Comparative Analysis of Trauma Scoring Systems Across Body Regions in Polytraumatized Patients: Outcomes from Tanta University Hospitals

Comparative Analysis of Trauma Scoring Systems Across Body Regions in Polytraumatized Patients: Outcomes from Tanta University Hospitals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative Analysis of Trauma Scoring Systems Across Body Regions in Polytraumatized Patients: Outcomes from Tanta University Hospitals Hend Mohamed Mansour, Radwa Muhammad Ashour, Hala Desouky Ali This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6841438/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Trauma remains a leading cause of morbidity and mortality, necessitating the use of trauma scoring systems to assess injury severity, guide clinical management, and predict patient outcomes. Various trauma scoring models exist, but their accuracy in predicting mortality among polytraumatized patients remains debated. This study aimed to evaluate and compare the predictive accuracy of different trauma scoring systems in polytraumatized patients with injuries across multiple anatomical regions admitted to Tanta University Hospitals. The study further explored the correlation between trauma scores and patient outcomes, including survival and mortality. Methods: A prospective study was conducted on 300 polytrauma patients admitted between December 2024 and May 2025. Patients were evaluated using multiple trauma scoring systems, including the Injury Severity Score (ISS), Abbreviated Injury Scale (AIS), Revised Trauma Score (RTS), Trauma and Injury Severity Score (TRISS), and Kampala Trauma Score (KTS). Physiological parameters such as heart rate, respiratory rate, blood pressure, and capillary refill time were recorded. The predictive performance of these scoring systems was assessed using regression analysis and Receiver Operating Characteristic (ROC) curve analysis. Results: The majority of the study population (79.67%) were male, with a mean age of 32.87 ± 12.06 years. Falls from heights (24%) and road traffic collisions (23%) were the leading causes of polytrauma. Among the trauma scores, TRISS (AUC = 0.99), RTS (AUC = 0.99), and Glasgow Coma Scale (GCS) (AUC = 0.99) demonstrated the highest predictive accuracy for mortality, while ISS showed poor performance (AUC = 0.18). Regression analysis confirmed that TRISS had the strongest predictive value for survival, followed by RTS and GCS, whereas ISS and KTS were less reliable predictors. Conclusion: TRISS, RTS, and GCS demonstrated the highest predictive accuracy for mortality (AUC = 0.99), whereas ISS showed limited predictive ability (AUC = 0.18). Our findings highlight the critical role of integrating physiological parameters in trauma scoring for improved clinical decision-making. Trauma Severity Indices Multiple Trauma Abbreviated Injury Scale Figures Figure 1 Figure 2 BACKGROUND Trauma is a leading cause of morbidity and mortality, making severity scales essential tools in trauma care. These scoring models help assess the nature and extent of injuries, aiding in triage, and supporting the evaluation and prediction of patient outcomes, ultimately contributing to more organized and efficient trauma systems. ( 1 ) According to the "Berlin Definition" of polytrauma, polytrauma is characterized by significant injuries of at least three points on the Abbreviated Injury Scale (AIS) in two or more body regions, along with added critical physiological factors such as hypotension (systolic blood pressure ≤ 90 mm Hg), coagulopathy, or severe acidosis. This definition has been developed to offer a more precise understanding of polytrauma, improving clinical care and research comparability. ( 2 ) In polytraumatized patients, injuries to different anatomical regions present distinct challenges, each influencing prognosis, treatment strategies, and overall patient outcomes in unique ways. Also, we should remember here that the outcome will depend on the quality of care provided to our patients during the entire healthcare process. ( 3 ) While various trauma scoring systems, such as the Injury Severity Score (ISS) and Abbreviated Injury Scale (AIS), are widely used, there is ongoing debate about their applicability and accuracy across different body regions. ( 4 ) The Abbreviated Injury Scale (AIS) is an anatomically based scoring system for assessing injury severity. It rates injuries in each body region on a six-point scale. The AIS serves as the foundation for calculating the Injury Severity Score (ISS) in patients with multiple injuries. ( 5 ) The Revised Trauma Score (RTS) is a physiologically based system that assesses a patient's condition using systolic blood pressure, respiratory rate, and the Glasgow Coma Scale (GCS). It is primarily used in pre-hospital and early trauma care to triage patients and predict outcomes, with lower RTS values showing more severe trauma and higher mortality risk. ( 6 ) The Trauma and Injury Severity Score (TRISS) combines anatomical and physiological measures, using the Injury Severity Score (ISS) for injury severity, the Revised Trauma Score (RTS) for physiological status, and the patient's age. This comprehensive model improves accuracy in predicting trauma patient survival compared to using either anatomical or physiological scores alone. However, the complexity of calculating TRISS, which involves multiple variables, can limit its use in emergency settings. ( 7 ) Several new trauma scoring systems, such as the Weighted Injury Severity Score (wISS), New Injury Severity Score (NISS), Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory Rate, and Systolic Blood Pressure (TRIAGES) score, and the BIG score, have been developed in recent years. ( 8 ) The TRIAGES score simplifies trauma prognostication by using easily measurable variables to predict outcomes, offering improved accuracy over older systems. ( 9 ) The BIG score, which combines Base deficit, International normalized ratio (INR), and Glasgow Coma Scale (GCS), is particularly useful for trauma patients. It provides a quick and efficient way to assess the severity of trauma and predict the need for critical care interventions, making it a valuable tool in emergency trauma care. ( 10 ) METHODS Aim of the Study: This study aimed to conduct a comparative analysis of different trauma scoring systems as they apply to polytraumatized patients with injuries to various body regions. By examining the performance of these systems in patients treated at Tanta University Hospitals, we look to offer valuable insights into their effectiveness in predicting patient outcomes and guiding treatment across diverse trauma scenarios. Our hypotheses were: Which trauma scoring system would perform best in predicting outcomes in polytraumatized patients? How would the predictive performance vary between different body regions? Study Design: A prospective study was conducted in the Emergency and Traumatology Department, Tanta University Hospitals. All patients underwent the standard procedures of the protocol. Study Population: This study was conducted on all polytrauma patients of both sexes presented to the Emergency Department, Tanta University Hospital. This study started from the start of December 2024 till the end of May 2025. The inclusion criteria for this study encompassed adult patients aged 18 years or older who met the Berlin definition of polytrauma. To qualify as polytraumatized, patients had to present with an Abbreviated Injury Scale (AIS) score of ≥ 3 in at least two different body regions and an Injury Severity Score (ISS) of ≥ 16. Additionally, patients had to exhibit at least one critical physiological parameter, which included systolic blood pressure ≤ 90 mmHg, Glasgow Coma Score (GCS) ≤ 8, base excess ≤ -6.0, international normalized ratio (INR) ≥ 1.4, partial thromboplastin time ≥ 40 seconds, or age ≥ 70 years. The exclusion criteria for this study included patients under 18 years of age and those with isolated trauma to a single body region or an Injury Severity Score (ISS) of less than 16. Patients with incomplete or missing medical records, particularly regarding trauma scores and outcomes, were excluded to maintain data integrity. Additionally, patients who died before trauma scoring could be applied or were transferred from another hospital after receiving initial trauma care were not included in the study. Pregnant patients, individuals with significant pre-existing chronic or terminal illnesses, and those with isolated burn injuries were also excluded. Furthermore, patients who experienced significant delays in receiving initial trauma care were not considered for inclusion in the study. Methodology: All included patients underwent a comprehensive evaluation, starting with a detailed history obtained from the patient or their relatives. This included sociodemographic data, medical history (hypertension, diabetes mellitus, hypercholesterolemia, cardiac disease such as ischemic heart disease or heart failure, and chest diseases like bronchial asthma or chronic obstructive pulmonary disease), surgical history, allergies, current medications, and special habits. Trauma evaluation followed the Advanced Trauma Life Support (ATLS) protocol, which included both a primary and secondary survey. The primary survey adhered to the ABCDE approach: Airway assessment involved identifying signs of airway obstruction and ensuring a patent, protected airway. Breathing assessment included a thorough examination of the neck and chest through inspection (breathing pattern, respiratory rate, use of accessory muscles indicating respiratory distress), palpation (tenderness, subcutaneous emphysema, or tracheal deviation), percussion (hyperresonance or dullness), and auscultation (added sounds or decreased breath sounds). Pulse oximetry was used to detect hypoxemia. Circulation assessment evaluated heart rate, pulse character, symmetry, blood pressure, preload, and perfusion, along with an abdominal, pelvic, and extremity examination. An electrocardiogram (ECG) was performed. Management included inserting two wide-bore cannulas to obtain blood samples, initiating fluid resuscitation, and administering medications as per the patient’s clinical condition. Disability assessment involved evaluating the patient’s consciousness level using the Glasgow Coma Scale (GCS), detecting any neurological deficits, performing pupil assessment, and measuring random blood sugar levels. Environmental assessment included monitoring temperature and ensuring proper patient exposure while maintaining safety. Additionally, the SAMPLE history (Signs/Symptoms, Allergies, Medications, Past Medical History, Last Oral Intake, and Events Leading to Injury) was obtained. Finally, all patients underwent trauma scoring using various trauma severity indices for further analysis. I. Assessment of Abbreviated Injury Scale (AIS) using: The 6-point ordinal AIS severity scale: 1 = minor, 2 = moderate, 3 = serious, 4 = severe, 5 = critical, 6 = maximum. Body regions affected and their number: Head, Face, Neck, Thorax, Abdomen and pelvic contents, Spine, Upper extremities, Lower extremities, and External, burns and other trauma. II. Injury Severity Score (ISS): The ISS is the sum of the squares of the highest AIS code in each of the three most severely injured ISS body regions. ISS ranges from 1 to 75. If an injury is assigned an AIS of 6 (finding a currently untreatable injury), the ISS score is automatically assigned 75. III. Glasco Coma Scale (GCS): The GCS is scored between 3 and 15, 3 being the worst and 15 being the best. It is composed of three parameters: best eye response (E), best verbal response (V), and best motor response (M). The components of the GCS should be recorded individually; for example, E2V3M4 results in a GCS score of 9. IV. Revised Trauma Scores (RTS) : ( 11 ) The Revised Trauma Score (RTS) is one of the more common scores aimed at measuring the functional consequences of an injury. It uses three specific physiological parameters: ( 1 ) the Glasgow Coma Scale (GCS); ( 2 ) systemic blood pressure; and ( 3 ) the respiratory rate. ( Table 1 ) $$\:RTS\:=\left(0.9368\:\times\:GCS\right)+\left(0.7326\times\:SBP\right)+\left(0.2908\times\:RR\right)$$ The RTS