Prehospital Index Research Articles

Enhancing Performance of the National Field Triage Guidelines Using Machine Learning: Development of a Prehospital Triage Model to Predict Severe Trauma.

Prehospital trauma triage is essential to get the right patient to the right hospital. However, the national field triage guidelines proposed by the American College of Surgeons have proven to be relatively insensitive when identifying severe traumas. This study aimed to build a prehospital triage model to predict severe trauma and enhance the performance of the national field triage guidelines. This was a multisite prediction study, and the data were extracted from the National Trauma Data Bank between 2017 and 2019. All patients with injury, aged 16 years of age or older, and transported by ambulance from the injury scene to any trauma center were potentially eligible. The data were divided into training, internal, and external validation sets of 672,309; 288,134; and 508,703 patients, respectively. As the national field triage guidelines recommended, age, 7 vital signs, and 8 injury patterns at the prehospital stage were included as candidate variables for model development. Outcomes were severe trauma with an Injured Severity Score ≥16 (primary) and critical resource use within 24 hours of emergency department arrival (secondary). The triage model was developed using an extreme gradient boosting model and Shapley additive explanation analysis. The model's accuracy regarding discrimination, calibration, and clinical benefit was assessed. At a fixed specificity of 0.5, the model showed a sensitivity of 0.799 (95% CI 0.797-0.801), an undertriage rate of 0.080 (95% CI 0.079-0.081), and an overtriage rate of 0.743 (95% CI 0.742-0.743) for predicting severe trauma. The model showed a sensitivity of 0.774 (95% CI 0.772-0.776), an undertriage rate of 0.158 (95% CI 0.157-0.159), and an overtriage rate of 0.609 (95% CI 0.608-0.609) when predicting critical resource use, fixed at 0.5 specificity. The triage model's areas under the curve were 0.755 (95% CI 0.753-0.757) for severe trauma prediction and 0.736 (95% CI 0.734-0.737) for critical resource use prediction. The triage model's performance was better than those of the Glasgow Coma Score, Prehospital Index, revised trauma score, and the 2011 national field triage guidelines RED criteria. The model's performance was consistent in the 2 validation sets. The prehospital triage model is promising for predicting severe trauma and achieving an undertriage rate of <10%. Moreover, machine learning enhances the performance of field triage guidelines.

Comparison of nine trauma scoring systems in prediction of inhospital outcomes of pediatric trauma patients: a multicenter study

Hereby, we aimed to comprehensively compare different scoring systems for pediatric trauma and their ability to predict in-hospital mortality and intensive care unit (ICU) admission. The current registry-based multicenter study encompassed a comprehensive dataset of 6709 pediatric trauma patients aged ≤ 18 years from July 2016 to September 2023. To ascertain the predictive efficacy of the scoring systems, the area under the receiver operating characteristic curve (AUC) was calculated. A total of 720 individuals (10.7%) required admission to the ICU. The mortality rate was 1.1% (n = 72). The most predictive scoring system for in-hospital mortality was the adjusted trauma and injury severity score (aTRISS) (AUC = 0.982), followed by trauma and injury severity score (TRISS) (AUC = 0.980), new trauma and injury severity score (NTRISS) (AUC = 0.972), Glasgow coma scale (GCS) (AUC = 0.9546), revised trauma score (RTS) (AUC = 0.944), pre-hospital index (PHI) (AUC = 0.936), injury severity score (ISS) (AUC = 0.901), new injury severity score (NISS) (AUC = 0.900), and abbreviated injury scale (AIS) (AUC = 0.734). Given the predictive performance of the scoring systems for ICU admission, NTRISS had the highest predictive performance (AUC = 0.837), followed by aTRISS (AUC = 0.836), TRISS (AUC = 0.823), ISS (AUC = 0.807), NISS (AUC = 0.805), GCS (AUC = 0.735), RTS (AUC = 0.698), PHI (AUC = 0.662), and AIS (AUC = 0.651). In the present study, we concluded the superiority of the TRISS and its two derived counterparts, aTRISS and NTRISS, compared to other scoring systems, to efficiently discerning individuals who possess a heightened susceptibility to unfavorable consequences. The significance of these findings underscores the necessity of incorporating these metrics into the realm of clinical practice.

