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1.
J Med Virol ; 93(12): 6703-6713, 2021 12.
Article in English | MEDLINE | ID: covidwho-1544323

ABSTRACT

Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77-0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77-0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the "first wave" of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78-0.87]; for full follow-up: 0.82 [95% CI: 0.78-0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.


Subject(s)
COVID-19/diagnosis , Adult , Age Factors , Aged , Aged, 80 and over , C-Reactive Protein/analysis , COVID-19/mortality , COVID-19/pathology , Female , Fibrin Fibrinogen Degradation Products/analysis , Humans , Male , Middle Aged , Reproducibility of Results , Risk Assessment , Risk Factors , Severity of Illness Index , Urea/blood , Young Adult
2.
JMIR Form Res ; 6(1): e32564, 2022 Jan 04.
Article in English | MEDLINE | ID: covidwho-1528774

ABSTRACT

BACKGROUND: Large-scale, polymerase chain reaction (PCR)-based SARS-CoV-2 testing is expensive, resource intensive, and time consuming. A self-collection approach is a probable alternative; however, its feasibility, cost, and ability to prevent infections need to be evaluated. OBJECTIVE: This study aims to compare an innovative self-collection approach with a regular SARS-CoV-2 testing strategy in a large European industrial manufacturing site. METHODS: The feasibility of a telemedicine-guided PCR-based self-collection approach was assessed for 150 employees (intervention group) and compared with a regular SARS-CoV-2 testing approach used for 143 employees (control group). Acceptance, ergonomics, and efficacy were evaluated using a software application. A simulation model was implemented to evaluate the effectiveness. An interactive R shiny app was created to enable customized simulations. RESULTS: The test results were successfully communicated to and interpreted without uncertainty by 76% (114/150) and 76.9% (110/143) of the participants in the intervention and control groups, respectively (P=.96). The ratings for acceptability, ergonomics, and efficacy among intervention group participants were noninferior when compared to those among control group participants (acceptability: 71.6% vs 37.6%; ergonomics: 88.1% vs 74.5%; efficacy: 86.4% vs 77.5%). The self-collection approach was found to be less time consuming (23 min vs 38 min; P<.001). The simulation model indicated that both testing approaches reduce the risk of infection, and the self-collection approach tends to be slightly less effective owing to its lower sensitivity. CONCLUSIONS: The self-collection approach for SARS-CoV-2 diagnosis was found to be technically feasible and well rated in terms of acceptance, ergonomics, and efficacy. The simulation model facilitates the evaluation of test effectiveness; nonetheless, considering context specificity, appropriate adaptation by companies is required.

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