Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City
ObjectiveThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-...
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| Published in | BMJ open Vol. 10; no. 11; p. e040736 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
British Medical Journal Publishing Group
27.11.2020
BMJ Publishing Group LTD BMJ Publishing Group |
| Series | Original research |
| Subjects | |
| Online Access | Get full text |
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| Abstract | ObjectiveThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.DesignDemographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.SettingAll patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.ParticipantsParticipants over the age of 18 years were included.Primary outcomesWe investigated in-hospital mortality during the study period.ResultsA total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.ConclusionsIn our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged. |
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| AbstractList | ObjectiveThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.DesignDemographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.SettingAll patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.ParticipantsParticipants over the age of 18 years were included.Primary outcomesWe investigated in-hospital mortality during the study period.ResultsA total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.ConclusionsIn our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged. The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.OBJECTIVEThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.DESIGNDemographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.SETTINGAll patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.Participants over the age of 18 years were included.PARTICIPANTSParticipants over the age of 18 years were included.We investigated in-hospital mortality during the study period.PRIMARY OUTCOMESWe investigated in-hospital mortality during the study period.A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.RESULTSA total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.CONCLUSIONSIn our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged. Objective The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.Design Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.Setting All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.Participants Participants over the age of 18 years were included.Primary outcomes We investigated in-hospital mortality during the study period.Results A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.Conclusions In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged. The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive. Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive. All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system. Participants over the age of 18 years were included. We investigated in-hospital mortality during the study period. A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL. In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged. |
| Author | Russak, Adam J Vaid, Akhil Nangia, Udit Narula, Jagat Kapoor, Arjun Fuster, V Just, Allan Bagiella, Emilia Charney, Dennis Levin, Matthew A Kia, Arash Danieletto, Matteo Paranjpe, Ishan Bottinger, Erwin P Charney, Alexander W Fayad, Zahi A Miotto, Riccardo Meyer, Dara De Freitas, Jessica K Kovatch, Patricia Johnson, Kipp W Cordon-Cardo, Carlos Golden, Eddye Horowitz, Carol R Somani, Sulaiman Freeman, Robert M Huckins, Laura M Jhang, Jeffrey Nadkarni, Girish N O’Reilly, Paul Nestler, Eric J Glowe, Patricia Finkelstein, Joseph Reich, David L O'Hagan, Ross Timsina, Prem Firpo, Adolfo Manna, Sayan Jaladanki, Suraj K Aberg, Judith A Murphy, Barbara Lala, Anuradha Singh, Manbir Glicksberg, Benjamin S |
| AuthorAffiliation | 2 Department of Internal Medicine , Icahn School of Medicine at Mount Sinai , New York , New York , USA 10 Mount Sinai Data Warehouse , Mount Sinai Health System , New York , New York , USA 23 Institute for Exposomic Research , Icahn School of Medicine at Mount Sinai , New York , New York , USA 1 The Hasso Plattner Institute for Digital Health at Mount Sinai , New York , New York , USA 14 Department of Radiology , Icahn School of Medicine at Mount Sinai , New York , New York , USA 3 Department of Genetics and Genomic Sciences , Icahn School of Medicine at Mount Sinai , New York , New York , USA 24 The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai , New York , New York , USA 13 Icahn School of Medicine at Mount Sinai BioMedical Engineering and Imaging Institute , New York , New York , USA 22 Icahn School of Medicine at Mount Sinai Department of Environmental Medicine and Public Health , New York , New York , USA 4 The Zena and Michael A. Wiener Car |
