Literature DB >> 32707517

Clinical comorbidities, characteristics, and outcomes of mechanically ventilated patients in the State of Michigan with SARS-CoV-2 pneumonia.

Sandeep Krishnan1, Kinjal Patel2, Ronak Desai3, Anupam Sule4, Peter Paik5, Ashley Miller6, Alicia Barclay7, Adam Cassella8, Jon Lucaj9, Yvonne Royster10, Joffer Hakim11, Zulfiqar Ahmed12, Farhad Ghoddoussi13.   

Abstract

Entities:  

Mesh:

Year:  2020        PMID: 32707517      PMCID: PMC7369577          DOI: 10.1016/j.jclinane.2020.110005

Source DB:  PubMed          Journal:  J Clin Anesth        ISSN: 0952-8180            Impact factor:   9.452


× No keyword cloud information.
In December 2019, a series of viral infections, eventually named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appeared in China and quickly spread across the world [1]. The United States (USA) has been profoundly affected, reporting the most confirmed cases of SARS-CoV-2 of any country. As of June 10, 2020, SARS-CoV-2 infection has been confirmed in more than 7.3 million individuals in 188 countries and regions, with an overall mortality rate of more than 5.7% [2]. The State of Michigan has been particularly devastated by this disease; it ranks 9th in the USA with 65,182 total confirmed cases of SARS-CoV-2 and 6th in the USA with 5955 total deaths [2]. While the clinical course of patients with SARS-CoV-2 infection can vary from completely asymptomatic to critically ill, an understanding of differing patient characteristics and outcomes of infected patients is critical for health and government officials engaged in planning efforts to address outbreaks. We sought to describe the demographics, baseline comorbidities, and outcomes in patients with SARS-CoV-2 who required mechanical ventilation from a single hospital system in the state of Michigan, USA. This retrospective observational study was conducted at St. Joseph Mercy Oakland Hospital, and data were obtained from medical records from the 7 hospitals in the health system (1996 beds). The institutional review board approved the study as minimal-risk research using data collected for routine clinical practice and waived the requirement for informed consent. All consecutive patients from March 10, 2020 to April 15, 2020 who required hospital admission with confirmed SARS-CoV-2 infection by positive result on polymerase chain reaction (PCR) testing of a nasopharyngeal sample were included in this study. The focus of this study was SARS-CoV-2 patients who required mechanical ventilation in the Intensive Care Unit (ICU), and only patients who completed their hospital course within the health system at study end (discharged alive or dead) were included in the study. During the study period a total of 901 adult patients with confirmed SARS-CoV-2 infection were admitted to the 7 hospitals within the health system. After initial chart review 152 patients requiring mechanical ventilation were included. Of the 152 mechanically ventilated patients with confirmed SARS-CoV-2 infection, 39% (60) survived until discharge and 61% (92) died. The median age of patients was 68 years old (IQR 58–75), and 62.5% (95) were male. Forty-eight percent of patients had three or more comorbidities, the most common being hypertension (73%), hypercholesterolemia (61%), and diabetes mellitus (45%). Increased age, pre-existing hypertension, pre-admission statin use, increased fluid administration, need for continuous renal replacement therapy (CRRT), and use of vasopressor/inotrope were associated with increased mortality. There was a decreased risk of mortality in patients treated with steroids and vitamin C, and in patients with greater urine output (Table 1 ).
Table 1

Demographics, comorbidities, events, medications pre & after admission to hospital.

Survivor (n = 60)Non-survivor (n = 92)Total (n = 152)P valueOdds ratio
95% C.I.
Pre-hospital demographics
Age (years)
 Mean ± St. Dev.59 ± 1371 ± 1066 ± 130.00001.081
 Median [IQR]61 [50–71]72 [64–78]68 [58–75]0.00001.047–1.116
Sex
 Male36 (60%)59 (64%)95 (62.5%)0.6101
 Female24 (40%)33 (36%)57 (37.5%)
Race
 Black33(55%)41(%)71(47%)0.2478
 White23(38%)51(%)70(46%)
 Other4(7%)8(%)11(7%)
Ethnicity
 Hispanic2 (3%)2 (2%)4 (3%)0.5168
 Non-Hispanic58 (97%)90 (98%)148 (97%)
BMI (kg/m2)
 Mean ± StDv32 ± 731 ± 732 ± 70.228
 Median [IQR]32 [27–36]29 [26–34]31[26–35]0.144



