Pao-Jen Kuo

Using the Reverse Shock Index at the Injury Scene and in the Emergency Department to Identify High-Risk Patients: A Cross-Sectional Retrospective Study

Background: The ratio of systolic blood pressure (SBP) to heart rate (HR), called the reverse shock index (RSI), is used to evaluate the hemodynamic stability of trauma patients. A SBP lower than the HR (RSI < 1) indicates the probability of hemodynamic shock. The objective of this study was to evaluate whether the RSI as evaluated by emergency medical services (EMS) personnel at the injury scene (EMS RSI) and the physician in the emergency department (ED RSI) could be used as an additional variable to identify patients who are at high risk of more severe injury. Methods: Data obtained from all 16,548 patients added to the trauma registry system at a Level I trauma center between January 2009 and December 2013 were retrospectively reviewed. Only patients transferred by EMS were included in this study. A total of 3715 trauma patients were enrolled and subsequently divided into four groups: group I patients had an EMS RSI ≥1 and an ED RSI ≥1 (n = 3485); group II an EMS RSI ≥ 1 and an ED RSI < 1 (n = 85); group III an EMS RSI < 1 and an ED RSI ≥ 1 (n = 98); and group IV an EMS RSI < 1 and a ED RSI < 1 (n = 47). A Pearson’s χ2 test, Fisher’s exact test, or independent Student’s t-test was conducted to compare trauma patients in groups II, III, and IV with those in group I. Results: Group II and IV patients had a higher injury severity score, a higher incidence of commonly associated injuries, and underwent more procedures (including intubation, chest tube insertion, and blood transfusion in the ED) than patients in group I. Group II and IV patients were also more likely to receive a severe injury to the thoracoabdominal area. These patients also had worse outcomes regarding the length of stay in hospital and intensive care unit (ICU), the proportion of patients admitted to ICU, and in-hospital mortality. Group II patients had a higher adjusted odds ratio for mortality (5.8-times greater) than group I patients. Conclusions: Using an RSI < 1 as a threshold to evaluate the hemodynamic condition of the patients at the injury scene and upon arrival to the ED provides valid information regarding deteriorating outcomes for certain subgroups of patients in the ED setting. Particular attention and additional resources should be provided to patients with an EMS RSI ≥ 1 that deteriorates to an RSI < 1 upon arrival to the ED since a higher odds of mortality was found in these patients.

Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System

Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0–2.5%. However, few data or predictive models are available for the identification of patients with a high mortality risk. In this study, we aimed to construct a model for mortality prediction using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry, in a Level 1 trauma center. Methods: Five hundred and forty-five patients with isolated tSAH, including 533 patients who survived and 12 who died, between January 2009 and December 2016, were allocated to training (n = 377) or test (n = 168) sets. Using the data on demographics and injury characteristics, as well as laboratory data of the patients, classification and regression tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: In this established DT model, three nodes (head Abbreviated Injury Scale (AIS) score ≤4, creatinine (Cr) <1.4 mg/dL, and age <76 years) were identified as important determinative variables in the prediction of mortality. Of the patients with isolated tSAH, 60% of those with a head AIS >4 died, as did the 57% of those with an AIS score ≤4, but Cr ≥1.4 and age ≥76 years. All patients who did not meet the above-mentioned criteria survived. With all the variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 90.9% and specificity of 98.1%) and 97.7% (sensitivity of 100% and specificity of 97.7%), for the training set and test set, respectively. Conclusions: The study established a DT model with three nodes (head AIS score ≤4, Cr <1.4, and age <76 years) to predict fatal outcomes in patients with isolated tSAH. The proposed decision-making algorithm may help identify patients with a high risk of mortality.

Stress-Induced Hyperglycemia, but Not Diabetic Hyperglycemia, Is Associated with Higher Mortality in Patients with Isolated Moderate and Severe Traumatic Brain Injury: Analysis of a Propensity Score-Matched Population

