Cargando…

Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients

BACKGROUND: COVID-19 has led to significant hospitalization and intensive care unit admission rates. The demographic parameters of COVID-19 patients, such as age, underlying illnesses, and clinical symptoms, substantially influence the incidence and mortality of these individuals. The current study...

Descripción completa

Detalles Bibliográficos
Autores principales: Gholinataj Jelodar, Mohsen, Rafieian, Shahab, Allah Dini, Azadeh, Khalaj, Fatemeh, Zare, Samira, Dehghanpour, Hanieh, Mirzaei, Samaneh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241583/
https://www.ncbi.nlm.nih.gov/pubmed/37283598
http://dx.doi.org/10.1155/2023/3081660
_version_ 1785054017136623616
author Gholinataj Jelodar, Mohsen
Rafieian, Shahab
Allah Dini, Azadeh
Khalaj, Fatemeh
Zare, Samira
Dehghanpour, Hanieh
Mirzaei, Samaneh
author_facet Gholinataj Jelodar, Mohsen
Rafieian, Shahab
Allah Dini, Azadeh
Khalaj, Fatemeh
Zare, Samira
Dehghanpour, Hanieh
Mirzaei, Samaneh
author_sort Gholinataj Jelodar, Mohsen
collection PubMed
description BACKGROUND: COVID-19 has led to significant hospitalization and intensive care unit admission rates. The demographic parameters of COVID-19 patients, such as age, underlying illnesses, and clinical symptoms, substantially influence the incidence and mortality of these individuals. The current study examined the clinical and demographic characteristics of COVID-19 intensive care unit (ICU) patients in Yazd, Iran. METHODS: The descriptive-analytical cross-sectional study was conducted on ICU patients with a positive RT-PCR test for coronavirus, admitted to the ICU in Yazd province, Iran, over 18 months. To this end, demographic, clinical, laboratory, and imaging data were collected. Moreover, patients were divided into good and worse clinical outcome groups based on their clinical outcomes. Subsequently, data analysis was performed at a 95% confidence interval (CI) using SPSS 26 software. RESULTS: 391 patients with positive PCR were analyzed. The average age of the patients in the study was 63.59 ± 17.76, where 57.3% were male. On the high-resolution computed tomography (HRCT) scan, the mean lung involvement score was 14.03 ± 6.04, where alveolar consolidation (34%) and ground-glass opacity (25.6%) were the most prevalent type of lung involvement. The most common underlying illnesses in the study participants were hypertension (HTN) (41.4%), diabetes mellitus (DM) (39.9%), ischemic heart disease (IHD) (21%), and chronic kidney disease (CKD) (20.7%). In hospitalized patients, the rates of endotracheal intubation and mortality were 38.9% and 38.1%, respectively. Age, DM, HTN, dyslipidemia, CKD, cerebral vascular accident (CVA), cerebral hemorrhage, and cancer were reported to be significantly different between these two groups of patients, indicating an increase in the rate of intubation and mortality among these patients. Furthermore, the multivariate logistic regression analysis revealed that DM, HTN, CKD, CVA, neutrophil-to-lymphocyte ratio (NLR), the percentage of lung involvement, and initial O(2) saturation significantly increase the mortality of ICU patients. CONCLUSION: Several features of COVID-19 patients influence the mortality in these individuals. According to the findings, early detection of this disease in people at high risk of death can prevent its progression and lower mortality rates.
format Online
Article
Text
id pubmed-10241583
