HEMATOLOGY, C-REACT IVE PROTE IN AND PROCA LCITON IN
IN COV ID-19 PAT IENTS AND HISTOR ICA L PNeUMONIA GROUP

Bilaszewski, Łukasz; Budrewicz, Katarzyna; Gogolewski, Grzegorz; Sycz, Krzysztof; Wolniakowski, Igor; Madziarska, Katarzyna; Obremska, Marta; Waligóra, Grzegorz; Jagielski, Dariusz; Nadolny, Klaudiusz; Zyśko, Dorota

doi:10.36740/emems202002101

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…The AUC of the Chinese protocol severity classi cation, PSI, and CURB-65 was 0.735, 0.951, and 0.912. The AUC of the presented scores is similar to our study [23].…”

Section: Discusionsupporting

confidence: 88%

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Simple Demographics and Laboratory Findings on Admission May Predict f In-hospital Mortality in Patients with SARS-CoV-2 Infection

Obremska

Pazgan−Simon²,

Budrewicz

et al. 2021

Preprint

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Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection could result in different laboratory abnormalities. The prediction of the outcome based on simple demographics and laboratory parameters could be useful for clinical purposes. The objective of the study is to develop and validate a score (Covid19-score) based on demographics and laboratory findings, performed at hospital admission in patients with a SARS-CoV-2 infection confirmed on a reverse transcriptase-polymerase chain reaction of the nasopharyngeal swab, to predict in-hospital mortality.Methods: Three cohorts of patients from three different hospitals were studied consecutively. The studied data came from patients’ electronic records. On the basis of the retrospective analysis of the mortality in the developing cohort from the first hospital the cut-off points predicting in-hospital mortality for gender, age, hemoglobin, mean corpuscular volume, platelet count, leukocyte count, sodium, potassium, creatinine level, C-reactive protein level were found and Covid19-score as a sum of points was calculated for each patient. The area under the receiver operating characteristic curve (AUC) of the Covid19-score for predicting survival to hospital discharge was counted. The Covid19-score was validated using data of patients from a second hospital. The significance of Covid19-score was confirmed on the prospective cohort of patients collected from a third hospital,Results: AUC of the Covid19-score for predicting survival to hospital discharge was 0.89 (0.84-0.95) p<0.001 in developing cohort, 0.850 (0.75-0.88) p<0.001 in validation cohort and 0.773 (0.731-0.816) p<0.001 in the prospective cohort.Conclusion: The Covid19-score is useful in predicting the clinical outcome for hospitalized patients with SARS-CoV-2 infection

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“…The AUC of the Chinese protocol severity classi cation, PSI, and CURB-65 was 0.735, 0.951, and 0.912. The AUC of the presented scores is similar to our study [23].…”

Section: Discusionsupporting

confidence: 88%

“…The tendency to admit patients to the hospital at the beginning of the epidemic was higher because the degree of risk related to COVID-19 infection was unknown [23].…”

Section: Discusionmentioning

confidence: 99%

Simple Demographics and Laboratory Findings on Admission May Predict f In-hospital Mortality in Patients with SARS-CoV-2 Infection

Obremska

Pazgan−Simon²,

Budrewicz

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Differences in age between our study cohorts may be related to the different time of recruitment. At the beginning of the pandemic, there was a tendency to admit more patients to the hospital because the health risks associated with COVID-19 was still unknown [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

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

Obremska

Pazgan−Simon²,

Budrewicz

et al. 2021

BMC Infect Dis

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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 < 2.64 103/µL, platelet count, < 81.49 or > 315.5 103/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.

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HEMATOLOGY, C-REACT IVE PROTE IN AND PROCA LCITON IN IN COV ID-19 PAT IENTS AND HISTOR ICA L PNeUMONIA GROUP

Cited by 2 publications

References 11 publications

Simple Demographics and Laboratory Findings on Admission May Predict f In-hospital Mortality in Patients with SARS-CoV-2 Infection

Simple Demographics and Laboratory Findings on Admission May Predict f In-hospital Mortality in Patients with SARS-CoV-2 Infection

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

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