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.

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.

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.

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.

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.