score ranges from 0 to 7.8408, with higher scores showing less severe trauma. An RTS of less than 4 is associated with a higher likelihood of mortality. V. Trauma Score and Injury Severity Score (TRISS) : ( 11 ) The TRISS includes the Revised Trauma Score (RTS) and Injury Severity Score (ISS) indexes as well as the trauma type (blunt or penetrating) and the patient age. ( Table 1 ) VI. Kampala Trauma Score II : ( 12 ) Kampala Trauma Score II total = A + B + C + D + E. ( Table 1 ) Interpretation: KTS II (< 6 = Severe injury − 7–8 = Moderate injury − 9–10 = Mild injury. Table 1 Trauma Scoring Systems and Their Calculation Methods Revised Trauma Scores (RTS) Value Glasgow Coma Scale Systolic Blood Pressure Respiratory Rate 4 13–15 > 89 10–29 3 9–12 76–89 > 29 2 6–8 50–75 6–9 1 4–5 1–49 1–5 0 3 0 0 Trauma Score and Injury Severity Score (TRISS) Probability of survival = 1/ (1 + e − b ) where b = b 0 + b 1 ( RTS ) + b 2 ( ISS ) + b 3 (A) A is decided by the following : Age, years A ≤ 54 0 > 54 1 Values for the coefficients : Trauma type b 0 b 1 b 2 b 3 Blunt -1.2470 0.9544 -0.0768 -1.9052 Penetrating -0.6029 1.1430 -0.1516 -2.6676 Kampala Trauma Score II Description Score A Age (in years) 5–55 1 55 0 B Systolic blood pressure on admission (mmHg) > 89 2 89 − 50 1 ≤ 49 0 C Respiratory rate 10–29/minutes 2 ≥ 30/minutes 1 ≤ 9/minutes 0 D Neurological status Alert 3 Responds to verbal stimuli 2 Responds to painful stimuli 1 Unresponsive 0 E Score for significant injury None 2 One injury 1 More than one injury 0 Study outcome: Application of different trauma scores in poly trauma patients. Assess polytrauma patients from the moment patients are admitted in, till when discharged from ICU, we compared the accuracy of few scoring systems in predicting mortality rate in polytrauma patients, and then assessed the cost-effectiveness applying these methods. Study Ethics: Approval from the ethical committee and informed consent was obtained from all participants or relatives in this research after an explanation of both benefits and risks. We maintained privacy of participants’ confidentiality of data through Putting a code number for each participant from the beginning to the end of the study. The results of this research were used only for scientific purposes. RESULTS The study involved 300 polytraumatized patients admitted to Tanta University Hospitals, with an average age of 32.87 ± 12.06 years. Males comprised the majority of the sample (79.67%). The most prevalent pre-existing conditions were a combination of hypertension and diabetes mellitus (18.67%), followed by hypertension alone (13%). Additionally, 51.67% of the patients were smokers. ( Table 2 ) Table 2 Patient Demographics and Characteristics Descriptive Statistics N = 300 Age (years) Mean ± SD 32.87 ± 12.06 Range 18–70 Sex Male 239 (79.67%) Female 61 (20.33%) Medical History No Co-morbidities 177 (59%) Hypertension and Diabetes Mellitus 56 (18.67%) Hypertension 39 (13%) Diabetes Mellitus 18 (6%) Hypertension and Ischemic Heart Disease 8 (2.67%) Ischemic Heart Disease 2 (0.67%) Special habits Smoking 155 (51.67%) The most frequent cause of injury was fallen from a height of two or more floors accounting for 24% (n = 72) of cases. High-speed road traffic collisions followed closely, contributing to 23% (n = 69) of trauma incidents, while motorcycle accidents were responsible for 19.33% (n = 58). Assaults involving weapons constituted 16% (n = 48) of cases, ejections from vehicles were observed in 7.67% (n = 23) of cases, and pedestrian or cyclist collisions with vehicles made up 4.67% (n = 14). Less frequent but severe mechanisms included crush injuries, which accounted for 3% (n = 9), and prolonged entrapments, occurring in 2.33% (n = 7) of cases. ( Fig. 1 ) Physiological parameters analysis showed significant differences between survivors (82.67%) and non-survivors (17.33%). Non-survivors exhibited significantly higher respiratory (31.37 ± 3.48 vs. 27.76 ± 5.69 bpm) and heart rates (129.48 ± 9.95 vs. 113.13 ± 16.07 bpm), while their mean arterial pressure (58.01 ± 21.74 vs. 72.36 ± 10.82 mmHg) was lower. Additionally, capillary refill time was notably prolonged (3.62 ± 1.01 vs. 2.34 ± 0.78 sec) in non-survivors (p < 0.001 for all), indicating hemodynamic instability and poor perfusion. ( Table 3 ) Table 3 Physiological Parameters and Outcomes in studied patients Parameter Group Range Mean ± Std T test t P-value Respiratory Rate (Breath/min) Alive (N = 248) 18–38 27.76 ± 5.69 − 4.39 < 0.001 Died (N = 52) 25–37 31.37 ± 3.48 Total (N = 300) 18–38 28.39 ± 5.54 Heart rate (Beat/ min) Alive (N = 248) 80–155 113.13 ± 16.07 -7.05 < 0.001 Died (N = 52) 110–140 129.48 ± 9.95 Total (N = 300) 80–155 115.96 ± 16.39 Mean arterial Blood Pressure (mmHg) Alive (N = 248) 40–96.67 72.36 ± 10.82 7.05 < 0.001 Died (N = 52) 26.67–106.67 58.01 ± 21.74 Total (N = 300) 26.67–106.67 69.87 ± 14.38 Capillary Refill Time (sec) Alive (N = 248) 2–5 2.34 ± 0.78 -10.12 < 0.001 Died (N = 52) 2–5 3.62 ± 1.01 Total (N = 300) 2–5 2.56 ± 0.96 Head trauma appears to be the most critical factor influencing mortality among polytraumatized patients, as non-survivors exhibited significantly higher head abbreviated injury Scale (5.48 ± 0.8) compared to survivors (1.79 ± 1.64, p < 0.00001). In contrast, injuries to the face, neck, thorax, abdomen, spine, and lower extremities did not show statistically significant differences between the two groups. ( Table 4 ) Table 4 Assessment of Abbreviated Injury Scale (AIS) Body Region Group Range Mean ± Std T test t P-value Head Alive (N = 248) 0–5 1.79 ± 1.64 -15.81966 < 0.00001 Died (N = 52) 1–6 5.48 ± 0.8 Total (N = 300) 0–6 2.43 ± 2.07 Face Alive (N = 248) 0–6 1.26 ± 1.62 -1.44448 0.149654 Died (N = 52) 0–3 1.62 ± 1.51 Total (N = 300) 0–6 1.32 ± 1.61 Neck Alive (N = 248) 0–5 0.67 ± 1.32 -0.18 0.853862 Died (N = 52) 0–5 0.63 ± 1.62 Total (N = 300) 0–5 0.67 ± 1.38 Thorax Alive (N = 248) 0–6 2.56 ± 1.83 1.42822 0.154277 Died (N = 52) 0–4 2.17 ± 1.5 Total (N = 300) 0–6 2.49 ± 1.78 Abdomen and pelvic contents Alive (N = 248) 0–6 2.6 ± 1.92 -0.38063 0.703749 Died (N = 52) 0–6 2.71 ± 1.84 Total (N = 300) 0–6 2.62 ± 1.9 Spine Alive (N = 248) 0–5 0.82 ± 1.59 -1.42206 0.156055 Died (N = 52) 0–6 1.19 ± 2.26 Total (N = 300) 0–6 0.88 ± 1.73 Upper extremities Alive (N = 248) 0–6 2.05 ± 1.79 2.48835 0.01338 Died (N = 52) 0–4 1.38 ± 1.6 Total (N = 300) 0–6 1.94 ± 1.77 Lower extremities Alive (N = 248) 0–6 2.03 ± 2.03 -0.73303 0.464118 Died (N = 52) 0–5 2.25 ± 1.71 Total (N = 300) 0–6 2.07 ± 1.98 External, burns and other trauma Alive (N = 248) 0–3 0.94 ± 1.4 1.09999 0.272224 Died (N = 52) 0–4 0.71 ± 1.32 Total (N = 300) 0–4 0.9 ± 1.38 Trauma severity scores clearly differentiate between survivors and non-survivors, with higher scores observed in non-survivors for the Injury Severity Score (ISS: 63.92 ± 13.35 vs. 44.57 ± 16.4, p < 0.00001). Similarly, non-survivors had significantly lower scores in key prognostic indicators, including the Glasgow Coma Scale (GCS: 6.17 ± 1.65 vs. 14.02 ± 2.1, p < 0.00001), Revised Trauma Score (RTS: 4.41 ± 1.01 vs. 7.32 ± 0.66, p < 0.00001), Trauma Score and Injury Severity Score (TRISS: 0.17 ± 0.15 vs. 0.83 ± 0.19, p < 0.00001), and Kampala Trauma Score II (KTS II: 3.62 ± 1.29 vs. 6.94 ± 1.02, p < 0.00001). ( Table 5 ) Table 5 Assessment of Trauma Scores: Score Group Range Mean ± Std T test t P-value Injury Severity Score (ISS) Alive (N = 248) 19–75 44.57 ± 16.4 -7.97102 < 0.00001 Died (N = 52) 43–75 63.92 ± 13.35 Total (N = 300) 19–75 47.92 ± 17.51 Glasco Coma Scale (GCS) Alive (N = 248) 7–15 14.02 ± 2.1 25.3204 < 0.00001 Died (N = 52) 3–8 6.17 ± 1.65 Total (N = 300) 3–15 12.66 ± 3.6 Revised Trauma Scores (RTS) Alive (N = 248) 5.68–7.84 7.32 ± 0.66 26.14526 < 0.00001 Died (N = 52) 3.07–5.97 4.41 ± 1.01 Total (N = 300) 3.07–7.84 6.82 ± 1.32 Trauma Score and Injury Severity Score (TRISS) Alive (N = 248) 0.15–0.99 0.83 ± 0.19 23.29156 < 0.00001 Died (N = 52) 0–0.54 0.17 ± 0.15 Total (N = 300) 0–0.99 0.71 ± 0.31 Kampala Trauma Score II Alive (N = 248) 4–8 6.94 ± 1.02 20.33228 < 0.00001 Died (N = 52) 1–6 3.62 ± 1.29 Total (N = 300) 1–8 6.36 ± 1.65 Pulmonary injuries were present in varying frequencies, with pneumothorax, hemothorax, and flail chest affecting 7.67%, 6.33%, and 5.33% of patients, respectively, while tension pneumothorax was identified in 4.67% of cases. In the abdominal and pelvic region, intraperitoneal free fluid (IPFF) was the most common finding, detected in 70.67% of patients. Liver injuries including hematoma or contusion and splenic injuries, including tear, contusion, or hematoma, were observed in 9% and 25.67%, respectively. Other noted abnormalities included retroperitoneal extension (11%), renal hematoma (7%), pelvic hematoma (3.67%), and pelvic fractures (5.67%). Neurological injuries were widespread, with subdural hematoma (SDH) and subarachnoid hemorrhage (SAH) each occurring in 22% of cases. Brain contusions were reported in 20.33%, intraventricular hemorrhage (IVH) in 11%, and brain edema in 18.33%. Less frequent findings included pneumocephalus (2%) and skull fractures (3%), while maxillofacial injuries were documented in 16% of patients. Subdural hematoma (SDH), subarachnoid hemorrhage (SAH), brain contusions, intraventricular hemorrhage (IVH), and Liver injuries were significantly more common in non-survivors (p < 0.001). Hemothorax was significantly associated with mortality (p = 0.039). The ROC (Receiver Operating Characteristic) curve presented in the image ( Fig. 1 ) evaluates the predictive performance of various trauma scoring systems for in-hospital mortality. The AUC (Area Under the Curve) values indicate how well each score differentiates between survivors and non-survivors. Notably, TRISS (AUC = 0.99), RTS (AUC = 0.99), and GCS (AUC = 0.99) demonstrate nearly perfect discrimination, with their curves positioned close to the upper left corner, indicating high sensitivity and specificity. The Kampala Trauma Score (KTS) also performs exceptionally well (AUC = 0.97). In contrast, the Injury Severity Score (ISS) shows poor predictive ability, with an AUC of only 0.18. ( Fig. 2 ) Ridge Regression and Logistic Regression models were employed to evaluate the predictive strength of various trauma scoring systems in determining in-hospital mortality. The Trauma Score and Injury Severity Score (TRISS) demonstrates the highest coefficient in both models (0.322 in Ridge Regression and 1.846 in Logistic Regression), confirming its strong predictive ability for survival. Similarly, GCS (1.753) and RTS (1.378) in Logistic Regression also show significant positive coefficients, indicating that higher values in these scores are associated with improved survival outcomes. Conversely, the Injury Severity Score (ISS) shows a negative coefficient (-0.763 in Logistic Regression), suggesting that higher ISS values correlate with increased mortality risk. The Kampala Trauma Score (KTS) also exhibits a negative coefficient in Ridge Regression (-0.1456), further supporting its association with higher mortality at lower values. ( Table 6 ) Table 6 Regression Analysis of Trauma Scoring Systems Trauma Scoring Systems Ridge Regression Coefficients Logistic Regression Coefficients Injury Severity Score (ISS) 0.11986693404395911 -0.763014553013029 GCS score (/15) 0.17584673790642844 1.752781132778722 Revised trauma Score (RTS) 0.086857 1.3782522396638301 Trauma Score and Injury Severity Score (TRISS) or Probability of Survival (Ps) 0.32204571491952233 1.8459908825077789 Kampala Trauma Score II -0.1456 0.7751296320199179 DISCUSSION This study was conducted on 300 polytraumatized patients admitted to Tanta University Hospitals, with an average age of 32.87 ± 12.06 years. The majority of the sample was male (79.67%). The most common pre-existing medical conditions included a combination of hypertension and diabetes mellitus (18.67%), followed by hypertension alone (13%). Additionally, a significant proportion of patients (51.67%) were smokers, which could have influenced trauma outcomes. Regarding the mechanism of injury, falls from a height of two or more floors were the leading cause, accounting for 24% (n = 72) of cases. This was followed closely by high-speed road traffic collisions (23%, n = 69) and motorcycle