Derivation and Validation of a Score Using Prehospital Data to Identify Adults With Trauma Requiring Early Laparotomy

Gutierrez, Adam; Matsushima, Kazuhide; Grigorian, Areg; Schellenberg, Morgan; Inaba, Kenji

doi:10.1001/jamanetworkopen.2021.45860

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…In cases where it is difficult to identify injuries or evaluate their severity, ISI may be a new alternative for predicting prognosis. Specifically, there is a possibility that it may be used to predict physiological derangement (33).…”

Section: Discussionmentioning

confidence: 99%

The Initial Ion Shift Index as a Prognostic Indicator to Predict Patient Survival in Traumatic Damage Control Laparotomy Patients

Jang

Jeung

Kang

et al. 2022

Shock

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Objective: The ion shift index (ISI), which considers extracellular fluid ions such as phosphate, calcium, and magnesium, represents the ion shift following ischemia; concentrations of these ions are maintained within narrow normal ranges by adenosine triphosphate-dependent homeostasis. The ISI is defined as follows: {potassium (mmol/L-1) + phosphate (mmol/L-1) + Mg (mmol/L-1)}/calcium (mmol/L-1). This study investigated the possibility of predicting the 30-day survival rate of patients who underwent traumatic damage control laparotomy by comparing ISI and other laboratory findings, as well as the initial Trauma and Injury Severity Score (TRISS) and shock indices. Methods: Among the 134 patients who underwent damage control surgery between November 2012 and December 2021, 115 patients were enrolled in this study. Data regarding injury mechanism, age, sex, laboratory findings, vital signs, Glasgow Coma Scale score, Injury Severity Score, Abbreviated Injury Scale score, blood component transfusion, type of surgery, postoperative laboratory outcomes, morbidity, mortality rates, fluids administered, and volume of transfusions were collected and analyzed. Results: In univariate analysis, the odds ratio of the initial ISI was 2.875 (95% confidence interval, 1.52–5.43; P = 0.04), which showed a higher correlation with mortality compared with other indices. The receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) were derived from different multivariable logistic regression models. The initial ISI had high sensitivity and specificity in predicting patient mortality (AUC, 0.7378). In addition, in the model combining the initial ISI, crystalloids, and TRISS, the AUC showed a high value (AUC, 0.8227). Conclusion: The ISI evaluated using electrolytes immediately after admission in patients undergoing traumatic damage control surgery may be a predictor of patient mortality.

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Section: Discussionmentioning

confidence: 99%

The Initial Ion Shift Index as a Prognostic Indicator to Predict Patient Survival in Traumatic Damage Control Laparotomy Patients

Jang

Jeung

Kang

et al. 2022

Shock

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“…The VIP score was then derived using a three-step methodology, which has been validated in the literature [13][14][15][16]. First, univariate analyses of known risk factors for early VATS were performed.…”

Section: Methodsmentioning

confidence: 99%

Scoring Tool to Predict Need for Early Video‐Assisted Thoracoscopic Surgery (VATS) After Pediatric Trauma

Kazempoor,

Nahmias,

Clark

et al. 2023

World j. surg.

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Background No widely used stratification tool exists to predict which pediatric trauma patients may require a video-assisted thoracoscopic surgery (VATS). We sought to develop a novel VATS-In-Pediatrics (VIP) score to predict the need for early VATS (within 72 h of admission) for pediatric trauma patients. Methods The pediatric 2017–2020 Trauma Quality Improvement Program database was used and divided into two sets (derivation set using 2017–2019 data and validation set using 2020 data). First, multiple logistic regression models were created to determine the risk of early VATS for patients ≤ 17 years old. Second, the weighted average and relative impact of each independent predictor were used to derive a VIP score. We then validated the score using the area under the receiver operating characteristic (AROC) curve. Results From 218,628 patients in the derivation set, 2183 (1.0%) underwent early VATS. A total of 8 independent predictors of VATS were identified, and the VIP score was derived with scores ranging from 0 to 9. The AROC for this was 0.91. The VATS rate increased steadily from 12.5 to 32% then 60.5% at scores of 3, 4, and 6, respectively. In the validation set, from 70,316 patients, 887 (1.3%) underwent VATS, and the AROC was 0.91. Conclusions VIP is a novel and validated scoring tool to predict the need for early VATS in pediatric trauma. This tool can potentially help hospital systems prepare for pediatric patients at high risk for requiring VATS during their first 72 h of admission. Future prospective research is needed to evaluate VIP as a tool that can improve clinical outcomes.

