Article Text

Original research
Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City
  1. Ishan Paranjpe1,
  2. Adam J Russak1,2,
  3. Jessica K De Freitas1,3,
  4. Anuradha Lala4,5,
  5. Riccardo Miotto1,3,
  6. Akhil Vaid1,3,
  7. Kipp W Johnson1,3,
  8. Matteo Danieletto1,3,
  9. Eddye Golden1,3,
  10. Dara Meyer3,
  11. Manbir Singh1,
  12. Sulaiman Somani1,
  13. Arjun Kapoor1,
  14. Ross O'Hagan1,
  15. Sayan Manna1,
  16. Udit Nangia1,
  17. Suraj K Jaladanki1,
  18. Paul O’Reilly3,6,
  19. Laura M Huckins3,6,
  20. Patricia Glowe1,3,
  21. Arash Kia5,7,
  22. Prem Timsina5,7,
  23. Robert M Freeman5,7,
  24. Matthew A Levin3,5,7,8,
  25. Jeffrey Jhang9,
  26. Adolfo Firpo9,
  27. Patricia Kovatch10,
  28. Joseph Finkelstein5,
  29. Judith A Aberg11,12,
  30. Emilia Bagiella4,5,
  31. Carol R Horowitz5,12,
  32. Barbara Murphy12,
  33. Zahi A Fayad13,14,
  34. Jagat Narula12,15,
  35. Eric J Nestler16,17,
  36. V Fuster18,
  37. Carlos Cordon-Cardo9,
  38. Dennis Charney19,20,
  39. David L Reich21,
  40. Allan Just22,23,
  41. Erwin P Bottinger1,
  42. Alexander W Charney3,6,
  43. Benjamin S Glicksberg1,3,6,
  44. Girish N Nadkarni1,12,24
  45. On behalf of Mount Sinai COVID Informatics Center (MSCIC)
  1. 1The Hasso Plattner Institute for Digital Health at Mount Sinai, New York, New York, USA
  2. 2Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  3. 3Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  4. 4The Zena and Michael A. Wiener Cardiovascular Institute, New York, New York, USA
  5. 5Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  6. 6The Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  7. 7Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  8. 8Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  9. 9Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  10. 10Mount Sinai Data Warehouse, Mount Sinai Health System, New York, New York, USA
  11. 11Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  12. 12Icahn School of Medicine at Mount Sinai Department of Medicine, New York, New York, USA
  13. 13Icahn School of Medicine at Mount Sinai BioMedical Engineering and Imaging Institute, New York, New York, USA
  14. 14Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  15. 15Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  16. 16Icahn School of Medicine at Mount Sinai Friedman Brain Institute, New York, New York, USA
  17. 17The Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  18. 18Department 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
  19. 19Icahn School of Medicine at Mount Sinai Department of Psychiatry, New York, New York, USA
  20. 20The Office of the Dean, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  21. 21Icahn School of Medicine at Mount Sinai Department of Anesthesiology Perioperative and Pain Medicine, New York, New York, USA
  22. 22Icahn School of Medicine at Mount Sinai Department of Environmental Medicine and Public Health, New York, New York, USA
  23. 23Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  24. 24The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  1. Correspondence to Mr Ishan Paranjpe; iparanjpe{at}berkeley.edu

Abstract

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.

  • infectious diseases
  • public health
  • internal medicine
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/.

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Supplementary materials

Footnotes

  • EPB, AWC, BSG and GNN are joint senior authors.

  • Twitter @ParanjpeIshan, @RFreeman_RN, @BenGlicksberg

  • IP, AJR, JKDF and AL contributed equally.

  • Contributors IP, AJR, JKDF, AL, MS, AV, KWJ, SS, AK, RO'H, SM, UN, SKJ, AK, PT, JJ and AF developed and performed the analysis. PG, MAL, JF, JAA, EB, CRH and BM critically appraised the manuscript and helped acquire data. IP, AL, AJR, JKDpF, RM, MD, EG, DM, LMH, RF, MS, PK, VF, EPB, JN, EJN, CC-C, DC and DLR supervised the project. IP, AL, AJR, JKDF, GNN, BSG, AWC and AJ drafted the manuscript.

  • Funding This work was Supported by U54 TR001433-05, National Center for Advancing Translational Sciences, National Institutes of Health.

  • Competing interests GNN reports grants, personal fees and non-financial support from Renalytix AI, non-financial support from Pensieve Health, personal fees from AstraZeneca, BioVie, GLG Consulting, from outside the submitted work. AL reports personal fees from Zoll, outside the submitted work. ZAF reports grants from Daiichi Sankyo, grants from Amgen, Bristol Myers Squibb and Siemens Healthineers, personal fees from Alexion, GlaxoSmithKline, Trained Therapeutix Discovery, outside the submitted work. In addition, ZAF has patents licensed to Trained Therapeutix Discovery. The other authors have nothing to disclose.

  • Patient consent for publication Not required.

  • Ethics approval The Mount Sinai Institutional Review Board approved this research under a broad regulatory protocol allowing for analysis of limited patient-level data.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement No data are available. Please contact authors for information on data availability.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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