Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 9 de 9
Filter
Add more filters










Database
Language
Publication year range
1.
Int J Med Inform ; 186: 105437, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38552267

ABSTRACT

INTRODUCTION: Health care patient records have been digitalised the past twenty years, and registries have been automated. Missing registrations are common, and can result in selection bias. OBJECTIVE: To assess the prevalence and characteristics of missed registrations in a Dutch regional trauma registry. METHODS: An automatically generated trauma registry export was done for ten out of eleven hospitals in trauma region Southwest Netherlands, between June 1 and August 31, 2020. Second, lists were checked for being falsely flagged as 'non-trauma'. Finally, a list was generated with trauma tick box flagged as 'trauma' but were not automatically in the export due to administrative errors. Automated and missed registration datasets were compared on patient characteristics and logistic regression models were run with random intercepts and missed registration as outcome variable on the complete dataset. RESULTS: A total of 2,230 automated registrations and 175 (7.3 %) missed registrations were included for the Dutch National Trauma Registry, ranging from 1 to 14 % between participating hospitals. Patients of the missed registration dataset had characteristics of a higher level of care, compared with patients of automated registrations. Level of trauma care (level II OR 0.464 95 % CI 0.328-0.666, p < 0.001; level III OR 0.179 95 % CI 0.092-0.325, p < 0.001), major trauma (OR 2.928 95 % CI 1.792-4.65, p < 0.001), ICU admission (OR 2.337 95 % CI 1.792-4.650, p < 0.001), and surgery (OR 1.871 95 % CI 1.371-2.570, p < 0.001) were potential predictors for missed registrations in multivariate logistic regression analysis. CONCLUSION: Missed registrations occur frequently and the rate of missed registrations differs greatly between hospitals. Automated and missed registration datasets display differences related to patients requiring more intensive care, which held for the major trauma subset. Checking for missed registrations is time consuming, automated registration lists need a human touch for validation and to be complete.


Subject(s)
Hospitals , Humans , Netherlands/epidemiology , Prevalence , Registries , Logistic Models
2.
Article in English | MEDLINE | ID: mdl-38226991

ABSTRACT

PURPOSE: With an increasingly older population and rise in incidence of traumatic brain injury (TBI), end-of-life decisions have become frequent. This study investigated the rate of withdrawal of life sustaining treatment (WLST) and compared treatment outcomes in patients with isolated TBI in two Dutch level-I trauma centers. METHODS: From 2011 to 2016, a retrospective cohort study of patients aged ≥ 18 years with isolated moderate-to-severe TBI (Abbreviated Injury Scale (AIS) head ≥ 3) was conducted at the University Medical Center Rotterdam (UMC-R) and the University Medical Center Utrecht (UMC-U). Demographics, radiologic injury characteristics, clinical outcomes, and functional outcomes at 3-6 months post-discharge were collected. RESULTS: The study population included 596 patients (UMC-R: n = 326; UMC-U: n = 270). There were no statistical differences in age, gender, mechanism of injury, and radiologic parameters between both institutes. UMC-R patients had a higher AIShead (UMC-R: 5 [4-5] vs. UMC-U: 4 [4-5], p < 0.001). There was no difference in the prehospital Glasgow Coma Scale (GCS). However, UMC-R patients had lower GCSs in the Emergency Department and used more prehospital sedation. Total in-hospital mortality was 29% (n = 170), of which 71% (n = 123) occurred after WLST. Two percent (n = 10) remained in unresponsive wakefulness syndrome (UWS) state during follow-up. DISCUSSION: This study demonstrated a high WLST rate among deceased patients with isolated TBI. Demographics and outcomes were similar for both centers even though AIShead was significantly higher in UMC-R patients. Possibly, prehospital sedation might have influenced AIS coding. Few patients persisted in UWS. Further research is needed on WLST patients in a broader spectrum of ethics, culture, and complex medical profiles, as it is a growing practice in modern critical care. LEVEL OF EVIDENCE: Level III, retrospective cohort study.

