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Mehrizi R, Golestani A, Malekpour MR, Karami H, Nasehi MM, Effatpanah M, Ranjbaran H, Shahali Z, Sari AA, Daroudi R. Drug prescription patterns and their association with mortality and hospitalization duration in COVID-19 patients: insights from big data. Front Public Health 2023; 11:1280434. [PMID: 38164450 PMCID: PMC10758044 DOI: 10.3389/fpubh.2023.1280434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 11/20/2023] [Indexed: 01/03/2024] Open
Abstract
Background Different medication prescription patterns have been associated with varying course of disease and outcomes in COVID-19. Health claims data is a rich source of information on disease treatment and outcomes. We aimed to investigate drug prescription patterns and their association with mortality and hospitalization via insurance data for a relatively long period of the pandemic in Iran. Methods We retrieved hospitalized patients' data from Iran Health Insurance Organization (IHIO) spanning 26 months (2020-2022) nationwide. Included were patients with ICD-10 codes U07.1/U07.2 for confirmed/suspected COVID-19. A case was defined as a single hospitalization event for an individual patient. Multiple hospitalizations of a patient within a 30-day interval were aggregated into a single case, while hospitalizations with intervals exceeding 30 days were treated as independent cases. The Anatomical Therapeutic Chemical (ATC) was used for medications classification. The two main study outcomes were general and intensive care unit (ICU) hospitalization periods and mortality. Besides, various demographic and clinical associate factors were analyzed to derive the associations with medication prescription patterns and study outcomes using accelerated failure time (AFT) and logistic regression models. Results During the 26 months of the study period, 1,113,678 admissions with COVID-19 diagnosis at hospitals working in company with IHIO were recorded. 917,198 cases were detected from the database, among which 51.91% were females and 48.09% were males. Among the main groups of medications, antithrombotics (55.84% [95% CI: 55.74-55.94]), corticosteroids (54.14% [54.04-54.24]), and antibiotics (42.22% [42.12-42.32]) were the top used medications among cases with COVID-19. Investigation of the duration of hospitalization based on main medication groups showed antithrombotics (adjusted median ratio = 0.94 [0.94-0.95]) were significantly associated with shorter periods of overall hospitalization. Also, antithrombotics (adjusted odds ratio = 0.74 [95%CI, 0.73-0.76]), corticosteroids (0.97 [0.95-0.99]), antivirals (0.82 [0.80-0.83]), and ACE inhibitor/ARB (0.79 [0.77-0.80]) were significantly associated with lower mortality. Conclusion Over 2 years of investigation, antithrombotics, corticosteroids, and antibiotics were the top medications for hospitalized patients with COVID-19. Trends in medication prescription varied based on various factors across the country. Medication prescriptions could potentially significantly impact the trends of mortality and hospitalization during epidemics, thereby affecting both health and economic burdens.
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Affiliation(s)
- Reza Mehrizi
- National Center for Health Insurance Research, Tehran, Iran
| | - Ali Golestani
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad-Reza Malekpour
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hossein Karami
- National Center for Health Insurance Research, Tehran, Iran
| | - Mohammad Mahdi Nasehi
- National Center for Health Insurance Research, Tehran, Iran
- Pediatric Neurology Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Effatpanah
- National Center for Health Insurance Research, Tehran, Iran
- School of Medicine, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Hossein Ranjbaran
- National Center for Health Insurance Research, Tehran, Iran
- Immunogenetics Research Center, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | - Zahra Shahali
- National Center for Health Insurance Research, Tehran, Iran
| | - Ali Akbari Sari
- Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Rajabali Daroudi
- Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
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Wang LK, Kuo YF, Westra J, Raji MA, Albayyaa M, Allencherril J, Baillargeon J. Association of Cardiovascular Medications With Adverse Outcomes in a Matched Analysis of a National Cohort of Patients With COVID-19. AMERICAN JOURNAL OF MEDICINE OPEN 2023; 9:100040. [PMID: 37207280 PMCID: PMC10032048 DOI: 10.1016/j.ajmo.2023.100040] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/22/2023] [Accepted: 03/14/2023] [Indexed: 03/24/2023]
Abstract
