Emergency department predictors of tracheostomy in patients with isolated traumatic brain injury requiring emergency cranial decompression

Machine learning algorithms for prediction of ventilator associated pneumonia in traumatic brain injury patients from the MIMIC-III database

BACKGROUND

Ventilator associated pneumonia (VAP) is a common complication and associated with poor prognosis of traumatic brain injury (TBI) patients.

OBJECTIVES

This study was conducted to explore the predictive performance of different machine-learning algorithms for VAP in TBI patients.

METHODS

TBI patients receiving mechanical ventilation more than 48 hours from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were eligible for the study. The VAP was confirmed based on the ICD-9 code. Included patients were separated to the training cohort and the validation cohort with a ratio of 7:3. Predictive models based on different machine learning algorithms were developed using 5-fold cross validation in the training cohort and then verified in the validation cohort by evaluating the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy and F score.

RESULTS

786 TBI patients from the MIMIC-III were finally included with the VAP incidence of 44.0%. The random forest performed the best on predicting VAP in the training cohort with a AUC of 1.000. The XGBoost and AdaBoost were ranked the second and the third with a AUC of 0.915 and 0.789 in the training cohort. While the AdaBoost performed the best on predicting VAP in the validation cohort with a AUC of 0.706. The XGBoost and random forest were ranked the second and the third with the AUC of 0.685 and 0.683 in the validation cohort. Generally, the random forest and XGBoost were likely to be over-fitting while the AdaBoost was relatively stable in predicting the VAP.

CONCLUSIONS

The AdaBoost performed well and stably on predicting the VAP in TBI patients. Developing programs using AdaBoost in portable electronic devices may effectively assist physicians in assessing the risk of VAP in TBI.

Craniotomy or Craniectomy for Acute Subdural Hematoma? Difference in Patient Characteristics and Outcomes at a Tertiary Care Hospital

Objective  This article compares the outcomes of patients with traumatic acute subdural hemorrhage (SDH) managed either with craniotomy (CO) or with decompressive craniectomy (DC). Methods  In this single-center, retrospective analysis we included all adult patients with acute traumatic SDH who were treated either using CO or DC. Sixteen-year hospital data was reviewed for patient demographics, injury details, and hospital course. Outcomes were noted in terms of intraoperative blood loss, intensive care unit stay, need for tracheostomy, post-surgery Glasgow Coma Score (GCS; calculated immediately after surgery), delayed GCS (DGCS; calculated 1 week after surgery), and delayed Glasgow Outcome Score (DGOS) after 6 months of surgery. Postoperative complications were noted during hospital stay, while mortality was noted within 6 months of surgery for each patient. Results  Patients who underwent DC were younger (mean age 34.4 ± 16.8 years vs. 42.4 ± 19.9 years in the CO group) ( p  = 0.006). Patients who underwent DC also had worst degree of traumatic brain injury as per Marshall grade (62.4% patients with Marshall grade 4 in the DC group vs. only 41.2% patients in the CO group) ( p  = 0.037). Mean size of hematoma was 23.8 ± 24.6 mm in the DC group versus 11.3 ± 8.2 mm in the CO group ( p  = 0.001). Mean postop GCS was lower in the DC group; 8.0 ± 4 versus 10.8 ± 4 in the CO group ( p  < 0.001). However, there was no significant difference in DGCS and DGOS between the DC and CO groups ( p  = 0.76 and 0.90, respectively). Mortality rate was 24 (30.8%) in the DC group versus 18 (20.7%) in the CO group ( p  = 0.14). Conclusion  The patients who underwent DC were younger, had larger size hematoma, and poor Marshall grade. We did not find any significant difference in the outcomes of CO and DC for management of subdural hematoma.

Patient Outcomes following Immediate Tracheostomy and Emergency Decompressive Craniectomy in the Same Setting