Pre-admission comorbidities
HTN37(62%)74(84%)111(73%)0.01082.5561.229–5.315
Coronary artery disease (CAD)6(10%)17(18%)23(15%)0.1542
Diabetes23(38%)43(47%)69(65%)0.1583
Hypercholesterolemia31(52%)61(66%)92(61%)0.0710
Asthma9(15%)16(17%)25(16%)0.6985
COPD6(10%)17(18%)23(15%)0.1463
Renal disease9(15%)13(14%)22(14%)0.9203
Cirrhosis1(2%)0(0%)1(1%)0.3947
Smoker0.8737
 Current (or quit < 6 months)2(3%)3(3%)5(3%)
 Former (quit > 6 months)16(27%)27(29%)43(28%)
 Never27(45%)37(40%)64(42%)
 Unknown15(25%)25(27%)40(26%)



Pre-admission medications
ACE inhibitors12(20%)23(25%)35(23%)0.4751
ARBs6(10%)17(18%)23(15%)0.1542
Statin24(40%)57(62%)81(53%)0.00802.4431.225–4.756
Oral steroids6(10%)10(11%)16(11%)0.8625
Antithrombotic19(32%)38(41%)57(38%)0.2301
Anticoagulant7(12%)15(16%)22(14%)0.4274



ICU stay information
Length of hospital stay (days)
 Mean ± SEM13.1 ± 1.28.3 ± 0.710.2 ± 0.70.00030.852
 Median [IQR]11 [8–17]7 [4–12]8 [4–14]0.00000.804–0.903
Length of ICU stay (days)
 Mean ± SEM21 ± 1.410.1 ± 0.714.4 ± 0.80.00000.923
 Median [IQR]19 [14–23]9 [5–14]13 [7–20]0.00020.882–0.968
Intub. fluid admin. (ml/kg/h)
 Mean ± SEM0.56 ± 0.050.76 ± 0.050.68 ± 0.040.00573.616
 Median [IQR]0.47 [0.4–0.7]0.64 [0.4–1.0]0.57[0.4–0.9]0.00431.394–9.379
Intub. urine output (ml/kg/h)
 Mean ± SEM0.75 ± 0.050.4 ± 0.030.54 ± 0.030.00000.048
 Median [IQR]0.76 [0.5–1.0]0.34 [0.2–0.6]0.49[0.2–0.8]0.00000.014–0.162



ICU stay events
Continuous renal replacement therapy (CRRT)5(8%)20(23%)26(17%)0.01893.3001.170–9.311
Acute drop of hemoglobin8(13%)16(7%)24(16%)0.4839
Cerebral thromboembolism1(2%)2(2%)3(2%)1.000
Pulmonary embolism4(7%)5(5%)9(6%)1.000
Deep vein thrombosis6(10%)4(4%)10(7%)0.1922
Coronary artery thrombosis0(0%)3(3%)3(2%)0.2793
Acute heart failure (EF < 30%)
 No54(90%)81(88%)135(89%)0.6483
 Yes3(5%)2(2%)5(3%)
 N/A3(5%)9(10%)12(8%)



ICU stay medications
Steroids46(77%)54(59%)100(66%)0.02250.4320.209–0.896
Deep vein therapy (Prophylactic)58(97%)86(93%)144(95%)0.2473
Therapeutic anti-coagulation25(42%)41(45%)66(43%)0.7290
Hydroxychloroquine sulfate58(97%)86(93%)144(95%)0.4803
Azithromycin49(82%)66(72%)115(76%)0.1637
Tocilizumab5(8%)11(12%)16(11%)0.4624
Zinc27(45%)31(34%)58(38%)0.1371
Vitamin C39(65%)40(43%)79(52%)0.00660.3940.200–0.778
Vitamin D8(13%)8(9%)16(11%)0.3428
Vasopressor/inotrope admin.33(55%)79(86%)112(74%)<0.00015.3862.439–11.90



ICU stay lab results
Ferritin at discharge (ng/mL)
 Mean ± SEM663 ± 971952 ± 4551812 ± 2110.02511.001
 Median [IQR]476 [359–881]1166[594–1500]849[462–1431]0.00011.00–1.002
LDH at discharge (U/L)
 Mean ± SEM301 ± 22947 ± 276705 ± 1770.076221.008
 Median [IQR]287 [230–347]461 [351–644]393[286–538]0.00011.003–1.014

