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Publications

Journal Article Ahead of print 2 citations

PubMed: 40683552 DOI: 10.1016/j.jtha.2025.07.007

Development and validation of risk models for hospital-acquired bleeding in medical inpatients: the Medical Inpatients Thrombosis and Hemostasis (MITH) study.

J Thromb Haemost

Authors: Neil A Zakai, Katherine Wilkinson, Andrew D Sparks, Ryan T Packer, Nicholas S Roetker, Allen B Repp, Mansour Gergi, Chris Holmes, Mary Cushman, Timothy B Plante, Hanny Al-Samkari, Allyson M Pishko, William A Wood, Camila Masias, Radhika Gangaraju, Ang Li, David Garcia, Kerri L Wiggins, Jordan K Schaefer, Nicholas L Smith, Augusto Ferraris, Karlyn A Martin, Deirdra R Terrell, Leslie A McClure

Affiliations

  • Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; Department of Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; University of Vermont Medical Center, Burlington, Vermont, USA.
  • Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA.
  • Department of Medical Biostatistics, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA.
  • Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota, USA.
  • Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; University of Vermont Medical Center, Burlington, Vermont, USA.
  • Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; Department of Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; University of Vermont Medical Center, Burlington, Vermont, USA.
  • Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Baptist Health South Florida, Miami, Florida, USA.
  • Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, Alabama, USA.
  • Section of Hematology-Oncology, Baylor College of Medicine, Houston, Texas, USA.
  • Division of Hematology, University of Washington School of Medicine, Seattle, Washington, USA.
  • Department of Medicine, University of Washington, Seattle, Washington, USA.
  • Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan USA.
  • Department of Epidemiology, University of Washington, Seattle, Washington, USA; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle Washington, USA; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, Washington, USA.
  • Department of Epidemiology, University of Washington, Seattle, Washington, USA.
  • Hudson College of Public Health, the University of Oklahoma Health Sciences, Oklahoma City, Oklahoma, USA.
  • Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice, St. Louis, Missouri, USA.

Abstract

BACKGROUND

Hospital-acquired (HA) bleeding in medical inpatients is a serious complication with limited tools to predict risk.

OBJECTIVES

This study aimed to develop and validate risk assessment models (RAMs) for anatomic location-specific HA bleeding in medical inpatients using objective and routinely available risk factors.

METHODS

Patients aged ≥18 years admitted to medical hospital services from 6 health systems and 15 hospitals in the United States between 2016 and 2020 for at least 1 midnight and without bleeding at admission were eligible for inclusion. Two health systems (10 hospitals) formed the development cohort, and 4 systems (5 hospitals) constituted the validation cohort. Bayesian Least absolute shrinkage and selection operator was used to develop anatomic site-specific RAMs.

RESULTS

Among the development (153 707 admissions) and validation (137 460 admissions) cohorts, 5999 (3.9%) and 3282 (2.4%) HA bleeds occurred. RAMs had varied risk factors by anatomic bleeding location; for instance, older age was associated with genitourinary bleeding in men but not in women. Different cancer types were associated with different anatomic bleeding locations such as genitourinary cancers associated with genitourinary bleeding and gynecologic bleeding. The RAMs demonstrated good predictive performance for most anatomical bleeding locations; the C-statistic was ≥0.67 for all anatomic location bleeding in the development and validation cohorts and generally higher in the anatomic location specific RAMs.

CONCLUSION

These RAMs provide anatomic location-specific and sex-specific HA-bleeding risk stratification, addressing a critical gap in individualized risk assessment. Integration into clinical workflows could enhance patient safety and outcomes. Implementation studies are essential to maximize their clinical utility.

MeSH

Hemorrhage, Hospitalization, Risk Assessment, Neoplasms, Risk Factors, Thrombosis, Hemostasis