Early tracheostomy is recommended for patients with severe traumatic brain injury or stroke. Tracheostomy in the same setting as emergency decompressive craniectomy, on the other hand, has never been investigated. Our goal was to compare the outcomes related to the duration of mechanical ventilation in patients who had immediate (IT) vs. early (ET) tracheostomy following an emergency decompressive craniectomy in a Neurosurgical centre in Sabah, Malaysia. We reviewed 135 patients who underwent emergency decompressive craniectomy for traumatic brain injury (TBI) and stroke patients between January 2013 and January 2018 in this retrospective cohort study. The cohort included 49 patients who received immediate tracheostomy (IT), while the control group included 86 patients who received a tracheostomy within 7 days of decompressive surgery (ET). The duration of mechanical ventilation, length of stay (LOS) in the critical-care unit, and intravenous sedation were significantly shorter in the IT group compared to the ET group, according to the study. There was no significant difference between the two groups in the incidence of ventilator-associated pneumonia (VAP), tracheostomy-related complications, or 30-day mortality rate. In conclusion, compared to early tracheostomy, immediate tracheostomy in the same setting as emergency decompressive craniectomy is associated with a shorter duration of mechanical ventilation and LOS in critical-care units with acceptable morbidity and mortality rates. This practise could be used in busy centres with limited resources, such as those where mechanical ventilators, critical-care unit beds, or OT wait times are an issue.

Early versus standard tracheostomy in ventilated patients in neurosurgical intensive care unit: A randomized controlled trial

INTRODUCTION

Tracheostomy is performed in patients with prolonged mechanical ventilation, who suffered catastrophic neurologic insult or upper airway obstruction. Thus far, there is no consensus on the optimal timing in performing a tracheostomy. This study aims to test whether early tracheostomy in mechanically ventilated patients in a neurosurgical setting would be associated with a shorter time of mechanical ventilation as compared to standard tracheostomy.

METHODS

This single-center prospective randomized controlled trial was conducted at University Malaya Medical Centre from July 2019 to July 2021. The likelihood of prolonged ventilation was determined objectively using the TRACH score and the patient's clinical presentation. The outcomes measured were days of mechanical ventilation post-tracheostomy, days of neuro-intensive care unit stay, and days of hospital stay. Tracheostomy-related complications were collected. The data collected were analyzed using Statistical Package for the Social Sciences version 25 for Windows (SPSS Inc., Chicago, IL, USA).

RESULTS

In all, 39 patients were randomly assigned. Of these, 20 were allocated to the early tracheostomy group (ET) and 19 were allocated to the standard tracheostomy group (ST). The demographic characteristics were similar between the groups. The primary outcome, mean (SD) days of mechanical ventilation post-tracheostomy, was statistically different in the 2 groups- early 11.9 (9.3) days, standard 18.9 (32.5) days; p = 0.014. There were comparable tracheostomy-related complications in both groups.

CONCLUSION

Early tracheostomy is associated with a shorter duration of mechanical ventilation in a neurosurgical intensive care unit setting.

Comparing the Outcomes of Early and Late Tracheostomy in Severe Traumatic Brain Injury Patient

Background

Patients with severe traumatic brain injury (TBI) were expected to have poor Glasgow Coma Scale (GCS) recovery and prolonged intubation. Therefore, an early tracheostomy procedure was indicated for all severe TBI. In view of growing concern regarding the safety and outcome of early tracheostomy on these patients, it was deemed valid and needed to be addressed.

Methods

This study was conducted to compare the outcomes of early and late tracheostomies in severe TBI. Only severe TBI patients who were admitted to the Neurosurgery High Dependency Unit (NHDU), Hospital Sultanah Aminah (HSA), Johor Bahru, Johor, Malaysia and who had underwent a tracheostomy were recruited. Three main outcomes noted: duration on ventilation, length of NHDU stay and rate of ventilator associated pneumonia (VAP).

Results

Out of 155 patients, 72 (46.5%) were in early tracheostomy group (ETG) and 83 (53.5%) were in late tracheostomy group (LTG). The majority of the participants, 95 (61.3%) were ethnic Malays. The mean duration on ventilator use was 2.65 days (1.57) for ETG and 5.63 days (2.35) for LTG. While, mean NHDU stay was 4.75 days (1.98) for ETG and 9.77 days (2.70) for LTG. Upon independent t-test, early duration of tracheostomies had shown significant outcome in reducing length of NHDU stay, (P < 0.001) and had shortening participants’ time on mechanical ventilator (P < 0.001). Then, based on forward multiple logistic regression test, there were significant association between comorbid (P = 0.003) and tracheostomy (P = 0.020) towards presence of VAP when adjusted for other variables.

Conclusion

In this study it was found that early tracheostomy was significant in shortening the duration on ventilator, reducing the length of NHDU stay and reducing the rate of VAP.