3.
J Trauma Acute Care Surg ; 94(6): 877-892, 2023 06 01.
Article in English | MEDLINE | ID: mdl-36726194

ABSTRACT

BACKGROUND: Trauma networks have multiple designated levels of trauma care. This classification parallels concentration of major trauma care, creating innovations and improving outcome measures. OBJECTIVES: The objective of this study is to assess associations of level of trauma care with patient outcomes for populations with specific severe injuries. METHODS: A systematic literature search was conducted using six electronic databases up to April 19, 2022 (PROSPERO CRD42022327576). Studies comparing fatal, nonfatal clinical, or functional outcomes across different levels of trauma care for trauma populations with specific severe injuries or injured body region (Abbreviated Injury Scale score ≥3) were included. Two independent reviewers included studies, extracted data, and assessed quality. Unadjusted and adjusted pooled effect sizes were calculated with random-effects meta-analysis comparing Level I and Level II trauma centers. RESULTS: Thirty-five studies (1,100,888 patients) were included, of which 25 studies (n = 443,095) used for meta-analysis, suggesting a survival benefit for the severely injured admitted to a Level I trauma center compared with a Level II trauma center (adjusted odds ratio [OR], 1.15; 95% confidence interval [CI], 1.06-1.25). Adjusted subgroup analysis on in-hospital mortality was done for patients with traumatic brain injuries (OR, 1.23; 95% CI, 1.01-1.50) and hemodynamically unstable patients (OR, 1.09; 95% CI, 0.98-1.22). Hospital and intensive care unit length of stay resulted in an unadjusted mean difference of -1.63 (95% CI, -2.89 to -0.36) and -0.21 (95% CI, -1.04 to 0.61), respectively, discharged home resulted in an unadjusted OR of 0.92 (95% CI, 0.78-1.09). CONCLUSION: Severely injured patients admitted to a Level I trauma center have a survival benefit. Nonfatal outcomes were indicative for a longer stay, more intensive care, and more frequently posthospital recovery trajectories after being admitted to top levels of trauma care. Trauma networks with designated levels of trauma care are beneficial to the multidisciplinary character of trauma care. LEVEL OF EVIDENCE: Systematic review and meta-analysis; Level III.


Subject(s)
Trauma Centers , Wounds and Injuries , Humans , Emergency Medical Services , Hospitalization , Intensive Care Units , Length of Stay , Outcome Assessment, Health Care , Wounds and Injuries/therapy
4.
Eur J Trauma Emerg Surg ; 48(4): 2999-3009, 2022 Aug.
Article in English | MEDLINE | ID: mdl-35137249

ABSTRACT

PURPOSE: The SARS-CoV-2 pandemic severely disrupted society and the health care system. In addition to epidemiological changes, little is known about the pandemic's effects on the trauma care chain. Therefore, in addition to epidemiology and aetiology, this study aims to describe the impact of the SARS-CoV-2 pandemic on prehospital times, resource use and outcome. METHODS: A multicentre observational cohort study based on the Dutch Nationwide Trauma Registry was performed. Characteristics, resource usage, and outcomes of trauma patients treated at all trauma-receiving hospitals during the first (W1, March 12 through May 11) and second waves (W2, May 12 through September 23), as well as the interbellum period in between (INT, September 23 through December 31), were compared with those treated from the same periods in 2018 and 2019. RESULTS: The trauma caseload was reduced by 20% during the W1 period and 11% during the W2 period. The median length of stay was significantly shortened for hip fracture and major trauma patients (ISS ≥ 16). A 33% and 66% increase in the prevalence of minor self-harm-related injuries was recorded during the W1 and W2 periods, respectively, and a 36% increase in violence-related injuries was recorded during the INT. Mortality was significantly higher in the W1 (2.9% vs. 2.2%) and W2 (3.2% vs. 2.7%) periods. CONCLUSION: The imposed restrictions in response to the SARS-CoV-2 pandemic led to diminished numbers of acute trauma admissions in the Netherlands. The long-lasting pressing demand for resources, including ICU services, has negatively affected trauma care. Further caution is warranted regarding the increased incidence of injuries related to violence and self-harm.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Hospitalization , Humans , Retrospective Studies , SARS-CoV-2 , Trauma Centers
5.
Eur J Trauma Emerg Surg ; 48(3): 2459-2467, 2022 Jun.
Article in English | MEDLINE | ID: mdl-34586442