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-102415832023-06-06 Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients Gholinataj Jelodar, Mohsen Rafieian, Shahab Allah Dini, Azadeh Khalaj, Fatemeh Zare, Samira Dehghanpour, Hanieh Mirzaei, Samaneh Can J Infect Dis Med Microbiol Research Article BACKGROUND: COVID-19 has led to significant hospitalization and intensive care unit admission rates. The demographic parameters of COVID-19 patients, such as age, underlying illnesses, and clinical symptoms, substantially influence the incidence and mortality of these individuals. The current study examined the clinical and demographic characteristics of COVID-19 intensive care unit (ICU) patients in Yazd, Iran. METHODS: The descriptive-analytical cross-sectional study was conducted on ICU patients with a positive RT-PCR test for coronavirus, admitted to the ICU in Yazd province, Iran, over 18 months. To this end, demographic, clinical, laboratory, and imaging data were collected. Moreover, patients were divided into good and worse clinical outcome groups based on their clinical outcomes. Subsequently, data analysis was performed at a 95% confidence interval (CI) using SPSS 26 software. RESULTS: 391 patients with positive PCR were analyzed. The average age of the patients in the study was 63.59 ± 17.76, where 57.3% were male. On the high-resolution computed tomography (HRCT) scan, the mean lung involvement score was 14.03 ± 6.04, where alveolar consolidation (34%) and ground-glass opacity (25.6%) were the most prevalent type of lung involvement. The most common underlying illnesses in the study participants were hypertension (HTN) (41.4%), diabetes mellitus (DM) (39.9%), ischemic heart disease (IHD) (21%), and chronic kidney disease (CKD) (20.7%). In hospitalized patients, the rates of endotracheal intubation and mortality were 38.9% and 38.1%, respectively. Age, DM, HTN, dyslipidemia, CKD, cerebral vascular accident (CVA), cerebral hemorrhage, and cancer were reported to be significantly different between these two groups of patients, indicating an increase in the rate of intubation and mortality among these patients. Furthermore, the multivariate logistic regression analysis revealed that DM, HTN, CKD, CVA, neutrophil-to-lymphocyte ratio (NLR), the percentage of lung involvement, and initial O(2) saturation significantly increase the mortality of ICU patients. CONCLUSION: Several features of COVID-19 patients influence the mortality in these individuals. According to the findings, early detection of this disease in people at high risk of death can prevent its progression and lower mortality rates. Hindawi 2023-05-29 /pmc/articles/PMC10241583/ /pubmed/37283598 http://dx.doi.org/10.1155/2023/3081660 Text en Copyright © 2023 Mohsen Gholinataj Jelodar et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gholinataj Jelodar, Mohsen
Rafieian, Shahab
Allah Dini, Azadeh
Khalaj, Fatemeh
Zare, Samira
Dehghanpour, Hanieh
Mirzaei, Samaneh
Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients
title Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients
title_full Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients
title_fullStr Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients
title_full_unstemmed Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients
title_short Analyzing Trends in Demographic, Laboratory, Imaging, and Clinical Outcomes of ICU-Hospitalized COVID-19 Patients
title_sort analyzing trends in demographic, laboratory, imaging, and clinical outcomes of icu-hospitalized covid-19 patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241583/
https://www.ncbi.nlm.nih.gov/pubmed/37283598
http://dx.doi.org/10.1155/2023/3081660
work_keys_str_mv AT gholinatajjelodarmohsen analyzingtrendsindemographiclaboratoryimagingandclinicaloutcomesoficuhospitalizedcovid19patients
AT rafieianshahab analyzingtrendsindemographiclaboratoryimagingandclinicaloutcomesoficuhospitalizedcovid19patients
AT allahdiniazadeh analyzingtrendsindemographiclaboratoryimagingandclinicaloutcomesoficuhospitalizedcovid19patients
AT khalajfatemeh analyzingtrendsindemographiclaboratoryimagingandclinicaloutcomesoficuhospitalizedcovid19patients
AT zaresamira analyzingtrendsindemographiclaboratoryimagingandclinicaloutcomesoficuhospitalizedcovid19patients
AT dehghanpourhanieh analyzingtrendsindemographiclaboratoryimagingandclinicaloutcomesoficuhospitalizedcovid19patients
AT mirzaeisamaneh analyzingtrendsindemographiclaboratoryimagingandclinicaloutcomesoficuhospitalizedcovid19patients