respiratory coronavirus 2 (SARS-CoV-2) and risk of adverse outcomes in a cohort of Veterans Affairs enrollees. METHOD: Adjusted relative risks/hazard ratios (HRs) were calculated for the associations between BMI category (underweight, normal weight, overweight, class 1 obesity, class 2 obesity, and class 3 obesity) and testing positive for SARS-CoV-2 or experiencing hospitalization, intensive care unit admission, mechanical ventilation, and death among those testing positive. RESULTS: Higher BMI categories were associated with higher risk of a positive SARS-CoV-2 test compared with the normal weight category (class 3 obesity adjusted relative risk: 1.34, 95% CI: 1.28-1.42). Among 25,952 patients who tested positive for SARS-CoV-2, class 3 obesity was associated with higher risk of mechanical ventilation (adjusted HR [aHR]: 1.77, 95% CI: 1.35-2.32) and mortality (aHR: 1.42, 95% CI: 1.12-1.78) compared with normal weight individuals. These associations were present primarily in patients younger than 65 and were attenuated or absent in older age groups (interaction P < 0.05). CONCLUSION: Veterans Affairs enrollees with higher BMI were more likely to test positive for SARS-CoV-2 and were more likely to be mechanically ventilated or die if infected with SARS-CoV-2. Higher BMI contributed relatively more to the risk of death in those younger than 65 years of age as compared with other age categories.

Risk Factors for Hospitalization, Mechanical Ventilation, or Death Among 10 131 US Veterans With SARS-CoV-2 Infection.

Importance: Identifying independent risk factors for adverse outcomes in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can support prognostication, resource utilization, and treatment. Objective: To identify excess risk and risk factors associated with hospitalization, mechanical ventilation, and mortality in patients with SARS-CoV-2 infection. Design, Setting, and Participants: This longitudinal cohort study included 88 747 patients tested for SARS-CoV-2 nucleic acid by polymerase chain reaction between Feburary 28 and May 14, 2020, and followed up through June 22, 2020, in the Department of Veterans Affairs (VA) national health care system, including 10 131 patients (11.4%) who tested positive. Exposures: Sociodemographic characteristics, comorbid conditions, symptoms, and laboratory test results. Main Outcomes and Measures: Risk of hospitalization, mechanical ventilation, and death were estimated in time-to-event analyses using Cox proportional hazards models. Results: The 10 131 veterans with SARS-CoV-2 were predominantly male (9221 [91.0%]), with diverse race/ethnicity (5022 [49.6%] White, 4215 [41.6%] Black, and 944 [9.3%] Hispanic) and a mean (SD) age of 63.6 (16.2) years. Compared with patients who tested negative for SARS-CoV-2, those who tested positive had higher rates of 30-day hospitalization (30.4% vs 29.3%; adjusted hazard ratio [aHR], 1.13; 95% CI, 1.08-1.13), mechanical ventilation (6.7% vs 1.7%; aHR, 4.15; 95% CI, 3.74-4.61), and death (10.8% vs 2.4%; aHR, 4.44; 95% CI, 4.07-4.83). Among patients who tested positive for SARS-CoV-2, characteristics significantly associated with mortality included older age (eg, ≥80 years vs <50 years: aHR, 60.80; 95% CI, 29.67-124.61), high regional COVID-19 disease burden (eg, ≥700 vs <130 deaths per 1 million residents: aHR, 1.21; 95% CI, 1.02-1.45), higher Charlson comorbidity index score (eg, ≥5 vs 0: aHR, 1.93; 95% CI, 1.54-2.42), fever (aHR, 1.51; 95% CI, 1.32-1.72), dyspnea (aHR, 1.78; 95% CI, 1.53-2.07), and abnormalities in the certain blood tests, which exhibited dose-response associations with mortality, including aspartate aminotransferase (>89 U/L vs ≤25 U/L: aHR, 1.86; 95% CI, 1.35-2.57), creatinine (>3.80 mg/dL vs 0.98 mg/dL: aHR, 3.79; 95% CI, 2.62-5.48), and neutrophil to lymphocyte ratio (>12.70 vs ≤2.71: aHR, 2.88; 95% CI, 2.12-3.91). With the exception of geographic region, the same covariates were independently associated with mechanical ventilation along with Black race (aHR, 1.52; 95% CI, 1.25-1.85), male sex (aHR, 2.07; 95% CI, 1.30-3.32), diabetes (aHR, 1.40; 95% CI, 1.18-1.67), and hypertension (aHR, 1.30; 95% CI, 1.03-1.64). Notable characteristics that were not significantly associated with mortality in adjusted analyses included obesity (body mass index ≥35 vs 18.5-24.9: aHR, 0.97; 95% CI, 0.77-1.21), Black race (aHR, 1.04; 95% CI, 0.88-1.21), Hispanic ethnicity (aHR, 1.03; 95% CI, 0.79-1.35), chronic obstructive pulmonary disease (aHR, 1.02; 95% CI, 0.88-1.19), hypertension (aHR, 0.95; 95% CI, 0.81-1.12), and smoking (eg, current vs never: aHR, 0.87; 95% CI, 0.67-1.13). Most deaths in this cohort occurred in patients with age of 50 years or older (63.4%), male sex (12.3%), and Charlson Comorbidity Index score of at least 1 (11.1%). Conclusions and Relevance: In this national cohort of VA patients, most SARS-CoV-2 deaths were associated with older age, male sex, and comorbidity burden. Many factors previously reported to be associated with mortality in smaller studies were not confirmed, such as obesity, Black race, Hispanic ethnicity, chronic obstructive pulmonary disease, hypertension, and smoking.