ABSTRACT

PURPOSE: The importance and impact of determining which trauma patients need to be transferred between hospitals, especially considering prehospital triage systems, is evident. The objective of this study was to investigate the association between mortality and primary admission and secondary transfer of patients to level I and II trauma centers, and to identify predictors of primary and secondary admission to a designated level I trauma center. METHODS: Data from the Dutch Trauma Registry South West (DTR SW) was obtained. Patients ≥ 18 years who were admitted to a level I or level II trauma center were included. Patients with isolated burn injuries were excluded. In-hospital mortality was compared between patients that were primarily admitted to a level I trauma center, patients that were transferred to a level I trauma center, and patients that were primarily admitted to level II trauma centers. Logistic regression models were used to adjust for potential confounders. A subgroup analysis was done including major trauma (MT) patients (ISS > 15). Predictors determining whether patients were primarily admitted to level I or level II trauma centers or transferred to a level I trauma center were identified using logistic regression models. RESULTS: A total of 17,035 patients were included. Patients admitted primarily to a level I center, did not differ significantly in mortality from patients admitted primarily to level II trauma centers (Odds Ratio (OR): 0.73; 95% confidence interval (CI) 0.51-1.06) and patients transferred to level I centers (OR: 0.99; 95%CI 0.57-1.71). Subgroup analyses confirmed these findings for MT patients. Adjusted logistic regression analyses showed that age (OR: 0.96; 95%CI 0.94-0.97), GCS (OR: 0.81; 95%CI 0.77-0.86), AIS head (OR: 2.30; 95%CI 2.07-2.55), AIS neck (OR: 1.74; 95%CI 1.27-2.45) and AIS spine (OR: 3.22; 95%CI 2.87-3.61) are associated with increased odds of transfers to a level I trauma center. CONCLUSIONS: This retrospective study showed no differences in in-hospital mortality between general trauma patients admitted primarily and secondarily to level I trauma centers. The most prominent predictors regarding transfer of trauma patients were age and neurotrauma. These findings could have practical implications regarding the triage protocols currently used.


Subject(s)
Trauma Centers , Wounds and Injuries , Hospital Mortality , Humans , Injury Severity Score , Patient Transfer , Retrospective Studies , Triage , Wounds and Injuries/therapy
6.
Eur J Trauma Emerg Surg ; 48(3): 2421-2431, 2022 Jun.
Article in English | MEDLINE | ID: mdl-34514511

ABSTRACT

INTRODUCTION: Major trauma often results in long-term disabilities. The aim of this study was to assess health-related quality of life, cognition, and return to work 1 year after major trauma from a trauma network perspective. METHODS: All major trauma patients in 2016 (Injury Severity Score > 15, n = 536) were selected from trauma region Southwest Netherlands. Eligible patients (n = 365) were sent questionnaires with the EQ-5D-5L and questions on cognition, level of education, comorbidities, and resumption of paid work 1 year after trauma. RESULTS: A 50% (n = 182) response rate was obtained. EQ-US and EQ-VAS scored a median (IQR) of 0.81 (0.62-0.89) and 70 (60-80), respectively. Limitations were prevalent in all health dimensions of the EQ-5D-5L; 90 (50%) responders reported problems with mobility, 36 (20%) responders reported problems with self-care, 108 (61%) responders reported problems during daily activities, 129 (73%) responders reported pain or discomfort, 70 (39%) responders reported problems with anxiety or depression, and 102 (61%) of the patients reported problems with cognition. Return to work rate was 68% (37% full, 31% partial). A median (IQR) EQ-US of 0.89 (0.82-1.00) and EQ-VAS of 80 (70-90) were scored for fully working responders; 0.77 (0.66-0.85, p < 0.001) and 70 (62-80, p = 0.001) for partial working respondents; and 0.49 (0.23-0.69, p < 0.001) and 55 (40-72, p < 0.001) for unemployed respondents. CONCLUSION: The majority experience problems in all health domains of the EQ-5D-5L and cognition. Return to work status was associated with all health domains of the EQ-5D-5L and cognition.


Subject(s)
Quality of Life , Return to Work , Anxiety , Health Status , Humans , Pain , Surveys and Questionnaires
7.
Scand J Trauma Resusc Emerg Med ; 29(1): 71, 2021 May 27.
Article in English | MEDLINE | ID: mdl-34044857

ABSTRACT

BACKGROUND: A threshold Injury Severity Score (ISS) ≥ 16 is common in classifying major trauma (MT), although the Abbreviated Injury Scale (AIS) has been extensively revised over time. The aim of this study was to determine effects of different AIS revisions (1998, 2008 and 2015) on clinical outcome measures. METHODS: A retrospective observational cohort study including all primary admitted trauma patients was performed (in 2013-2014 AIS98 was used, in 2015-2016 AIS08, AIS08 mapped to AIS15). Different ISS thresholds for MT and their corresponding observed mortality and intensive care (ICU) admission rates were compared between AIS98, AIS08, and AIS15 with Chi-square tests and logistic regression models. RESULTS: Thirty-nine thousand three hundred seventeen patients were included. Thresholds ISS08 ≥ 11 and ISS15 ≥ 12 were similar to a threshold ISS98 ≥ 16 for in-hospital mortality (12.9, 12.9, 13.1% respectively) and ICU admission (46.7, 46.2, 46.8% respectively). AIS98 and AIS08 differed significantly for in-hospital mortality in ISS 4-8 (χ2 = 9.926, p = 0.007), ISS 9-11 (χ2 = 13.541, p = 0.001), ISS 25-40 (χ2 = 13.905, p = 0.001) and ISS 41-75 (χ2 = 7.217, p = 0.027). Mortality risks did not differ significantly between AIS08 and AIS15. CONCLUSION: ISS08 ≥ 11 and ISS15 ≥ 12 perform similarly to a threshold ISS98 ≥ 16 for in-hospital mortality and ICU admission. This confirms studies evaluating mapped datasets, and is the first to present an evaluation of implementation of AIS15 on registry datasets. Defining MT using appropriate ISS thresholds is important for quality indicators, comparing datasets and adjusting for injury severity. LEVEL OF EVIDENCE: Prognostic and epidemiological, level III.


