Sensitivity and specificity of alternative screening methods for systematic reviews using text mining tools.

OBJECTIVES: To evaluate the impact of text mining (TM) on the sensitivity and specificity of title and abstract screening strategies for systematic reviews (SRs). STUDY DESIGN AND SETTING: Twenty reviewers each evaluated a 500-citation set. We compared five screening methods: conventional double screen (CDS), single screen, double screen with TM, combined double screen and single screen with TM, and single screen with TM. Rayyan, Abstrackr, and SWIFT-Review were used for each TM method. The results of a published SR were used as the reference standard. RESULTS: The mean sensitivity and specificity achieved by CDS were 97.0% (95% confidence interval [CI]: 94.7, 99.3) and 95.0% (95% CI: 93.0, 97.1). When compared with single screen, CDS provided a greater sensitivity without a decrease in specificity. Rayyan, Abstrackr, and SWIFT-Review identified all relevant studies. Specificity was often higher for TM-assisted methods than that for CDS, although with mean differences of only one-to-two percentage points. For every 500 citations not requiring manual screening, 216 minutes (95% CI: 169, 264) could be saved. CONCLUSION: TM-assisted screening methods resulted in similar sensitivity and modestly improved specificity as compared to CDS. The time saved with TM makes this a promising new tool for SR.

Outcomes of hospitalized COVID-19 patients in Canada: impact of ethnicity, migration status and country of birth.

BACKGROUND: Ethnoracial groups in high-income countries have a 2-fold higher risk of SARS-CoV-2 infection, associated hospitalizations, and mortality than Whites. Migrants are an ethnoracial subset that may have worse COVID-19 outcomes due to additional barriers accessing care, but there are limited data on in-hospital outcomes. We aimed to disaggregate and compare COVID-19 associated hospital outcomes by ethnicity, immigrant status and region of birth. METHODS: Adults with community-acquired SARS-CoV-2 infection, hospitalized March 1-June 30, 2020, at four hospitals in Montréal, Quebec, Canada, were included. Age, sex, socioeconomic status, comorbidities, migration status, region of birth, self-identified ethnicity [White, Black, Asian, Latino, Middle East/North African], intensive care unit (ICU) admissions and mortality were collected. Adjusted hazard ratios (aHR) for ICU admission and mortality by immigrant status, ethnicity and region of birth adjusted for age, sex, socioeconomic status and comorbidities were estimated using Fine and Gray competing risk models. RESULTS: Of 1104 patients (median [IQR] age, 63.0 [51.0-76.0] years; 56% males), 57% were immigrants and 54% were White. Immigrants were slightly younger (62 vs 65 years; p = 0.050), had fewer comorbidities (1.0 vs 1.2; p < 0.001), similar crude ICU admissions rates (33.0% vs 28.2%) and lower mortality (13.3% vs 17.6%; p < 0.001) than Canadian-born. In adjusted models, Blacks (aHR 1.39, 95% confidence interval 1.05-1.83) and Asians (1.64, 1.15-2.34) were at higher risk of ICU admission than Whites, but there was significant heterogeneity within ethnic groups. Asians from Eastern Asia/Pacific (2.15, 1.42-3.24) but not Southern Asia (0.97, 0.49-1.93) and Caribbean Blacks (1.39, 1.02-1.89) but not SSA Blacks (1.37, 0.86-2.18) had a higher risk of ICU admission. Blacks had a higher risk of mortality (aHR 1.56, p = 0.049). CONCLUSIONS: Data disaggregated by region of birth identified subgroups of immigrants at increased risk of COVID-19 ICU admission, providing more actionable data for health policymakers to address health inequities.