Background: Admission hyperglycemia is associated with higher morbidity and mortality in patients with traumatic brain injury (TBI). Stress-induced hyperglycemia (SIH), a form of hyperglycemia induced by the stress response, is associated with increased patient mortality following TBI. However, admission hyperglycemia occurs not only in SIH but also in patients with diabetic hyperglycemia (DH). Current information regarding whether trauma patients with SIH represent a distinct group with differential outcomes compared to those with DH remains limited. Methods: Serum glucose concentration ≥200 mg/dL upon arrival at the emergency department was defined as hyperglycemia. Presence of diabetes mellitus (DM) was determined by patient history and/or admission glycated hemoglobin (HbA1c) level ≥6.5%. In the present study, the patient cohort included those with moderate and severe TBI, as defined by an Abbreviated Injury Scale (AIS) score ≥3 points in the head, and excluded those who had additional AIS scores ≥3 points in any other region of the body. A total of 1798 adult patients with isolated moderate to severe TBI were allocated into four groups: SIH (n = 140), DH (n = 187), diabetic normoglycemia (DN, n = 186), and non-diabetic normoglycemia (NDN, n = 1285). Detailed patient information was retrieved from the Trauma Registry System at a level I trauma center between 1 January 2009, and 31 December 2015. Unpaired Student’s t- and Mann–Whitney U-tests were used to analyze normally and non-normally distributed continuous data, respectively. Categorical data were compared using the Pearson chi-square or two-sided Fisher’s exact tests. Matched patient populations were allocated in a 1:1 ratio according to propensity scores calculated by NCSS software. Logistic regression was used to evaluate the effect of SIH and DH on the adjusted mortality outcome. Results: In patients with isolated moderate to severe TBI, the presence of SIH and DH led to 9.1-fold and 2.3-fold higher odds of mortality, respectively, than patients with NDN. After adjusting for confounding factors, including sex and age, pre-existing co-morbidities, existence of different kinds of intracerebral hemorrhage, and injury severity, patients with SIH still had 6.6-fold higher odds of mortality than those with NDN; however, DH did not present significantly higher adjusted mortality odds. SIH and DH presented different effects on outcomes after TBI. The results also suggested that the pathophysiological effect associated with SIH was different from that of DH. Conclusions: This study demonstrated that patients with SIH and DH had significantly higher mortality than patients with NDN. However, the adjusted mortality was significantly higher only in the selected propensity score-matched patients with SIH and not in those with DH.

Higher Mortality in Trauma Patients Is Associated with Stress-Induced Hyperglycemia, but Not Diabetic Hyperglycemia: A Cross-Sectional Analysis Based on a Propensity-Score Matching Approach

Background: Stress-induced hyperglycemia (SIH) is a form of hyperglycemia secondary to stress and commonly occurs in patients with trauma. Trauma patients with SIH have been reported to have an increased risk of mortality. However, information regarding whether these trauma patients with SIH represent a distinct group with differential outcomes when compared to those with diabetic hyperglycemia (DH) remains limited. Methods: Diabetes mellitus (DM) was determined by patient history and/or admission glycated hemoglobin (HbA1c) ≥6.5%. Non-diabetic normoglycemia (NDN) was determined by a serum glucose level <200 mg/dL in the patients without DM. Diabetic normoglycemia (DN) was determined by a serum glucose level <200 mg/dL in the patients with DM. DH and SIH was diagnosed by a serum glucose level ≥200 mg/dL in the patients with and without DM, respectively. Detailed data of these four groups of hospitalized patients, which included NDN (n = 7806), DN (n = 950), SIH (n = 493), and DH (n = 897), were retrieved from the Trauma Registry System at a level I trauma center between 1 January 2009 and 31 December 2015. Patients with incomplete registered data were excluded. Categorical data were compared with Pearson chi-square tests or two-sided Fisher exact tests. The unpaired Student’s t-test and the Mann–Whitney U-test were used to analyze normally distributed continuous data and non-normally distributed data, respectively. Propensity-score-matched cohorts in a 1:1 ratio were allocated using NCSS software with logistic regression to evaluate the effect of SIH and DH on the outcomes of patients. Results: The SIH (median [interquartile range: Q1–Q3], 13 [9–24]) demonstrated a significantly higher Injury Severity Score (ISS) than NDN (9 [4–10]), DN (9 [4–9]), and DH (9 [5–13]). SIH and DH had a 12.3-fold (95% confidence interval [CI] 9.31–16.14; p < 0.001) and 2.4-fold (95% CI 1.71–3.45; p < 0.001) higher odds of mortality, respectively, when compared to NDN. However, in the selected propensity-score-matched patient population, SIH had a 3.0-fold higher odd ratio of mortality (95% CI 1.96–4.49; p < 0.001) than NDN, but DH did not have a significantly higher mortality (odds ratio 1.2, 95% CI 0.99–1.38; p = 0.065). In addition, SIH had 2.4-fold higher odds of mortality (95% CI 1.46–4.04; p = 0.001) than DH. These results suggest that the characteristics and injury severity of the trauma patients contributed to the higher mortality of these patients with hyperglycemia upon admission, and that the pathophysiological effect of SIH was different from that of DH. Conclusions: Although there were worse mortality outcomes among trauma patients presenting with hyperglycemia, this effect was only seen in patients with SIH, but not DH when controlling for age, sex, pre-existed co-morbidities, and ISS.

