Metabolic Augmentation of mREMS: Improved 30-day Mortality Prediction through Lactate and Base Excess Integration in Emergency Patients

ObjectiveAccurate risk stratification of emergency department (ED) patients transferred to the intensive care unit (ICU) is essential for improving outcomes. The traditional Modified Early Warning Score (MEWS) alone has limited utility in predicting mortality risk. Combining MEWS with arterial blood gas parameters—lactate (Lac) and base excess (BE)—may enhance predictive performance.MethodsA retrospective cohort study was conducted involving 262 ED patients admitted to the ICU, who were divided into a non-survivor group (n = 83, 28-day mortality rate: 31.68%) and a survivor group (n = 179). Multivariable Cox regression analysis was used to identify independent predictors of 28-day mortality. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, DeLong test, net reclassification improvement (NRI)/integrated discrimination improvement (IDI) metrics, and stratified validation.ResultsMultivariate Cox regression analysis showed that both Lac were independent risk factors for 28-day mortality (both p < 0.05). ROC curve analysis revealed that the Lac + BE + MEWS combined model achieved the highest area under the curve (AUC) of 0.819 (95% CI: 0.760–0.870), which was significantly superior to other models. The BE + MEWS model yielded an AUC of 0.805 (95% CI: 0.749–0.864), with no statistically significant difference from the Lac + BE + MEWS model (p = 0.098). NRI and IDI analyses indicated that both the BE + MEWS and Lac + BE + MEWS models markedly improved predictive performance (NRI: 85.9 and 83.1%, respectively; IDI: 0.249 and 0.255, respectively; both p < 0.001). Notably, BE conferred greater incremental value to MEWS than Lac. Stratified validation confirmed that the Lac + BE + MEWS model exhibited the best stability and risk-stratification capacity, especially in the intermediate-risk stratum (5 ≤ MEWS ≤ 8, AUC = 0.812).ConclusionLac and BE are independent predictors of 28-day mortality in ED patients admitted to the ICU. BE adds significantly more predictive value to MEWS than Lac. The Lac + BE + MEWS combined model demonstrates the strongest stability and optimal risk-stratification performance, particularly for patients with MEWS scores of 5–8.

Severe injury and shock are frequently associated with abnormalities in patient body temperature. Substantial increases in mortality have been associated with profound hypothermia, especially below 35 degrees C. The purpose of this study was to further characterize the impact of hypothermia in a large dataset of trauma patients. This study was a retrospective analysis of the 2004 version of the National Trauma Data Bank (NTDB), which contains approximately 1.1 million patients from over 400 trauma centers. Admission temperature was analyzed with respect to mortality, injury severity score (ISS), base deficit (BD), Glasgow Coma Score (GCS), and hospital outcomes. The NTDB contained 701,491 patients with temperatures recorded upon trauma center admission. Of these, 11,026 patients had admission temperatures <35 degrees C, and 802 had temperatures <32 degrees C. Comparison of core temperature versus mortality revealed that as temperature decreased, the mortality rate increased, reaching approximately 39% at 32 degrees C, and remained constant at lower temperatures. Surprisingly, 477 patients (59.5%) survived with temperatures <32 degrees C. Similarly, BD increased as hypothermia worsened until body temperature reached 31 degrees C, below which there was little further increase. Patients with admission temperatures less than 35 degrees C had significantly greater mortality (25.5% vs. 3.0%, P < 0.001) and BD (7.8 vs. 3.7, P < 0.001) when compared with patients with temperatures >or=35 degrees C. In survivors, average ventilator days and intensive care unit (ICU) days were 14.4 and 12.8, respectively, for patients with temperatures <35 degrees C as opposed to more normothermic patients who demonstrated an average of 9.5 ventilator days and 9.1 ICU days (P < 0.001). When grouped by individual ISS, BD level, and GCS motor score, mortality was significantly greater when admission temperature was below 35 degrees C (ISS mean difference = 11.4%, BD mean difference = 22.8%, and GCS motor mean difference = 9.85%). Logistic regression revealed that hypothermia remains an independent determinant of mortality after correction for confounding variables (odds ratio = 1.54, 95% confidence interval 1.40-1.71). Admission hypothermia is associated with greater mortality, increased injury severity, more profound acidosis, and prolonged ICU/ventilator courses. However, although mortality at <32 degrees C is high, patients with temperatures this low do survive. As temperatures drop below 32 degrees C, mortality rates remain constant, which may indicate a threshold below which physiologic mechanisms are unable to correct body temperature regardless of injury severity. Although shock severity is highly indicative of outcome, hypothermia independently contributes to the substantial mortality associated with severe injury.

