title: Venous thromboembolism and the utility of the Padua Prediction Score in patients with sepsis admitted to internal medicine departments.
abstract: BACKGROUND
  Sepsis is prevalent in internal medicine (IM) departments. Elderly patients with sepsis and chronic medical conditions are at an increased risk for venous thromboemolism (VTE). The objective of this study was to assess the rate of VTE and the accuracy of the Padua Prediction Score (PPS) to predict VTE in patient with sepsis admitted to IM departments.
  
  
  METHODS
  We prospectively collected data on septic patients admitted to IM departments in a community-based medical center. Additionally, we retrospectively collected VTE risk factors and events throughout a 1-year post hospitalization period. We computed the PPS for every patient, and analyzed the data accordingly.
  
  
  RESULTS
  In total, 1080 patients were included in the study. The mean age was 74.68 ± 16.1 years. The average PPS was 4.86 ± 2.26, and 71.2% of the patients had a positive PPS. Only 17.8% of the patients received anticoagulant prophylaxis during their hospital stay. Seven patients had VTE on admission, 14 (1.29%) acquired in-hospital VTE, and 7 (0.65%) had VTE post discharge throughout 1 year. In all, 21.9% patients died during hospitalization, and the overall survival rate was 64%. PPS was not correlated with anticoagulant administration (P = 0.36), in-hospital VTE (P = 0.23) or 1-year VTE (P = 0.40), but was significantly associated with in-hospital death and survival (P < 0.0001).
  
  
  CONCLUSIONS
  The rate of VTE in medical patients with sepsis in IM departments is low, and PPS lacks granularity in detecting patients at risk of acquiring it. In this population, a positive PPS is highly associated with death, and may reflect a more general co-morbidity and disease severity index.
authors.affiliation: Harvard Clinical Research Institute, Boston, MA 02215, USA. vardi.moshe@gmail.com
authors.forename: M
authors.initials: M
authors.lastname: Vardi
authors.forename: N O
authors.initials: NO
authors.lastname: Ghanem-Zoubi
authors.forename: R
authors.initials: R
authors.lastname: Zidan
authors.forename: V
authors.initials: V
authors.lastname: Yurin
authors.forename: H
authors.initials: H
authors.lastname: Bitterman
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000925:Anticoagulants / Q000627:therapeutic use; D016009:Chi-Square Distribution; D015897:Comorbidity; D005260:Female; D006748:Hospital Departments; D017052:Hospital Mortality; D006801:Humans; D007388:Internal Medicine; D007557:Israel; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010343:Patient Admission; D010351:Patient Discharge; D011237:Predictive Value of Tests; D011446:Prospective Studies; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D018805:Sepsis / Q000175:diagnosis / Q000453:epidemiology* / Q000401:mortality / Q000628:therapy; D012720:Severity of Illness Index; D013997:Time Factors; D016896:Treatment Outcome; D054556:Venous Thromboembolism / Q000175:diagnosis* / Q000188:drug therapy / Q000453:epidemiology / Q000401:mortality; D055815:Young Adult
chemical_list: D000925:Anticoagulants