Characteristics and Outcomes of Patients Injured in Road Traffic Crashes and Transported by Emergency Medical Services

To investigate the injury characteristics and mortality of patients transported by emergency medical services (EMS) and hospitalized for trauma following a road traffic crash, data obtained from the Trauma Registry System were retrospectively reviewed for trauma admissions between 1 January 2009 and 31 December 2013 in a Level I trauma center. Of 16,548 registered patients, 3978 and 1440 patients injured in road traffic crashes were transported to the emergency department by EMS and non-EMS, respectively. Patients transported by EMS had lower Glasgow coma scale (GCS) scores and worse hemodynamic measures. Compared to patients transported by non-EMS, more patients transported by EMS required procedures (intubation, chest tube insertion, and blood transfusion) at the emergency department. They also sustained a higher injury severity, as measured by the injury severity score (ISS) and the new injury severity score (NISS). Lastly, in-hospital mortality was higher among the EMS than the non-EMS group (1.8% vs. 0.3%, respectively; p < 0.001). However, we found no statistically significant difference in the adjusted odds ratio (AOR) for mortality among patients transported by EMS after adjustment for ISS (AOR 4.9, 95% CI 0.33–2.26), indicating that the higher incidence of mortality was likely attributed to the patients’ higher injury severity. In addition, after propensity score matching, logistic regression of 58 well-matched pairs did not show a significant influence of transportation by EMS on mortality (OR: 0.578, 95% CI: 0.132–2.541 p = 0.468).

Systolic Blood Pressure Lower than Heart Rate upon Arrival at and Departure from the Emergency Department Indicates a Poor Outcome for Adult Trauma Patients

Background: Hemorrhage is a leading cause of preventable trauma death. In this study, we used the reverse shock index (RSI), a ratio of systolic blood pressure (SBP) to heart rate (HR), to evaluate the hemodynamic stability of trauma patients. As an SBP lower than the HR (RSI < 1) may indicate hemodynamic instability, the objective of this study was to assess the associated complications in trauma patients with an RSI < 1 upon arrival at the emergency department (ED) (indicated as (A)RSI) and at the time of departure from the ED (indicated as (L)RSI) to the operative room or for admission. Methods: Data obtained from all 16,548 hospitalized patients recorded in the trauma registry system at a Level I trauma center between January 2009 and December 2013 were retrospectively reviewed. A total of 10,234 adult trauma patients aged ≥20 were enrolled and subsequently divided into four groups: Group I, (A)RSI ≥ 1 and (L)RSI ≥ 1 (n = 9827); Group II, (A)RSI ≥ 1 and (L)RSI < 1 (n = 76); Group III, (A)RSI < 1 and (L)RSI ≥ 1 (n = 251); and Group IV, (A)RSI < 1 and (L)RSI < 1 (n = 80). Pearson’s χ2 test, Fisher’s exact test, or independent Student’s t-test was conducted to compare trauma patients in Groups II, III, and IV with those in Group I. Results: Patients in Groups II, III, and IV had a higher injury severity score and underwent a higher number of procedures, including intubation, chest tube insertion, and blood transfusion, than Group I patients. Additionally, patients of these groups had increased hospital length of stay (16.3 days, 14.9 days, and 22.0 days, respectively), proportion of patients admitted to the intensive care unit (ICU) (48.7%, 43.0%, and 62.5%, respectively), and in-hospital mortality (19.7%, 7.6%, and 27.5%, respectively). Although the trauma patients who had a SBP < 90 mmHg either upon arrival at or departure from the ED also present a more severe injury and poor outcome, those patients who had a SBP ≥ 90 mmHg but an RSI < 1 had a more severe injury and poor outcome than those patients who had a SBP ≥ 90 mmHg and an RSI ≥ 1. Conclusions: SBP lower than heart rate (RSI < 1) either upon arrival at or departure from the ED may indicate a detrimental sign of poor outcome in adult trauma patients even in the absence of noted hypotension.