accidents (19.33%, n = 58). Notably, assault-related injuries accounted for 16% (n = 48) of cases, emphasizing the role of interpersonal violence in trauma admissions. Other mechanisms included vehicle ejections (7.67%), pedestrian or cyclist collisions (4.67%), crush injuries (3%), and prolonged entrapments (2.33%). A study by Besra RC et al. (2024) , which examined 204 patients, found that the majority were aged 21–30 years and that males comprised 85.3%. Road traffic accidents (RTA) were the leading cause of injury, accounting for 50% of cases, followed by assaults (24.5%), stab wounds (9.3%), and falls from height (8.3%). ( 13 ) When compared to other studies, our findings align with the research conducted by Merchant AA, et al. (2023) , who studied 2,817 trauma patients and reported a mean age of 41.2 ± 17.8 years, with 80.6% being male. In that study, blunt trauma was the predominant injury type (85.2%), and road traffic crashes were the leading cause (59.2%). About half of the patients (50.9%) were admitted as polytrauma patients. ( 14 ) Another study by Milton M, et al. (2021) , which analyzed 108 polytrauma cases, reported a slightly older patient population with a mean age of 36.5 ± 14.4 years, and a similar male predominance (86.1%). Their findings also identified road traffic injuries (63%) and assaults (33.3%) as the most frequent causes of trauma. ( 15 ) Physiological Parameters and Mortality Prediction Analysis of physiological parameters revealed significant differences between survivors (82.67%) and non-survivors (17.33%). Non-survivors had notably higher respiratory rates (31.37 ± 3.48 vs. 27.76 ± 5.69 bpm, p < 0.001) and heart rates (129.48 ± 9.95 vs. 113.13 ± 16.07 bpm, p < 0.001). They also exhibited lower mean arterial blood pressure (58.01 ± 21.74 vs. 72.36 ± 10.82 mmHg, p < 0.001) and prolonged capillary refill time (3.62 ± 1.01 vs. 2.34 ± 0.78 sec, p < 0.001), indicating hemodynamic instability and poor perfusion. These findings are consistent with those of Merchant AA, et al. (2023) , who reported an average systolic blood pressure of 124.4 ± 22.3 mmHg and a mean respiratory rate of 20.3 ± 4.9 breaths per minute. Their study also highlighted the significant role of physiological parameters in trauma outcome prediction. ( 14 ) Trauma Severity Scores and Mortality Trauma severity scores effectively distinguish between survivors and non-survivors. Non-survivors had significantly higher ISS scores (63.92 ± 13.35 vs. 44.57 ± 16.4, p < 0.00001) and lower scores in key prognostic indicators such as GCS (6.17 ± 1.65 vs. 14.02 ± 2.1, p < 0.00001), RTS (4.41 ± 1.01 vs. 7.32 ± 0.66, p < 0.00001), TRISS (0.17 ± 0.15 vs. 0.83 ± 0.19, p < 0.00001), and Kampala Trauma Score II (KTS II: 3.62 ± 1.29 vs. 6.94 ± 1.02, p < 0.00001). In the study by Besra RC, et al. (2024) , the mean and standard deviation values for TRISS, RTS, NISS, and ISS were 15.91 ± 19.65, 19.66 ± 21.70, 7.23 ± 1.02, and 6.01 ± 21.90, respectively. The higher mean scores of ISS and NISS suggest a greater severity of injuries among the study population. Their findings further support the significance of trauma scores in predicting mortality, with NISS and TRISS emerging as the most effective predictors (p < 0.0001). These results align with our study, where TRISS consistently demonstrated superior predictive accuracy for in-hospital mortality, emphasizing its reliability in assessing trauma outcomes in polytraumatized patients. ( 13 ) In comparison, Merchant AA, et al. (2023) reported an ISS of 12.2 ± 7.3 across all trauma patients, with survivors averaging 10.9 ± 6.7 and non-survivors 18.6 ± 7.0. Their TRISS scores were 93.8 ± 12.8 (alive: 96.9 ± 6.4, deceased: 78.6 ± 21.8), and RTS scores were 7.2 ± 1.1 (alive: 7.5 ± 0.7, deceased: 5.6 ± 1.4). GCS scores followed a similar pattern, with an overall mean of 12.4 ± 3.9, but significantly lower in deceased patients (6.8 ± 4.0). ( 14 ) The findings by Milton M, et al. (2021) also support these trends, reporting baseline ISS (31.07 ± 11.52), RTS (6.28 ± 1.76), and TRISS (76.48 ± 26.58). 30-day survivors had lower ISS (28.01 ± 9.05 vs. 38.83 ± 13.98) and higher RTS (7.05 ± 1.12 vs. 5.09 ± 1.88) and TRISS (87.82 ± 15.81 vs. 52.81 ± 31.47) compared to non-survivors, indicating greater trauma severity in those who did not survive. ( 15 ) ROC Curve and Predictive Performance The Receiver Operating Characteristic (ROC) curve analysis demonstrated that TRISS (AUC = 0.99), RTS (AUC = 0.99), and GCS (AUC = 0.99) had the highest predictive accuracy for in-hospital mortality. The Kampala Trauma Score (KTS) also performed well (AUC = 0.97), whereas the Injury Severity Score (ISS) exhibited poor predictive ability (AUC = 0.18). The study by Besra RC, et al. (2024) assessed the predictive accuracy of various trauma scoring systems using Receiver Operating Characteristic (ROC) curves, demonstrating their effectiveness in mortality prediction. The Area Under the ROC Curve (AUROC) values were highest for TRISS (0.8521) and NISS (0.8361), followed by ISS (0.8169) and RTS (0.7953). While all four scores were statistically significant in predicting mortality, TRISS and NISS emerged as the most precise predictors. These findings reinforce the superior role of TRISS in trauma prognosis, supporting its effectiveness in predicting in-hospital mortality in polytraumatized patients, as observed in our study. ( 13 ) Merchant AA, et al. (2023) found that for polytrauma patients, TRISS (AUC = 0.729) and ISS (AUC = 0.722) were the most effective predictors of in-hospital mortality compared to other trauma scoring systems. In contrast to its high predictive value in other trauma groups, GCS had a lower AUC (0.638) for polytrauma patients. Similarly, RTS showed the least predictive power for in-hospital mortality in this group (AUC = 0.595) and was not statistically significant (p = 0.052). ( 14 ) Similarly, Milton M, et al. (2021) reported TRISS (AUROC = 0.828) as the best predictor of mortality, followed by ISS (AUROC = 0.755), RTS (AUROC = 0.715), and REMS (AUROC = 0.656). ( 15 ) Regression Analysis and Trauma Score Comparison Regression analysis further confirmed that TRISS was the most significant predictor of survival, with the highest coefficients in both Ridge Regression (0.322) and Logistic Regression (1.846) models. GCS (1.753) and RTS (1.378) also demonstrated strong predictive power in the Logistic Regression model. In contrast, ISS (-0.763) and KTS (-0.1456) had negative coefficients, indicating that higher scores correlated with increased mortality risk. These findings highlight the superior predictive power of combined anatomical and physiological trauma scores (TRISS) over purely anatomical ones (ISS). The results align with the conclusions of previous research, suggesting that trauma scoring systems integrating physiological parameters offer better mortality predictions than those relying solely on injury severity. In this respect, according to Besra RC, et al. (2024) , in which the logistic regression analysis of the results revealed the NISS and TRISS to be major predictors of mortality, particularly in individuals with injuries to their abdomen and thoracic cavity. ( 13 ) This study has several limitations that should be considered. First, as a single-center study conducted at Tanta University Hospitals, the findings may not be generalizable to other healthcare settings with different trauma management protocols and resources. Second, although the sample size of 300 patients is adequate, it may not capture the full variability of trauma severity seen in larger, multi-center studies. Third, the study focused on in-hospital outcomes over a six-month period, limiting the ability to assess long-term survival, functional recovery, and post-discharge complications. Additionally, the exclusion of patients with incomplete medical records or pre-existing chronic conditions may introduce selection bias, potentially affecting the applicability of the results to all polytrauma patients. Lastly, while this study analyzed well-established trauma scoring systems (TRISS, RTS, ISS, and KTS), newer models such as the BIG score and TRIAGES score were not fully explored. Future research should address these limitations by incorporating larger, multi-center datasets, extending follow-up periods, and integrating newer trauma scoring systems to enhance predictive accuracy and clinical applicability. CONCLUSION This study provides a comprehensive comparative analysis of various trauma scoring systems applied to polytraumatized patients. Our findings indicate that TRISS, RTS, and GCS are the most accurate predictors of in-hospital mortality, confirming their reliability in clinical settings. In contrast, ISS showed limited predictive capability, suggesting that anatomical scores alone may not sufficiently capture trauma severity. The integration of physiological parameters significantly enhances the accuracy of trauma scoring systems, as demonstrated by the superior performance of TRISS and RTS. These results align with previous research indicating that a combined anatomical and physiological approach is superior to standalone anatomical scoring methods in predicting trauma outcomes. Clinically, these findings support the routine application of TRISS and RTS in trauma centers to optimize patient assessment, triage, and treatment planning. Future research should focus on further refining trauma scoring models, integrating newer biomarkers, and exploring the applicability of these findings across diverse trauma populations and healthcare settings. Abbreviations AIS Abbreviated Injury Scale ATLS Advanced Trauma Life Support AUC Area Under the Curve ECG Electrocardiogram GCS Glasgow Coma Scale INR International normalized ratio ISS Injury Severity Score IVH intraventricular hemorrhage KTS Kampala Trauma Score NISS New Injury Severity Score ROC curve Receiver Operating Characteristic curve RTS Revised Trauma Score SAH subarachnoid hemorrhage SDH Subdural hematoma TRIAGES Trauma Rating Index in Age Glasgow Coma Scale Respiratory Rate and Systolic Blood Pressure score TRISS Trauma and Injury Severity Score wISS Weighted Injury Severity Score. Declarations Disclaimer: No large language models (LLMs), including ChatGPT, have been credited with authorship in this manuscript. Any use of LLMs is documented appropriately within the methods section of the manuscript. Ethics approval and consent to participate: This study was approved by the ethical committee under approval code (36264PR927/11/24) at Tanta University Hospitals. Informed consent was obtained from all participants or their legal representatives prior to participation. Consent for publication: Consent for publication was obtained from all participants or their legal representatives. All participants were informed that their data might be published anonymously in scientific publications. Competing interests: The authors declare that they have no competing interests. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution All authors contributed significantly to the study design and implementation. Data collection was primarily conducted by Hala Desouky Ali and Hend Mohamed Mansour. Data analysis and interpretation were performed by all authors. The manuscript was drafted by Radwa Muhammad Ashour and critically reviewed and revised by all authors. All authors have read and approved the final manuscript. Acknowledgements: We gratefully acknowledge the contributions of the Emergency and Traumatology Department staff at Tanta University Hospitals for their assistance and support during the study. Data Availability The datasets generated and analyzed during this study are available from the corresponding author on reasonable request. References Rapsang AG, Shyam DC. Scoring systems of severity in patients with multiple trauma. Cirugía Española (English Edition). 2015;93(4):213–21. Rau CS, Wu SC, Kuo PJ, Chen YC, Chien PC, Hsieh HY, et al. Polytrauma defined by the new Berlin definition: a validation test based on propensity-score matching approach. Int J Environ Res Public Health. 2017;14(9):1045. Serviá L, Badia M, Montserrat N, Trujillano J. Severity scores in trauma patients admitted to ICU. Physiological and anatomic models. Med Intensiva (English Edition). 