Background The use of statins, angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs), and anticoagulants may be associated with fewer adverse outcomes in COVID-19 patients. Methods Nested within a cohort of 800,913 patients diagnosed with COVID-19 between April 1, 2020 and June 24, 2021 from the Optum COVID-19 database, three case-control studies were conducted. Cases-defined as persons who: (1) were hospitalized within 30 days of COVID-19 diagnosis (n = 88,405); (2) were admitted to the intensive care unit (ICU)/received mechanical ventilation during COVID-19 hospitalization (n = 22,147); and (3) died during COVID-19 hospitalization (n = 2300)-were matched 1:1 using demographic/clinical factors with controls randomly selected from a pool of patients who did not experience the case definition/event. Medication use was based on prescription ≤90 days before COVID-19 diagnosis. Results Statin use was associated with decreased risk of hospitalization (adjusted odds ratio [aOR], 0.72; 95% confidence interval [95% CI], 0.69, 0.75) and ICU admission/mechanical ventilation (aOR, 0.90; 95% CI, 0.84, 0.97). ACEI/ARB use was associated with decreased risk of hospitalization (aOR, 0.67; 95% CI, 0.65, 0.70), ICU admission/mechanical ventilation (aOR, 0.92; 95% CI, 0.86, 0.99), and death (aOR, 0.60; 95% CI, 0.47, 0.78). Anticoagulant use was associated with decreased risk of hospitalization (aOR, 0.94; 95% CI, 0.89, 0.99) and death (aOR, 0.56; 95% CI, 0.41, 0.77). Interaction effects-in the model predicting hospitalization-were statistically significant for statins and ACEI/ARBs (P < .0001), statins and anticoagulants (P = .003), ACEI/ARBs and anticoagulants (P < .0001). An interaction effect-in the model predicting ventilator use/ICU-was statistically significant for statins and ACEI/ARBs (P = .002). Conclusions Statins, ACEI/ARBs, and anticoagulants were associated with decreased risks of the adverse outcomes under study. These findings may provide clinically relevant information regarding potential treatment for patients with COVID-19.
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Affiliation(s)
- Leonard K. Wang
- John Sealy School of Medicine, University of Texas Medical Branch, Galveston
| | - Yong-Fang Kuo
- Department of Preventive Medicine and Population Health, University of Texas Medical Branch, Galveston
- Department of Internal Medicine, University of Texas Medical Branch, Galveston
| | - Jordan Westra
- Department of Preventive Medicine and Population Health, University of Texas Medical Branch, Galveston
| | - Mukaila A. Raji
- Department of Preventive Medicine and Population Health, University of Texas Medical Branch, Galveston
- Department of Internal Medicine, University of Texas Medical Branch, Galveston
| | - Mohanad Albayyaa
- Institute for Translational Sciences, University of Texas Medical Branch
| | - Joseph Allencherril
- Texas Heart Institute, Houston
- Section of Cardiology, Baylor College of Medicine, Houston, Texas
| | - Jacques Baillargeon
- Department of Preventive Medicine and Population Health, University of Texas Medical Branch, Galveston
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3
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Robinson K, Schott LL, Matthews T, Tyagi M, Ajmani VB, Sacco N, Cao Z. Assessment of Healthcare Resource Utilization by Anticoagulant Heparinoid Dosage Level in Patients Hospitalized with COVID-19. Clin Appl Thromb Hemost 2022; 28:10760296221137848. [DOI: 10.1177/10760296221137848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
The aim was to describe inpatients with COVID-19 empirically prescribed heparinoid anticoagulants and compare resource utilization between prophylactic/low-dose and therapeutic/high-dose groups. Methods: This retrospective observational study used real-world data from 880 US hospitals in the PINC AI™ Healthcare Database during 4/1/2020–11/30/2020. Descriptive analysis was used to characterize patients. Multivariable regression was used to evaluate intensive care unit (ICU) admissions, length of stay (LOS), mortality, and costs by anticoagulation dose group, adjusting for cohort characteristics. Among 122,508 inpatients, 29,225 (23.9%) received therapeutic/high-dose, and 93,283 (76.1%) received prophylactic/low-dose anticoagulation. The high-dose group had more comorbidities and worse laboratory values compared with low-dose. Respectively, ICU admission rates were 36.7% and 19.1% and LOS median (Q1, Q3) was 8 (5, 15) and 5 (3, 9) days. In separate adjusted models, high-dose anticoagulation was associated with a 45% increase in odds of ICU admission, 26% increase in odds of in-hospital mortality, 21% longer average LOS, and 28% greater average total cost compared with low-dose (each P < 0.001). Prophylactic/low-dose anticoagulation treatment was associated with decreased healthcare resource utilization (HRU) in hospitalized patients with COVID-19.