Identification of Pancreatic Injury in Patients with Elevated Amylase or Lipase Level Using a Decision Tree Classifier: A Cross-Sectional Retrospective Analysis in a Level I Trauma Center

Background: In trauma patients, pancreatic injury is rare; however, if undiagnosed, it is associated with high morbidity and mortality rates. Few predictive models are available for the identification of pancreatic injury in trauma patients with elevated serum pancreatic enzymes. In this study, we aimed to construct a model for predicting pancreatic injury using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry in a Level I trauma center. Methods: A total of 991 patients with elevated serum levels of amylase (>137 U/L) or lipase (>51 U/L), including 46 patients with pancreatic injury and 865 without pancreatic injury between January 2009 and December 2016, were allocated in a ratio of 7:3 to training (n = 642) or test (n = 269) sets. Using the data on patient and injury characteristics as well as laboratory data, the DT algorithm with Classification and Regression Tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: Among the trauma patients with elevated amylase or lipase levels, three groups of patients were identified as having a high risk of pancreatic injury, using the DT model. These included (1) 69% of the patients with lipase level ≥306 U/L; (2) 79% of the patients with lipase level between 154 U/L and 305 U/L and shock index (SI) ≥ 0.72; and (3) 80% of the patients with lipase level <154 U/L with abdomen injury, glucose level <158 mg/dL, amylase level <90 U/L, and neutrophil percentage ≥76%; they had all sustained pancreatic injury. With all variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 91.4% and specificity of 98.3%) for the training set. In the test set, the DT achieved an accuracy of 93.3%, sensitivity of 72.7%, and specificity of 94.2%. Conclusions: We established a DT model using lipase, SI, and additional conditions (injury to the abdomen, glucose level <158 mg/dL, amylase level <90 U/L, and neutrophils ≥76%) as important nodes to predict three groups of patients with a high risk of pancreatic injury. The proposed decision-making algorithm may help in identifying pancreatic injury among trauma patients with elevated serum amylase or lipase levels.

Derivation and validation of different machine-learning models in mortality prediction of trauma in motorcycle riders: a cross-sectional retrospective study in southern Taiwan

Objectives This study aimed to build and test the models of machine learning (ML) to predict the mortality of hospitalised motorcycle riders. Setting The study was conducted in a level-1 trauma centre in southern Taiwan. Participants Motorcycle riders who were hospitalised between January 2009 and December 2015 were classified into a training set (n=6306) and test set (n=946). Using the demographic information, injury characteristics and laboratory data of patients, logistic regression (LR), support vector machine (SVM) and decision tree (DT) analyses were performed to determine the mortality of individual motorcycle riders, under different conditions, using all samples or reduced samples, as well as all variables or selected features in the algorithm. Primary and secondary outcome measures The predictive performance of the model was evaluated based on accuracy, sensitivity, specificity and geometric mean, and an analysis of the area under the receiver operating characteristic curves of the two different models was carried out. Results In the training set, both LR and SVM had a significantly higher area under the receiver operating characteristic curve (AUC) than DT. No significant difference was observed in the AUC of LR and SVM, regardless of whether all samples or reduced samples and whether all variables or selected features were used. In the test set, the performance of the SVM model for all samples with selected features was better than that of all other models, with an accuracy of 98.73%, sensitivity of 86.96%, specificity of 99.02%, geometric mean of 92.79% and AUC of 0.9517, in mortality prediction. Conclusion ML can provide a feasible level of accuracy in predicting the mortality of motorcycle riders. Integration of the ML model, particularly the SVM algorithm in the trauma system, may help identify high-risk patients and, therefore, guide appropriate interventions by the clinical staff.