| AuthorAffiliation_xml | – name: 6 The Pamela Sklar Division of Psychiatric Genomics , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 3 Department of Genetics and Genomic Sciences , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 2 Department of Internal Medicine , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 13 Icahn School of Medicine at Mount Sinai BioMedical Engineering and Imaging Institute , New York , New York , USA – name: 17 The Nash Family Department of Neuroscience , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 20 The Office of the Dean , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 4 The Zena and Michael A. Wiener Cardiovascular Institute , New York , New York , USA – name: 16 Icahn School of Medicine at Mount Sinai Friedman Brain Institute , New York , New York , USA – name: 23 Institute for Exposomic Research , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 5 Department of Population Health Science and Policy , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 14 Department of Radiology , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 7 Institute for Healthcare Delivery Science , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 15 Department of Cardiology , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 8 Icahn Institute for Data Science and Genomic Technology , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 19 Icahn School of Medicine at Mount Sinai Department of Psychiatry , New York , New York , USA – name: 12 Icahn School of Medicine at Mount Sinai Department of Medicine , New York , New York , USA – name: 9 Department of Pathology, Molecular and Cell-Based Medicine , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 24 The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 1 The Hasso Plattner Institute for Digital Health at Mount Sinai , New York , New York , USA – name: 11 Division of Infectious Diseases , Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 22 Icahn School of Medicine at Mount Sinai Department of Environmental Medicine and Public Health , New York , New York , USA – name: 18 Department of Medicine, Division of Cardiology , Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josée and Henry R. Kravis Center for Cardiovascular Health, Icahn School of Medicine at Mount Sinai , New York , New York , USA – name: 10 Mount Sinai Data Warehouse , Mount Sinai Health System , New York , New York , USA – name: 21 Icahn School of Medicine at Mount Sinai Department of Anesthesiology Perioperative and Pain Medicine , New York , New York , USA |
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organization: Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA – sequence: 27 givenname: Patricia surname: Kovatch fullname: Kovatch, Patricia organization: Mount Sinai Data Warehouse, Mount Sinai Health System, New York, New York, USA – sequence: 28 givenname: Joseph surname: Finkelstein fullname: Finkelstein, Joseph organization: Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA – sequence: 29 givenname: Judith A surname: Aberg fullname: Aberg, Judith A organization: Icahn School of Medicine at Mount Sinai Department of Medicine, New York, New York, USA – sequence: 30 givenname: Emilia surname: Bagiella fullname: Bagiella, Emilia organization: Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA – sequence: 31 givenname: Carol R surname: Horowitz fullname: Horowitz, Carol R organization: Icahn School of Medicine at Mount Sinai Department of Medicine, New York, New York, USA – sequence: 32 givenname: Barbara surname: Murphy fullname: Murphy, Barbara organization: Icahn School of Medicine at Mount Sinai Department of Medicine, New York, New York, USA – sequence: 33 givenname: Zahi A surname: Fayad fullname: Fayad, Zahi A organization: Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA – sequence: 34 givenname: Jagat surname: Narula fullname: Narula, Jagat organization: Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA – sequence: 35 givenname: Eric J surname: Nestler fullname: Nestler, Eric J organization: The Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA – sequence: 36 givenname: V surname: Fuster fullname: Fuster, V organization: Department of Medicine, Division of Cardiology, Zena and Michael A. 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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33247020$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. 2020 Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (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, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. 2020 |