Association between prehospital shock index variation and 28-day mortality among patients with septic shock

PurposeSeptic shock (SS) hyperdynamic phase is characterized by tachycardia and low-blood pressure reflecting the relative hypovolemia. Shock index (SI), the ratio between heart rate and systolic blood pressure, is a simple objective tool, usable for SS prognosis assessment.This study aims to evaluate the relationship between prehospital SI variation and 28-day mortality of SS patients initially cared for in prehospital setting by a mobile intensive care unit (mICU).MethodsFrom April 6th, 2016 to December 31st, 2020, 406 patients with SS requiring prehospital mICU were retrospectively analyzed. Initial SI, i.e. first measurement after mICU arrival to the scene, and final SI, i.e. last measurement of the prehospital stage, were used to calculate delta SI (initial SI—final SI) and to define positive and negative delta SI. A survival analysis after propensity score matching compared the 28-day mortality of SS patients with positive/negative delta SI.ResultsThe main suspected origins of infection were pulmonary (42%), digestive (25%) and urinary (17%). The 28-day overall mortality reached 29%.Cox regression analysis revealed a significant association between 28-day mortality and delta SI. A negative delta SI was associated with an increase in mortality (adjusted hazard ratio (HRa) of 1.88 [1.07–3.31] (p = 0.03)), whereas a positive delta SI was associated with a mortality decrease (HRa = 0.53 [0.30–0.94] (p < 10–3)).ConclusionPrehospital hemodynamic delta SI among SS patients cared for by a mICU is associated with 28-day mortality. A negative prehospital delta SI could help physicians to identify SS with higher risk of 28-day mortality.

Association between Scene Time Interval and Survival in EMS-Treated Major Trauma Admitted to the Intensive Care Unit: A Multinational, Multicenter Observational Study

Objective: Major trauma is a major concern in public health and a leading cause of mortality worldwide. This study aimed to evaluate the association between the prehospital scene time interval (STI) and survival in emergency medical service (EMS)-assessed major trauma patients admitted to the intensive care unit (ICU). Methods: A retrospective observational study using the Pan-Asian Trauma Outcomes Study (PATOS) database was conducted. Adult trauma patients with injury severity scores (ISSs) greater than 15 who were admitted to the ICU were selected. EMS STIs were categorized into three groups: short (0–8 minutes), intermediate (9–16 minutes), and long (over 16 minutes). The primary outcome was survival to hospital discharge, and the secondary outcome was good neurological outcome at hospital discharge. Multivariable logistic regression analysis was conducted to calculate odds ratios and confidence intervals, adjusting for age, sex, mechanism of injury, prehospital alertness, prehospital shock index, response time interval, and EMS intervention (airway, oxygen supplementation, and intravenous fluid administration). Sensitivity analysis for patients who underwent surgery or nontraumatic brain injury cases and interaction analysis by EMS intervention were performed. Results: Data from a total of 1,874 eligible patients were analyzed. Intermediate and long STIs showed significant associations with outcomes, with adjusted ORs (95% CI) of 1.21 (1.07–1.38) in the intermediate STI group and 1.74 (1.55–1.96) in the long STI group for survival and 1.37 (1.32–1.40) in the intermediate STI group and 1.31 (1.22–1.41) in the long STI group for neurological outcome. In the sensitivity analysis, the highest ORs were found in the intermediate STI group, with adjusted ORs (95% CI) of 1.40 (1.37–1.42) for survival and 1.32 (1.26–1.38) for neurological outcome. In the interaction analysis, EMS intervention showed a positive interaction effect with an intermediate STI on survival. Conclusion: In EMS-assessed adult major trauma patients admitted to the ICU, we found significant associations between STIs longer than 8 minutes and outcomes. EMS intervention has a positive interaction effect with an intermediate STI on survival. More research is needed to understand the implications of practice for major trauma in the field.

Injury Assessment of Individuals Wounded in the Lushan Earthquake and the Emergency Department Workload: A Corresponding Correlation Study.