Objectives: The shock index (SI) and its derivations, the modified shock index (MSI) and the age shock index (Age SI), have been used to identify trauma patients with unstable hemodynamic status. The aim of this study was to evaluate their use in predicting the requirement for massive transfusion (MT) in trauma patients upon arrival at the hospital. Participants: A patient receiving transfusion of 10 or more units of packed red blood cells or whole blood within 24 h of arrival at the emergency department was defined as having received MT. Detailed data of 2490 patients hospitalized for trauma between 1 January 2009, and 31 December 2014, who had received blood transfusion within 24 h of arrival at the emergency department, were retrieved from the Trauma Registry System of a level I regional trauma center. These included 99 patients who received MT and 2391 patients who did not. Patients with incomplete registration data were excluded from the study. The two-sided Fisher exact test or Pearson chi-square test were used to compare categorical data. The unpaired Student t-test was used to analyze normally distributed continuous data, and the Mann-Whitney U-test was used to compare non-normally distributed data. Parameters including systolic blood pressure (SBP), heart rate (HR), hemoglobin level (Hb), base deficit (BD), SI, MSI, and Age SI that could provide cut-off points for predicting the patients’ probability of receiving MT were identified by the development of specific receiver operating characteristic (ROC) curves. High accuracy was defined as an area under the curve (AUC) of more than 0.9, moderate accuracy was defined as an AUC between 0.9 and 0.7, and low accuracy was defined as an AUC less than 0.7. Results: In addition to a significantly higher Injury Severity Score (ISS) and worse outcome, the patients requiring MT presented with a significantly higher HR and lower SBP, Hb, and BD, as well as significantly increased SI, MSI, and Age SI. Among these, only four parameters (SBP, BD, SI, and MSI) had a discriminating power of moderate accuracy (AUC > 0.7) as would be expected. A SI of 0.95 and a MSI of 1.15 were identified as the cut-off points for predicting the requirement of MT, with an AUC of 0.760 (sensitivity: 0.563 and specificity: 0.876) and 0.756 (sensitivity: 0.615 and specificity: 0.823), respectively. However, in the groups of patients with comorbidities such as hypertension, diabetes mellitus, or coronary artery disease, the discriminating power of these three indices in predicting the requirement of MT was compromised. Conclusions: This study reveals that the SI is moderately accurate in predicting the need for MT. However, this predictive power may be compromised in patients with HTN, DM or CAD. Moreover, the more complex calculations of MSI and Age SI failed to provide better discriminating power than the SI.

Aim: Methanol poisoning (MP) is an significant medical problem worldwide, and despite advances in diagnosis and treatment, the mortality rate in these cases remains high. This study aimed to evaluate the clinical and laboratory factors to determine in-hospital mortality in patients with MP.Methods: This single-center, retrospective, observational study was conducted with 65 adult MP cases visiting the emergency department (ED) of a tertiary training and research hospital, between January 01, 2017 and February 01, 2022. Data was statistically compared between survivors and non-survivors.Results: The in-hospital mortality rate was 41.5%. The rate of cases with respiratory distress, low Glasgow coma scale (GCS) (≤8), and delayed arrival to the hospital (&amp;gt;24 hours) was higher in the group of non-survivors compared to the group of survivors. Non-survivors had a higher anion gap (30.5 mEq/L vs. 25.5mEq/L), base excess (-25.0 mmol/L vs. -18.6 mmol/L), lactate (10.2 mmol/L vs. 2.2 mmol/L) levels, and lower pH (6.76 vs. 7.14) and bicarbonate (6.3 mmol/L vs. 10.3 mmol/L) levels than survivors (p&amp;lt;0.001). In ROC analysis, pH (AUC= 0.916) and base excess (AUC=0.915) were blood gas parameters with the highest AUC values in predicting mortality in MP cases. Folate use in the treatment had a statistically significant effect on mortality (P=0.015).Conclusion: In MP cases, delay in a hospital visit, severe metabolic acidosis, high lactate levels, low GCS on arrival to the ED and no folate therapy, were associated with increased in-hospital mortality rates. Our data will contribute to the clinical management of MP patients and the development of treatment protocols.