2019;43(1):26–34. Maduz R, Kugelmeier P, Meili S, Döring R, Meier C, Wahl P. Major influence of interobserver reliability on polytrauma identification with the Injury Severity Score (ISS): Time for a centralised coding in trauma registries? Injury. 2017;48(4):885–9. Grandic L, Olic I, Pogorelic Z, Mrklic I, Perko Z. The value of injury severity score and abbreviated injury scale in the management of traumatic injuries of parenchymal abdominal organs. Acta Clin Croat. 2017;56:453–9. Yu Z, Xu F, Chen D. Predictive value of Modified Early Warning Score (MEWS) and Revised Trauma Score (RTS) for the short-term prognosis of emergency trauma patients: a retrospective study. BMJ Open. 2021;11(3):e041882. Indurkar Sr SK, Ghormade PS, Akhade S, Sarma B. Use of the Trauma and Injury Severity Score (TRISS) as a predictor of patient outcome in cases of trauma presenting in the trauma and emergency department of a tertiary care institute. Cureus. 2023;15(6). Shi J, Shen J, Zhu M, Wheeler KK, Lu B, Kenney B, et al. A new weighted injury severity scoring system: better predictive power for adult trauma mortality. Inj Epidemiol. 2019;6:1–10. Shiraishi A, Otomo Y, Yoshikawa S, Morishita K, Roberts I, Matsui H. Derivation and validation of an easy-to-compute trauma score that improves prognostication of mortality or the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure (TRIAGES) score. Crit Care. 2019;23:1–8. Höke MH, Usul E, Özkan S. Comparison of trauma severity scores (ISS, NISS, RTS, BIG Score, and TRISS) in multiple trauma patients. J Trauma Nursing| JTN. 2021;28(2):100–6. Restrepo-Álvarez CA, Valderrama-Molina CO, Giraldo-Ramírez N, Constain-Franco A, Puerta A, León AL et al. Trauma severity scores. Colombian Journal of Anesthesiology [Internet]. 2016;44(4):317–23. Available from: https://www.sciencedirect.com/science/article/pii/S2256208716300347 Rastogi D, Meena S, Sharma V, Singh GK. Causality of injury and outcome in patients admitted in a major trauma center in North India. Int J Crit Illn Inj Sci. 2014;4(4):298–302. Besra RC, Toppo S, Bodra P, Kujur A, Tudu MB, Bharti B et al. Prediction of Mortality and Outcome of Various Trauma Scores in Polytrauma Patients. Cureus. 2024;16(9). Merchant AAH, Shaukat N, Ashraf N, Hassan S, Jarrar Z, Abbasi A et al. Which curve is better? A comparative analysis of trauma scoring systems in a South Asian country. Trauma Surg Acute Care Open. 2023;8(1). Milton M, Engelbrecht A, Geyser M. Predicting mortality in trauma patients-A retrospective comparison of the performance of six scoring systems applied to polytrauma patients from the emergency centre of a South African central hospital. Afr J Emerg Med. 2021;11(4):453–8. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6841438","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":470052336,"identity":"a591164e-a8dc-4b4c-a5de-2f25700c4cee","order_by":0,"name":"Hend Mohamed Mansour","email":"","orcid":"","institution":"Tanta University","correspondingAuthor":false,"prefix":"","firstName":"Hend","middleName":"Mohamed","lastName":"Mansour","suffix":""},{"id":470052337,"identity":"5004ee26-ead2-46f3-abc6-7f790ad1b2e3","order_by":1,"name":"Radwa Muhammad Ashour","email":"data:image/png;base64,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","orcid":"","institution":"Suez university","correspondingAuthor":true,"prefix":"","firstName":"Radwa","middleName":"Muhammad","lastName":"Ashour","suffix":""},{"id":470052339,"identity":"ed875e6f-44ac-497b-a6ac-5c22416ffe9f","order_by":2,"name":"Hala Desouky Ali","email":"","orcid":"","institution":"Tanta University","correspondingAuthor":false,"prefix":"","firstName":"Hala","middleName":"Desouky","lastName":"Ali","suffix":""}],"badges":[],"createdAt":"2025-06-07 08:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6841438/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6841438/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84818842,"identity":"f83c1238-ae28-4e61-8c1c-6e4d8dd762b1","added_by":"auto","created_at":"2025-06-17 15:55:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":169966,"visible":true,"origin":"","legend":"\u003cp\u003eMechanisms of Injury in studied patients\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6841438/v1/ea5068d9b2215c3a3c4ca5a5.png"},{"id":84818841,"identity":"0c447465-0fed-489e-b49d-6ea2c407bbef","added_by":"auto","created_at":"2025-06-17 15:55:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":187751,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC Curve Analysis of Trauma Scores for Predicting In-Hospital Mortality\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6841438/v1/53dcf8dcd0746735b89c4619.png"},{"id":86711983,"identity":"c0e77e1a-81d3-4f08-8b85-aae7b26055f5","added_by":"auto","created_at":"2025-07-14 19:01:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2569696,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6841438/v1/1f9ddacb-c71b-4575-a9b8-e866923bce1e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Analysis of Trauma Scoring Systems Across Body Regions in Polytraumatized Patients: Outcomes from Tanta University Hospitals","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eTrauma is a leading cause of morbidity and mortality, making severity scales essential tools in trauma care. These scoring models help assess the nature and extent of injuries, aiding in triage, and supporting the evaluation and prediction of patient outcomes, ultimately contributing to more organized and efficient trauma systems. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAccording to the \"Berlin Definition\" of polytrauma, polytrauma is characterized by significant injuries of at least three points on the Abbreviated Injury Scale (AIS) in two or more body regions, along with added critical physiological factors such as hypotension (systolic blood pressure\u0026thinsp;\u0026le;\u0026thinsp;90 mm Hg), coagulopathy, or severe acidosis. This definition has been developed to offer a more precise understanding of polytrauma, improving clinical care and research comparability. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn polytraumatized patients, injuries to different anatomical regions present distinct challenges, each influencing prognosis, treatment strategies, and overall patient outcomes in unique ways. Also, we should remember here that the outcome will depend on the quality of care provided to our patients during the entire healthcare process. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWhile various trauma scoring systems, such as the Injury Severity Score (ISS) and Abbreviated Injury Scale (AIS), are widely used, there is ongoing debate about their applicability and accuracy across different body regions. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe Abbreviated Injury Scale (AIS) is an anatomically based scoring system for assessing injury severity. It rates injuries in each body region on a six-point scale. The AIS serves as the foundation for calculating the Injury Severity Score (ISS) in patients with multiple injuries. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe Revised Trauma Score (RTS) is a physiologically based system that assesses a patient's condition using systolic blood pressure, respiratory rate, and the Glasgow Coma Scale (GCS). It is primarily used in pre-hospital and early trauma care to triage patients and predict outcomes, with lower RTS values showing more severe trauma and higher mortality risk. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe Trauma and Injury Severity Score (TRISS) combines anatomical and physiological measures, using the Injury Severity Score (ISS) for injury severity, the Revised Trauma Score (RTS) for physiological status, and the patient's age. This comprehensive model improves accuracy in predicting trauma patient survival compared to using either anatomical or physiological scores alone. However, the complexity of calculating TRISS, which involves multiple variables, can limit its use in emergency settings. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSeveral new trauma scoring systems, such as the Weighted Injury Severity Score (wISS), New Injury Severity Score (NISS), Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory Rate, and Systolic Blood Pressure (TRIAGES) score, and the BIG score, have been developed in recent years. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe TRIAGES score simplifies trauma prognostication by using easily measurable variables to predict outcomes, offering improved accuracy over older systems. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe BIG score, which combines Base deficit, International normalized ratio (INR), and Glasgow Coma Scale (GCS), is particularly useful for trauma patients. It provides a quick and efficient way to assess the severity of trauma and predict the need for critical care interventions, making it a valuable tool in emergency trauma care. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eAim of the Study:\u003c/h2\u003e\n \u003cp\u003eThis study aimed to conduct a comparative analysis of different trauma scoring systems as they apply to polytraumatized patients with injuries to various body regions. By examining the performance of these systems in patients treated at Tanta University Hospitals, we look to offer valuable insights into their effectiveness in predicting patient outcomes and guiding treatment across diverse trauma scenarios.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eOur hypotheses were:\u003c/h3\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eWhich trauma scoring system would perform best in predicting outcomes in polytraumatized patients?\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eHow would the predictive performance vary between different body regions?\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eStudy Design:\u003c/h3\u003e\n\u003cp\u003eA prospective study was conducted in the Emergency and Traumatology Department, Tanta University Hospitals. All patients underwent the standard procedures of the protocol.\u003c/p\u003e\n\u003ch3\u003eStudy Population:\u003c/h3\u003e\n\u003cp\u003eThis study was conducted on all polytrauma patients of both sexes presented to the Emergency Department, Tanta University Hospital. This study started from the start of December 2024 till the end of May 2025.\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria for this study encompassed adult patients aged 18 years or older who met the Berlin definition of polytrauma. To qualify as polytraumatized, patients had to present with an Abbreviated Injury Scale (AIS) score of \u0026ge;\u0026thinsp;3 in at least two different body regions and an Injury Severity Score (ISS) of \u0026ge;\u0026thinsp;16. Additionally, patients had to exhibit at least one critical physiological parameter, which included systolic blood pressure\u0026thinsp;\u0026le;\u0026thinsp;90 mmHg, Glasgow Coma Score (GCS)\u0026thinsp;\u0026le;\u0026thinsp;8, base excess \u0026le; -6.0, international normalized ratio (INR)\u0026thinsp;\u0026ge;\u0026thinsp;1.4, partial thromboplastin time\u0026thinsp;\u0026ge;\u0026thinsp;40 seconds, or age\u0026thinsp;\u0026ge;\u0026thinsp;70 years.\u003c/p\u003e\n\u003cp\u003eThe exclusion criteria for this study included patients under 18 years of age and those with isolated trauma to a single body region or an Injury Severity Score (ISS) of less than 16. Patients with incomplete or missing medical records, particularly regarding trauma scores and outcomes, were excluded to maintain data integrity. Additionally, patients who died before trauma scoring could be applied or were transferred from another hospital after receiving initial trauma care were not included in the study. Pregnant patients, individuals with significant pre-existing chronic or terminal illnesses, and those with isolated burn injuries were also excluded. Furthermore, patients who experienced significant delays in receiving initial trauma care were not considered for inclusion in the study.