In this study, we aimed to evaluate the correlation between the trauma score of individuals wounded in the Lushan earthquake and emergency workload for treatment. We further created a trauma score-emergency workload calculation model. We included data from patients wounded in the Lushan earthquake and treated at West China Hospital, Sichuan University. We calculated scores per the following models separately: Revised Trauma Score (RTS), Prehospital Index (PHI), Circulation Respiration Abdominal Movement Speech (CRAMS), Therapeutic Intervention Scoring System (TISS-28), and Nursing Activities Score (NAS). We assessed the association between values for CRAMS, PHI, and RTS and those for TISS-28 and NAS. Subsequently, we built a trauma score-emergency workload calculation model to quantitative workload estimation. Significant correlations were observed for all pairs of trauma scoring models with emergency workload scoring models. TISS-28 score was significantly associated with PHI score and RTS; however, no significant correlation was observed between the TISS-28 score and CRAMS score. CRAMS, PHI, and RTS were consistent in evaluating the injury condition of wounded individuals; TISS-28 and NAS scores were consistent in evaluating the required treatment workload. Dynamic changes in emergency workload in unit time were closely associated with wounded patient visits.

Accuracy of early warning scores for predicting serious adverse events in pre-hospital traumatic injury

BackgroundTraumatically injured patients are at higher risk of serious adverse events. Numerous physiological scoring systems are employed as diagnostic and/or prognostic tools. The objective of this study was to evaluate the scales most commonly used by emergency medical services for the early detection of prehospital serious adverse events. MethodsDesign. Preliminary longitudinal prospective observational study without intervention study in adults with prehospital traumatic injury.Setting. The study was carried out in the public health system of Castile and León (Spain), from April 1, 2018 to October 31, 2019, involving seven advanced life support units and five hospitals.Participants. Traumatically injured patients over 18 years of age who were stabilized and transferred in advanced life support units to their referral hospital.Main outcome measures. Appearance of serious adverse events at the prehospital level at the scene or during the transfer to the emergency department. ResultsA total of 346 patients were included in the study. The median age was 50 years (IQR: 38–65). 32 cases (7.8%) presented serious adverse events at the prehospital level. Areas under the curve for the detection of serious adverse events were obtained with the Prehospital Index (0.979; 95% CI: 0.94–1.00) and National Early Warning Score 2 (0.956; 95% CI: 0.90–1.00); p <0.001 for all scores. The Prehospital Index had a positive probability coefficient of 78.4 (95% CI: 62.8–68.6) and the National Early Warning Score 2 obtained 52.9 (95% CI: 39.7–65.6). A comparison of the curves was not significant for any of the scores studied (p> 0.05). ConclusionsAll scoring systems were able to detect prehospital serious adverse events early in traumatic injury; therefore, any of the scoring systems could be useful and represent an ideal tool for routine use by emergency medical services in cases of traumatic injury.

Prehospital Index provides prognosis for hospitalized patients with acute trauma.

ObjectiveTo evaluate the prognostic value of the Prehospital Index (PHI) for hospitalized patients with acute trauma.Materials and methodsPHI score and the Injury Severity Score (ISS) were determined in 1,802 hospitalized patients with acute trauma. Receiver-operator characteristic (ROC) curves were used to compare the PHI and ISS in subgroups, and corresponding prediction indicators were calculated.ResultsThere were significant differences in PHI score and ISS between the survival group and the death group (Z=2.674, P=0.007). The area under the ROC curve was 0.871 (95% CI 0.855–0.886) for PHI score and 0.792 (95% CI 0.773–0.811) for ISS. Optimal cutoff points to determine the risk of critical illness were PHI ≥4 and ISS ≥22. The sensitivity of the PHI was superior to the ISS (χ2=6.975, P=0.008), but the specificity and the accuracy of the PHI and ISS showed no significant difference (P>0.05).ConclusionThe PHI is valuable in prognostic prediction of hospitalized patients with acute trauma, and it is superior to the ISS. The PHI has such advantages as being simple in operation, easy to learn, capable of reflecting conditions timely and reliably, and suitable for dynamic evaluation and screening for critical patients with trauma.