Stress-Induced Hyperglycemia in Diabetes: A Cross-Sectional Analysis to Explore the Definition Based on the Trauma Registry Data

Background: The diagnosis of diabetic hyperglycemia (DH) does not preclude a diabetes patient from having a stress-induced hyperglycemic response. This study aimed to define the optimal level of elevated glucose concentration for determining the occurrence of stress-induced hyperglycemia (SIH) in patients with diabetes. Methods: This retrospective study reviewed the data of all hospitalized trauma patients, in a Level I trauma center, from 1 January 2009 to 31 December 2016. Only adult patients aged ≥20 years, with available data on serum glucose and glycated hemoglobin A1c (HbA1c) levels upon admission, were included in the study. Long-term average glucose levels, as A1c-derived average glucose (ADAG), using the equation, ADAG = ((28.7 × HbA1c) − 46.7), were calculated. Patients with high glucose levels were divided into three SIH groups with diabetes mellitus (DM), based on the following definitions: (1) same glycemic gap from ADAG; (2) same percentage of elevated glucose of ADAG, from which percentage could also be reflected by the stress hyperglycemia ratio (SHR), calculated as the admission glucose level divided by ADAG; or (3) same percentage of elevated glucose as patients with a defined SIH level, in trauma patients with and without diabetes. Patients with incomplete registered data were excluded. The primary hypothesis of this study was that SIH in patients with diabetes would present worse mortality outcomes than in those without. Detailed data of SIH in patients with diabetes were retrieved from the Trauma Registry System. Results: Among the 546 patients with DH, 332 (32.0%), 188 (18.1%), and 106 (10.2%) were assigned as diabetes patients with SIH, based on defined glucose levels, set at 250 mg/dL, 300 mg/dL, and 350 mg/dL, respectively. In patients with defined cut-off glucose levels of 250 mg/dL and 300 mg/dL, SIH was associated with a 3.5-fold (95% confidence interval (CI) 1.61–7.46; p = 0.001) and 3-fold (95% CI 1.11–8.03; p = 0.030) higher odds of mortality, adjusted by sex, age, pre-existing comorbidities, and injury severity score, than the 491 patients with diabetic normoglycemia (DN). However, in patients with a defined cut-off glucose level of 350 mg/dL, adjusted mortality in SIH in DM was insignificantly different than that in DM. According to the receiver operating characteristic (ROC) curve analysis, a blood sugar of 233 mg/dL, a glycemic gap of 79 (i.e., blood sugar of 251 mg/dL), and a SHR of 1.45 (i.e., blood sugar of 250 mg/dL) were identified as cut-offs for mortality outcomes, with AUCs of 0.622, 0.653, and 0.658, respectively. Conclusions: In this study, a cut-off glucose level of 250 mg/dL was selected to provide a better definition of SIH in DM than glucose levels of 300 mg/dL or 350 mg/dL.

Hyponatremia Is Associated with Worse Outcomes from Fall Injuries in the Elderly

Background: Hyponatremia has been proposed as a contributor to falls in the elderly, which have become a major global issue with the aging of the population. This study aimed to assess the clinical presentation and outcomes of elderly patients with hyponatremia admitted due to fall injuries in a Level I trauma center. Methods: We retrospectively reviewed data obtained from the Trauma Registry System for trauma admissions from January 2009 through December 2014. Hyponatremia was defined as a serum sodium level <135 mEq/L, and only patients who had sustained a fall at ground level (<1 m) were included. We used Chi-square tests, Student t-tests, and Mann-Whitney U tests to compare elderly patients (age ≥65 years) with hyponatremia (n = 492) to those without (n = 2002), and to adult patients (age 20–64 years) with hyponatremia (n = 125). Results: Significantly more elderly patients with hyponatremia presented to the emergency department (ED) due to falls compared to elderly patients without hyponatremia (73.7% vs. 52.6%; OR: 2.5, 95% CI: 2.10–3.02; p < 0.001). Elderly patients with hyponatremia presented with a worse outcome, measured by significantly higher odds of intubation (OR: 2.4, 95% CI: 1.15–4.83; p = 0.025), a longer in-hospital length of stay (LOS) (11 days vs. 9 days; p < 0.001), higher proportion of intensive care unit (ICU) admission (20.9% vs. 16.2%; OR: 1.4, 95% CI: 1.07–1.76; p = 0.013), and higher mortality (OR: 2.5, 95% CI: 1.53–3.96; p < 0.001), regardless of adjustment by Injury Severity Scores (ISS) (AOR: 2.4, 95% CI: 1.42–4.21; p = 0.001). Conclusions: Our results show that hyponatremia is associated with worse outcome from fall-related injuries in the elderly, with an increased ISS, longer LOS, and a higher risk of death.