Data are Mean ± St. Dev., Median [IQR] or n (%). p values were calculated by t-test, Mann-Whitney U test, χ2 test, or Fisher's exact test, as appropriate. Univariate logistic regression odds ratio and 95% Confidence of intervals (C.I.) are given for the variables with significant difference (P < 0.05). *: indicates significant difference. ACE: angiotensin-converting enzyme. ARB: angiotensin receptor blockers, BMI: body mass index, care unit, COPD: chronic obstructive pulmonary disease, EF: ejection fraction, HTN: hypertension, ICU = intensive care unit, IQR = Inter quartile range, LDH: lactate dehydrogenase.

Demographics, comorbidities, events, medications pre & after admission to hospital. Data are Mean ± St. Dev., Median [IQR] or n (%). p values were calculated by t-test, Mann-Whitney U test, χ2 test, or Fisher's exact test, as appropriate. Univariate logistic regression odds ratio and 95% Confidence of intervals (C.I.) are given for the variables with significant difference (P < 0.05). *: indicates significant difference. ACE: angiotensin-converting enzyme. ARB: angiotensin receptor blockers, BMI: body mass index, care unit, COPD: chronic obstructive pulmonary disease, EF: ejection fraction, HTN: hypertension, ICU = intensive care unit, IQR = Inter quartile range, LDH: lactate dehydrogenase. As this is a previously unknown virus, the mainstay of treatment for hospitalized patients has been isolation and supportive care including supplemental oxygen therapy, fluid resuscitation, administration of antimicrobials for treatment of secondary bacterial infections, and prevention of end-organ dysfunction [3]. Due to the constantly changing hypotheses on best management practices for SARS-CoV-2, treatment protocols vary widely between hospitals and mortality in patients with critical disease characteristics requiring ICU care have been reported to be as high as 78% [1,4,5]. SARS-CoV-2 has placed a tremendous strain on hospitals and hospital resources all over the world; this study can potentially help health officials identify patients who are at higher risk of death, guide planning efforts for management of this disease, as well as direct further prospective study looking at specific therapies in an effort to improve patient outcomes.

Disclosures

No grants, no sponsors, and no funding sources provided direct or indirect financial support to the research work contained in the manuscript. The authors have no conflict of interest to report.

CRediT authorship contribution statement

Sandeep Krishnan:Investigation, Methodology, Data curation, Writing - original draft, Writing - review & editing.Kinjal Patel:Investigation, Writing - original draft, Writing - review & editing.Ronak Desai:Investigation, Writing - original draft, Writing - review & editing.Anupam Sule:Investigation, Writing - original draft, Writing - review & editing.Peter Paik:Investigation, Writing - review & editing.Ashley Miller:Investigation, Writing - review & editing.Alicia Barclay:Investigation, Writing - review & editing.Adam Cassella:Investigation, Writing - review & editing.Jon Lucaj:Investigation, Writing - review & editing.Yvonne Royster:Investigation, Writing - review & editing.Joffer Hakim:Writing - review & editing.Zulfiqar Ahmed:Writing - review & editing.Farhad Ghoddoussi:Investigation, Formal analysis, Data curation, Methodology, Writing - original draft, Writing - review & editing.
  3 in total

1.  Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area.

Authors:  Safiya Richardson; Jamie S Hirsch; Mangala Narasimhan; James M Crawford; Thomas McGinn; Karina W Davidson; Douglas P Barnaby; Lance B Becker; John D Chelico; Stuart L Cohen; Jennifer Cookingham; Kevin Coppa; Michael A Diefenbach; Andrew J Dominello; Joan Duer-Hefele; Louise Falzon; Jordan Gitlin; Negin Hajizadeh; Tiffany G Harvin; David A Hirschwerk; Eun Ji Kim; Zachary M Kozel; Lyndonna M Marrast; Jazmin N Mogavero; Gabrielle A Osorio; Michael Qiu; Theodoros P Zanos
Journal:  JAMA       Date:  2020-05-26       Impact factor: 56.272

2.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

3.  Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study.