Subject(s)
Abbreviated Injury Scale , Wounds and Injuries/epidemiology , Adult , Aged , Aged, 80 and over , Cohort Studies , Female , Hospital Mortality , Hospitalization/statistics & numerical data , Humans , Injury Severity Score , Logistic Models , Male , Middle Aged , Outcome and Process Assessment, Health Care , Registries , Retrospective Studies , Trauma Centers , Wounds and Injuries/diagnosis , Wounds and Injuries/mortality
8.
J Clin Med ; 10(8)2021 Apr 15.
Article in English | MEDLINE | ID: mdl-33920899

ABSTRACT

Centralization of trauma centers leads to a higher hospital volume of severely injured patients (Injury Severity Score (ISS) > 15), but the effect of volume on outcome remains unclear. The aim of this study was to determine the association between hospital volume of severely injured patients and in-hospital mortality in Dutch Level-1 trauma centers. A retrospective observational cohort study was performed using the Dutch trauma registry. All severely injured adults (ISS > 15) admitted to a Level-1 trauma center between 2015 and 2018 were included. The effect of hospital volume on in-hospital mortality was analyzed with random effects logistic regression models with a random intercept for Level-1 trauma center, adjusted for important demographic and injury characteristics. A total of 11,917 severely injured patients from 13 Dutch Level-1 trauma centers was included in this study. Hospital volume varied from 120 to 410 severely injured patients per year. Observed mortality rates varied between 12% and 24% per center. After case-mix correction, no statistically significant differences between low- and high-volume centers were demonstrated (adjusted odds ratio 0.97 per 50 extra patients per year, 95% Confidence Interval 0.90-1.04, p = 0.44). The variation in hospital volume of the included Level-1 trauma centers was not associated with the outcome of severely injured patients. Our results suggest that well-organized trauma centers with a similar organization of care could potentially achieve comparable outcomes.

9.
J Trauma Acute Care Surg ; 89(4): 801-812, 2020 10.
Article in English | MEDLINE | ID: mdl-33017136

ABSTRACT

BACKGROUND: With implementation of trauma systems, a level of trauma care classification was introduced. Use of such a system has been linked to significant improvements in survival and other outcomes. OBJECTIVES: The aim of this study was assessing the association between level of trauma care and fatal and nonfatal outcome measures for general and major trauma (MT) populations. METHODS: A systematic literature search was conducted using six electronic databases up to December 18, 2019. Studies comparing mortality or nonfatal outcomes between different levels of trauma care in general and MT populations (preferably Injury Severity Score of >15) were included. Two independent reviewers performed selection of relevant studies, data extraction, and a quality assessment of included articles. With a random-effects meta-analysis, adjusted and unadjusted pooled effect sizes were calculated for level I versus non-level I trauma centers. RESULTS: Twenty-two studies were included. Quality of the included studies was good; however, adjustment for comorbidity (32%) and interhospital transfer (38%) was performed less frequently. Nine (60%) of the 15 studies analyzing in-hospital mortality in general trauma populations reported a survival benefit for level I trauma centers. Level I trauma centers were not associated with higher mortality than non-level I trauma centers (adjusted odd ratio, 0.97; 95% confidence interval, 0.61-1.52). Of the 11 studies reporting in-hospital mortality in MT populations, 10 (91%) reported a survival benefit for level I trauma centers. Level I trauma centers were associated with lower mortality than non-level I trauma centers (adjusted odd ratio, 0.77; 95% confidence interval, 0.69-0.87). CONCLUSION: The association between level of trauma care and in-hospital mortality is evident for MT populations; however, this does not hold for general trauma populations. Level I trauma centers produce improved survival in MT populations. This association could not be proven for nonfatal outcomes in general and MT populations because of inconsistencies in the body of evidence. LEVEL OF EVIDENCE: Systematic review and meta-analysis, level III.


Subject(s)
Delivery of Health Care/organization & administration , Trauma Centers/standards , Wounds and Injuries/therapy , Hospital Mortality , Humans , Injury Severity Score , Wounds and Injuries/mortality
SELECTION OF CITATIONS
SEARCH DETAIL
...