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Affiliation(s)
- Keith Robinson
- Medical and Scientific Management, Syneos Health, Morrisville, NC, USA
| | - Laura L. Schott
- PINC AI™ Applied Sciences®, Premier Inc., Charlotte, NC, USA
| | - Tom Matthews
- Specialty Pharma, Meitheal Pharmaceuticals, Inc., Chicago, IL, USA
| | - Manu Tyagi
- PINC AI™ Applied Sciences®, Premier Inc., Charlotte, NC, USA
| | - Vivek B. Ajmani
- PINC AI™ Applied Sciences®, Premier Inc., Charlotte, NC, USA
| | - Nancy Sacco
- Specialty Pharma, Meitheal Pharmaceuticals, Inc., Chicago, IL, USA
| | - Zhun Cao
- PINC AI™ Applied Sciences®, Premier Inc., Charlotte, NC, USA
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Rando HM, MacLean AL, Lee AJ, Lordan R, Ray S, Bansal V, Skelly AN, Sell E, Dziak JJ, Shinholster L, D’Agostino McGowan L, Ben Guebila M, Wellhausen N, Knyazev S, Boca SM, Capone S, Qi Y, Park Y, Mai D, Sun Y, Boerckel JD, Brueffer C, Byrd JB, Kamil JP, Wang J, Velazquez R, Szeto GL, Barton JP, Goel RR, Mangul S, Lubiana T, Gitter A, Greene CS. Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure. mSystems 2021; 6:e0009521. [PMID: 34698547 PMCID: PMC8547481 DOI: 10.1128/msystems.00095-21] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/27/2021] [Indexed: 02/06/2023] Open
Abstract
The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host. Because the genomic content of coronaviruses, which specifies the virus's structure, is highly conserved, early genomic analysis provided a significant head start in predicting viral pathogenesis and in understanding potential differences among variants. The pathogenesis of the virus offers insights into symptomatology, transmission, and individual susceptibility. Additionally, prior research into interactions between the human immune system and coronaviruses has identified how these viruses can evade the immune system's protective mechanisms. We also explore systems-level research into the regulatory and proteomic effects of SARS-CoV-2 infection and the immune response. Understanding the structure and behavior of the virus serves to contextualize the many facets of the COVID-19 pandemic and can influence efforts to control the virus and treat the disease. IMPORTANCE COVID-19 involves a number of organ systems and can present with a wide range of symptoms. From how the virus infects cells to how it spreads between people, the available research suggests that these patterns are very similar to those seen in the closely related viruses SARS-CoV-1 and possibly Middle East respiratory syndrome-related CoV (MERS-CoV). Understanding the pathogenesis of the SARS-CoV-2 virus also contextualizes how the different biological systems affected by COVID-19 connect. Exploring the structure, phylogeny, and pathogenesis of the virus therefore helps to guide interpretation of the broader impacts of the virus on the human body and on human populations. For this reason, an in-depth exploration of viral mechanisms is critical to a robust understanding of SARS-CoV-2 and, potentially, future emergent human CoVs (HCoVs).
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Affiliation(s)
- Halie M. Rando
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, USA
- Center for Health AI, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Adam L. MacLean
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA
| | - Alexandra J. Lee
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ronan Lordan
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sandipan Ray
- Department of Biotechnology, Indian Institute of Technology Hyderabad, Sangareddy, Telangana, India
| | - Vikas Bansal
- Biomedical Data Science and Machine Learning Group, German Center for Neurodegenerative Diseases, Tübingen, Germany
| | - Ashwin N. Skelly
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Elizabeth Sell
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John J. Dziak
- Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, Pennsylvania, USA
| | | | - Lucy D’Agostino McGowan
- Department of Mathematics and Statistics, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Marouen Ben Guebila
- Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Nils Wellhausen
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Simina M. Boca
- Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC, USA
| | - Stephen Capone
- St. George’s University School of Medicine, St. George’s, Grenada
| | - Yanjun Qi
- Department of Computer Science, University of Virginia, Charlottesville, Virginia, USA
| | - YoSon Park
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David Mai
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Yuchen Sun
- Department of Computer Science, University of Virginia, Charlottesville, Virginia, USA
| | - Joel D. Boerckel
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - James Brian Byrd
- University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Jeremy P. Kamil
- Department of Microbiology and Immunology, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Jinhui Wang
