Literature DB >> 32443899

Early Predictors of Clinical Deterioration in a Cohort of 239 Patients Hospitalized for Covid-19 Infection in Lombardy, Italy.

Maurizio Cecconi1,2, Daniele Piovani1,2, Enrico Brunetta1,2, Alessio Aghemo1,2, Massimiliano Greco1,2, Michele Ciccarelli1,2, Claudio Angelini1,2, Antonio Voza1,2, Paolo Omodei1,2, Edoardo Vespa1,2, Nicola Pugliese1,2, Tommaso Lorenzo Parigi1,2, Marco Folci1,2, Silvio Danese1,2, Stefanos Bonovas1,2.   

Abstract

We described features of hospitalized Covid-19 patients and identified predictors of clinical deterioration. We included patients consecutively admitted at Humanitas Research Hospital (Rozzano, Milan, Italy); retrospectively extracted demographic; clinical; laboratory and imaging findings at admission; used survival methods to identify factors associated with clinical deterioration (defined as intensive care unit (ICU) transfer or death), and developed a prognostic index. Overall; we analyzed 239 patients (29.3% females) with a mean age of 63.9 (standard deviation [SD]; 14.0) years. Clinical deterioration occurred in 70 patients (29.3%), including 41 (17.2%) ICU transfers and 36 (15.1%) deaths. The most common symptoms and signs at admission were cough (77.8%) and elevated respiratory rate (34.1%), while 66.5% of patients had at least one coexisting medical condition. Imaging frequently revealed ground-glass opacity (68.9%) and consolidation (23.8%). Age; increased respiratory rate; abnormal blood gas parameters and imaging findings; coexisting coronary heart disease; leukocytosis; lymphocytopenia; and several laboratory parameters (elevated procalcitonin; interleukin-6; serum ferritin; C-reactive protein; aspartate aminotransferase; lactate dehydrogenase; creatinine; fibrinogen; troponin-I; and D-dimer) were significant predictors of clinical deterioration. We suggested a prognostic index to assist risk-stratification (C-statistic; 0.845; 95% CI; 0.802‒0.887). These results could aid early identification and management of patients at risk, who should therefore receive additional monitoring and aggressive supportive care.

Entities:  

Keywords:  2019 novel coronavirus; 2019-nCoV; COVID-19; SARS-CoV-2; severe acute respiratory syndrome coronavirus 2

Year:  2020        PMID: 32443899     DOI: 10.3390/jcm9051548

Source DB:  PubMed          Journal:  J Clin Med        ISSN: 2077-0383            Impact factor:   4.241


  39 in total

1.  Supervised Machine Learning Approach to Identify Early Predictors of Poor Outcome in Patients with COVID-19 Presenting to a Large Quaternary Care Hospital in New York City.

Authors:  Jason Zucker; Angela Gomez-Simmonds; Lawrence J Purpura; Sherif Shoucri; Elijah LaSota; Nicholas E Morley; Brit W Sovic; Marvin A Castellon; Deborah A Theodore; Logan L Bartram; Benjamin A Miko; Matthew L Scherer; Kathrine A Meyers; William C Turner; Maureen Kelly; Martina Pavlicova; Cale N Basaraba; Matthew R Baldwin; Daniel Brodie; Kristin M Burkart; Joan Bathon; Anne-Catrin Uhlemann; Michael T Yin; Delivette Castor; Magdalena E Sobieszczyk
Journal:  J Clin Med       Date:  2021-08-11       Impact factor: 4.964

2.  Predicting COVID-19 county-level case number trend by combining demographic characteristics and social distancing policies.

Authors:  Megan Mun Li; Anh Pham; Tsung-Ting Kuo
Journal:  JAMIA Open       Date:  2022-06-25

3.  Usefulness of monocyte distribution width and presepsin for early assessment of disease severity in COVID-19 patients.

Authors:  Sei Won Kim; Heayon Lee; Sang Haak Lee; Sung Jin Jo; Jehoon Lee; Jihyang Lim
Journal:  Medicine (Baltimore)       Date:  2022-07-08       Impact factor: 1.817

4.  Age-Dependent Biomarkers for Prediction of In-Hospital Mortality in COVID-19 Patients.

Authors:  Eugene Feigin; Tal Levinson; Asaf Wasserman; Shani Shenhar-Tsarfaty; Shlomo Berliner; Tomer Ziv-Baran
Journal:  J Clin Med       Date:  2022-05-10       Impact factor: 4.964

5.  Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements.

Authors:  Kai Zhou; Yaoting Sun; Lu Li; Zelin Zang; Jing Wang; Jun Li; Junbo Liang; Fangfei Zhang; Qiushi Zhang; Weigang Ge; Hao Chen; Xindong Sun; Liang Yue; Xiaomai Wu; Bo Shen; Jiaqin Xu; Hongguo Zhu; Shiyong Chen; Hai Yang; Shigao Huang; Minfei Peng; Dongqing Lv; Chao Zhang; Haihong Zhao; Luxiao Hong; Zhehan Zhou; Haixiao Chen; Xuejun Dong; Chunyu Tu; Minghui Li; Yi Zhu; Baofu Chen; Stan Z Li; Tiannan Guo
Journal:  Comput Struct Biotechnol J       Date:  2021-06-17       Impact factor: 7.271

Review 6.  Review of Current COVID-19 Diagnostics and Opportunities for Further Development.

Authors:  Yan Mardian; Herman Kosasih; Muhammad Karyana; Aaron Neal; Chuen-Yen Lau
Journal:  Front Med (Lausanne)       Date:  2021-05-07

Review 7.  Prevalence and prognosis of otorhinolaryngological symptoms in patients with COVID-19: a systematic review and meta-analysis.

Authors:  Jingjing Qiu; Xin Yang; Limei Liu; Ting Wu; Limei Cui; Yakui Mou; Yan Sun
Journal:  Eur Arch Otorhinolaryngol       Date:  2021-05-25       Impact factor: 2.503

8.  COVID-19 Digestive System Involvement and Clinical Outcomes in a Large Academic Hospital in Milan, Italy.

Authors:  Alessio Aghemo; Daniele Piovani; Tommaso Lorenzo Parigi; Enrico Brunetta; Nicola Pugliese; Edoardo Vespa; Paolo Dario Omodei; Paoletta Preatoni; Ana Lleo; Alessandro Repici; Antonio Voza; Maurizio Cecconi; Alberto Malesci; Stefanos Bonovas; Silvio Danese
Journal:  Clin Gastroenterol Hepatol       Date:  2020-05-11       Impact factor: 11.382

Review 9.  Cardiac Injury and COVID-19: A Systematic Review and Meta-analysis.

Authors:  Fengwei Zou; Zhiyong Qian; Yao Wang; Yang Zhao; Jianling Bai
Journal:  CJC Open       Date:  2020-06-23

Review 10.  COVID-19 and COPD.

Authors:  Janice M Leung; Masahiro Niikura; Cheng Wei Tony Yang; Don D Sin
Journal:  Eur Respir J       Date:  2020-08-13       Impact factor: 16.671

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