Dataset Information

Sociodemographic features and mortality of individuals on haemodialysis treatment who test positive for SARS-CoV-2: A UK Renal Registry data analysis.

ABSTRACT: Kidney disease is a recognised risk factor for poor COVID-19 outcomes. Up to 30 June 2020, the UK Renal Registry (UKRR) collected data for 2,385 in-centre haemodialysis (ICHD) patients with COVID-19 in England and Wales. Overall unadjusted survival at 1 week after date of positive COVID-19 test was 87.5% (95% CI 86.1-88.8%); mortality increased with age, treatment vintage and there was borderline evidence of Asian ethnicity (HR 1.16, 95% CI 0.94-1.44) being associated with higher mortality. Compared to the general population, the relative risk of mortality for ICHD patients with COVID-19 was 45.4 and highest in younger adults. This retrospective cohort study based on UKRR data supports efforts to protect this vulnerable patient group.

SUBMITTER: Savino M

PROVIDER: S-EPMC7584244 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Sociodemographic features and mortality of individuals on haemodialysis treatment who test positive for SARS-CoV-2: A UK Renal Registry data analysis.

Savino Manuela M Casula Anna A Santhakumaran Shalini S Pitcher David D Wong Esther E Magadi Winnie W Evans Katharine M KM Benoy-Deeney Fran F Griffin James J Plumb Lucy L Steenkamp Retha R Nitsch Dorothea D Medcalf James J

PloS one 20201023 10

Kidney disease is a recognised risk factor for poor COVID-19 outcomes. Up to 30 June 2020, the UK Renal Registry (UKRR) collected data for 2,385 in-centre haemodialysis (ICHD) patients with COVID-19 in England and Wales. Overall unadjusted survival at 1 week after date of positive COVID-19 test was 87.5% (95% CI 86.1-88.8%); mortality increased with age, treatment vintage and there was borderline evidence of Asian ethnicity (HR 1.16, 95% CI 0.94-1.44) being associated with higher mortality. Comp ...[more]

PMID: 33095841

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Project description:BackgroundDespite increased testing efforts and the deployment of vaccines, COVID-19 cases and death toll continue to rise at record rates. Health systems routinely collect clinical and non-clinical information in electronic health records (EHR), yet little is known about how the minimal or intermediate spectra of EHR data can be leveraged to characterize patient SARS-CoV-2 pretest probability in support of interventional strategies.Methods and findingsWe modeled patient pretest probability for SARS-CoV-2 test positivity and determined which features were contributing to the prediction and relative to patients triaged in inpatient, outpatient, and telehealth/drive-up visit-types. Data from the University of Washington (UW) Medicine Health System, which excluded UW Medicine care providers, included patients predominately residing in the Seattle Puget Sound area, were used to develop a gradient-boosting decision tree (GBDT) model. Patients were included if they had at least one visit prior to initial SARS-CoV-2 RT-PCR testing between January 01, 2020 through August 7, 2020. Model performance assessments used area-under-the-receiver-operating-characteristic (AUROC) and area-under-the-precision-recall (AUPR) curves. Feature performance assessments used SHapley Additive exPlanations (SHAP) values. The generalized pretest probability model using all available features achieved high overall discriminative performance (AUROC, 0.82). Performance among inpatients (AUROC, 0.86) was higher than telehealth/drive-up testing (AUROC, 0.81) or outpatient testing (AUROC, 0.76). The two-week test positivity rate in patient ZIP code was the most informative feature towards test positivity across visit-types. Geographic and sociodemographic factors were more important predictors of SARS-CoV-2 positivity than individual clinical characteristics.ConclusionsRecent geographic and sociodemographic factors, routinely collected in EHR though not routinely considered in clinical care, are the strongest predictors of initial SARS-CoV-2 test result. These findings were consistent across visit types, informing our understanding of individual SARS-CoV-2 risk factors with implications for deployment of testing, outreach, and population-level prevention efforts.

Project description:BackgroundA fecal test followed by diagnostic colonoscopy for a positive result is a widely endorsed screening strategy for colorectal cancer (CRC). However, the relationship between the time delay from the positive test to the follow-up colonoscopy and CRC mortality has not been established.MethodsFrom a population-based screening program, we identified CRC patients newly diagnosed from 2005 through 2015 by a positive fecal occult test followed by a colonoscopy. The primary outcome measure was CRC-specific mortality according to four categories for the time elapsed between the positive result and the subsequent colonoscopy.ResultsThe 1749 patients underwent colonoscopies within 0-3 months (n = 981, 56.1%), 4-6 months (n = 307, 17.5%), 7-12 months (n = 157, 9.0%), and later than 12 months (n = 304, 17.4%). CRC-specific deaths according to exposure groups were: 13.8% (135 of 981) for 0-3 months, 10.7% (33 of 307) for 4-6 months (crude hazards ratio [HR] = 0.74, 95% confidence interval [CI] = 0.51 to 1.14), 11.5% (18 of 157) for 7-12 months (crude HR = 0.83, 95% CI = 0.51 to 1.42), and 22.7% (69 of 304) for longer than 12 months (crude HR = 1.40, 95% CI = 1.04 to 1.90). The only variable that was associated with mortality risk was the number of positive slides (P = .003). High positivity was twice the value in the 0-3 as the longer-than-12 months group: 51.9% vs 25.0% and similar for the 4-6 and 7-12 months groups (38.1% and 36.5%), respectively. The adjusted HRs for CRC mortality were 0.81 (95% CI = 0.55 to 1.19); 0.83 (95% CI = 0.50 to 1.41), and 1.53 (95% CI = 1.13 to 2.12, P = .006) for the 4-12, 7-12, and longer-than-12-months groups, respectively, compared with the shortest delay group.ConclusionsAmong screen-diagnosed CRC patients, performance of colonoscopy more than 12 months after the initial positive fecal occult blood test was associated with more advanced disease and higher mortality due to CRC.

Dataset Information

Sociodemographic features and mortality of individuals on haemodialysis treatment who test positive for SARS-CoV-2: A UK Renal Registry data analysis.

Publications

Sociodemographic features and mortality of individuals on haemodialysis treatment who test positive for SARS-CoV-2: A UK Renal Registry data analysis.

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