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | | | - John P. Barton
- Department of Physics and Astronomy, University of California-Riverside, Riverside, California, USA
| | - Rishi Raj Goel
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, California, USA
| | - Tiago Lubiana
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - COVID-19 Review Consortium
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, USA
- Center for Health AI, University of Colorado School of Medicine, Aurora, Colorado, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biotechnology, Indian Institute of Technology Hyderabad, Sangareddy, Telangana, India
- Biomedical Data Science and Machine Learning Group, German Center for Neurodegenerative Diseases, Tübingen, Germany
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, Pennsylvania, USA
- Mercer University, Macon, Georgia, USA
- Department of Mathematics and Statistics, Wake Forest University, Winston-Salem, North Carolina, USA
- Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA
- Georgia State University, Atlanta, Georgia, USA
- Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC, USA
- St. George’s University School of Medicine, St. George’s, Grenada
- Department of Computer Science, University of Virginia, Charlottesville, Virginia, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Clinical Sciences, Lund University, Lund, Sweden
- University of Michigan School of Medicine, Ann Arbor, Michigan, USA
- Department of Microbiology and Immunology, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
- Azimuth1, McLean, Virginia, USA
- Allen Institute for Immunology, Seattle, Washington, USA
- Department of Physics and Astronomy, University of California-Riverside, Riverside, California, USA
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, California, USA
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Morgridge Institute for Research, Madison, Wisconsin, USA
- Childhood Cancer Data Lab, Alex’s Lemonade Stand Foundation, Philadelphia, Pennsylvania, USA
| | - Anthony Gitter
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Morgridge Institute for Research, Madison, Wisconsin, USA
| | - Casey S. Greene
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, USA
- Center for Health AI, University of Colorado School of Medicine, Aurora, Colorado, USA
- Childhood Cancer Data Lab, Alex’s Lemonade Stand Foundation, Philadelphia, Pennsylvania, USA
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Kumar G, Patel D, Odeh T, Rojas E, Sakhuja A, Meersman M, Dalton D, Nanchal R, Guddati AK. Incidence of Venous Thromboembolism and Effect of Anticoagulant Dosing in Hospitalized COVID-19 Patients. J Hematol 2021; 10:162-170. [PMID: 34527112 PMCID: PMC8425807 DOI: 10.14740/jh836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 05/07/2021] [Indexed: 12/15/2022] Open
Abstract
Background Coronavirus disease 2019 (COVID-19) is characterized by coagulopathy and thrombotic events. We examined factors associated with development of venous thromboembolism (VTE) in COVID-19 and to discern if higher dose of anticoagulation was beneficial in these patients. Methods This study involves an observational study of prospectively collected data in the setting of a large community hospital in a rural setting in Northeast Georgia with COVID-19 between March 1, 2020 and February 5, 2021. Anticoagulation dose (none, standard, intermediate, and therapeutic dosages) was studied in adult patients (≥ 18 years). We constructed multivariable logistic regression model to examine the association of clinical characteristics with VTE. To examine the effect of dose of anticoagulation in preventing VTE, we used inverse probability weighted regression adjustment. Results Of the 4,645 patients with COVID-19, 251 (5.4%) patients were found to have VTE. Of these, 91 had pulmonary embolism, 148 had deep venous thrombosis (DVT) and 12 had both. A total of 129 of VTE cases were diagnosed at admission. Of all admissions, 12.9% did not receive any DVT prophylaxis, 70.4% received prophylactic dose, 1.3% received intermediate dose and 15.5% received therapeutic dose. Male gender (odds ratio (OR): 1.55, 95% confidence interval (CI): 1.0 - 2.4, P = 0.04) and Black race (OR: 2.0, 95% CI: 1.2 - 3.4, P = 0.01), along with higher levels of lactate dehydrogenase (LDH) and D-dimer were associated with higher odds of developing VTE. Patients receiving steroids had lower rates of VTE (3.9% vs. 8.3%, P < 0.001). Use of intermediate or therapeutic anticoagulation was not associated with lower odds of developing VTE. However, patients on therapeutic anticoagulation had lower odds of in hospital mortality when compared to standard dose (OR: 0.47, 95% CI: 0.27 - 0.80, P = 0.006). Conclusions In COVID-19, D-dimer and LDH can be useful in predicting VTE. Steroids appear to have some protective role in development of VTE. Therapeutic anticoagulation did not result in lower rates of VTE but was associated with in-hospital mortality.