Current state of trauma care in China, tools to predict death and ICU admission after arrival to hospital

BackgroundIn China, a nationwide emergency system takes charge of pre-hospital emergency services, and it adopts a proximity principle to send trauma patients to the nearest hospitals. However, many severely injured patients have been sent to low level hospitals with no capability to treat severe trauma. Thus those patients with high probability of in-hospital death or intensive care unit (ICU) admission need to be identified in the emergency department (ED) for optimal utilisation of hospital resources and better patient outcomes. The purpose of the study was to develop a computerised tool to aid ED physicians’ prediction of in-hospital death and ICU admission for trauma patients after arrival to hospital. MethodsWe reviewed a sample of 1,299 trauma patients who had been directly sent to the ED at Kailuan Hospital, North China. After excluding those cases with incomplete data entry, information of 1,195 patients was employed for analysis. The primary outcome was severe trauma that either resulted in death in hospital or in ICU admission. We proposed to use a complementary approach to combine the Pre-Hospital Index (PHI), the Trauma Index (TI), and the Glasgow Coma Score (GCS) in a decision support system (DSS) to assess trauma and predict in-hospital death and ICU admission. The sensitivity, specificity, over-triage rate, and under-triage rate were used as measurements to compare system performances of the DSS with the three scoring tools. ResultsAmong the 1,195 patients, 30 (2.5%) had severe trauma. The proposed DSS showed the best sensitivity (66.7%; 95% CI: 49.8–83.6%) among all the four studied tools. The TI (sensitivity 50.0%, 95% CI: 32.2–67.8%) performed slightly better than the GCS (sensitivity 46.7%, 95% CI: 28.9–64.5%), while both the TI and GCS performed better than the PHI (sensitivity 30.0%, 95% CI: 13.5–46.5%). The performance differences between the DSS and the three extant scoring tools were statistically significant. ConclusionsThe proposed DSS outperformed the extant trauma scoring systems. It has a strong potential to help ED physicians identify severe trauma, optimally utilise hospital resources, and recommend appropriate triage and treatment strategies for trauma patients that have strong possibilities for in-hospital death and ICU admission.

The application value of prehospital index in hospitalized patients with acute trauma

Objective To evaluate application value of prehospital index (PHI) in hospitalized with acute trauma.Methods A study was done in 1802 hospitalized with acute trauma by random sampling.PHI and injury severity score (ISS) were made respectively.Receiver operating characteristic curve (ROC curve) was used for detecting optimal cut-off point by taking date of discharge as endpoint and outcome as observed indicator.In order to compare predicting prognosis value of PHI in hospitalized with acute trauma,the corresponding predicting indicators were calculated and ISS was used for reference.Results The area under ROC curve was 0.871 (95％ CI:0.855-0.886) by score of PHI and 0.792 (95％ CI:0.773-0.811) by score of ISS,and there was statistically difference between two scoring systems (Z =2.674,P =0.007),and optimal cut-off point was used for judging the potential for critically ill patients when PHI was ≥ 4,ISS ≥ 22.The sensitivity predictors of critically ill death of PHI was superior to ISS (x2 =6.975,P =0.008),the specificity and accuracy of PHI and ISS showed no significant difference (P ＞ 0.05).Conclusions PHI has high potential for assessing patient condition and predicting death of hospitalized with acute trauma,and it is equivalent to ISS in prediction value.The advantages of PHI are simple in operation,easy to learn,reflecting condition timely and reliably,suitable for dynamic evaluation and comparison,which is suitable for critical with trauma of preliminary screening. Key words: Prehospital index; Trauma; Acute; Hospitalized patient; Injury severity score ; Condition assessment

Risk Adjustment Measures and Outcome Measures for Prehospital Trauma Research: Recommendations from the Emergency Medical Services Outcomes Project (EMSOP)

