“July Effect”: An Evaluation of a Level I Teaching Hospital's Trauma Service Seasonal Mortality Rates

Background Leukocytosis is a rise in white blood cell (WBC) count and clinical outcomes of moderate to severe leukocytosis in trauma patients have not been described. We hypothesized that trauma patients with severe leukocytosis (SL; ≥40.0 × 109 leukocytes/L) have higher rates of in-hospital complications and mortality than those with moderate leukocytosis (ML; 25.0–39 × 109 leukocytes/L). Methods We performed a retrospective analysis (2010-2017) on trauma patients developing ML or SL at a single Level-I trauma center. A multivariable logistic regression analysis for risk factors were performed. Results From 15,807 trauma admissions, 332 (2.1%) had ML or SL. Of these, 308 (92.8%) were ML and 24 (7.2%) were SL. Patients with ML and SL reached their peak WBC count in 1 and 10 days after admission respectively (p < 0.001). SL patients suffered higher rates of in-hospital complications (p < 0.05) and mortality compared to those without ML or SL (14.5% vs. 3.3%, p < 0.001). Between ML and SL, mortality rates rose with leukocytosis severity (13.3% vs. 29.2%, p = 0.03). Among all patients with ML or SL, vasopressor use was the strongest independent risk factor for mortality (OR 12.61, p < 0.001). Conclusion Clinicians should be weary of the increased mortality rates and in-hospital complications in SL patients. Among patients with ML or SL, vasopressor use, rather than SL, was the strongest predictor of mortality. Patients with ML had a quicker time course to peak leukocytosis compared to SL, suggesting these two entities to be distinct in etiology and outcome, warranting future research.

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Withdrawal of Care in a Trauma Intensive Care Unit: The Impact on Mortality Rate

The American Surgeon ◽

10.1177/000313481408000824 ◽

2014 ◽

Vol 80 (8) ◽

pp. 764-767 ◽

Cited By ~ 2

Author(s):

Leonard J. Weireter ◽

Jay N. Collins ◽

Rebecca C. Britt ◽

T. J. Novosel ◽

L. D. Britt

Keyword(s):

Intensive Care Unit ◽

Decision Making ◽

Mortality Rate ◽

Trauma Center ◽

Mortality Rates ◽

Active Aging ◽

Neurologic Injury ◽

Trauma Service ◽

The Impact ◽

Overall Mortality

Withdrawal of care has increased in recent years as the population older than 65 years of age has increased. We sought to investigate the impact of this decision on our mortality rate. We retrospectively reviewed a prospectively collected database to determine the percentage of cases in which care was actively withdrawn. Neurologic injury as the cause for withdrawal, age of the patient, number of days to death, number of cases thought to be treatment failures, and the reason for failure were analyzed. Between January 2008 and December 2012, there were 536 trauma service deaths; 158 (29.5%) had care withdrawn. These patients were 67 (6 18.5) years old and neurologic injury was responsible in 63 per cent (6 5.29%). Fifty-two per cent of the patients died by Day 3; 65 per cent by Day 5; and 74 per cent Day 7. A total of 22.7 per cent (6 7.9%) could be considered a treatment failure. Accounting for cases in which care was withdrawn for futility would decrease the overall mortality rate by approximately 23 per cent. Trauma center mortality calculation does not account for care withdrawn. Treating an active, aging population, with advance directives, requires methodologies that account for such decision-making when determining mortality rates.

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Influence of a Stay-At-Home Order on Trauma Volume and Injury Patterns at a Level I Trauma Center in Ohio

The American Surgeon ◽

10.1177/00031348211047488 ◽

2021 ◽

pp. 000313482110474

Author(s):

Gregory S. Huang ◽

Elisha A. Chance ◽

C. Michael Dunham

Keyword(s):

Trauma Center ◽

Drug Testing ◽

Injury Severity ◽

Census Data ◽

Retrospective Chart Review ◽

Trauma Patients ◽

Injury Patterns ◽

Trauma Service ◽

Level I ◽

At Home

Background Changes in injury patterns during the COVID pandemic have been reported in other states. The objective was to explore changes to trauma service volume and admission characteristics at a trauma center in northeast Ohio during a stay-at-home order (SAHO) and compare the 2020 data to historic trauma census data. Methods Retrospective chart review of adult trauma patients admitted to a level I trauma center in northeast Ohio. Trauma admissions from January 21 to July 21, 2020 (COVID period) were compared to date-matched cohorts of trauma admissions from 2018 to 2019 (historic period). The COVID period was further categorized as pre-SAHO, active-SAHO, and post-SAHO. Results The SAHO was associated with a reduction in trauma center admissions that increased after the SAHO ( P = .0033). Only outdoor recreational vehicle (ORV) injuries ( P = .0221) and self-inflicted hanging ( P = .0028) mechanisms were increased during the COVID period and had substantial effect sizes. Glasgow Coma Scores were lower during the COVID period ( P = .0286) with a negligible effect size. Violence-related injuries, injury severity, mortality, and admission characteristics including alcohol and drug testing and positivity were similar in the COVID and historic periods. Discussion The SAHO resulted in a temporary decrease in trauma center admissions. Although ORV and hanging mechanisms were increased, other mechanisms such as alcohol and toxicology proportions, injury severity, length of stay, and mortality were unchanged.