Sepsis is a critical condition resulting from a poor immune response to infection, often leading to complications like sepsis-associated encephalopathy (SAE). Research suggests a link between sedation and analgesia use and SAE development in intensive care unit (ICU) patients, but study inconsistencies limit definitive conclusions. This study aims to explore the relationship between sedation and analgesia scores and the occurrence of SAE in the ICU, as well as their impact on clinical effectiveness and patient prognosis. Between January 1, 2021, and August 30, 2022, a retrospective analysis of 356 sepsis cases was conducted in the Emergency ICU of the Affiliated Hospital of Guizhou Medical University. After excluding 102 patients, 219 were included and divided into SAE and non-SAE groups for analysis. The SAE group demonstrated higher age, Sequential Organ Failure Assessment (SOFA) scores, and APACHE II scores, alongside longer ICU durations and lower Glasgow Coma Scale (GCS) scores (p < 0.05) compared to the non-SAE group. Furthermore, the levels of lactate dehydrogenase (LDH), interleukin-6 (IL-6), and blood lactate were significantly increased in the SAE group (p < 0.05). After adjustments for baseline characteristics, biochemical indices, risk assessment scores, and clinical features, multivariate analysis identified age, APACHE II score, LDH, IL-6, oxygenation index, base excess (BE), and base excess of extracellular fluid (BE(ecf)) as significant risk factors for encephalopathy in septic patients (p < 0.05). ROC curve analysis indicated that the area under the curve (AUC) for predicting SAE was 0.810 (95% CI: 0.785-0.831) for the APACHE II score, 0.780 (95% CI: 0.743-0.801) for IL-6, and 0.769 (95% CI: 0.730-0.836) for BE. Sensitivity values were 81.1, 77.4, and 70.6%, while specificity values were 70.3, 72.3, and 71.3%. Patients with sepsis influenced by these factors exhibited an increased likelihood of developing SAE. Additionally, RASS and BPS scores were significantly correlated with the prognosis of sepsis patients (p < 0.05). The study demonstrated that patients with SAE exhibit physiological disturbances, including elevated inflammatory markers (IL-6 and LDH), impaired oxygenation, and acid-base imbalances, which may contribute to more severe clinical courses. Additionally, RASS and BPS scores were found to be reliable indicators of patient prognosis in sepsis. These findings may guide clinical practice in managing patients with SAE.