The objectives were to conduct a comprehensive, systematic review of the literature for risk adjustment measures (RAMs) and outcome measures (OMs) for prehospital trauma research and to use a structured expert panel process to recommend measures for use in future emergency medical services (EMS) trauma outcomes research. A systematic literature search and review was performed identifying the published studies evaluating RAMs and OMs for prehospital injury research. An explicit structured review of all articles pertaining to each measure was conducted using the previously established methodology developed by the Canadian Physiotherapy Association ("Physical Rehabilitation Outcome Measures"). Among the 4,885 articles reviewed, 96 RAMs and/or OMs were identified from the existing literature (January 1958 to February 2010). Only one measure, the Glasgow Coma Scale (GCS), currently meets Level 1 quality of evidence status and a Category 1 (strong) recommendation for use in EMS trauma research. Twelve RAMs or OMs received Category 2 status (promising, but not sufficient current evidence to strongly recommend), including the motor component of GCS, simplified motor score (SMS), the simplified verbal score (SVS), the revised trauma score (RTS), the prehospital index (PHI), EMS provider judgment, the revised trauma index (RTI), the rapid acute physiology score (RAPS), the rapid emergency medicine score (REMS), the field trauma triage (FTT), the pediatric triage rule, and the out-of-hospital decision rule for pediatrics. Using a previously published process, a structured literature review, and consensus expert panel opinion, only the GCS can currently be firmly recommended as a specific RAM or OM for prehospital trauma research (along with core measures that have already been established and published). This effort highlights the paucity of reliable, validated RAMs and OMs currently available for outcomes research in the prehospital setting and hopefully will encourage additional, methodologically sound evaluations of the promising, Category 2 RAMs and OMs, as well as the development of new measures.

Evaluation of the Prehospital Index, presence of high-velocity impact and judgment of emergency medical technicians as criteria for trauma triage

We sought to evaluate the performance of the Prehospital Index (PHI), the high velocity impact (HVI) criterion and emergency medical technician (EMT) judgment for the prehospital triage of injured patients. The study population included all prehospital trauma patients transported by an emergency medical service to 2 level I trauma centres for adults. All prehospital run sheets were linked to trauma registry data. The main outcome was severe trauma, defined as death within 72 hours, admission to the intensive care unit within 24 hours or an Injury Severity Score greater than 15. We assessed sensitivity, specificity and rates of overtriage. Of 16,805 patients in the study population, 1113 (6.62%) had severe trauma. The combination of all 3 triage criteria (PHI score > or = 4, HVI presence and EMT judgment) performed best for identifying patients with severe trauma, with a sensitivity of 74.2% but with an overtriage rate of 85.1%. Alone, EMT judgment had the highest sensitivity and a PHI score of 4 or greater had the low est rate of overtriage. Although the combination of PHI score, HVI presence and EMT judgment offers the highest sensitivity for the identification of patients that could benefit from direct transport to a level I trauma centre, overall sensitivity remains low and over triage is high. More research is required to improve prehospital triage.

Assessment of Mortality in Older Trauma Patients Sustaining Injuries from Falls or Motor Vehicle Collisions Treated in Regional Level I Trauma Centers

To compare mortality in elderly trauma patients sustaining fall or motor vehicle collision (MVC) related injuries and who are subsequently treated at regional Level I (tertiary) trauma centers. An increase in the mean age of the Canadian population is leading to a higher proportion of older patients injured in falls who are subsequently treated at Level 1 trauma centers in Quebec. The Level 1 centers were designed to treat younger patients injured in MVCs and violent acts. As a result, discordance may exist between the type of care supplied at these centers and the increased demand for care tailored to older trauma patients. A retrospective cohort study comprised of 4,717 patients over the age of 65; 606 (12.8%) injured in MVCs and 4,111 (87.2%) in falls. The mean (SD) age was 79.6 (8.0) years and 67.9% were female. The mean (SD) Injury Severity Score (ISS) was 10.8 (7.4). Data were obtained from the Quebec Trauma Registry (QTR) for patients treated at 3 Level I trauma centers in the province of Quebec, Canada. The primary outcome measure in this study was mortality. Being injured in a fall was a strong predictor for mortality, with an odds ratio of 5.11 (95% C.I. = 1.84-14.17, P = 0.002). Additionally, the adjusted mortality rate was 25.3% among fall victims, versus 7.8% for MVC patients. Female gender, older age, higher ISS and an increasing number of injuries were all associated with heightened mortality. In contrast, the number of body regions injured, experiencing complications, sustaining a hip fracture, the Revised Trauma Score, the Prehospital Index and the Charlson (comorbidity) Index had no association with mortality in the Level I centers. Elderly patients sustaining fall-related injuries and treated at Level I trauma centers are at risk for excess mortality when compared with those injured in MVCs. Effective and efficient methods for treating this population must be determined.