Absence of calvarial fracture could predict the need for tracheostomy in traumatic brain injury

Aim

Tracheostomy is a common procedure for intubated patients with traumatic brain injury (TBI) in the intensive care unit (ICU) but optimal timing and the predictors of tracheostomy are still unclear. The aim of our study was to explore whether the traumatic variables of head injury predict the need for tracheostomy in intubated TBI patients.

Methods

A single‐center, retrospective observational study including a series of TBI patients admitted to Fukui Prefectural Hospital from April 1, 2004 to March 31, 2020 was carried out. Our primary outcome was tracheostomy. Patients with TBI who were intubated and admitted into the ICU within 24 h after injury were enrolled. Exclusion criteria were age less than 18 years, pregnancy, mortality within 24 h, post‐cardiac arrest syndrome, and patients for whom life‐sustaining interventions were withheld. Radiologic images were also reviewed and the morphology of the head injury was categorized.

Results

Seventy‐six patients were included. Forty‐six patients (60.5%) underwent tracheostomy and 30 patients (39.5%) were successfully extubated. Calvarial fracture (odds ratio [OR] 0.34; 95% confidence interval [CI], 0.13–0.88; P = 0.03), Injury Severity Score (OR 1.07; 95% CI, 1.00–1.15; P = 0.04), and Glasgow Comas Scale score (OR 0.84; 95% CI, 0.73–0.96) were statistically significant in the univariable analysis. Multivariate logistic regression identified calvarial fracture as an independent predictor for tracheostomy. The model involving calvarial fracture, Injury Severity Score ≥16, and Glasgow Coma Scale score ≤8 showed the area under the receiver operating characteristic curve for the model was 0.737 (95% CI, 0.629–0.846).

Conclusions

The absence of calvarial fracture could predict the necessity for tracheostomy in intubated TBI patients when combined with other factors. Further prospective randomized trials are necessary to confirm the findings.

Inpatient Complications Predict Tracheostomy Better than Admission Variables After Traumatic Brain Injury

BACKGROUND

Data regarding who will require tracheostomy are lacking which may limit investigations into therapeutic effects of early tracheostomy.

METHODS

We performed an observational study of adult traumatic brain injury (TBI) patients requiring intensive care unit (ICU) admission for ≥ 72 h and mechanical ventilation for ≥ 24 h between January 2014 and December 2014 at a level 1 trauma center. Patients who had life-sustaining measures withdrawn were excluded. Multivariable logistic regression analyses were used to assess admission and inpatient factors associated with receiving a tracheostomy and to develop predictive models. Inpatient complications prior to day 7 were used to standardize data collection for patients with and without tracheostomy. Patients who received tracheostomy prior to day 7 were excluded from analysis.

RESULTS

In total, 209 patients (78% men, mean 48 years old, median Glasgow Coma Scale score (GCS) 8) met study criteria with tracheostomy performed in 94 (45%). Admission predictors of tracheostomy included GCS, chest tube, Injury Severity Score, and Marshall score. Inpatient factors associated with tracheostomy included the requirement for an external ventricular drain (EVD), number of operations, inpatient dialysis, aspiration, GCS on day 5, and reintubation. Multiple logistic regression analysis demonstrated that the number of operation room trips (adjusted odds ratio [AOR], 1.75; 95% CI, 1.04-2.97; P = 0.036), reintubation (AOR, 8.45; 95% CI, 1.91-37.44; P = .005), and placement of an EVD (AOR, 3.48; 95% CI, 1.27-9.58; P = .016) were independently associated with patients undergoing tracheostomy. Higher GCS on hospital day 5 (AOR, 0.52; 95% CI, 0.40-0.68; P < 0.001) was protective against tracheostomy. A model of inpatient variables only had a stronger association with tracheostomy than one with admission variables only (ROC AUC 0.93 vs 0.72, P < 0.001) and did not benefit from the addition of admission variables (ROC AUC 0.93 vs 0.92, P = 0.78).

CONCLUSION

Potentially modifiable inpatient factors have a stronger association with tracheostomy than do admission characteristics. Multicenter studies are needed to validate the results.

Patient characteristics, incidence, technique, outcomes and early prediction of tracheostomy in the state of Victoria, Australia

BACKGROUND

Tracheostomy is a relatively common procedure in Intensive Care Unit (ICU) patients.

AIMS

To study the patient characteristics, incidence, technique, outcomes and prediction of tracheostomy in the State of Victoria, Australia.