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“…Every minute delayed before an emergency laparotomy for hemorrhage control has been associated with an increased probability of mortality . Gutierrez et al developed and validated a much needed tool to identify patients at risk of requiring early laparotomy within 2 hours of hospital arrival after injury. The Prehopsital Preparation for Surgery (PREPS) Score was derived using encounters of adults aged 18 years or older in the 2017 Trauma Quality Improvement Program database.…”

mentioning

confidence: 99%

“…Including too many variables in a model risks overfitting and lacks practicality. In addition to the variable selection strategy used by Gutierrez et al, other strategies can be used, ranging from removing variables with near-zero variance to regularization and other machine learning algorithms . Third, model validity must be assessed using appropriate performance metrics.…”

mentioning

confidence: 99%

Clinical Prediction Tools in Trauma: Where Do We Go From Here?

Choi

Forrester

2022

JAMA Netw Open

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Expeditious hemorrhage control is a fundamental tenet of trauma surgery. Every minute delayed before an emergency laparotomy for hemorrhage control has been associated with an increased probability of mortality. 1 Gutierrez et al 2 developed and validated a much needed tool to identify patients at risk of requiring early laparotomy within 2 hours of hospital arrival after injury. The Prehopsital Preparation for Surgery (PREPS) Score was derived using encounters of adults aged 18 years or older in the 2017 Trauma Quality Improvement Program database. The PREPS Score (0-20) comprised 7 binary variables, with factors more strongly associated with early laparotomy contributing more points and input variables that could be used by emergency medical service (EMS) technicians in the field.Building this type of clinical tool requires thoughtful study design. First, the tool should have the potential to alter clinical decision-making. The PREP Score certainly meets this criterion; early identification of patients requiring emergency laparotomy may help hospitals mobilize resources, ensure patients are triaged to appropriate centers, and alert clinicians to patients with a higher likelihood of deterioration. Second, variable selection must follow an a priori determined and statistically sound approach. Including too many variables in a model risks overfitting and lacks practicality. In addition to the variable selection strategy used by Gutierrez et al, 2 other strategies can be used, ranging from removing variables with near-zero variance to regularization and other machine learning algorithms. [3][4][5] Third, model validity must be assessed using appropriate performance metrics. Various performance metrics exist, including the C-statistic, which the authors used. The C-statistic is equivalent to area under the receiver operating characteristic curve (AUROC) for binary outcomes, a frequently reported yet commonly misunderstood value. Derived from the area under the curve plotting sensitivity (true positive rate) vs 1 − specificity (false positive rate), AUROC denotes the probability that a randomly selected point in the positive class will be scored higher than a randomly selected point in the negative class. While the concept that a higher C-statistic or AUROC close to 1 indicates good performance, applying the value itself for clinical decision-making is challenging.Alternative performance metrics rather than AUROC or C-statistic may be more interpretable.For example, if the cost of a false negative is high (eg, most screening tools), sensitivity or recall would be an appropriate performance metric to evaluate, while precision would be the more informative metric if the cost of a false positive is high (eg, if positive result necessitates invasive or high-risk intervention). Class imbalance (the ratio of positives to negatives in the study population) is an important consideration when choosing the performance metric. For example, in scenarios with few positives, accuracy would be a misleading metric. If a tool always ...

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Derivation and Validation of a Score Using Prehospital Data to Identify Adults With Trauma Requiring Early Laparotomy

Cited by 4 publications

References 19 publications

The Initial Ion Shift Index as a Prognostic Indicator to Predict Patient Survival in Traumatic Damage Control Laparotomy Patients

The Initial Ion Shift Index as a Prognostic Indicator to Predict Patient Survival in Traumatic Damage Control Laparotomy Patients

Scoring Tool to Predict Need for Early Video‐Assisted Thoracoscopic Surgery (VATS) After Pediatric Trauma

Clinical Prediction Tools in Trauma: Where Do We Go From Here?

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