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| Issue | 11 |
| Keywords | internal medicine public health infectious diseases |
| Language | English |
| License | This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (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, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. |
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| References | Fisher, Neugarten, Bellin (R4) 2020; 31 Lippi, Plebani (R27) 2020; 505 Paranjpe, Fuster, Lala (R7) 2020; 76 Ng, Marimuthu, Chia (R19) 2020; 382 Yang, Yu, Xu (R13) 2020; 8 Bhatraju, Ghassemieh, Nichols (R23) 2020; 382 Vena, Giacobbe, Di Biagio (R14) 2020 Menter, Haslbauer, Nienhold (R8) 2020; 77 Bilaloglu, Aphinyanaphongs, Jones (R11) 2020; 324 Arentz, Yim, Klaff (R25) 2020; 323 Han, Zhang, Mu (R26) Verity, Okell, Dorigatti (R21) 2020; 20 McMichael, Currie, Clark (R18) 2020; 382 Chan, Chaudhary, Saha (R5) 2020 Lala, Johnson, Januzzi (R6) 2020; 76 Lauer, Grantz, Bi (R29) 2020; 172 Guan, Ni, Hu (R2) 2020; 382 Holshue, DeBolt, Lindquist (R20) 2020; 382 Zhang, Xiao, Zhang (R9) 2020; 382 Grasselli, Zangrillo, Zanella (R12) 2020; 323 Lipsitch, Swerdlow, Finelli (R16) 2020; 382 Zhou, Yu, Du (R22) 2020; 395 Yin, Huang, Li (R10) 2020; 395 Gupta, Madhavan, Sehgal (R3) 2020; 26 CDC (R24) 2020 Goyal, Choi, Pinheiro (R28) 2020; 382 Chan, Chaudhary, Saha 2020 Yang, Yu, Xu 2020; 8 Paranjpe, Fuster, Lala 2020; 76 Lauer, Grantz, Bi 2020; 172 Fisher, Neugarten, Bellin 2020; 31 Gupta, Madhavan, Sehgal 2020; 26 Grasselli, Zangrillo, Zanella 2020; 323 Vena, Giacobbe, Di Biagio 2020 Lipsitch, Swerdlow, Finelli 2020; 382 Ng, Marimuthu, Chia 2020; 382 McMichael, Currie, Clark 2020; 382 Verity, Okell, Dorigatti 2020; 20 Bhatraju, Ghassemieh, Nichols 2020; 382 CDC 2020 Zhang, Xiao, Zhang 2020; 382 Holshue, DeBolt, Lindquist 2020; 382 Guan, Ni, Hu 2020; 382 Lala, Johnson, Januzzi 2020; 76 Goyal, Choi, Pinheiro 2020; 382 Han, Zhang, Mu Lippi, Plebani 2020; 505 Zhou, Yu, Du 2020; 395 Arentz, Yim, Klaff 2020; 323 Bilaloglu, Aphinyanaphongs, Jones 2020; 324 Menter, Haslbauer, Nienhold 2020; 77 Yin, Huang, Li 2020; 395 Chan (2020112712401907000_10.11.e040736.5) 2020 Lipsitch (2020112712401907000_10.11.e040736.16) 2020; 382 Menter (2020112712401907000_10.11.e040736.8) 2020; 77 2020112712401907000_10.11.e040736.3 Bilaloglu (2020112712401907000_10.11.e040736.11) 2020; 324 2020112712401907000_10.11.e040736.15 2020112712401907000_10.11.e040736.2 2020112712401907000_10.11.e040736.4 Goyal (2020112712401907000_10.11.e040736.28) 2020; 382 2020112712401907000_10.11.e040736.1 Vena (2020112712401907000_10.11.e040736.14) 2020 2020112712401907000_10.11.e040736.17 Yin (2020112712401907000_10.11.e040736.10) 2020; 395 Yang (2020112712401907000_10.11.e040736.13) 2020; 8 2020112712401907000_10.11.e040736.18 2020112712401907000_10.11.e040736.7 2020112712401907000_10.11.e040736.6 2020112712401907000_10.11.e040736.9 Grasselli (2020112712401907000_10.11.e040736.12) 2020; 323 Ng (2020112712401907000_10.11.e040736.19) 2020; 382 2020112712401907000_10.11.e040736.22 2020112712401907000_10.11.e040736.23 2020112712401907000_10.11.e040736.20 2020112712401907000_10.11.e040736.21 2020112712401907000_10.11.e040736.26 2020112712401907000_10.11.e040736.27 2020112712401907000_10.11.e040736.24 2020112712401907000_10.11.e040736.25 2020112712401907000_10.11.e040736.29 |
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| Snippet | ObjectiveThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the... The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course... ObjectiveThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the... Objective The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the... |
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| SubjectTerms | Adolescent Adult African Americans Age Aged Aged, 80 and over Blood pressure C-Reactive Protein - metabolism Cardiovascular disease Cohort analysis Comorbidity Coronary vessels Coronaviruses COVID-19 COVID-19 - blood COVID-19 - epidemiology COVID-19 - mortality Critical Care - statistics & numerical data Demographics Diabetes Electronic health records Ethnicity Female Fibrin Fibrinogen Degradation Products - metabolism Heart failure Hispanic Americans Hospital Mortality Hospitalization Hospitals Humans Hypertension Infectious Diseases internal medicine Kidney diseases Laboratories Lymphocytes - metabolism Male Middle Aged Mortality New York City - epidemiology Pacific Islander people Pandemics Patient admissions Pre-existing conditions Procalcitonin - blood Public health Race Retrospective Studies Risk Factors SARS-CoV-2 Vital signs Young Adult |
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| Title | Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City |
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