Cargando…
Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases
BACKGROUND: Coronavirus disease 2019 (COVID-19) has been far more devastating than expected, showing no signs of slowing down at present. Heilongjiang Province is the most northeastern province of China, and has cold weather for nearly half a year and an annual temperature difference of more than 60...
Autores principales: | , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403670/ https://www.ncbi.nlm.nih.gov/pubmed/36159523 http://dx.doi.org/10.12998/wjcc.v10.i23.8161 |
_version_ | 1784773430147547136 |
---|---|
author | Wang, Lei Gao, Yang Zhang, Zhao-Jin Pan, Chang-Kun Wang, Ying Zhu, Yu-Cheng Qi, Yan-Peng Xie, Feng-Jie Du, Xue Li, Na-Na Chen, Peng-Fei Yue, Chuang-Shi Wu, Ji-Han Wang, Xin-Tong Tang, Yu-Jia Lai, Qi-Qi Kang, Kai |
author_facet | Wang, Lei Gao, Yang Zhang, Zhao-Jin Pan, Chang-Kun Wang, Ying Zhu, Yu-Cheng Qi, Yan-Peng Xie, Feng-Jie Du, Xue Li, Na-Na Chen, Peng-Fei Yue, Chuang-Shi Wu, Ji-Han Wang, Xin-Tong Tang, Yu-Jia Lai, Qi-Qi Kang, Kai |
author_sort | Wang, Lei |
collection | PubMed |
description | BACKGROUND: Coronavirus disease 2019 (COVID-19) has been far more devastating than expected, showing no signs of slowing down at present. Heilongjiang Province is the most northeastern province of China, and has cold weather for nearly half a year and an annual temperature difference of more than 60ºC, which increases the underlying morbidity associated with pulmonary diseases, and thus leads to lung dysfunction. The demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province, China with such climatic characteristics are still not clearly illustrated. AIM: To illustrate the demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province by comparing with those of surviving severe and critically ill cases. METHODS: COVID-19 deceased patients from different hospitals in Heilongjiang Province were included in this retrospective study and compared their characteristics with those of surviving severe and critically ill cases in the COVID-19 treatment center of the First Affiliated Hospital of Harbin Medical University. The surviving patients were divided into severe group and critically ill group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (the seventh edition). Demographic data were collected and recorded upon admission. Laboratory parameters were obtained from the medical records, and then compared among the groups. RESULTS: Twelve COVID-19 deceased patients, 27 severe cases and 26 critically ill cases were enrolled in this retrospective study. No differences in age, gender, and number of comorbidities between groups were found. Neutrophil percentage (NEUT%), platelet (PLT), C-reactive protein (CRP), creatine kinase isoenzyme (CK-MB), serum troponin I (TNI) and brain natriuretic peptides (BNP) showed significant differences among the groups (P = 0.020, P = 0.001, P < 0.001, P = 0.001, P < 0.001, P < 0.001, respectively). The increase of CRP, D-dimer and NEUT% levels, as well as the decrease of lymphocyte count (LYMPH) and PLT counts, showed significant correlation with death of COVID-19 patients (P = 0.023, P = 0.008, P = 0.045, P = 0.020, P = 0.015, respectively). CONCLUSION: Compared with surviving severe and critically ill cases, no special demographic features of COVID-19 deceased patients were observed, while some laboratory parameters including NEUT%, PLT, CRP, CK-MB, TNI and BNP showed significant differences. COVID-19 deceased patients had higher CRP, D-dimer and NEUT% levels and lower LYMPH and PLT counts. |
format | Online Article Text |
id | pubmed-9403670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-94036702022-09-23 Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases Wang, Lei Gao, Yang Zhang, Zhao-Jin Pan, Chang-Kun Wang, Ying Zhu, Yu-Cheng Qi, Yan-Peng Xie, Feng-Jie Du, Xue Li, Na-Na Chen, Peng-Fei Yue, Chuang-Shi Wu, Ji-Han Wang, Xin-Tong Tang, Yu-Jia Lai, Qi-Qi Kang, Kai World J Clin Cases Retrospective Study BACKGROUND: Coronavirus disease 2019 (COVID-19) has been far more devastating than expected, showing no signs of slowing down at present. Heilongjiang Province is the most northeastern province of China, and has cold weather for nearly half a year and an annual temperature difference of more than 60ºC, which increases the underlying morbidity associated with pulmonary diseases, and thus leads to lung dysfunction. The demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province, China with such climatic characteristics are still not clearly illustrated. AIM: To illustrate the demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province by comparing with those of surviving severe and critically ill cases. METHODS: COVID-19 deceased patients from different hospitals in Heilongjiang Province were included in this retrospective study and compared their characteristics with those of surviving severe and critically ill cases in the COVID-19 treatment center of the First Affiliated Hospital of Harbin Medical University. The surviving patients were divided into severe group and critically ill group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (the seventh edition). Demographic data were collected and recorded upon admission. Laboratory parameters were obtained from the medical records, and then compared among the groups. RESULTS: Twelve COVID-19 deceased patients, 27 severe cases and 26 critically ill cases were enrolled in this retrospective study. No differences in age, gender, and number of comorbidities between groups were found. Neutrophil percentage (NEUT%), platelet (PLT), C-reactive protein (CRP), creatine kinase isoenzyme (CK-MB), serum troponin I (TNI) and brain natriuretic peptides (BNP) showed significant differences among the groups (P = 0.020, P = 0.001, P < 0.001, P = 0.001, P < 0.001, P < 0.001, respectively). The increase of CRP, D-dimer and NEUT% levels, as well as the decrease of lymphocyte count (LYMPH) and PLT counts, showed significant correlation with death of COVID-19 patients (P = 0.023, P = 0.008, P = 0.045, P = 0.020, P = 0.015, respectively). CONCLUSION: Compared with surviving severe and critically ill cases, no special demographic features of COVID-19 deceased patients were observed, while some laboratory parameters including NEUT%, PLT, CRP, CK-MB, TNI and BNP showed significant differences. COVID-19 deceased patients had higher CRP, D-dimer and NEUT% levels and lower LYMPH and PLT counts. Baishideng Publishing Group Inc 2022-08-16 2022-08-16 /pmc/articles/PMC9403670/ /pubmed/36159523 http://dx.doi.org/10.12998/wjcc.v10.i23.8161 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Retrospective Study Wang, Lei Gao, Yang Zhang, Zhao-Jin Pan, Chang-Kun Wang, Ying Zhu, Yu-Cheng Qi, Yan-Peng Xie, Feng-Jie Du, Xue Li, Na-Na Chen, Peng-Fei Yue, Chuang-Shi Wu, Ji-Han Wang, Xin-Tong Tang, Yu-Jia Lai, Qi-Qi Kang, Kai Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases |
title | Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases |
title_full | Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases |
title_fullStr | Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases |
title_full_unstemmed | Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases |
title_short | Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases |
title_sort | comparison of demographic features and laboratory parameters between covid-19 deceased patients and surviving severe and critically ill cases |
topic | Retrospective Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403670/ https://www.ncbi.nlm.nih.gov/pubmed/36159523 http://dx.doi.org/10.12998/wjcc.v10.i23.8161 |
work_keys_str_mv | AT wanglei comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT gaoyang comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT zhangzhaojin comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT panchangkun comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT wangying comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT zhuyucheng comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT qiyanpeng comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT xiefengjie comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT duxue comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT linana comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT chenpengfei comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT yuechuangshi comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT wujihan comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT wangxintong comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT tangyujia comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT laiqiqi comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases AT kangkai comparisonofdemographicfeaturesandlaboratoryparametersbetweencovid19deceasedpatientsandsurvivingsevereandcriticallyillcases |