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Affiliation(s)
- Gagan Kumar
- Department of Pulmonary and Critical Care, Northeast Georgia Health System, Gainesville, GA 30501, USA
| | - Dhaval Patel
- Department of Pulmonary and Critical Care, Northeast Georgia Health System, Gainesville, GA 30501, USA
| | - Tariq Odeh
- Department of Internal Medicine, Northeast Georgia Health System, Gainesville, GA 30501, USA
| | - Erine Rojas
- Department of Pulmonary and Critical Care, Northeast Georgia Health System, Gainesville, GA 30501, USA
| | - Ankit Sakhuja
- Division of Cardiovascular Critical Care, Department of Cardiovascular and Thoracic Surgery, West Virginia University, WV 26506, USA
| | - Mark Meersman
- IPC Global, 4080 McGinnis Ferry Road, Building 100, Suite 103, Alpharetta, GA 30005, USA
| | - Drew Dalton
- IPC Global, 4080 McGinnis Ferry Road, Building 100, Suite 103, Alpharetta, GA 30005, USA
| | - Rahul Nanchal
- Division of Pulmonary and Critical Care, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Achuta Kumar Guddati
- Division of Hematology/Oncology, Georgia Cancer Center, Augusta University, Augusta, GA 30909, USA
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Szekely L, Bozoky B, Bendek M, Ostad M, Lavignasse P, Haag L, Wu J, Jing X, Gupta S, Saccon E, Sönnerborg A, Cao Y, Björnstedt M, Szakos A. Pulmonary stromal expansion and intra-alveolar coagulation are primary causes of COVID-19 death. Heliyon 2021; 7:e07134. [PMID: 34056141 PMCID: PMC8141733 DOI: 10.1016/j.heliyon.2021.e07134] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 03/04/2021] [Accepted: 05/19/2021] [Indexed: 12/12/2022] Open
Abstract
Most COVID-19 victims are old and die from unrelated causes. Here we present twelve complete autopsies, including two rapid autopsies of young patients where the cause of death was COVID-19 ARDS. The main virus induced pathology was in the lung parenchyma and not in the airways. Most coagulation events occurred in the intra-alveolar and not in the intra-vascular space and the few thrombi were mainly composed of aggregated thrombocytes. The dominant inflammatory response was the massive accumulation of CD163 + macrophages and the disappearance of T killer, NK and B-cells. The virus was replicating in the pneumocytes and macrophages but not in bronchial epithelium, endothelium, pericytes or stromal cells. The lung consolidations were produced by a massive regenerative response, stromal and epithelial proliferation and neovascularization. We suggest that thrombocyte aggregation inhibition, angiogenesis inhibition and general proliferation inhibition may have a roll in the treatment of advanced COVID-19 ARDS.
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Affiliation(s)
- Laszlo Szekely
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
| | - Bela Bozoky
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
| | - Matyas Bendek
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
| | - Masih Ostad
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
| | - Pablo Lavignasse
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
| | - Lars Haag
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
| | - Jieyu Wu
- Microbiology and Tumor Biology Center, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Xu Jing
- Microbiology and Tumor Biology Center, Karolinska Institutet, 171 77 Stockholm, Sweden
- The Second Hospital of Shandong University, Department of Clinical Laboratory, 250033 Jinan, China
| | - Soham Gupta
- Department of Laboratory Medicine, Clinical Microbiology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Elisa Saccon
- Department of Laboratory Medicine, Clinical Microbiology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Anders Sönnerborg
- Department of Laboratory Medicine, Clinical Microbiology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Yihai Cao
- Microbiology and Tumor Biology Center, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Mikael Björnstedt
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
| | - Attila Szakos
- Department of Pathology/Cytology, Karolinska University Laboratory, 141 86 Stockholm, Sweden
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7
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Parisi R, Costanzo S, Di Castelnuovo A, de Gaetano G, Donati MB, Iacoviello L. Different Anticoagulant Regimens, Mortality, and Bleeding in Hospitalized Patients with COVID-19: A Systematic Review and an Updated Meta-Analysis. Semin Thromb Hemost 2021; 47:372-391. [PMID: 33851386 DOI: 10.1055/s-0041-1726034] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
We conducted a systematic review and a meta-analysis to assess the association of anticoagulants and their dosage with in-hospital all-cause mortality in COVID-19 patients. Articles were retrieved until January 8, 2021, by searching in seven electronic databases. The main outcome was all-cause mortality occurred during hospitalization. Data were combined using the general variance-based method on the effect estimate for each study. Separate meta-analyses according to type of COVID-19 patients (hospitalized or intensive care unit [ICU] patients), anticoagulants (mainly heparin), and regimens (therapeutic or prophylactic) were conducted. A total of 29 articles were selected, but 23 retrospective studies were eligible for quantitative meta-analyses. No clinical trial was retrieved. The majority of studies were of good quality; however, 34% did not distinguish heparin from other anticoagulants. Meta-analysis on 25,719 hospitalized COVID-19 patients showed that anticoagulant use was associated with 50% reduced in-hospital mortality risk (pooled risk ratio [RR]: 0.50, 95% confidence interval [CI]: 0.40-0.62; I 2: 87%). Both anticoagulant regimens (therapeutic and prophylactic) reduced in-hospital all-cause mortality, compared with no anticoagulation. Particularly in ICU patients, the anticoagulant therapeutic regimen was associated with a reduced in-hospital mortality risk (RR: 0.30, 95% CI: 0.15-0.60; I 2: 58%) compared with the prophylactic one. However, the former was also associated with a higher risk of bleeding (RR: 2.53, 95% CI: 1.60-4.00; I 2: 65%). Anticoagulant use, mainly heparin, reduced all-cause mortality in COVID-19 patients during hospitalization. Due to the higher risk of bleeding at therapeutic doses, the use of prophylactic dosages of anticoagulant is probably to be preferred in noncritically ill COVID-19 patients.
