Unveiling the Unexpected: Why Doctors Should Look Beyond the Lungs When Predicting COVID-19 Mortality

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064173%3A_____%2F23%3A43925900" target="_blank" >RIV/00064173:_____/23:43925900 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11130/23:10465918 RIV/00216208:11120/23:43925900

Výsledek na webu

<a href="https://doi.org/10.1159/000530803" target="_blank" >https://doi.org/10.1159/000530803</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1159/000530803" target="_blank" >10.1159/000530803</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Unveiling the Unexpected: Why Doctors Should Look Beyond the Lungs When Predicting COVID-19 Mortality

Popis výsledku v původním jazyce

Introduction: The main objective of this study was to identify the best combination of admission day parameters for predicting COVID-19 mortality in hospitalized patients. Furthermore, we sought to compare the predictive capacity of pulmonary parameters to that of renal parameters for mortality from COVID-19.Methods: In this retrospective study, all patients admitted to a tertiary hospital between September 1st, 2020 and December 31st, 2020, who were clinically symptomatic and tested positive for COVID-19, were included. We gathered extensive data on patient admissions, including laboratory results, comorbidities, chest X-rays (CXR) images, and SpO2 levels, to determine their role in predicting mortality. Experienced radiologists evaluated the CXR images and assigned a score from 0 to 18 based on the severity of COVID-19 pneumonia.Further, we categorized patients into two independent groups based on their renal function using the RIFLE and KDIGO criteria to define the AKI and CKD groups. The first group (&quot;AKI &amp; CKD&quot;) was subdivided into six sub-groups: normal renal function (A); CKD Grade 2+3a (B); AKI-DROP (C); CKD Grade 3b (D); AKI-RISE (E); and Grade 4+5 CKD (F). The second group was based only on eGFR at the admission and thus it was divided into four grades: Grade 1, Grade 2+3a, Grade 3b, and Grade 4+5. Results: The cohort comprised 619 patients. Patients who died during hospitalization had a significantly higher mean radiological score (8.6 &amp; PLUSMN; 1.5) compared to those who survived (7.1 &amp; PLUSMN; 1.2), with a P-value &lt; 0.01. Moreover, we observed that the risk for mortality was significantly increased as renal function deteriorated, as evidenced by the AKI &amp; CKD and eGFR groups (P &lt; 0.001 for each group). Regarding mortality prediction, the area under the curve (AUC) for renal parameters (AKI &amp; CKD group, eGFR group, and age) was found to be superior to that of pulmonary parameters (age, radiological score, SpO2, CRP, and D-dimer) with an AUC of 0.8068 versus 0.7667. However, when renal and pulmonary parameters were combined, the AUC increased to 0.8813.Optimal parameter combinations for predicting mortality from COVID-19 were identified for three medical settings: Emergency Medical Service (EMS), the emergency department, and the Internal medicine floor. The AUC for these settings was 0.7874, 0.8614, and 0.8813, respectively. Conclusions: Our study demonstrated that selected renal parameters are superior to pulmonary parameters in predicting COVID-19 mortality for patients requiring hospitalization. When combining both renal and pulmonary factors, the predictive ability of mortality significantly improved. Additionally, we identified the optimal combination of factors for mortality prediction in three distinct settings: EMS, Emergency Department, and Internal Medicine Floor.

Název v anglickém jazyce

Unveiling the Unexpected: Why Doctors Should Look Beyond the Lungs When Predicting COVID-19 Mortality

Popis výsledku anglicky

Introduction: The main objective of this study was to identify the best combination of admission day parameters for predicting COVID-19 mortality in hospitalized patients. Furthermore, we sought to compare the predictive capacity of pulmonary parameters to that of renal parameters for mortality from COVID-19.Methods: In this retrospective study, all patients admitted to a tertiary hospital between September 1st, 2020 and December 31st, 2020, who were clinically symptomatic and tested positive for COVID-19, were included. We gathered extensive data on patient admissions, including laboratory results, comorbidities, chest X-rays (CXR) images, and SpO2 levels, to determine their role in predicting mortality. Experienced radiologists evaluated the CXR images and assigned a score from 0 to 18 based on the severity of COVID-19 pneumonia.Further, we categorized patients into two independent groups based on their renal function using the RIFLE and KDIGO criteria to define the AKI and CKD groups. The first group (&quot;AKI &amp; CKD&quot;) was subdivided into six sub-groups: normal renal function (A); CKD Grade 2+3a (B); AKI-DROP (C); CKD Grade 3b (D); AKI-RISE (E); and Grade 4+5 CKD (F). The second group was based only on eGFR at the admission and thus it was divided into four grades: Grade 1, Grade 2+3a, Grade 3b, and Grade 4+5. Results: The cohort comprised 619 patients. Patients who died during hospitalization had a significantly higher mean radiological score (8.6 &amp; PLUSMN; 1.5) compared to those who survived (7.1 &amp; PLUSMN; 1.2), with a P-value &lt; 0.01. Moreover, we observed that the risk for mortality was significantly increased as renal function deteriorated, as evidenced by the AKI &amp; CKD and eGFR groups (P &lt; 0.001 for each group). Regarding mortality prediction, the area under the curve (AUC) for renal parameters (AKI &amp; CKD group, eGFR group, and age) was found to be superior to that of pulmonary parameters (age, radiological score, SpO2, CRP, and D-dimer) with an AUC of 0.8068 versus 0.7667. However, when renal and pulmonary parameters were combined, the AUC increased to 0.8813.Optimal parameter combinations for predicting mortality from COVID-19 were identified for three medical settings: Emergency Medical Service (EMS), the emergency department, and the Internal medicine floor. The AUC for these settings was 0.7874, 0.8614, and 0.8813, respectively. Conclusions: Our study demonstrated that selected renal parameters are superior to pulmonary parameters in predicting COVID-19 mortality for patients requiring hospitalization. When combining both renal and pulmonary factors, the predictive ability of mortality significantly improved. Additionally, we identified the optimal combination of factors for mortality prediction in three distinct settings: EMS, Emergency Department, and Internal Medicine Floor.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30217 - Urology and nephrology

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Kidney &amp; Blood Pressure Research

ISSN

1420-4096

e-ISSN

1423-0143

Svazek periodika

48

Číslo periodika v rámci svazku

December

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

10

Strana od-do

347-356

Kód UT WoS článku

001022397600001

EID výsledku v databázi Scopus

2-s2.0-85181179057