Authors:  Fei Zhou; Ting Yu; Ronghui Du; Guohui Fan; Ying Liu; Zhibo Liu; Jie Xiang; Yeming Wang; Bin Song; Xiaoying Gu; Lulu Guan; Yuan Wei; Hui Li; Xudong Wu; Jiuyang Xu; Shengjin Tu; Yi Zhang; Hua Chen; Bin Cao
Journal:  Lancet       Date:  2020-03-11       Impact factor: 79.321

  3 in total
  19 in total

Review 1.  Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis.

Authors:  Abraham Degarege; Zaeema Naveed; Josiane Kabayundo; David Brett-Major
Journal:  Pathogens       Date:  2022-05-10

Review 2.  Severity and Mortality Associated with Steroid Use among Patients with COVID-19: A Systematic Review and Meta-Analysis.

Authors:  Tamiru Sahilu; Tadesse Sheleme; Tsegaye Melaku
Journal:  Interdiscip Perspect Infect Dis       Date:  2021-05-06

Review 3.  Protecting older patients with cardiovascular diseases from COVID-19 complications using current medications.

Authors:  Mariana Alves; Marília Andreia Fernandes; Gülistan Bahat; Athanase Benetos; Hugo Clemente; Tomasz Grodzicki; Manuel Martínez-Sellés; Francesco Mattace-Raso; Chakravarthi Rajkumar; Andrea Ungar; Nikos Werner; Timo E Strandberg
Journal:  Eur Geriatr Med       Date:  2021-05-25       Impact factor: 1.710

Review 4.  Improved COVID-19 ICU admission and mortality outcomes following treatment with statins: a systematic review and meta-analysis.

Authors:  Amir Vahedian-Azimi; Seyede Momeneh Mohammadi; Farshad Heidari Beni; Maciej Banach; Paul C Guest; Tannaz Jamialahmadi; Amirhossein Sahebkar
Journal:  Arch Med Sci       Date:  2021-02-10       Impact factor: 3.318

5.  Asthma in patients with coronavirus disease 2019: A systematic review and meta-analysis.

Authors:  Li Shi; Jie Xu; Wenwei Xiao; Ying Wang; Yuefei Jin; Shuaiyin Chen; Guangcai Duan; Haiyan Yang; Yadong Wang
Journal:  Ann Allergy Asthma Immunol       Date:  2021-02-18       Impact factor: 6.347

6.  In-hospital use of statins is associated with a reduced risk of mortality in coronavirus-2019 (COVID-19): systematic review and meta-analysis.

Authors:  Hikmat Permana; Ian Huang; Aga Purwiga; Nuraini Yasmin Kusumawardhani; Teddy Arnold Sihite; Erwan Martanto; Rudi Wisaksana; Nanny Natalia M Soetedjo
Journal:  Pharmacol Rep       Date:  2021-02-20       Impact factor: 3.024

Review 7.  Evaluation of the Current Therapeutic Approaches for COVID-19: A Systematic Review and a Meta-analysis.

Authors:  Zeinab Abdelrahman; Qian Liu; Shanmei Jiang; Mengyuan Li; Qingrong Sun; Yue Zhang; Xiaosheng Wang
Journal:  Front Pharmacol       Date:  2021-03-15       Impact factor: 5.810

Review 8.  A Comprehensive Overview of the COVID-19 Literature: Machine Learning-Based Bibliometric Analysis.

Authors:  Alaa Abd-Alrazaq; Jens Schneider; Borbala Mifsud; Tanvir Alam; Mowafa Househ; Mounir Hamdi; Zubair Shah
Journal:  J Med Internet Res       Date:  2021-03-08       Impact factor: 5.428

9.  Obesity or increased body mass index and the risk of severe outcomes in patients with COVID-19: A protocol for systematic review and meta-analysis.

Authors:  Yaxian Yang; Liting Wang; Jingfang Liu; Songbo Fu; Liyuan Zhou; Yan Wang
Journal:  Medicine (Baltimore)       Date:  2022-01-07       Impact factor: 1.889

10.  Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions.

Authors:  Arthur Eumann Mesas; Iván Cavero-Redondo; Celia Álvarez-Bueno; Marcos Aparecido Sarriá Cabrera; Selma Maffei de Andrade; Irene Sequí-Dominguez; Vicente Martínez-Vizcaíno
Journal:  PLoS One       Date:  2020-11-03       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.