METHODS

We used data from the Australian and New Zealand Intensive Care Society Adult Patient Database (ANZICS APD) and the Victorian Admitted Episode Dataset (VAED) to identify and match patients who had received a tracheostomy from 2004 to 2014.

RESULTS

Between 1st January 2004 and 30th June 2014, 9750 patients received a tracheostomy with 7670 available for matching and 6010 (78.4%) successfully matched. Of the matched tracheostomy patients, median age was 61years, median APACHE IIIJ score was 66 and overall hospital mortality was 21%. The incidence of tracheostomy almost halved over the decade with more than half of tracheostomies (53.5%) being percutaneous. Hospital mortality of patients receiving a tracheostomy decreased from 26.5% in 2004 to 16.5% in 2014 by an average decrease of 6%/year. No robust model could be developed to predict tracheostomy.

CONCLUSION

The incidence of tracheostomy and the adjusted mortality rate of patients who received a tracheostomy have significantly decreased over a decade. Day of admission information could not be used to predict subsequent tracheostomy.

Low cost quality initiatives for management of neurosurgical patients in developing nations: Perspective from a tertiary care centre in Pakistan

BACKGROUND

Targeting resources on cost-effective care strategies is pertinent for developing nations, specifically for already burdened specialties such as neurosurgery, where without state support and insurance companies, expenses are borne by the patient themselves.

METHODS

This was a descriptive review of literary work published by the section of neurosurgery at Aga Khan University Hospital, Pakistan. We searched PubMed and CiNAHL databases to identify articles, which were then critically analyzed and discussed from a perspective of low-cost quality care.

RESULTS

We demonstrate the cost effectiveness of three initiatives, namely, blood ordering protocol for elective spine arthrodesis, nonoperative management being superior to surgical stabilization in spine injury patients with complete neurological deficits, and early tracheostomy in patients with isolated severe traumatic brain injury.

CONCLUSION

Initiation and implementation of such cost-effective strategies without compromising quality health standards must be emphasized by neurosurgical centers throughout the developing world for smart allocation and utilization of funds.

Tracheostomy risk factors and outcomes after severe traumatic brain injury

OBJECTIVE

To determine risk factors associated with tracheostomy placement after severe traumatic brain injury (TBI) and subsequent outcomes among those who did and did not receive a tracheostomy.

METHODS

This retrospective cohort study compared adult trauma patients with severe TBI (n = 583) who did and did not receive tracheostomy. A multivariable logistic regression model assessed the associations between age, sex, race, insurance status, admission GCS, AIS (Head, Face, Chest) and tracheostomy placement. Ordinal logistic regression models assessed tracheostomy's influence on ventilator days and ICU LOS. To limit immortal time bias, Cox proportional hazards models assessed mortality at 1, 3 and 12-months.

RESULTS

In this multivariable model, younger age and private insurance were associated with increased probability of tracheostomy. AIS, ISS, GCS, race and sex were not risk factors for tracheostomy placement. Age showed a non-linear relationship with tracheostomy placement; likelihood peaked in the fourth decade and declined with age. Compared to uninsured patients, privately insured patients had an increased probability of receiving a tracheostomy (OR = 1.89 [95% CI = 1.09-3.23]). Mortality was higher in those without tracheostomy placement (HR = 4.92 [95% CI = 3.49-6.93]). Abbreviated injury scale-Head was an independent factor for time to death (HR = 2.53 [95% CI = 2.00-3.19]), but age, gender and insurance were not.

CONCLUSIONS

Age and insurance status are independently associated with tracheostomy placement, but not with mortality after severe TBI. Tracheostomy placement is associated with increased survival after severe TBI.

Prolonged mechanical ventilation is associated with pulmonary complications, increased length of stay, and unfavorable discharge destination among patients with subdural hematoma

BACKGROUND

Although subdural hematoma (SDH) is common in neurocritical practice, little is known about SDH patients requiring prolonged mechanical ventilation (PMV). We aimed to determine predictors of PMV and its relationship with outcome in patients with SDH.

METHODS

SDH patients admitted to Rush University neurointensive care unit from January 2009 to March 2012 were reviewed. Duration of intubation, pulmonary complications, demographics, treatment, discharge disposition, and length of stay (LOS) were reviewed. PMV was defined as duration of intubation >4 days. Univariate and multivariate analyses were performed to identify predictors of PMV and association with outcome among survivors with SDH.