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Affiliation(s)
- Roberta Parisi
- Department of Epidemiology and Prevention. IRCCS Neuromed, via dell'Elettronica, Pozzilli, Isernia, Italy
| | - Simona Costanzo
- Department of Epidemiology and Prevention. IRCCS Neuromed, via dell'Elettronica, Pozzilli, Isernia, Italy
| | | | - Giovanni de Gaetano
- Department of Epidemiology and Prevention. IRCCS Neuromed, via dell'Elettronica, Pozzilli, Isernia, Italy
| | - Maria Benedetta Donati
- Department of Epidemiology and Prevention. IRCCS Neuromed, via dell'Elettronica, Pozzilli, Isernia, Italy
| | - Licia Iacoviello
- Department of Epidemiology and Prevention. IRCCS Neuromed, via dell'Elettronica, Pozzilli, Isernia, Italy.,Research Center in Epidemiology and Preventive Medicine (EPIMED), Department of Medicine and Surgery, University of Insubria, Varese, Italy
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8
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Cau R, Bassareo PP, Mannelli L, Suri JS, Saba L. Imaging in COVID-19-related myocardial injury. Int J Cardiovasc Imaging 2021; 37:1349-1360. [PMID: 33211242 PMCID: PMC7676417 DOI: 10.1007/s10554-020-02089-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 10/26/2020] [Indexed: 02/07/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2), previously named "2019 novel coronavirus" (2019-nCoV) is an emerging disease and a major public health issue. At the moment, little is known, except that its spread is on a steady upward trend. That is the reason why it was declared pandemic since March 11th, 2020. Respiratory symptoms dominate the clinical manifestations of the virus, but in a few patients also other organs are involved, such as their heart. This review article provides an overview of the existing literature regarding imaging of heart injury during COVID-19 acute infection and follow-up.
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Affiliation(s)
- Riccardo Cau
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato s.s. 554 Monserrato, 09045, Cagliari, Italy
| | - Pier Paolo Bassareo
- Mater Misericordiae University Hospital and Our Lady's Children's Hospital, University College of Dublin, Crumlin, Dublin, Republic of Ireland
| | | | - Jasjit S Suri
- Stroke Monitoring and Diagnostic Division, ATHEROPOINT LLC, Roseville, CA, USA
| | - Luca Saba
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato s.s. 554 Monserrato, 09045, Cagliari, Italy.
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9
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Nijman G, Wientjes M, Ramjith J, Janssen N, Hoogerwerf J, Abbink E, Blaauw M, Dofferhoff T, van Apeldoorn M, Veerman K, de Mast Q, ten Oever J, Hoefsloot W, Reijers MH, van Crevel R, van de Maat JS. Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis. PLoS One 2021; 16:e0249231. [PMID: 33770140 PMCID: PMC7997038 DOI: 10.1371/journal.pone.0249231] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 03/14/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND To date, survival data on risk factors for COVID-19 mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients in the Netherlands, considering recovery as a competing risk. METHODS In this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hospitals in the Netherlands (March to May 2020). We performed a competing risk survival analysis, presenting cause-specific hazard ratios (HRCS) for the effect of preselected factors on the absolute risk of death and recovery. RESULTS 1,006 patients were included (63.9% male; median age 69 years, IQR: 58-77). Patients were hospitalized for a median duration of 6 days (IQR: 3-13); 243 (24.6%) of them died, 689 (69.9%) recovered, and 74 (7.4%) were censored. Patients with higher age (HRCS 1.10, 95% CI 1.08-1.12), immunocompromised state (HRCS 1.46, 95% CI 1.08-1.98), who used anticoagulants or antiplatelet medication (HRCS 1.38, 95% CI 1.01-1.88), with higher modified early warning score (MEWS) (HRCS 1.09, 95% CI 1.01-1.18), and higher blood LDH at time of admission (HRCS 6.68, 95% CI 1.95-22.8) had increased risk of death, whereas fever (HRCS 0.70, 95% CI 0.52-0.95) decreased risk of death. We found no increased mortality risk in male patients, high BMI or diabetes. CONCLUSION Our competing risk survival analysis confirms specific risk factors for COVID-19 mortality in a the Netherlands, which can be used for prediction research, more intense in-hospital monitoring or prioritizing particular patients for new treatments or vaccination.