BackgroundThe World Health Organization (WHO) reports that Asia and Africa have the highest Chronic Liver Disease (CLD) mortality rate. Cirrhosis, responsible for 22.2 fatalities per 100,000 people, is India’s 10th most common cause of mortality. The increasing prevalence of chronic liver disease necessitates a study to identify predictive factors for patients who visit the emergency department. Identifying elements that enhance the predictive value of mortality in unstable patients with CLD complications is important in emergency departments. This study aims to determine Clinical and Laboratory Parameters as mortality predictors in adult chronic liver disease patients.MethodologyThe study was conducted at the emergency department of a tertiary healthcare center in Northern India. Patients with chronic liver disease above 18 years of age who satisfied the inclusion criteria were clinically evaluated. Clinical and demographic details were collected, and data was analyzed.ResultsTwo hundred thirty-six patients were enrolled. The mean age was 50.77 ± 14.26 years. 78.4% of the participants were men. Abdominal distension, affecting 59.7% of patients, was the most common presenting ailment, followed by melena and hematemesis, affecting 41.9% and 32.6%, respectively. The mean stay in the emergency department was 10.29 ± 8.10 h. Refractory septic shock, the leading cause of mortality, accounts for 69.2% of all deaths, alongside grade 4 hepatic encephalopathy and massive Upper Gastrointestinal (UGI) bleeding, as identified in our study. Factors such as altered mental sensorium, high respiratory rate, low SpO2, increased heart rate, low systolic blood pressure, low diastolic blood pressure, and low Glasgow Coma Scale (GCS) on Emergency Department (ED) arrival are significantly associated with mortality.ConclusionsChronic liver disease, a prevalent condition in India, most commonly seen in middle aged men and lower socioeconomic groups. The parameters independently associated with mortality in our study were presence of altered mental sensorium, Glasgow coma scale, Child Pugh class and need for ICU admission. Understanding the presentation pattern, and mortality predictors can help ED physicians in managing acute events and follow-ups.

Military and civilian data would suggest that hemostatic resuscitation results in improved outcomes for exsanguinating patients. However, identification of those patients who are at risk of significant hemorrhage is not clearly defined. We attempted to identify factors that would predict the need for massive transfusion (MT) in an Australasian trauma population, by comparing those trauma patients who did receive massive transfusion with those who did not. Between 1985 and 2010, 1,686 trauma patients receiving at least 1 U of packed red blood cells were identified from our prospectively maintained trauma registry. Demographic, physiologic, laboratory, injury, and outcome variables were reviewed. Univariate analysis determined significant factors between those who received MT and those who did not. A predictive multivariate logistic regression model with backward conditional stepwise elimination was used for MT risk. Statistical analysis was performed using SPSS PASW. MT patients had a higher pulse rate, lower Glasgow Coma Scale (GCS) score, lower systolic blood pressure, lower hemoglobin level, higher Injury Severity Score (ISS), higher international normalized ratio (INR), and longer stay. Initial logistic regression identified base deficit (BD), INR, and hemoperitoneum at laparotomy as independent predictive variables. After assigning cutoff points of BD being greater than 5 and an INR of 1.5 or greater, a further model was created. A BD greater than 5 and either INR of 1.5 or greater or hemoperitoneum was associated with 51 times increase in MT risk (odds ratio, 51.6; 95% confidence interval, 24.9-95.8). The area under the receiver operating characteristic curve for the model was 0.859. From this study, a combination of BD, INR, and hemoperitoneum has demonstrated good predictability for MT. This tool may assist in the determination of those patients who might benefit from hemostatic resuscitation. Prognostic study, level III.

Background: Military and civilian data would suggest that hemostatic resuscitation results in improved outcomes for exsanguinating patients. However, identification of those patients who are at risk of significant hemorrhage is not clearly defined. We attempted to identify factors that would predict the need for massive transfusion (MT) in an Australasian trauma population, by comparing those trauma patients who did receive massive transfusion with those who did not. Methods: Between 1985 and 2010, 1,686 trauma patients receiving at least 1 U of packed red blood cells were identified from our prospectively maintained trauma registry. Demographic, physiologic, laboratory, injury, and outcome variables were reviewed. Univariate analysis determined significant factors between those who received MT and those who did not. A predictive multivariate logistic regression model with backward conditional stepwise elimination was used for MT risk. Statistical analysis was performed using SPSS PASW. Results: MT patients had a higher pulse rate, lower Glasgow Coma Scale (GCS) score, lower systolic blood pressure, lower hemoglobin level, higher Injury Severity Score (ISS), higher international normalized ratio (INR), and longer stay. Initial logistic regression identified base deficit (BD), INR, and hemoperitoneum at laparotomy as independent predictive variables. After assigning cutoff points of BD being greater than 5 and an INR of 1.5 or greater, a further model was created. A BD greater than 5 and either INR of 1.5 or greater or hemoperitoneum was associated with 51 times increase in MT risk (odds ratio, 51.6; 95% confidence interval, 24.9Y95.8). The area under the receiver operating characteristic curve for the model was 0.859. Conclusion: From this study, a combination of BD, INR, and hemoperitoneum has demonstrated good predictability for MT. This tool may assist in the determination of those patients who might benefit from hemostatic resuscitation.

