Dataset Information

Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT) Study.

ABSTRACT: Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated). We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating on parameters that have more direct policy implications, these potentially automated approaches allow methodological standardization across similar comparativeness effectiveness studies.

SUBMITTER: Moore SE

PROVIDER: S-EPMC4546674 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT) Study.

Moore Sara E SE Decker Anna A Hubbard Alan A Callcut Rachael A RA Fox Erin E EE Del Junco Deborah J DJ Holcomb John B JB Rahbar Mohammad H MH Wade Charles E CE Schreiber Martin A MA Alarcon Louis H LH Brasel Karen J KJ Bulger Eileen M EM Cotton Bryan A BA Muskat Peter P Myers John G JG Phelan Herb A HA Cohen Mitchell J MJ

PloS one 20150821 8

Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admissi ...[more]

PMID: 26296088

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Project description:ImportanceAlthough most massive transfusion protocols incorporate cryoprecipitate in the treatment of hemorrhaging injured patients, minimal data exist on its use in children, and whether its addition improves their survival is unclear.ObjectiveTo determine whether cryoprecipitate use for injured children who receive massive transfusion is associated with lower mortality.Design, setting, and participantsThis retrospective cohort study included injured patients examined between January 1, 2014, and December 31, 2017, at one of multiple centers across the US and Canada participating in the Pediatric Trauma Quality Improvement Program. Patients were aged 18 years or younger and had received massive transfusion, which was defined as at least 40 mL/kg of total blood products in the first 4 hours after emergency department arrival. Exclusion criteria included hospital transfer, arrival without signs of life, time of death or hospital discharge not recorded, and isolated head injuries. To adjust for potential confounding, a propensity score for treatment was created and inverse probability weighting was applied. The propensity score accounted for age, sex, race/ethnicity, injury type, payment type, Glasgow Coma Scale score, hypoxia, hypotension, assisted respirations, chest tube status, Injury Severity Score, total volume of blood products received, hemorrhage control procedure, hospital size, academic status, and trauma center designation. Data were analyzed from December 11, 2019, to August 31, 2020.ExposuresCryoprecipitate use within the first 4 hours of emergency department arrival.Main outcomes and measuresIn-hospital 24-hour and 7-day mortality.ResultsOf the 2387 injured patients who received massive transfusion, 1948 patients were eligible for analysis. The median age was 16 years (interquartile range, 9-17 years), 1382 patients (70.9%) were male, and 807 (41.4%) were White. A total of 541 patients (27.8%) received cryoprecipitate. After propensity score weighting, patients who received cryoprecipitate had a significantly lower 24-hour mortality when compared with those who did not (adjusted difference, -6.9%; 95% CI, -10.6% to -3.2%). Moreover, cryoprecipitate use was associated with a significantly lower 7-day mortality but only in children with penetrating trauma (adjusted difference, -9.2%; 95% CI, -15.4% to -3.0%) and those transfused at least 100 mL/kg of total blood products (adjusted difference, -7.7%; 95% CI, -15.0% to -0.5%).Conclusions and relevanceIn this cohort study, early use of cryoprecipitate was associated with lower 24-hour mortality among injured children who required massive transfusion. The benefit of cryoprecipitate appeared to persist for 7 days only in those with penetrating trauma and in those who received extremely large-volume transfusion.

Project description:BackgroundHaemorrhage is a common cause of death in trauma patients. Although transfusions are extensively used in the care of bleeding trauma patients, there is uncertainty about the balance of risks and benefits and how this balance depends on the baseline risk of death. Our objective was to evaluate the association of red blood cell (RBC) transfusion with mortality according to the predicted risk of death.Methods and findingsA secondary analysis of the CRASH-2 trial (which originally evaluated the effect of tranexamic acid on mortality in trauma patients) was conducted. The trial included 20,127 trauma patients with significant bleeding from 274 hospitals in 40 countries. We evaluated the association of RBC transfusion with mortality in four strata of predicted risk of death: <6%, 6%-20%, 21%-50%, and >50%. For this analysis the exposure considered was RBC transfusion, and the main outcome was death from all causes at 28 days. A total of 10,227 patients (50.8%) received at least one transfusion. We found strong evidence that the association of transfusion with all-cause mortality varied according to the predicted risk of death (p-value for interaction <0.0001). Transfusion was associated with an increase in all-cause mortality among patients with <6% and 6%-20% predicted risk of death (odds ratio [OR] 5.40, 95% CI 4.08-7.13, p<0.0001, and OR 2.31, 95% CI 1.96-2.73, p<0.0001, respectively), but with a decrease in all-cause mortality in patients with >50% predicted risk of death (OR 0.59, 95% CI 0.47-0.74, p<0.0001). Transfusion was associated with an increase in fatal and non-fatal vascular events (OR 2.58, 95% CI 2.05-3.24, p<0.0001). The risk associated with RBC transfusion was significantly increased for all the predicted risk of death categories, but the relative increase was higher for those with the lowest (<6%) predicted risk of death (p-value for interaction <0.0001). As this was an observational study, the results could have been affected by different types of confounding. In addition, we could not consider haemoglobin in our analysis. In sensitivity analyses, excluding patients who died early; conducting propensity score analysis adjusting by use of platelets, fresh frozen plasma, and cryoprecipitate; and adjusting for country produced results that were similar.ConclusionsThe association of transfusion with all-cause mortality appears to vary according to the predicted risk of death. Transfusion may reduce mortality in patients at high risk of death but increase mortality in those at low risk. The effect of transfusion in low-risk patients should be further tested in a randomised trial.Trial registrationwww.ClinicalTrials.gov NCT01746953.

Project description:ObjectivesTo estimate the evolution of compressible absenteeism in a hospital center and identify the professional and sociodemographic factors that influence absenteeism.MethodAll hospital center employees have been included over a period of twelve consecutive years (2007 to 2019). Compressible absences and occupational and sociodemographic factors were analyzed using Occupational Health data. Since the distribution of the data did not follow a normal distribution, the number of days of absence was presented as a median (interquartile range (IQR): 1st quartile-3rd quartile), and comparisons were made using non-parametric tests followed by a negative binomial model with zero inflation (ZINB).ResultsA total of 16,413 employees were included, for a total of 2,828,599 days of absence, of which 2,081,553 were compressible absences (73.6% of total absences). Overall, 42% of employees have at least one absence per year. Absent employees had a median of 15 (IQR 5-53) days of absence per year, with an increase of a factor of 1.9 (CI95 1.8-2.1) between 2007 and 2019 (p < 0.001). Paramedical staff were most at risk of absence (p < 0.001 vs. all other occupational categories). Between 2007 and 2019, the number of days of absence was multiplied by 2.4 (CI95 1.8-3.1) for administrative staff, 2.1 (CI95 1.9-2.3) for tenured, 1.7 (CI95 1.5-2.0) for those living more than 12 km from the workplace, 1.8 (CI95 1.6-2.0) among women, 2.1 (CI95 1.8-2.6) among those over 50 years of age, 2.4 (CI95 1.8-3.0) among "separated" workers, and 2.0 (CI95 1.8-2.2) among those with at least one child.ConclusionsParamedical personnel are most at risk of absenteeism. Meanwhile, absenteeism is increasing steadily, and overall, the increase is major for administrative staff. The profile of an employee at risk of absenteeism is a titular employee, living at distance from work, probably female, over 50 years old, separated, and with children. Identifying professionals at risk of absenteeism is essential to propose adapted and personalized preventive measures.

Dataset Information

Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT) Study.

Publications

Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT) Study.

Similar Datasets

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