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Affiliation(s)
- Gerine Nijman
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Maike Wientjes
- Department of Research, Sint Maartenskliniek, Nijmegen, The Netherlands
| | - Jordache Ramjith
- Department of Health Evidence, Section Biostatistics, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Nico Janssen
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
- Centre of Expertise in Mycology, Radboud University Medical Centre, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | - Jacobien Hoogerwerf
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Evertine Abbink
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Marc Blaauw
- Department of Internal Medicine, Bernhoven Hospital, Uden, The Netherlands
| | - Ton Dofferhoff
- Department of Internal Medicine, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | - Marjan van Apeldoorn
- Department of Internal Medicine, Jeroen Bosch Hospital, Den Bosch, The Netherlands
| | - Karin Veerman
- Department of Internal Medicine, Sint Maartenskliniek, Nijmegen, The Netherlands
| | - Quirijn de Mast
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Jaap ten Oever
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Wouter Hoefsloot
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
- Department of Pulmonary Diseases, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Monique H. Reijers
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
- Department of Pulmonary Diseases, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Reinout van Crevel
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Josephine S. van de Maat
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands
- * E-mail:
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10
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Rentsch CT, Beckman JA, Tomlinson L, Gellad WF, Alcorn C, Kidwai-Khan F, Skanderson M, Brittain E, King JT, Ho YL, Eden S, Kundu S, Lann MF, Greevy RA, Ho PM, Heidenreich PA, Jacobson DA, Douglas IJ, Tate JP, Evans SJW, Atkins D, Justice AC, Freiberg MS. Early initiation of prophylactic anticoagulation for prevention of coronavirus disease 2019 mortality in patients admitted to hospital in the United States: cohort study. BMJ 2021; 372:n311. [PMID: 33574135 PMCID: PMC7876672 DOI: 10.1136/bmj.n311] [Citation(s) in RCA: 138] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/01/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To evaluate whether early initiation of prophylactic anticoagulation compared with no anticoagulation was associated with decreased risk of death among patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United States. DESIGN Observational cohort study. SETTING Nationwide cohort of patients receiving care in the Department of Veterans Affairs, a large integrated national healthcare system. PARTICIPANTS All 4297 patients admitted to hospital from 1 March to 31 July 2020 with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and without a history of anticoagulation. MAIN OUTCOME MEASURES The main outcome was 30 day mortality. Secondary outcomes were inpatient mortality, initiating therapeutic anticoagulation (a proxy for clinical deterioration, including thromboembolic events), and bleeding that required transfusion. RESULTS Of 4297 patients admitted to hospital with covid-19, 3627 (84.4%) received prophylactic anticoagulation within 24 hours of admission. More than 99% (n=3600) of treated patients received subcutaneous heparin or enoxaparin. 622 deaths occurred within 30 days of hospital admission, 513 among those who received prophylactic anticoagulation. Most deaths (510/622, 82%) occurred during hospital stay. Using inverse probability of treatment weighted analyses, the cumulative incidence of mortality at 30 days was 14.3% (95% confidence interval 13.1% to 15.5%) among those who received prophylactic anticoagulation and 18.7% (15.1% to 22.9%) among those who did not. Compared with patients who did not receive prophylactic anticoagulation, those who did had a 27% decreased risk for 30 day mortality (hazard ratio 0.73, 95% confidence interval 0.66 to 0.81). Similar associations were found for inpatient mortality and initiation of therapeutic anticoagulation. Receipt of prophylactic anticoagulation was not associated with increased risk of bleeding that required transfusion (hazard ratio 0.87, 0.71 to 1.05). Quantitative bias analysis showed that results were robust to unmeasured confounding (e-value lower 95% confidence interval 1.77 for 30 day mortality). Results persisted in several sensitivity analyses. CONCLUSIONS Early initiation of prophylactic anticoagulation compared with no anticoagulation among patients admitted to hospital with covid-19 was associated with a decreased risk of 30 day mortality and no increased risk of serious bleeding events. These findings provide strong real world evidence to support guidelines recommending the use of prophylactic anticoagulation as initial treatment for patients with covid-19 on hospital admission.