BACKGROUNDS: A reliable and readily available neurological prognostic index for the cerebral resuscitation of out-of-hospital cardiac arrest (OHCA) patients (pts) is required. We have previously reported in a single center cohort study of OHCA pts that regional brain oxygen saturation (rSO 2 ) measured on hospital arrival may help predict neurological outcomes. OBJECTIVE: To compare the power of rSO 2 and conventional indexes−lactate, base excess (BE), and ammonia (NH 3 )−measured on hospital arrival to prognose neurological outcomes at 30 days after cardiac arrest that are assessed according to the cerebral performance category (CPC) criteria in a multicenter prospective cohort study. METHODS: The database of the J-POP registry (conducted at 14 tertiary emergency hospitals in Japan) has prospectively enrolled 764 OHCA pts. Of these pts, 596 (77.5%) who were examined for rSO 2 , lactate, BE, and NH 3 were analyzed in the present study. The exclusion criteria included 1) trauma, 2) accidental hypothermia, 3) age under 18, 4) do not attempt resuscitation order, 5) Glasgow Coma Scale &gt; 8 on hospital arrival, and 6) missing data. Immediately after hospital arrival, rSO 2 was measured using a near-infrared spectroscopy device (INVOS; Covidien, USA) placed on the forehead, along with the measurement of lactate, BE, and NH 3 . Regardless of the rSO 2 readings, all pts received the best available therapy. RESULTS: Among 596 OHCA pts, 31 (5.2%) had good neurological outcome. The areas under the curve (AUCs) for the prognostic indexes-rSO 2 , lactate, BE, and NH 3 −were 0.912, 0.794, 0.773 and 0.853, respectively (Table). The AUC was significantly greater for rSO 2 than for lactate ( p = 0.0001) or BE ( p = 0.0057) and tended to be greater for NH 3 ( p = 0.0844). CONCLUSIONS: Compared with the conventional neurological prognostic indexes, rSO 2 may be more reliable for neurological prognostication based on its specificity, positive predictive value, and AUC.

OBJECTIVES:It is crucial to promptly identify high-mortality patients in emergency departments and initiate their treatment as soon as possible. Although many parameters have been studied to select patients with high mortality, no comprehensive evaluation exists in previous literature on these parameters in critically ill patients, regardless of patient groups. The aim of this study is to evaluate the Glasgow Coma Scale (GCS), quick Sepsis-related Organ Failure Assessment (qSOFA), blood gas base excess (BE), and blood gas lactate in predicting mortality in critically ill patients admitted to the emergency department.METHODS:This prospective observational cohort study included adult patients with Emergency Severity Index 1–2 (critically ill) admitted to the emergency department. All patients were evaluated by the physician within 10 min, and blood gas samples were taken. The data collection forms recorded the patients’ GCS and qSOFA scores at the time of first evaluation by the physician. The qSOFA score assessment was performed in all patients with ESI levels 1 and 2, regardless of whether infective pathology was suspected. Blood gas BE and lactate values were also from laboratory test results. Patients or their relatives were contacted by phone at the end of the 1st month to obtain information about the clinical condition (survival or mortality).RESULTS:A total of 868 patients were included, with 163 deaths observed within 30 days. GCS score, qSOFA score, and lactate value were significant in predicting mortality within 30 days. While the BE value was significant for predicting 30-day mortality for values equal to or below the lower limit of −1.5 (P < 0.001), it was not significant for values equal to or above the upper limit of +3 (P > 0.05). The most successful prediction model for predicting 30-day mortality was found to be qSOFA with a cutoff value of ≥1.CONCLUSION:In emergency departments, each of the GCS, qSOFA scores, BE, and lactate values can be used independently as a practical mortality prediction model in critically ill patients. Among these four models, qSOFA is the most successful practical mortality prediction model in critically ill patients.