Automatically-Computed Prehospital Severity Scores are Equivalent to Scores Based on Medic Documentation

Prehospital severity scores can be used in routine prehospital care, mass casualty care, and military triage. If computers could reliably calculate clinical scores, new clinical and research methodologies would be possible. One obstacle is that vital signs measured automatically can be unreliable. We hypothesized that Signal Quality Indices (SQI's), computer algorithms that differentiate between reliable and unreliable monitored physiologic data, could improve the predictive power of computer-calculated scores. In a retrospective analysis of trauma casualties transported by air ambulance, we computed the Triage Revised Trauma Score (RTS) from archived travel monitor data. We compared the areas-under-the-curve (AUC's) of receiver operating characteristic curves for prediction of mortality and red blood cell transfusion for 187 subjects with comparable quantities of good-quality and poor-quality data. Vital signs deemed reliable by SQI's led to significantly more discriminatory severity scores than vital signs deemed unreliable. We also compared automatically-computed RTS (using the SQI's) versus RTS computed from vital signs documented by medics. For the subjects in whom the SQI algorithms identified 15 consecutive seconds of reliable vital signs data (n = 350), the automatically-computed scores' AUC's were the same as the medic-based scores' AUC's. Using the Prehospital Index in place of RTS led to very similar results, corroborating our findings. SQI algorithms improve automatically-computed severity scores, and automatically-computed scores using SQI's are equivalent to medic-based scores.

Effect of Emergency Medical Technician Certification for All Prehospital Personnel in a Latin American City

In Mexico and most other Latin American countries, many emergency medical services (EMS) systems rely on employees and volunteers with only on-the-job training and without formal Emergency Medical Technician (EMT) certification. This study sought to evaluate the costs and effectiveness of providing EMT certification to all personnel working in an EMS service in a Mexican city. At baseline, only 20% of the prehospital personnel (medics) working for the EMS service in Santa Catarina, Nuevo Leon, Mexico had EMT certification. During a 14-month period, all such medics obtained EMT certification. The process and outcome of trauma care were assessed before and after this training. Mortality among persons treated by this EMS service decreased from 1.8% Before to 0.5% after the training. The injury severity, as reflected by the prehospital index (PHI), was different between the two periods. Hence, adjustment for PHI by logistic regression was performed. The PHI- adjusted odds ratio for death in the after period was 0.55 compared with the before period, representing a 45% reduction in risk of death after EMT training. These data support the promotion of policies that require and enable EMT certification for all prehospital care providers in Mexico and potentially also in other Latin American and other middle-income developing countries.

Long-Term Evaluation of Prehospital Trauma Patient Triage in a Large Urban Area*

To evaluate emergency medical technician (EMT) compliance after introduction of trauma patient triage protocols to level I or II trauma centers in a major urban area. A population-based cohort of all trauma victims transported from 1994 to 2001 was assembled. Triage protocols based on the Prehospital Index and high-velocity impact were introduced in July of 1995. Two sets of criteria were developed, one for patients intended specifically for the level I trauma centers and another for patients intended to either level I or II centers. Trauma patients having met triage criteria were identified and the type of hospital to which the patient was taken was compared to that expected by the protocols. Overall, 16,356 patients met trauma triage criteria for direct transport to a trauma center (level I or II) during the 7 years under study. In the 10 months prior to implementation of trauma triage protocols, 57% of these patients were directly transported to appropriate level centers. Following protocol implementation, compliance rose to 80% (p < 0.001). 2 years following protocol implementation, the appropriate triage rate reached 91% (p < 0.001). For the specific protocol pertaining to the most severely injured intended for the level I centers, compliance was lower and took longer to improve. A systematic approach to triage of severely injured trauma patients in the prehospital setting is possible to implement and is appropriately applied by EMTs.