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Affiliation(s)
- Christopher T Rentsch
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
| | - Joshua A Beckman
- Cardiovascular Division, Vanderbilt University Medical Center and Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | - Laurie Tomlinson
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - Walid F Gellad
- Center for Pharmaceutical Policy and Prescribing, Health Policy Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Division of General Internal Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veterans Affairs Pittsburgh Healthcare System, US Department of Veterans Affairs, Pittsburgh, PA, USA
| | - Charles Alcorn
- Center for Occupational Biostatistics and Epidemiology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Farah Kidwai-Khan
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Melissa Skanderson
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
| | - Evan Brittain
- Department of Medicine, Vanderbilt University Medical Center and Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | - Joseph T King
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Svetlana Eden
- Faculty of Biostatistics, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Suman Kundu
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael F Lann
- Center for Occupational Biostatistics and Epidemiology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert A Greevy
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - P Michael Ho
- Rocky Mountain Regional VA Medical Center, US Department of Veterans Affairs, Aurora, CO, USA
| | - Paul A Heidenreich
- VA Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Daniel A Jacobson
- Oak Ridge National Laboratory, Biosciences Division, Oak Ridge, TN, USA
| | - Ian J Douglas
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - Janet P Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Stephen J W Evans
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - David Atkins
- Health Services Research and Development, US Department of Veterans Affairs, Washington, DC, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | - Matthew S Freiberg
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Geriatric Research Education and Clinical Center, Tennessee Valley Healthcare System, US Department of Veterans Affairs, Nashville, TN, USA
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11
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Singh S, Jain K, Paul D, Singh J. A review of the pathological mechanisms and clinical implications of coagulopathy in COVID-19. JOURNAL OF APPLIED HEMATOLOGY 2021. [DOI: 10.4103/joah.joah_19_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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12
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Early initiation of prophylactic anticoagulation for prevention of COVID-19 mortality: a nationwide cohort study of hospitalized patients in the United States. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.12.09.20246579. [PMID: 33330896 PMCID: PMC7743107 DOI: 10.1101/2020.12.09.20246579] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
IMPORTANCE Deaths among patients with coronavirus disease 2019 (COVID-19) are partially attributed to venous thromboembolism and arterial thromboses. Anticoagulants prevent thrombosis formation, possess anti-inflammatory and anti-viral properties, and may be particularly effective for treating patients with COVID-19. OBJECTIVE To evaluate whether initiation of prophylactic anticoagulation within 24 hours of admission is associated with decreased risk of death among patients hospitalized with COVID-19. DESIGN Observational cohort study. SETTING Nationwide cohort of patients receiving care in the Department of Veterans Affairs, the largest integrated healthcare system in the United States. PARTICIPANTS All patients hospitalized with laboratory-confirmed SARS-CoV-2 infection March 1 to July 31, 2020, without a history of therapeutic anticoagulation. EXPOSURES Prophylactic doses of subcutaneous heparin, low-molecular-weight heparin, or direct oral anticoagulants. MAIN OUTCOMES AND MEASURES 30-day mortality. Secondary outcomes: inpatient mortality and initiating therapeutic anticoagulation. RESULTS Of 4,297 patients hospitalized with COVID-19, 3,627 (84.4%) received prophylactic anticoagulation within 24 hours of admission. More than 99% (n=3,600) received subcutaneous heparin or enoxaparin. We observed 622 deaths within 30 days of admission, 513 among those who received prophylactic anticoagulation. Most deaths (510/622, 82%) occurred during hospitalization. In inverse probability of treatment weighted analyses, cumulative adjusted incidence of mortality at 30 days was 14.3% (95% CI 13.1-15.5) among those receiving prophylactic anticoagulation and 18.7% (95% CI 15.1-22.9) among those who did not. Compared to patients who did not receive prophylactic anticoagulation, those who did had a 27% decreased risk for 30-day mortality (HR 0.73, 95% CI 0.66-0.81). Similar associations were found for inpatient mortality and initiating therapeutic anticoagulation. Quantitative bias analysis demonstrated that results were robust to unmeasured confounding (e-value lower 95% CI 1.77). Results persisted in a number of sensitivity analyses. CONCLUSIONS AND RELEVANCE Early initiation of prophylactic anticoagulation among patients hospitalized with COVID-19 was associated with a decreased risk of mortality. These findings provide strong real-world evidence to support guidelines recommending the use of prophylactic anticoagulation as initial therapy for COVID-19 patients upon hospital admission.
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