Development of a prognostic model of COVID-19 severity: a population-based cohort study in Iceland

Abstract

Background The severity of SARS-CoV-2 infection varies from asymptomatic state to severe respiratory failure and the clinical course is difficult to predict. The aim of the study was to develop a prognostic model to predict the severity of COVID-19 in unvaccinated adults at the time of diagnosis. Methods All SARS-CoV-2-positive adults in Iceland were prospectively enrolled into a telehealth service at diagnosis. A multivariable proportional-odds logistic regression model was derived from information obtained during the enrollment interview of those diagnosed between February 27 and December 31, 2020 who met the inclusion criteria. Outcomes were defined on an ordinal scale: (1) no need for escalation of care during follow-up; (2) need for urgent care visit; (3) hospitalization; and (4) admission to intensive care unit (ICU) or death. Missing data were multiply imputed using chained equations and the model was internally validated using bootstrapping techniques. Decision curve analysis was performed. Results The prognostic model was derived from 4756 SARS-CoV-2-positive persons. In total, 375 (7.9%) only required urgent care visits, 188 (4.0%) were hospitalized and 50 (1.1%) were either admitted to ICU or died due to complications of COVID-19. The model included age, sex, body mass index (BMI), current smoking, underlying conditions, and symptoms and clinical severity score at enrollment. On internal validation, the optimism-corrected Nagelkerke’s R2 was 23.4% (95%CI, 22.7–24.2), the C-statistic was 0.793 (95%CI, 0.789-0.797) and the calibration slope was 0.97 (95%CI, 0.96–0.98). Outcome-specific indices were for urgent care visit or worse (calibration intercept -0.04 [95%CI, -0.06 to -0.02], Emax 0.014 [95%CI, 0.008–0.020]), hospitalization or worse (calibration intercept -0.06 [95%CI, -0.12 to -0.03], Emax 0.018 [95%CI, 0.010–0.027]), and ICU admission or death (calibration intercept -0.10 [95%CI, -0.15 to -0.04] and Emax 0.027 [95%CI, 0.013–0.041]). Conclusion Our prognostic model can accurately predict the later need for urgent outpatient evaluation, hospitalization, and ICU admission and death among unvaccinated SARS-CoV-2-positive adults in the general population at the time of diagnosis, using information obtained by telephone interview.

Serum VEGF Levels on Admission in COVID-19 Patients Correlate with SP-D and Neutrophils, Reflecting Disease Severity: A Prospective Study

“…Additionally, the severe COVID-19 group exhibited a significantly higher prevalence of comorbidities such as hypertension, chronic kidney disease, kidney transplantation (Table 1), and uric acid (dana not shown 20 ). Based on our patient characteristics and biological markers, these findings suggest that factors contributing to disease severity are consistent with previous public reports and risk assessment tests 21,22 . These results reinforce the consistency between our patient characteristics and biological markers in relation to disease severity.…”

Telemedicine in Primary Practice in the Age of the COVID-19 Pandemic—Review

“…The articles on the use of ultrasonography in patient follow-up were exclusively from North America [ 32 , 33 ]. The creation of algorithms useful in medicine based on artificial intelligence has been described in Asia [ 21 ], Europe [ 19 , 20 ], North America [ 18 , 22 ], and Australia [ 17 ]. These divisions are presented in Figure 3 .…”

“…2.37 (0.62; 15.58) (32] 0.892 (1.0; 1.0) (33] • 0.75 (0.71; 0.8 2) (30] 0.99 (0.98; 0.99) (29] 0.84 (0.82; 0.86) (24] 0.70 (0.04; 1.37) (22] 0.97 (0.95; 0.99) (21] 0.79 (0.79; 0.80) (19] 2.35 (1.08; 5.09) (17] 0.86 (0.11; 0.66) (12] ,__.…”