Selection bias found in interpreting analyses with missing data for the prehospital index for trauma

Objective To evaluate the effects of missing data on analyses of data from trauma databases, and to verify whether commonly used techniques for handling missing data work well in theses settings. Study design and setting Measures of trauma severity such as the Pre-Hospital Index (PHI) are used for triage and the evaluation of trauma care. As conditions of trauma patients can rapidly change over time, estimating the change in PHI from the arrival at the emergency room to hospital admission is important. We used both simulated and real data to investigate the estimation of PHI data when some data are missing. Techniques compared include complete case analysis, single imputation, and multiple imputation. Results It is well known that complete case analyses and single imputation methods often lead to highly misleading results that can be corrected by multiple imputation, an increasingly popular method for missing data situations. In practice, unverifiable assumptions may not hold, meaning that it may not be possible to draw definitive conclusions from any of the methods. Conclusion Great care is required whenever missing data arises. This is especially true in trauma databases, which often have much missing data and where the data may not missing at random.

Selection bias found in interpreting analyses with missing data for the prehospital index for trauma

Selection bias found in interpreting analyses with missing data for the prehospital index for trauma

Analysis of prehospital transport of head-injured patients after consolidation of neurosurgery resources.

Consolidation of neurosurgical (NS) services resulted in emergency medical services guidelines mandating transport of head-injured patients to the NS center if the Glasgow Coma Scale score is < 14 and prehospital index is > 3. This study determined what paramedic, system, or patient factors were associated with secondary head-injury transfer. This study was a retrospective chart review from January 1996 to November 1998. Ninety-one patient charts were reviewed. The median transport delay to the NS site was 4 hours 22 minutes. After transfer, 79 (96%) patients were admitted, 25 (30%) underwent craniotomy, and 18 (22%) died. The final diagnosis in 35 (43%) cases was subdural hematoma. Triage guidelines were violated in five patients (6%) and the NS center was on diversion in three (4%) cases. Most delays were related to patient presentations; 17 (21%) patients had no history of head trauma. Unpredictable patient factors were the most frequent reasons patients required secondary transfer; few protocol violations or system factors were identified. No modifications to the current NS triage criteria are recommended.

Adopting the pre-hospital index for interfacility helicopter transport: a proposal

Background: Interfacility helicopter transport is expensive without proven outcome benefit in trauma patients. Our objectives were to determine the fastest method of rural to urban interfacility transport, and develop a triage tool to identify patients most in need of rapid transport. Methods: Retrospective cohort study. Adults ISS≥12 transported from January 1996 to December 1998. Transport time variables were compared between geographical zones. A pre-transport index (PTI) identified two patient cohorts in which outcome was assessed. Results: Air ambulance was faster than ground transport, with helicopter overall superior to fixed-wing (<225km range). Seventy-two percent of patients with PTI<4 (n=196) had no outcome indicating severe injury versus 29% of the PTI≥4 cohort (n=151). Mortality for PTI<4 was 1.4% versus 22% for PTI≥4. Conclusion: Interfacility helicopter transport of severely injured rural trauma patients was the overall fastest method within a 225km range. PTI>4 identifies patients most in need of this fast but expensive method of transport.

Field triage of trauma patients: Improving on the Prehospital Index

The purpose of the present study was to evaluate the predictive ability of the Prehospital Index (PHI) in identifying injury severity and to develop a trauma triage scale that incorporates, along with the PHI, a subset of time independent variables to improve the predictive ability of the PHI-based triage instrument. This study included 1,291 trauma patients treated in Montreal, Canada. The developed trauma triage protocol was based on logistic regression analysis, in which the model that predicts the data best was selected by using Bayesian information criterion. The selected regression model included the variables age, body region injured, mechanism of injury, comorbidity, and PHI. This algorithm was a substantial improvement in detecting major versus nonmajor injuries (major injury defined based on death, intensive care unit admission, and surgery intervention) over the PHI alone (area under the receiver operating characteristic curve: 0.76 v 0.66, P < .05). Considering time independent variables could lead to better injury triage decisions. (Am J Emerg Med 2002;20:170-176. Copyright 2002, Elsevier Science (USA). All rights reserved.)