BackgroundRisks of predicting time-related in-hospital mortality varies in pelvic trauma patients. We aim to identify potential independent risks predictive of time-related (early versus late) mortality among pelvic trauma patients.MethodsLocal trauma registry data from 2004 through 2013 were reviewed. Mortality causes and timing of death were investigated. Multivariate logistic regression identified independent risks predictive of early versus late mortality in pelvic trauma patients while adjusting for patient demographics (age, sex, race), clinical variables (initial vital signs, mental status, injury severity, associated injuries, comorbidities), and hospital outcomes (surgical interventions, crystalloid resuscitations, blood transfusions).ResultsWe retrospectively collected data on 1566 pelvic trauma patients with a mortality rate of 9.96 % (156/1566). Approximately 74 % of patients died from massive hemorrhage within the first 24 h of hospitalization (early mortality). Revised trauma score (RTS), injury severity score (ISS), initial hemoglobin, direct transfer to operating room, and blood transfusion administration in the Emergency Department were considered independent risk factors predictive of early mortality. Age, ISS, and Glasgow Coma Scale (GCS) were deemed risk factors predictive of death after 24 h (late mortality).DiscussionGiven the fact of a substantial number of patients died within the first 24 h of hospital arrival, it is reasonable to consider the first 24 h of hospitalization as the appropriate window within which early mortality may be expected to occur in pelvic trauma patients. The risk factors associated with massive hemorrhage were strong predictors of early mortality, whereas late mortality predictors were more closely linked with comorbidities or in-hospital complications.ConclusionsWhile risk factors predictive of early versus late mortality vary, ISS seems to predict both early and late mortality accurately in pelvic trauma patients.

BackgroundThromboelastography (TEG) has been utilized for the guidance of blood component therapy (BCT). We aimed to investigate the association between emergent TEG-guided BCT and clinical outcomes in patients with traumatic abdominal solid organ (liver and/or spleen) injuries.MethodsA single center retrospective study of patients who sustained traumatic liver and/or spleen injuries receiving emergent BCT was conducted. TEG was ordered in all these patients. Patient demographics, general injury information, outcomes, BCT, and TEG parameters were analyzed and compared in patients receiving TEG-guided BCT versus those without.ResultsA total of 166 patients were enrolled, of whom 52% (86/166) received TEG-guided BCT. A mortality of 12% was noted among patients with TEG-guided BCT when compared with 19% of mortality in patients with non-TEG-guided BCT (P > 0.05). An average of 4 units of packed red blood cell (PRBC) was received in patients with TEG-guided BCT when compared to an average of 9 units of PRBC received in non-TEG-guided BCT patients (P < 0.01). A longer hospital length of stay (LOS, 19 ± 16 days) was found among non-TEG-guided BCT patients when compared to the TEG-guided BCT group (14 ± 12 days, P < 0.05). TEG-guided BCT showed as an independent factor associated with hospital LOS after other variables were adjusted (coefficiency: 5.44, 95% confidence interval: 0.69 - 10.18).ConclusionsTraumatic abdominal solid organ injury patients receiving blood transfusions might benefit from TEG-guided BCT as indicated by less blood products needed and less hospitalization stay among the cohort.

BackgroundRisks prediction models of 30-day all-cause hospital readmissions are multi-factorial. Severity of illness (SOI) and risk of mortality (ROM) categorized by All Patient Refined Diagnosis Related Groups (APR-DRG) seem to predict hospital readmission but lack large sample validation. Effects of risk reduction interventions including providing post-discharge outpatient visits remain uncertain. We aim to determine the accuracy of using SOI and ROM to predict readmission and further investigate the role of outpatient visits in association with hospital readmission.MethodsHospital readmission data were reviewed retrospectively from September 2012 through June 2015. Patient demographics and clinical variables including insurance type, homeless status, substance abuse, psychiatric problems, length of stay, SOI, ROM, ICD-10 diagnoses and medications prescribed at discharge, and prescription ratio at discharge (number of medications prescribed divided by number of ICD-10 diagnoses) were analyzed using logistic regression. Relationships among SOI, type of hospital visits, time between hospital visits, and readmissions were also investigated.ResultsA total of 6011 readmissions occurred from 55,532 index admissions. The adjusted odds ratios of SOI and ROM predicting readmissions were 1.31 (SOI: 95 % CI 1.25–1.38) and 1.09 (ROM: 95 % CI 1.05–1.14) separately. Ninety percent (5381/6011) of patients were readmitted from the Emergency Department (ED) or Urgent Care Center (UCC). Average time interval from index discharge date to ED/UCC visit was 9 days in both the no readmission and readmission groups (p > 0.05). Similar hospital readmission rates were noted during the first 10 days from index discharge regardless of whether post-index discharge patient clinic visits occurred when time-to-event analysis was performed.ConclusionsSOI and ROM significantly predict hospital readmission risk in general. Most readmissions occurred among patients presenting for ED/UCC visits after index discharge. Simply providing early post-discharge follow-up clinic visits does not seem to prevent hospital readmissions.