Background. Alcohol intoxication is known to be associated with increased probability of traumatic injury. Although, the Glasgow coma scale (GCS) and computed tomography (CT) of the brain are useful diagnostic tools in patients with head injuries, the interactions among blood alcohol concentration (BAH), Glasgow coma scale and computed tomography findings are not clear. Methods. This study included 109 patients with head injuries and alcohol intoxication. Forty-three patients (group I) had blood alcohol concentrations less than 50 mg/dl, and 66 patients (group II) had blood alcohol concentrations more than 50 mg/dl. All the patients had neurological examination using the mean of GCS, blood alcohol concentration and CT of brain upon admission to the emergency department. Results. There were similar score of GCS (10.1±3.4 vs. 10.1±3.2) and incidence of positive CT findings (60% vs. 50%) between the two groups. In group I, the patients with a low GCS (＜11 points) had higher incidence of positive brain CT findings than the patients with a high GCS (≧11 points) (22% vs. 88%, p=0.05). In group II, there was a similar incidence of positive brain CT findings between the patients with low and high GCS (42% vs 60%, p＞0.05). Conclusions. The results of this study demonstrate different results of GCS and brain injury in patients with a low or high blood alcohol concentration. Our results suggest that brain CT scan is a strong indicator for trauma in patients with lower blood alcohol and lower GCS scores.

17 Saline Versus Plasma Solution-A in Initial Resuscitation of Patients With Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial

Objective To dynamically monitor the base excess(BE) in traumatic brain injury(TBI) patients within 3 d after admission,and to assess the impact of the early BE on prognosis.Methods Blood BE was monitored for 3 d in 56 TBI patients.Patients were classified into mild group(15 patients),moderate group (22 patients) and severe group (19 patients) according to the scores of Glasgow coma scale(GCS).Patients were classified into survival group(42 patients) and dead group(14 patients) according to prognosis.Patients were classified into high BE group (35 patients,BE≥-8 mmol/L) and low BE group (21 patients,BE ＜-8 mmol/L).The relations among BE,degree of injury and prognosis were analyzed.Results The level of BE in mild group,moderate group and severe group was increased after treatment for 1,2,3 d than that before treatment.The level of BE was consistent with the degree of injury [mild group:(-3.02 ± 0.21)mmol/L; moderate group:(-8.49 ± 1.44) mmol/L;severe group:(-9.64 ± 1.19) mmol/L].The level of BE in mild group and severe group had significant difference than that in moderate group (P＜ 0.01).The level of BE in dead group before treatment and after treatment for 1,2,3 d was significantly lower than that in survival group [(-11.97 ±2.13) mmol/L vs.(-6.29 ± 1.16) mmol/L,(-9.84 ± 1.33) mmol/L vs.(-4.89 ± 1.78)mmol/L,(-8.78 ± 2.01) mmol/L vs.(-3.61 ± 1.43) mmol/L,(-7.84 ± 1.42) mmol/L vs.(-3.10 ±0.98)mmol/L] (P ＜0.01).The scores of APACHE Ⅱ before treatment and fatality rate in low BE group were significantly higher than those in high BE group [(24.84 ± 3.68) scores vs.(16.27 ± 2.21) scores,52.4％ (11/21) vs.8.6％(3/35)] (P ＜ 0.01).The scores of GCS before treatment in low BE group was significantly higher than that in high BE group [(7.56 ± 3.09) scores vs.(10.51 ± 2.43) scores](P ＜ 0.01).Conclusion The level of early BE is a good factor on evaluating the condition and prognosis in TBI patients. Key words: Craniocerebral trauma; Prognosis; Base excess