\u003c/p\u003e\n\u003ch3\u003eMethodology:\u003c/h3\u003e\n\u003cp\u003eAll included patients underwent a comprehensive evaluation, starting with a detailed history obtained from the patient or their relatives. This included sociodemographic data, medical history (hypertension, diabetes mellitus, hypercholesterolemia, cardiac disease such as ischemic heart disease or heart failure, and chest diseases like bronchial asthma or chronic obstructive pulmonary disease), surgical history, allergies, current medications, and special habits.\u003c/p\u003e\n\u003cp\u003eTrauma evaluation followed the Advanced Trauma Life Support (ATLS) protocol, which included both a primary and secondary survey. The primary survey adhered to the ABCDE approach:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eAirway assessment\u003c/strong\u003e involved identifying signs of airway obstruction and ensuring a patent, protected airway.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eBreathing assessment\u003c/strong\u003e included a thorough examination of the neck and chest through inspection (breathing pattern, respiratory rate, use of accessory muscles indicating respiratory distress), palpation (tenderness, subcutaneous emphysema, or tracheal deviation), percussion (hyperresonance or dullness), and auscultation (added sounds or decreased breath sounds). Pulse oximetry was used to detect hypoxemia.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eCirculation assessment\u003c/strong\u003e evaluated heart rate, pulse character, symmetry, blood pressure, preload, and perfusion, along with an abdominal, pelvic, and extremity examination. An electrocardiogram (ECG) was performed. Management included inserting two wide-bore cannulas to obtain blood samples, initiating fluid resuscitation, and administering medications as per the patient\u0026rsquo;s clinical condition.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eDisability assessment\u003c/strong\u003e involved evaluating the patient\u0026rsquo;s consciousness level using the Glasgow Coma Scale (GCS), detecting any neurological deficits, performing pupil assessment, and measuring random blood sugar levels.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eEnvironmental assessment\u003c/strong\u003e included monitoring temperature and ensuring proper patient exposure while maintaining safety.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAdditionally, the SAMPLE history (Signs/Symptoms, Allergies, Medications, Past Medical History, Last Oral Intake, and Events Leading to Injury) was obtained. Finally, all patients underwent trauma scoring using various trauma severity indices for further analysis.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eI. Assessment of Abbreviated Injury Scale (AIS) using:\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eThe 6-point ordinal AIS severity scale: 1\u0026thinsp;=\u0026thinsp;minor, 2\u0026thinsp;=\u0026thinsp;moderate, 3\u0026thinsp;=\u0026thinsp;serious, 4\u0026thinsp;=\u0026thinsp;severe, 5\u0026thinsp;=\u0026thinsp;critical, 6\u0026thinsp;=\u0026thinsp;maximum.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eBody regions affected and their number: Head, Face, Neck, Thorax, Abdomen and pelvic contents, Spine, Upper extremities, Lower extremities, and External, burns and other trauma.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003ch3\u003eII. Injury Severity Score (ISS):\u003c/h3\u003e\n\u003cp\u003eThe ISS is the sum of the squares of the highest AIS code in each of the three most severely injured ISS body regions. ISS ranges from 1 to 75. If an injury is assigned an AIS of 6 (finding a currently untreatable injury), the ISS score is automatically assigned 75.\u003c/p\u003e\n\u003ch3\u003eIII. Glasco Coma Scale (GCS):\u003c/h3\u003e\n\u003cp\u003eThe GCS is scored between 3 and 15, 3 being the worst and 15 being the best. It is composed of three parameters: best eye response (E), best verbal response (V), and best motor response (M). The components of the GCS should be recorded individually; for example, E2V3M4 results in a GCS score of 9.\u003c/p\u003e\n\u003ch3\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eIV. Revised Trauma Scores (RTS)\u003c/span\u003e: (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/h3\u003e\n\u003cp\u003eThe Revised Trauma Score (RTS) is one of the more common scores aimed at measuring the functional consequences of an injury. It uses three specific physiological parameters: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) the Glasgow Coma Scale (GCS); (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) systemic blood pressure; and (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) the respiratory rate. \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$\\:RTS\\:=\\left(0.9368\\:\\times\\:GCS\\right)+\\left(0.7326\\times\\:SBP\\right)+\\left(0.2908\\times\\:RR\\right)$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eThe RTS score ranges from 0 to 7.8408, with higher scores showing less severe trauma. An RTS of less than 4 is associated with a higher likelihood of mortality.\u003c/p\u003e\n\u003ch3\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eV. Trauma Score and Injury Severity Score (TRISS)\u003c/span\u003e: (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/h3\u003e\n\u003cp\u003eThe TRISS includes the Revised Trauma Score (RTS) and Injury Severity Score (ISS) indexes as well as the trauma type (blunt or penetrating) and the patient age. \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eVI. Kampala Trauma Score II\u003c/span\u003e: (\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/h3\u003e\n\u003cp\u003eKampala Trauma Score II total\u0026thinsp;=\u0026thinsp;A\u0026thinsp;+\u0026thinsp;B\u0026thinsp;+\u0026thinsp;C\u0026thinsp;+\u0026thinsp;D\u0026thinsp;+\u0026thinsp;E. \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInterpretation: KTS II (\u0026lt;\u0026thinsp;6\u0026thinsp;=\u0026thinsp;Severe injury \u0026minus;\u0026thinsp;7\u0026ndash;8\u0026thinsp;=\u0026thinsp;Moderate injury \u0026minus;\u0026thinsp;9\u0026ndash;10\u0026thinsp;=\u0026thinsp;Mild injury.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTrauma Scoring Systems and Their Calculation Methods\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth colspan=\"11\" align=\"left\"\u003e\n \u003cp\u003eRevised Trauma Scores (RTS)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003eGlasgow Coma Scale\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eSystolic Blood Pressure\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eRespiratory Rate\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003e13\u0026ndash;15\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;89\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;29\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u0026ndash;12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e76\u0026ndash;89\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;\u0026thinsp;29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u0026ndash;8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e50\u0026ndash;75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u0026ndash;9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u0026ndash;5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u0026ndash;49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u0026ndash;5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrauma Score and Injury Severity Score (TRISS)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProbability of survival\u0026thinsp;=\u0026thinsp;1/ (1\u0026thinsp;+\u0026thinsp;e\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;b\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ewhere\u0026nbsp;b\u0026thinsp;=\u0026thinsp;b\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/sub\u003e \u003cstrong\u003e+ b\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eRTS\u003c/span\u003e\u003cstrong\u003e)\u0026thinsp;+\u0026thinsp;b\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eISS\u003c/span\u003e\u003cstrong\u003e)\u0026thinsp;+\u0026thinsp;b\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e(A)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eA is decided by the following\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eValues for the coefficients\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrauma type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eBlunt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.2470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e0.9544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e-0.0768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e-1.9052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003ePenetrating\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.6029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e1.1430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e-0.1516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e-2.6676\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eKampala Trauma Score II\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;5 or \u0026gt;\u0026thinsp;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystolic blood pressure on admission (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e89\u0026thinsp;\u0026minus;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory rate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;29/minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;30/minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;9/minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeurological status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003eAlert\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003eResponds to verbal stimuli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003eResponds to painful stimuli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003eUnresponsive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore for significant injury\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003eOne injury\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd colspan=\"9\" align=\"left\"\u003e\n \u003cp\u003eMore than one injury\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy outcome:\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eApplication of different trauma scores in poly trauma patients.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAssess polytrauma patients from the moment patients are admitted in, till when discharged from ICU, we compared the accuracy of few scoring systems in predicting mortality rate in polytrauma patients, and then assessed the cost-effectiveness applying these methods.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy Ethics:\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eApproval from the ethical committee and informed consent was obtained from all participants or relatives in this research after an explanation of both benefits and risks.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eWe maintained privacy of participants\u0026rsquo; confidentiality of data through Putting a code number for each participant from the beginning to the end of the study.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eThe results of this research were used only for scientific purposes.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe study involved 300 polytraumatized patients admitted to Tanta University Hospitals, with an average age of 32.87\u0026thinsp;\u0026plusmn;\u0026thinsp;12.06 years. Males comprised the majority of the sample (79.67%). The most prevalent pre-existing conditions were a combination of hypertension and diabetes mellitus (18.67%), followed by hypertension alone (13%). Additionally, 51.67% of the patients were smokers. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Demographics and Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;300\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.87\u0026thinsp;\u0026plusmn;\u0026thinsp;12.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239 (79.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (20.33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eMedical History\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Co-morbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e177 (59%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypertension and Diabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (18.