tetano
Editor, Senior Moderator
BMC Infect Dis
. 2021 Sep 14;21(1):945.
doi: 10.1186/s12879-021-06645-z.
Simple demographic characteristics and laboratory findings on admission may predict in-hospital mortality in patients with SARS-CoV-2 infection: development and validation of the covid-19 score
Marta Obremska[SUP] 1 [/SUP], Monika Pazgan-Simon[SUP] 2 [/SUP], Katarzyna Budrewicz[SUP] 3 [/SUP], Lukasz Bilaszewski[SUP] 4 [/SUP], Joanna Wizowska[SUP] 4 [/SUP], Dariusz Jagielski[SUP] 5 [/SUP], Beata Jankowska-Polanska[SUP] 6 [/SUP], Klaudiusz Nadolny[SUP] 7 8 [/SUP], Jarosław Madowicz[SUP] 9 10 [/SUP], Jolanta Zuwala-Jagiello[SUP] 11 [/SUP], Dorota Zysko[SUP] 4 [/SUP], Waldemar Banasiak[SUP] 5 [/SUP], Krzysztof Simon[SUP] 2 12 [/SUP]
Affiliations
Abstract
Background: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitutes a major health burden worldwide due to high mortality rates and hospital bed shortages. SARS-CoV-2 infection is associated with several laboratory abnormalities. We aimed to develop and validate a risk score based on simple demographic and laboratory data that could be used on admission in patients with SARS-CoV-2 infection to predict in-hospital mortality.
Methods: Three cohorts of patients from different hospitals were studied consecutively (developing, validation, and prospective cohorts). The following demographic and laboratory data were obtained from medical records: sex, age, hemoglobin, mean corpuscular volume (MCV), platelets, leukocytes, sodium, potassium, creatinine, and C-reactive protein (CRP). For each variable, classification and regression tree analysis were used to establish the cut-off point(s) associated with in-hospital mortality outcome based on data from developing cohort and before they were used for analysis in the validation and prospective cohort. The covid-19 score was calculated as a sum of cut-off points associated with mortality outcome.
Results: The developing, validation, and prospective cohorts included 129, 239, and 497 patients, respectively (median age, 71, 67, and 70 years, respectively). The following cut of points associated with in-hospital mortality: age > 56 years, male sex, hemoglobin < 10.55 g/dL, MCV > 92.9 fL, leukocyte count > 9.635 or < 2.64 10[SUP]3[/SUP]/µL, platelet count, < 81.49 or > 315.5 10[SUP]3[/SUP]/µL, CRP > 51.14 mg/dL, creatinine > 1.115 mg/dL, sodium < 134.7 or > 145.4 mEq/L, and potassium < 3.65 or > 6.255 mEq/L. The AUC of the covid-19 score for predicting in-hospital mortality was 0.89 (0.84-0.95), 0.850 (0.75-0.88), and 0.773 (0.731-0.816) in the developing, validation, and prospective cohorts, respectively (P < 0.001The mortality of the prospective cohort stratified on the basis of the covid-19 score was as follows: 0-2 points,4.2%; 3 points, 15%; 4 points, 29%; 5 points, 38.2%; 6 and more points, 60%.
Conclusion: The covid-19 score based on simple demographic and laboratory parameters may become an easy-to-use, widely accessible, and objective tool for predicting mortality in hospitalized patients with SARS-CoV-2 infection.
. 2021 Sep 14;21(1):945.
doi: 10.1186/s12879-021-06645-z.
Simple demographic characteristics and laboratory findings on admission may predict in-hospital mortality in patients with SARS-CoV-2 infection: development and validation of the covid-19 score
Marta Obremska[SUP] 1 [/SUP], Monika Pazgan-Simon[SUP] 2 [/SUP], Katarzyna Budrewicz[SUP] 3 [/SUP], Lukasz Bilaszewski[SUP] 4 [/SUP], Joanna Wizowska[SUP] 4 [/SUP], Dariusz Jagielski[SUP] 5 [/SUP], Beata Jankowska-Polanska[SUP] 6 [/SUP], Klaudiusz Nadolny[SUP] 7 8 [/SUP], Jarosław Madowicz[SUP] 9 10 [/SUP], Jolanta Zuwala-Jagiello[SUP] 11 [/SUP], Dorota Zysko[SUP] 4 [/SUP], Waldemar Banasiak[SUP] 5 [/SUP], Krzysztof Simon[SUP] 2 12 [/SUP]
Affiliations
- PMID: 34521357
- DOI: 10.1186/s12879-021-06645-z
Abstract
Background: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitutes a major health burden worldwide due to high mortality rates and hospital bed shortages. SARS-CoV-2 infection is associated with several laboratory abnormalities. We aimed to develop and validate a risk score based on simple demographic and laboratory data that could be used on admission in patients with SARS-CoV-2 infection to predict in-hospital mortality.
Methods: Three cohorts of patients from different hospitals were studied consecutively (developing, validation, and prospective cohorts). The following demographic and laboratory data were obtained from medical records: sex, age, hemoglobin, mean corpuscular volume (MCV), platelets, leukocytes, sodium, potassium, creatinine, and C-reactive protein (CRP). For each variable, classification and regression tree analysis were used to establish the cut-off point(s) associated with in-hospital mortality outcome based on data from developing cohort and before they were used for analysis in the validation and prospective cohort. The covid-19 score was calculated as a sum of cut-off points associated with mortality outcome.
Results: The developing, validation, and prospective cohorts included 129, 239, and 497 patients, respectively (median age, 71, 67, and 70 years, respectively). The following cut of points associated with in-hospital mortality: age > 56 years, male sex, hemoglobin < 10.55 g/dL, MCV > 92.9 fL, leukocyte count > 9.635 or < 2.64 10[SUP]3[/SUP]/µL, platelet count, < 81.49 or > 315.5 10[SUP]3[/SUP]/µL, CRP > 51.14 mg/dL, creatinine > 1.115 mg/dL, sodium < 134.7 or > 145.4 mEq/L, and potassium < 3.65 or > 6.255 mEq/L. The AUC of the covid-19 score for predicting in-hospital mortality was 0.89 (0.84-0.95), 0.850 (0.75-0.88), and 0.773 (0.731-0.816) in the developing, validation, and prospective cohorts, respectively (P < 0.001The mortality of the prospective cohort stratified on the basis of the covid-19 score was as follows: 0-2 points,4.2%; 3 points, 15%; 4 points, 29%; 5 points, 38.2%; 6 and more points, 60%.
Conclusion: The covid-19 score based on simple demographic and laboratory parameters may become an easy-to-use, widely accessible, and objective tool for predicting mortality in hospitalized patients with SARS-CoV-2 infection.