We aimed to build a nomogram, based on patients with spontaneous intracerebral hemorrhage (SICH), to predict the probability of mortality and morbidity at 7days and 90days, respectively. We performed a retrospective study, with patients at less than 6h from ictus admitted to the department of neurosurgery in a single institute, from January 2011 to December 2018. A total of 1036 patients with SICH were included, 486 patients (46.9%) were 47-66years old at diagnosis, and 711 patients (68.6%) were male. The least absolute shrinkage and section operator method was performed to identify the key adverse factors predicting the outcomes in patients with SICH, and multivariate logistic regression analysis was built on these variables, and then the results were visualized by a nomogram. The discrimination of the prognostic models was measured and compared by means of Harrell's concordance index (C-index), calibration curve, area under the curve (AUC), and decision curve analysis (DCA). Multivariate logistic regression analysis revealed that factors affecting 7-day mortality, including the following: age, therapy, Glasgow Coma Scale (GCS) admission, location, ventricle involved, hematoma volume, white blood cell (WBC), uric acid (UA), and L-lactic dehydrogenase (LDH); and factors affecting 90-day mortality, including temperature, therapy, GCS admission, ventricle involved, WBC, international normalized ratio, UA, LDH, and systolic blood pressure. The C-index for the 7-day mortality and 90-day mortality prediction nomogram was 0.9239 (95% CI = 0.9061-0.9416) and 0.9241 (95% CI = 0.9064-0.9418), respectively. The AUC of 7-day mortality was 92.4, as is true of 90-day mortality. The calibration curve and DCA indicated that nomograms in our study had a good prediction ability. For 90-day morbidity, age, marital status, and GCS at 7-day remained statistically significant in multivariate analysis. The C-index for the prediction nomogram was 0.6898 (95% CI = 0.6511-0.7285), and the calibration curve, AUC as well as DCA curve indicated that the nomogram for the prediction of good outcome demonstrated good agreement in this cohort. Nomograms in this study revealed many novel prognostic demographic and laboratory factors, and the individualized quantitative risk estimation by this model would be more practical for treatment management and patient counseling.

Background: Early identification of severe injury and patients at risk of death remains a core challenge in the emergency management of multiple trauma. Base excess (BE), obtained rapidly from venous blood gas analysis, reflects metabolic derangement and may support early risk stratification. To evaluate the association between admission venous BE and mortality/clinical disposition in adult multiple-trauma patients, and to assess the discriminative performance of absolute BE for predicting trauma severity using the New Trauma Severity Score (NTSS). Methods: This prospective observational study included 307 adult (≥16 years) multiple-trauma patients presenting to the emergency department between 1 June 2012 and 1 February 2013. Venous blood gas samples were obtained within the first hour of arrival, and BE was measured using a blood gas analyzer. BE values were compared across comorbidity strata and disposition/outcome groups (death, ICU admission, ward admission, discharge). The ability of |BE| to discriminate NTSS ≤15 vs NTSS&gt;15 was evaluated using ROC analysis and agreement metrics at predefined cut-offs. Results: Admission BE did not differ significantly according to the presence of comorbidity, including coronary artery disease, diabetes mellitus, hypertension, congestive heart failure, or chronic kidney disease (all p&gt;0.05). In contrast, BE differed significantly across disposition/outcome categories, demonstrating a stepwise increase with clinical severity: death 16.35±0.92, ICU 9.57±4.79, ward 4.48±2.07, and discharge 1.70±1.23 (overall p&lt;0.001). |BE| showed excellent discrimination for YTCS &gt;15 (AUC 0.959). At |BE|&gt;2, discrimination was moderate (AUC 0.810) with high sensitivity (98.8%) and negative predictive value (99.3%), whereas |BE|&gt;4 improved overall classification balance (AUC 0.887; sensitivity 84.5%, specificity 92.9%, PPV 82.6%, NPV 93.8%). Conclusions: Early venous BE, particularly |BE|, is strongly associated with adverse disposition and mortality in multiple-trauma patients and demonstrates high performance for identifying patients with YTCS &gt;15. BE may serve as a rapid, practical adjunct for early emergency department triage and severity assessment.