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (13%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypertension and Ischemic Heart Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIschemic Heart Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecial habits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155 (51.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe most frequent cause of injury was fallen from a height of two or more floors accounting for 24% (n\u0026thinsp;=\u0026thinsp;72) of cases. High-speed road traffic collisions followed closely, contributing to 23% (n\u0026thinsp;=\u0026thinsp;69) of trauma incidents, while motorcycle accidents were responsible for 19.33% (n\u0026thinsp;=\u0026thinsp;58).\u003c/p\u003e \u003cp\u003eAssaults involving weapons constituted 16% (n\u0026thinsp;=\u0026thinsp;48) of cases, ejections from vehicles were observed in 7.67% (n\u0026thinsp;=\u0026thinsp;23) of cases, and pedestrian or cyclist collisions with vehicles made up 4.67% (n\u0026thinsp;=\u0026thinsp;14). Less frequent but severe mechanisms included crush injuries, which accounted for 3% (n\u0026thinsp;=\u0026thinsp;9), and prolonged entrapments, occurring in 2.33% (n\u0026thinsp;=\u0026thinsp;7) of cases. \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePhysiological parameters analysis showed significant differences between survivors (82.67%) and non-survivors (17.33%). Non-survivors exhibited significantly higher respiratory (31.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48 vs. 27.76\u0026thinsp;\u0026plusmn;\u0026thinsp;5.69 bpm) and heart rates (129.48\u0026thinsp;\u0026plusmn;\u0026thinsp;9.95 vs. 113.13\u0026thinsp;\u0026plusmn;\u0026thinsp;16.07 bpm), while their mean arterial pressure (58.01\u0026thinsp;\u0026plusmn;\u0026thinsp;21.74 vs. 72.36\u0026thinsp;\u0026plusmn;\u0026thinsp;10.82 mmHg) was lower. Additionally, capillary refill time was notably prolonged (3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01 vs. 2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78 sec) in non-survivors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all), indicating hemodynamic instability and poor perfusion. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysiological Parameters and Outcomes in studied patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eParameter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;Std\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eT test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eRespiratory Rate (Breath/min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e18\u0026ndash;38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e27.76\u0026thinsp;\u0026plusmn;\u0026thinsp;5.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e25\u0026ndash;37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e31.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e18\u0026ndash;38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e28.39\u0026thinsp;\u0026plusmn;\u0026thinsp;5.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eHeart rate\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(Beat/ min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e80\u0026ndash;155\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e113.13\u0026thinsp;\u0026plusmn;\u0026thinsp;16.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-7.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e110\u0026ndash;140\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e129.48\u0026thinsp;\u0026plusmn;\u0026thinsp;9.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e80\u0026ndash;155\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e115.96\u0026thinsp;\u0026plusmn;\u0026thinsp;16.39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMean arterial Blood Pressure (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e40\u0026ndash;96.67\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e72.36\u0026thinsp;\u0026plusmn;\u0026thinsp;10.82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e7.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e26.67\u0026ndash;106.67\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e58.01\u0026thinsp;\u0026plusmn;\u0026thinsp;21.74\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e26.67\u0026ndash;106.67\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e69.87\u0026thinsp;\u0026plusmn;\u0026thinsp;14.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eCapillary Refill Time (sec)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-10.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHead trauma appears to be the most critical factor influencing mortality among polytraumatized patients, as non-survivors exhibited significantly higher head abbreviated injury Scale (5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8) compared to survivors (1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). In contrast, injuries to the face, neck, thorax, abdomen, spine, and lower extremities did not show statistically significant differences between the two groups. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssessment of Abbreviated Injury Scale (AIS)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBody Region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;Std\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eT test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-15.81966\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.00001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-1.44448\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.149654\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNeck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-0.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.853862\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eThorax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e1.42822\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.154277\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAbdomen and pelvic contents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-0.38063\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.703749\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-1.42206\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.156055\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eUpper extremities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e2.48835\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.01338\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLower extremities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-0.73303\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.464118\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eExternal, burns and other trauma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e1.09999\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.272224\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTrauma severity scores clearly differentiate between survivors and non-survivors, with higher scores observed in non-survivors for the Injury Severity Score (ISS: 63.92\u0026thinsp;\u0026plusmn;\u0026thinsp;13.35 vs. 44.57\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). Similarly, non-survivors had significantly lower scores in key prognostic indicators, including the Glasgow Coma Scale (GCS: 6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65 vs. 14.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), Revised Trauma Score (RTS: 4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01 vs. 7.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), Trauma Score and Injury Severity Score (TRISS: 0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 vs. 0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), and Kampala Trauma Score II (KTS II: 3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29 vs. 6.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssessment of Trauma Scores:\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eScore\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;Std\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eT test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eInjury Severity Score (ISS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e19\u0026ndash;75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e44.57\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e-7.97102\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.00001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e43\u0026ndash;75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e63.92\u0026thinsp;\u0026plusmn;\u0026thinsp;13.35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e19\u0026ndash;75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e47.92\u0026thinsp;\u0026plusmn;\u0026thinsp;17.51\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGlasco Coma Scale (GCS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7\u0026ndash;15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e25.3204\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.00001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3\u0026ndash;8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3\u0026ndash;15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e12.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eRevised Trauma Scores (RTS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5.68\u0026ndash;7.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e26.14526\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.00001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.07\u0026ndash;5.97\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.07\u0026ndash;7.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTrauma Score and Injury Severity Score (TRISS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.15\u0026ndash;0.99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e23.29156\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.00001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;0.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;0.99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eKampala Trauma Score II\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAlive (N\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4\u0026ndash;8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e20.33228\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.00001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDied (N\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u0026ndash;6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal (N\u0026thinsp;=\u0026thinsp;300)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u0026ndash;8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePulmonary injuries were present in varying frequencies, with pneumothorax, hemothorax, and flail chest affecting 7.67%, 6.33%, and 5.33% of patients, respectively, while tension pneumothorax was identified in 4.67% of cases.\u003c/p\u003e \u003cp\u003eIn the abdominal and pelvic region, intraperitoneal free fluid (IPFF) was the most common finding, detected in 70.67% of patients. Liver injuries including hematoma or contusion and splenic injuries, including tear, contusion, or hematoma, were observed in 9% and 25.67%, respectively. Other noted abnormalities included retroperitoneal extension (11%), renal hematoma (7%), pelvic hematoma (3.67%), and pelvic fractures (5.67%).\u003c/p\u003e \u003cp\u003eNeurological injuries were widespread, with subdural hematoma (SDH) and subarachnoid hemorrhage (SAH) each occurring in 22% of cases. Brain contusions were reported in 20.33%, intraventricular hemorrhage (IVH) in 11%, and brain edema in 18.33%. Less frequent findings included pneumocephalus (2%) and skull fractures (3%), while maxillofacial injuries were documented in 16% of patients.\u003c/p\u003e \u003cp\u003eSubdural hematoma (SDH), subarachnoid hemorrhage (SAH), brain contusions, intraventricular hemorrhage (IVH), and Liver injuries were significantly more common in non-survivors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hemothorax was significantly associated with mortality (p\u0026thinsp;=\u0026thinsp;0.039).