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333 Undertriage in Trauma: Differences in Outcome Among Trauma Patients With Delayed Trauma Service Activation at a Level I Trauma Center

Annals of Emergency Medicine ◽

10.1016/j.annemergmed.2011.06.364 ◽

2011 ◽

Vol 58 (4) ◽

pp. S289-S290

Author(s):

C. Rogen ◽

T. Shiuh ◽

P. Veneri ◽

B. Campbell ◽

C.J. Hoon ◽

...

Keyword(s):

Trauma Center ◽

Trauma Patients ◽

Trauma Service ◽

Level I

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Models of care for traumatically injured patients at trauma centres in British Columbia: variability and sustainability

CJEM ◽

10.1017/cem.2017.50 ◽

2017 ◽

Vol 20 (2) ◽

pp. 200-206 ◽

Cited By ~ 1

Author(s):

Benjamin Tuyp ◽

Kasra Hassani ◽

Lisa Constable ◽

Joseph Haegert

Keyword(s):

Trauma Care ◽

Trauma System ◽

Models Of Care ◽

Short Stay ◽

Trauma Centres ◽

Trauma Unit ◽

Trauma Service ◽

Level Ii ◽

Level I ◽

Injured Patients

AbstractBackgroundSuccessful trauma systems employ a network of variably-resourced hospitals, staffed by experienced providers, to deliver optimal care for injured patients. The “model of care”—the manner by which inpatients are admitted and overseen, is an important determinant of patient outcomes.ObjectivesTo describe the models of inpatient trauma care at British Columbia’s (BC’s) ten adult trauma centres, their sustainability, and their compatibility with accreditation guidelines.MethodsQuestionnaires were distributed to the trauma medical directors at BC’s ten Level I-III adult trauma centres. Follow-up semi-structured interviews clarified responses.ResultsThree different models of inpatient trauma care exist within BC. The “admitting trauma service” was a multidisciplinary team providing exclusive care for injured patients. The “on-call consultant” assisted with Emergency Department (ED) resuscitation before transferring patients to a non-trauma admitting service. The single “short-stay trauma unit” employed on-call consultants who also oversaw a 48-hour short-stay ward.Both level I trauma centres utilized the admitting trauma service model (2/2). All Level II sites employed an on-call consultant model (3/3), deviating from Level II trauma centre accreditation standards. Level III sites employed all three models in similar proportions. None of the on-call consultant sites believed their current care model was sustainable. Inadequate compensation, insufficient resources, and difficulty recruiting physicians were cited barriers to sustainability and accreditation compliance.ConclusionsThree distinct models of care are distributed inconsistently across BC’s Level I-III trauma hospitals. Greater use of admitting trauma service and short-stay trauma unit models may improve the sustainability and accreditation compliance of our trauma system.

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A Twelve-Year Analysis Of Disease and Provider Complications on an Organized Level I Trauma Service: As Good As it Gets?

Journal of Trauma and Acute Care Surgery ◽

10.1097/00005373-200301000-00004 ◽

2003 ◽

Vol 54 (1) ◽

pp. 26-37 ◽

Cited By ~ 60

Author(s):

David B. Hoyt ◽

Raul Coimbra ◽

Bruce Potenza ◽

Jay Doucet ◽

Dale Fortlage ◽

...

Keyword(s):

Trauma Service ◽

Level I

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Motorcycle-related trauma: effects of age and site of injuries on mortality. A single-center, retrospective study.

10.21203/rs.2.22131/v1 ◽

2020 ◽

Author(s):

Stefano Granieri ◽

Elisa Reitano ◽

Francesca Bindi ◽

Federica Renzi ◽

Fabrizio Sammartano ◽

...