RESULTS

Of the 288 survivors with SDH, the mean age was 68, and of them 179 were male. A total of 137 required surgical SDH evacuation. Pneumonia occurred in 26 patients. Forty-eight patients (17%) required intubation, with duration of intubation being 1 to 20 days (median 3.0). Factors independently associated with PMV included alcohol abuse (OR, 4.31; 95% CI, 1.36-13.67), admission GCS<15 (OR, 11; 95% CI, 2.36-51.52), and surgical evacuation (OR, 9.27; 95% CI, 1.93-44.54). PMV predicted pneumonia (OR, 5.85; 95% CI, 1.52-22.57), tracheostomy (OR, 26.67; 95% CI, 2.93-242.67), increased LOS, and unfavorable discharge destination (OR, 73.1; 95% CI, 14.03-380.69).

CONCLUSIONS

PMV is associated with pulmonary complications, increased LOS, and unfavorable discharge destination in patients with SDH. Alcohol abuse, admission GCS, and surgical evacuation are associated with PMV among patients with SDH. Future studies should investigate the role of early tracheostomy in high-risk patients and impact on outcomes.

Radiological prognostication in patients with head trauma requiring decompressive craniectomy: Analysis of optic nerve sheath diameter and Rotterdam CT Scoring System

INTRODUCTION

Optic nerve sheath diameter (ONSD) measured on CT scan has been shown to predict outcomes of patients with severe traumatic brain injury. No such relation has been studied in patients undergoing decompressive craniectomy (DC). We evaluated ONSD on admission CT scan to predict outcomes of patients undergoing DC along with Rotterdam CT Score (RCTS).

MATERIALS AND METHODS

This retrospective cohort study was approved by the institutional ethics committee. All the consecutive patients undergoing DC with available images and records were included. We measured ONSD 3mm behind the eyeball and calculated RCTS. Glasgow Outcome Scale (GOS) was measured at last follow-up. We analyzed the data on SPSS v 19. Receiver operator curve analysis (ROC) was done to measure the predictive values of ONSD and RCTS for mortality and unfavorable outcomes.

RESULTS

One hundred and seventeen patients were included. Twenty patients had bilateral DC. Mean GCS at presentation was 8.5±3.5. Mean follow-up was 7.5±1.2 months. Thirty-day mortality was 19%. Mean ONSD of both eyes was 6.73±0.89mm. Area under the curve (AUC) for bilateral mean ONSD as predictor of mortality was 0.49 [95%CI: 0.36-0.62]. AUC for RCTS was as a predictor of 30-day mortality was significant, i.e. 0.67 [95%CI: 0.572-0.820]. The difference of mean ONSD was also not significantly different between survivor and non-survivors.

CONCLUSION

Admission ONSD in DC patients is high but does not predict mortality and unfavorable outcomes. RCTS has a better prognostic value for predicting mortality and unfavorable outcomes in DC patients.

Case-control studies in neurosurgery

OBJECT

Observational studies, such as cohort and case-control studies, are valuable instruments in evidence-based medicine. Case-control studies, in particular, are becoming increasingly popular in the neurosurgical literature due to their low cost and relative ease of execution; however, no one has yet systematically assessed these types of studies for quality in methodology and reporting.

METHODS

The authors performed a literature search using PubMed/MEDLINE to identify all studies that explicitly identified themselves as "case-control" and were published in the JNS Publishing Group journals (Journal of Neurosurgery, Journal of Neurosurgery: Pediatrics, Journal of Neurosurgery: Spine, and Neurosurgical Focus) or Neurosurgery. Each paper was evaluated for 22 descriptive variables and then categorized as having either met or missed the basic definition of a case-control study. All studies that evaluated risk factors for a well-defined outcome were considered true case-control studies. The authors sought to identify key features or phrases that were or were not predictive of a true case-control study. Those papers that satisfied the definition were further evaluated using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist.