Keyword(s):

Trauma Center ◽

Injury Severity ◽

Age Groups ◽

Mortality Rates ◽

Rank Test ◽

Younger Patients ◽

Risk Of Death ◽

Increased Risk ◽

Level I ◽

The Impact

Abstract BackgroundMotorcyclists are often victims of road traffic incidents. Though elderly patients seem to have worse survival outcomes and sustain more severe injuries than younger patients, concordance in the literature for this does not exist. The aim of the study is to evaluate the impact of age and injury severity on the mortality of patients undergoing motorcycle trauma. MethodsData of 1725 patients consecutively admitted to our Trauma Center were selected from 2002 to 2016 and retrospectively analyzed. The sample was divided into three age groups: ≤ 17 years, 18-54 years and ≥ 55 years. Mortality rates were analyzed for the overall population and patients with Injury Severity Score (ISS) ≥ 25. Differences in survival among age groups were evaluated with Log-Rank test and multivariate logistic regression models were created to identify independent predictors of mortality.ResultsA lower survival rate was detected in patients older than 55 years (83,6% vs 94,7%; p = 0.049) and in those sustaining critical injuries (ISS ≥ 25, 61% vs 83% p = 0.021). Age (p =0,027; OR: 1,03), ISS (p <0,001; OR: 1,09), Revised Trauma Score (RTS) (p <0,001; OR: 0,47) resulted independent predictors of death. Multivariate analysis identified head (p <0,001; OR: 2,04), chest (p <0,001; OR: 1,54), abdominal (p <0,001; OR: 1,37) and pelvic (p =0,014; OR: 1,26) injuries as independent risk factors related to mortality as well. Compared to the theoretical probability of survival, patients of all age groups showed a survival advantage when managed at a level I Trauma Center.ConclusionsWe detected anatomical injury distributions and mortality rates among three age groups. Patients aging more than 55 years had an increased risk of death, with a prevalence of severe chest injuries, while younger patients sustained more severe head trauma. Age represented an independent predictor of death. Management of these patients at a Level I Trauma Center may lead to improved outcomes.

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Effects of a More Restrictive Transfusion Trigger in Trauma Patients

The American Surgeon ◽

10.1177/000313481908500433 ◽

2019 ◽

Vol 85 (4) ◽

pp. 409-413 ◽

Cited By ~ 1

Author(s):

Mary Garland-Kledzik ◽

Michaela Gaffley ◽

David Crouse ◽

Collin Conrad ◽

Preston Miller ◽

...

Keyword(s):

Length Of Hospital Stay ◽

Retrospective Chart Review ◽

Trauma Patients ◽

Transfusion Trigger ◽

Transfusion Threshold ◽

Trauma Service ◽

Transfusion Requirements ◽

Organ System Failure ◽

Urban Level ◽

Level I

Since the Transfusion Requirements in Critical Care trial, studies have shown that acutely ill patients can drift as a low as 5 g/dL. This study reviews a transfusion trigger change to 6.5 g/dL, which we hypothesize will conserve resources and improve quality of care. This is a retrospective chart review at an urban Level I trauma center from January through December 2015 after our trauma service changed the transfusion trigger from 7 to 6.5 g/dL. Outcomes in patients before (TT7) and after (TT6.5) the change in transfusion threshold were then compared. One hundred thirty-one discrete patients were included in this trial, with 285 instances of a hemoglobin of 7 g/dL or less and 178 transfusions. Seventy-two patients were before the change in threshold and 59 after. There was no change in length of hospital stay, ICU stay, ventilator days, mortality, and organ system failure after change in the transfusion threshold. After initiation of a more conservative threshold, 72 units of blood were saved. Decreased transfusion threshold was associated with no worse outcomes associated with decreased resource utilization.

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35. Emergency Medical Services Use of Trauma Triage Criteria to Stratify Patients by Injury Severity and Need for Emergent Intervention

Prehospital and Disaster Medicine ◽

10.1017/s1049023x00045702 ◽

1996 ◽

Vol 11 (S2) ◽

pp. S32-S32

Author(s):

Robert E. O'Connor ◽

Glen H. Tinkoff ◽

Susan Mascioli ◽

Ross E. Megargel

Keyword(s):

Injury Severity ◽

Vital Signs ◽

Penetrating Trauma ◽

Trauma Patients ◽

Chi Square ◽

Probability Of Survival ◽

Trauma Service ◽

Severity Scores ◽

Serious Injury ◽

Level I

Purpose: Prehospital triage criteria (PTC) have been used to classify patients according to risk of serious injury. This study was conducted determine whether PTC could be used to identify serious injury, the need for intensive care (ICU), or immediate operative intervention (IOI).Methods: Data for this observational study were gathered prospectively, at a level-I trauma center, from a patient cohort admitted to the trauma service from 01 February to 31 July 1995. Specific triage criteria, based on information given by EMS prior to arrival were used to categorize patients by severity. Patients classified as most serious (codes) had the following: shock, major anatomic injury or proximal penetrating trauma. Patients classified as more serious (alerts) had one of the following: abnormal vital signs, Glasgow Coma Scale <13, moderate anatomic injury, high-risk mechanism of injury, or co-morbid factors. Patients not meeting either set of criteria, but were admitted, served as controls (consults). Injury severity scores (ISS) and probability of survival (Probsurvival) were calculated for each patient. The percentage admitted to the ICU, operating room (OR), or requiring IOI, were tabulated. Statistical analysis was performed using ANOVA, Mest and chi-square.

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