RESULTS

The search detected 67 papers that met the inclusion criteria, of which 32 (48%) represented true case-control studies. The frequency of true case-control studies has not changed with time. Use of odds ratios (ORs) and logistic regression (LR) analysis were strong positive predictors of true case-control studies (for odds ratios, OR 15.33 and 95% CI 4.52-51.97; for logistic regression analysis, OR 8.77 and 95% CI 2.69-28.56). Conversely, negative predictors included focus on a procedure/intervention (OR 0.35, 95% CI 0.13-0.998) and use of the word "outcome" in the Results section (OR 0.23, 95% CI 0.082-0.65). After exclusion of nested case-control studies, the negative correlation between focus on a procedure/intervention and true case-control studies was strengthened (OR 0.053, 95% CI 0.0064-0.44). There was a trend toward a negative association between the use of survival analysis or Kaplan-Meier curves and true case-control studies (OR 0.13, 95% CI 0.015-1.12). True case-control studies were no more likely than their counterparts to use a potential study design "expert" (OR 1.50, 95% CI 0.57-3.95). The overall average STROBE score was 72% (range 50-86%). Examples of reporting deficiencies were reporting of bias (28%), missing data (55%), and funding (44%).

CONCLUSIONS

The results of this analysis show that the majority of studies in the neurosurgical literature that identify themselves as "case-control" studies are, in fact, labeled incorrectly. Positive and negative predictors were identified. The authors provide several recommendations that may reverse the incorrect and inappropriate use of the term "case-control" and improve the quality of design and reporting of true case-control studies in neurosurgery.

In-hospital mortality after traumatic brain injury surgery: a nationwide population-based comparison of mortality predictors used in artificial neural network and logistic regression models

Object

Most reports compare artificial neural network (ANN) models and logistic regression models in only a single data set, and the essential issue of internal validity (reproducibility) of the models has not been adequately addressed. This study proposes to validate the use of the ANN model for predicting in-hospital mortality after traumatic brain injury (TBI) surgery and to compare the predictive accuracy of ANN with that of the logistic regression model.

Methods

The authors of this study retrospectively analyzed 16,956 patients with TBI nationwide who were surgically treated in Taiwan between 1998 and 2009. For every 1000 pairs of ANN and logistic regression models, the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow statistics, and accuracy rate were calculated and compared using paired t-tests. A global sensitivity analysis was also performed to assess the relative importance of input parameters in the ANN model and to rank the variables in order of importance.

Results

The ANN model outperformed the logistic regression model in terms of accuracy in 95.15% of cases, in terms of Hosmer-Lemeshow statistics in 43.68% of cases, and in terms of the AUC in 89.14% of cases. The global sensitivity analysis of in-hospital mortality also showed that the most influential (sensitive) parameters in the ANN model were surgeon volume followed by hospital volume, Charlson comorbidity index score, length of stay, sex, and age.

Conclusions

This work supports the continued use of ANNs for predictive modeling of neurosurgery outcomes. However, further studies are needed to confirm the clinical efficacy of the proposed model.

Temporal trends and volume-outcome associations after traumatic brain injury: a 12-year study in Taiwan

OBJECT

The purpose of this study was to evaluate temporal trends in traumatic brain injury (TBI); the impact of hospital volume and surgeon volume on length of stay (LOS), hospitalization cost, and in-hospital mortality rate; and to explore predictors of these outcomes in a nationwide population in Taiwan.

METHODS

This population-based patient cohort study retrospectively analyzed 16,956 patients who had received surgical treatment for TBI between 1998 and 2009. Bootstrap estimation was used to derive 95% confidence intervals for differences in effect sizes. Hierarchical linear regression models were used to predict outcomes.

RESULTS

Patients treated in very-high-volume hospitals were more responsive than those treated in low-volume hospitals in terms of LOS (-0.11; 95% CI -0.20 to -0.03) and hospitalization cost (-0.28; 95% CI -0.49 to -0.06). Patients treated by high-volume surgeons were also more responsive than those treated by low-volume surgeons in terms of LOS (-0.19; 95% CI -0.37 to -0.01) and hospitalization cost (-0.43; 95% CI -0.81 to -0.05). The mean LOS was 24.3 days and the average LOS for very-high-volume hospitals and surgeons was 61% and 64% shorter, respectively, than that for low-volume hospitals and surgeons. The mean hospitalization cost was US $7,292.10, and the average hospitalization cost for very-high-volume hospitals and surgeons was 19% and 22% lower, respectively, than that for low-volume hospitals and surgeons. Advanced age, male sex, high Charlson Comorbidity Index score, treatment in a low-volume hospital, and treatment by a low-volume surgeon were significantly associated with adverse outcomes (p < 0.001).

CONCLUSIONS

The data suggest that annual surgical volume is the key factor in surgical outcomes in patients with TBI. The results improve the understanding of medical resource allocation for this surgical procedure, and can help to formulate public health policies for optimizing hospital resource utilization for related diseases.