\u003c/p\u003e \u003cp\u003eThe ROC (Receiver Operating Characteristic) curve presented in the image \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e evaluates the predictive performance of various trauma scoring systems for in-hospital mortality. The AUC (Area Under the Curve) values indicate how well each score differentiates between survivors and non-survivors. Notably, TRISS (AUC\u0026thinsp;=\u0026thinsp;0.99), RTS (AUC\u0026thinsp;=\u0026thinsp;0.99), and GCS (AUC\u0026thinsp;=\u0026thinsp;0.99) demonstrate nearly perfect discrimination, with their curves positioned close to the upper left corner, indicating high sensitivity and specificity. The Kampala Trauma Score (KTS) also performs exceptionally well (AUC\u0026thinsp;=\u0026thinsp;0.97). In contrast, the Injury Severity Score (ISS) shows poor predictive ability, with an AUC of only 0.18. \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRidge Regression and Logistic Regression models were employed to evaluate the predictive strength of various trauma scoring systems in determining in-hospital mortality. The Trauma Score and Injury Severity Score (TRISS) demonstrates the highest coefficient in both models (0.322 in Ridge Regression and 1.846 in Logistic Regression), confirming its strong predictive ability for survival. Similarly, GCS (1.753) and RTS (1.378) in Logistic Regression also show significant positive coefficients, indicating that higher values in these scores are associated with improved survival outcomes.\u003c/p\u003e \u003cp\u003eConversely, the Injury Severity Score (ISS) shows a negative coefficient (-0.763 in Logistic Regression), suggesting that higher ISS values correlate with increased mortality risk. The Kampala Trauma Score (KTS) also exhibits a negative coefficient in Ridge Regression (-0.1456), further supporting its association with higher mortality at lower values. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression Analysis of Trauma Scoring Systems\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrauma Scoring Systems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRidge Regression Coefficients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLogistic Regression Coefficients\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInjury Severity Score (ISS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11986693404395911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.763014553013029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGCS score (/15)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.17584673790642844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.752781132778722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRevised trauma Score (RTS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.086857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3782522396638301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrauma Score and Injury Severity Score (TRISS) or Probability of Survival (Ps)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32204571491952233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8459908825077789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKampala Trauma Score II\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7751296320199179\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study was conducted on 300 polytraumatized patients admitted to Tanta University Hospitals, with an average age of 32.87\u0026thinsp;\u0026plusmn;\u0026thinsp;12.06 years. The majority of the sample was male (79.67%). The most common pre-existing medical conditions included a combination of hypertension and diabetes mellitus (18.67%), followed by hypertension alone (13%). Additionally, a significant proportion of patients (51.67%) were smokers, which could have influenced trauma outcomes.\u003c/p\u003e \u003cp\u003eRegarding the mechanism of injury, falls from a height of two or more floors were the leading cause, accounting for 24% (n\u0026thinsp;=\u0026thinsp;72) of cases. This was followed closely by high-speed road traffic collisions (23%, n\u0026thinsp;=\u0026thinsp;69) and motorcycle accidents (19.33%, n\u0026thinsp;=\u0026thinsp;58). Notably, assault-related injuries accounted for 16% (n\u0026thinsp;=\u0026thinsp;48) of cases, emphasizing the role of interpersonal violence in trauma admissions. Other mechanisms included vehicle ejections (7.67%), pedestrian or cyclist collisions (4.67%), crush injuries (3%), and prolonged entrapments (2.33%).\u003c/p\u003e \u003cp\u003eA study by \u003cb\u003eBesra RC et al. (2024)\u003c/b\u003e, which examined 204 patients, found that the majority were aged 21\u0026ndash;30 years and that males comprised 85.3%. Road traffic accidents (RTA) were the leading cause of injury, accounting for 50% of cases, followed by assaults (24.5%), stab wounds (9.3%), and falls from height (8.3%). (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) When compared to other studies, our findings align with the research conducted by \u003cb\u003eMerchant AA, et al. (2023)\u003c/b\u003e, who studied 2,817 trauma patients and reported a mean age of 41.2\u0026thinsp;\u0026plusmn;\u0026thinsp;17.8 years, with 80.6% being male. In that study, blunt trauma was the predominant injury type (85.2%), and road traffic crashes were the leading cause (59.2%). About half of the patients (50.9%) were admitted as polytrauma patients. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) Another study by \u003cb\u003eMilton M, et al. (2021)\u003c/b\u003e, which analyzed 108 polytrauma cases, reported a slightly older patient population with a mean age of 36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4 years, and a similar male predominance (86.1%). Their findings also identified road traffic injuries (63%) and assaults (33.3%) as the most frequent causes of trauma. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePhysiological Parameters and Mortality Prediction\u003c/h2\u003e \u003cp\u003eAnalysis of physiological parameters revealed significant differences between survivors (82.67%) and non-survivors (17.33%). Non-survivors had notably higher respiratory rates (31.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48 vs. 27.76\u0026thinsp;\u0026plusmn;\u0026thinsp;5.69 bpm, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and heart rates (129.48\u0026thinsp;\u0026plusmn;\u0026thinsp;9.95 vs. 113.13\u0026thinsp;\u0026plusmn;\u0026thinsp;16.07 bpm, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). They also exhibited lower mean arterial blood pressure (58.01\u0026thinsp;\u0026plusmn;\u0026thinsp;21.74 vs. 72.36\u0026thinsp;\u0026plusmn;\u0026thinsp;10.82 mmHg, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and prolonged capillary refill time (3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01 vs. 2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78 sec, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating hemodynamic instability and poor perfusion.\u003c/p\u003e \u003cp\u003eThese findings are consistent with those of \u003cb\u003eMerchant AA, et al. (2023)\u003c/b\u003e, who reported an average systolic blood pressure of 124.4\u0026thinsp;\u0026plusmn;\u0026thinsp;22.3 mmHg and a mean respiratory rate of 20.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 breaths per minute. Their study also highlighted the significant role of physiological parameters in trauma outcome prediction. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTrauma Severity Scores and Mortality\u003c/h2\u003e \u003cp\u003eTrauma severity scores effectively distinguish between survivors and non-survivors. Non-survivors had significantly higher ISS scores (63.92\u0026thinsp;\u0026plusmn;\u0026thinsp;13.35 vs. 44.57\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) and lower scores in key prognostic indicators such as GCS (6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65 vs. 14.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), RTS (4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01 vs. 7.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), TRISS (0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 vs. 0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), and Kampala Trauma Score II (KTS II: 3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29 vs. 6.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001).\u003c/p\u003e \u003cp\u003eIn the study by \u003cb\u003eBesra RC, et al. (2024)\u003c/b\u003e, the mean and standard deviation values for TRISS, RTS, NISS, and ISS were 15.91\u0026thinsp;\u0026plusmn;\u0026thinsp;19.65, 19.66\u0026thinsp;\u0026plusmn;\u0026thinsp;21.70, 7.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02, and 6.01\u0026thinsp;\u0026plusmn;\u0026thinsp;21.90, respectively. The higher mean scores of ISS and NISS suggest a greater severity of injuries among the study population. Their findings further support the significance of trauma scores in predicting mortality, with NISS and TRISS emerging as the most effective predictors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). These results align with our study, where TRISS consistently demonstrated superior predictive accuracy for in-hospital mortality, emphasizing its reliability in assessing trauma outcomes in polytraumatized patients. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) In comparison, \u003cb\u003eMerchant AA, et al. (2023)\u003c/b\u003e reported an ISS of 12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3 across all trauma patients, with survivors averaging 10.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7 and non-survivors 18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0. Their TRISS scores were 93.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8 (alive: 96.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4, deceased: 78.6\u0026thinsp;\u0026plusmn;\u0026thinsp;21.8), and RTS scores were 7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 (alive: 7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7, deceased: 5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4). GCS scores followed a similar pattern, with an overall mean of 12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9, but significantly lower in deceased patients (6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0). (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) The findings by \u003cb\u003eMilton M, et al. (2021)\u003c/b\u003e also support these trends, reporting baseline ISS (31.07\u0026thinsp;\u0026plusmn;\u0026thinsp;11.52), RTS (6.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76), and TRISS (76.48\u0026thinsp;\u0026plusmn;\u0026thinsp;26.58). 30-day survivors had lower ISS (28.01\u0026thinsp;\u0026plusmn;\u0026thinsp;9.05 vs. 38.83\u0026thinsp;\u0026plusmn;\u0026thinsp;13.98) and higher RTS (7.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12 vs. 5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88) and TRISS (87.82\u0026thinsp;\u0026plusmn;\u0026thinsp;15.81 vs. 52.81\u0026thinsp;\u0026plusmn;\u0026thinsp;31.47) compared to non-survivors, indicating greater trauma severity in those who did not survive. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eROC Curve and Predictive Performance\u003c/h2\u003e \u003cp\u003eThe Receiver Operating Characteristic (ROC) curve analysis demonstrated that TRISS (AUC\u0026thinsp;=\u0026thinsp;0.99), RTS (AUC\u0026thinsp;=\u0026thinsp;0.99), and GCS (AUC\u0026thinsp;=\u0026thinsp;0.99) had the highest predictive accuracy for in-hospital mortality. The Kampala Trauma Score (KTS) also performed well (AUC\u0026thinsp;=\u0026thinsp;0.97), whereas the Injury Severity Score (ISS) exhibited poor predictive ability (AUC\u0026thinsp;=\u0026thinsp;0.18).\u003c/p\u003e \u003cp\u003eThe study by \u003cb\u003eBesra RC, et al. (2024)\u003c/b\u003e assessed the predictive accuracy of various trauma scoring systems using Receiver Operating Characteristic (ROC) curves, demonstrating their effectiveness in mortality prediction. The Area Under the ROC Curve (AUROC) values were highest for TRISS (0.8521) and NISS (0.8361), followed by ISS (0.8169) and RTS (0.7953). While all four scores were statistically significant in predicting mortality, TRISS and NISS emerged as the most precise predictors. These findings reinforce the superior role of TRISS in trauma prognosis, supporting its effectiveness in predicting in-hospital mortality in polytraumatized patients, as observed in our study. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) \u003cb\u003eMerchant AA, et al. (2023)\u003c/b\u003e found that for polytrauma patients, TRISS (AUC\u0026thinsp;=\u0026thinsp;0.729) and ISS (AUC\u0026thinsp;=\u0026thinsp;0.722) were the most effective predictors of in-hospital mortality compared to other trauma scoring systems. In contrast to its high predictive value in other trauma groups, GCS had a lower AUC (0.638) for polytrauma patients. Similarly, RTS showed the least predictive power for in-hospital mortality in this group (AUC\u0026thinsp;=\u0026thinsp;0.595) and was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.052). (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) Similarly, \u003cb\u003eMilton M, et al. (2021)\u003c/b\u003e reported TRISS (AUROC\u0026thinsp;=\u0026thinsp;0.828) as the best predictor of mortality, followed by ISS (AUROC\u0026thinsp;=\u0026thinsp;0.755), RTS (AUROC\u0026thinsp;=\u0026thinsp;0.715), and REMS (AUROC\u0026thinsp;=\u0026thinsp;0.656). (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eRegression Analysis and Trauma Score Comparison\u003c/h2\u003e \u003cp\u003eRegression analysis further confirmed that TRISS was the most significant predictor of survival, with the highest coefficients in both Ridge Regression (0.322) and Logistic Regression (1.846) models. GCS (1.753) and RTS (1.378) also demonstrated strong predictive power in the Logistic Regression model. In contrast, ISS (-0.763) and KTS (-0.1456) had negative coefficients, indicating that higher scores correlated with increased mortality risk.\u003c/p\u003e \u003cp\u003eThese findings highlight the superior predictive power of combined anatomical and physiological trauma scores (TRISS) over purely anatomical ones (ISS). The results align with the conclusions of previous research, suggesting that trauma scoring systems integrating physiological parameters offer better mortality predictions than those relying solely on injury severity.\u003c/p\u003e \u003cp\u003eIn this respect, according to \u003cb\u003eBesra RC, et al. (2024)\u003c/b\u003e, in which the logistic regression analysis of the results revealed the NISS and TRISS to be major predictors of mortality, particularly in individuals with injuries to their abdomen and thoracic cavity. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThis study has several limitations that should be considered. First, as a single-center study conducted at Tanta University Hospitals, the findings may not be generalizable to other healthcare settings with different trauma management protocols and resources. Second, although the sample size of 300 patients is adequate, it may not capture the full variability of trauma severity seen in larger, multi-center studies. Third, the study focused on in-hospital outcomes over a six-month period, limiting the ability to assess long-term survival, functional recovery, and post-discharge complications. Additionally, the exclusion of patients with incomplete medical records or pre-existing chronic conditions may introduce selection bias, potentially affecting the applicability of the results to all polytrauma patients. Lastly, while this study analyzed well-established trauma scoring systems (TRISS, RTS, ISS, and KTS), newer models such as the BIG score and TRIAGES score were not fully explored. Future research should address these limitations by incorporating larger, multi-center datasets, extending follow-up periods, and integrating newer trauma scoring systems to enhance predictive accuracy and clinical applicability.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study provides a comprehensive comparative analysis of various trauma scoring systems applied to polytraumatized patients. Our findings indicate that TRISS, RTS, and GCS are the most accurate predictors of in-hospital mortality, confirming their reliability in clinical settings. In contrast, ISS showed limited predictive capability, suggesting that anatomical scores alone may not sufficiently capture trauma severity.\u003c/p\u003e \u003cp\u003eThe integration of physiological parameters significantly enhances the accuracy of trauma scoring systems, as demonstrated by the superior performance of TRISS and RTS. These results align with previous research indicating that a combined anatomical and physiological approach is superior to standalone anatomical scoring methods in predicting trauma outcomes.\u003c/p\u003e \u003cp\u003eClinically, these findings support the routine application of TRISS and RTS in trauma centers to optimize patient assessment, triage, and treatment planning. Future research should focus on further refining trauma scoring models, integrating newer biomarkers, and exploring the applicability of these findings across diverse trauma populations and healthcare settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAbbreviated Injury Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eATLS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdvanced Trauma Life Support\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea Under the Curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectrocardiogram\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlasgow Coma Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eINR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational normalized ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eISS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInjury Severity Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIVH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintraventricular hemorrhage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKTS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKampala Trauma Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNISS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNew Injury Severity Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC curve\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver Operating Characteristic curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRTS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRevised Trauma Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esubarachnoid hemorrhage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSDH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSubdural hematoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTRIAGES\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTrauma Rating Index in Age\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGlasgow Coma Scale\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRespiratory Rate\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eand Systolic Blood Pressure score\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTRISS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTrauma and Injury Severity Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ewISS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWeighted Injury Severity Score.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclaimer:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo large language models (LLMs), including ChatGPT, have been credited with authorship in this manuscript. Any use of LLMs is documented appropriately within the methods section of the manuscript.\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e \u003cp\u003e This study was approved by the ethical committee under approval code (36264PR927/11/24) at Tanta University Hospitals. Informed consent was obtained from all participants or their legal representatives prior to participation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication:\u003c/strong\u003e \u003cp\u003eConsent for publication was obtained from all participants or their legal representatives. All participants were informed that their data might be published anonymously in scientific publications.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed significantly to the study design and implementation. Data collection was primarily conducted by Hala Desouky Ali and Hend Mohamed Mansour. Data analysis and interpretation were performed by all authors. The manuscript was drafted by Radwa Muhammad Ashour and critically reviewed and revised by all authors. All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e \u003cp\u003eWe gratefully acknowledge the contributions of the Emergency and Traumatology Department staff at Tanta University Hospitals for their assistance and support during the study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during this study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRapsang AG, Shyam DC. Scoring systems of severity in patients with multiple trauma. Cirug\u0026iacute;a Espa\u0026ntilde;ola (English Edition). 2015;93(4):213\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRau CS, Wu SC, Kuo PJ, Chen YC, Chien PC, Hsieh HY, et al. Polytrauma defined by the new Berlin definition: a validation test based on propensity-score matching approach. Int J Environ Res Public Health. 2017;14(9):1045.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eServi\u0026aacute; L, Badia M, Montserrat N, Trujillano J. Severity scores in trauma patients admitted to ICU. Physiological and anatomic models. Med Intensiva (English Edition). 2019;43(1):26\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaduz R, Kugelmeier P, Meili S, D\u0026ouml;ring R, Meier C, Wahl P. Major influence of interobserver reliability on polytrauma identification with the Injury Severity Score (ISS): Time for a centralised coding in trauma registries? Injury. 2017;48(4):885\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrandic L, Olic I, Pogorelic Z, Mrklic I, Perko Z. The value of injury severity score and abbreviated injury scale in the management of traumatic injuries of parenchymal abdominal organs. Acta Clin Croat. 2017;56:453\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu Z, Xu F, Chen D. Predictive value of Modified Early Warning Score (MEWS) and Revised Trauma Score (RTS) for the short-term prognosis of emergency trauma patients: a retrospective study. BMJ Open. 2021;11(3):e041882.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndurkar Sr SK, Ghormade PS, Akhade S, Sarma B. Use of the Trauma and Injury Severity Score (TRISS) as a predictor of patient outcome in cases of trauma presenting in the trauma and emergency department of a tertiary care institute. Cureus. 2023;15(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi J, Shen J, Zhu M, Wheeler KK, Lu B, Kenney B, et al. A new weighted injury severity scoring system: better predictive power for adult trauma mortality. Inj Epidemiol. 2019;6:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShiraishi A, Otomo Y, Yoshikawa S, Morishita K, Roberts I, Matsui H. Derivation and validation of an easy-to-compute trauma score that improves prognostication of mortality or the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure (TRIAGES) score. Crit Care. 2019;23:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH\u0026ouml;ke MH, Usul E, \u0026Ouml;zkan S. Comparison of trauma severity scores (ISS, NISS, RTS, BIG Score, and TRISS) in multiple trauma patients. J Trauma Nursing| JTN. 2021;28(2):100\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRestrepo-\u0026Aacute;lvarez CA, Valderrama-Molina CO, Giraldo-Ram\u0026iacute;rez N, Constain-Franco A, Puerta A, Le\u0026oacute;n AL et al. Trauma severity scores. Colombian Journal of Anesthesiology [Internet]. 2016;44(4):317\u0026ndash;23. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.sciencedirect.com/science/article/pii/S2256208716300347\u003c/span\u003e\u003cspan address=\"https://www.sciencedirect.com/science/article/pii/S2256208716300347\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRastogi D, Meena S, Sharma V, Singh GK. Causality of injury and outcome in patients admitted in a major trauma center in North India. Int J Crit Illn Inj Sci. 2014;4(4):298\u0026ndash;302.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBesra RC, Toppo S, Bodra P, Kujur A, Tudu MB, Bharti B et al. Prediction of Mortality and Outcome of Various Trauma Scores in Polytrauma Patients. Cureus. 2024;16(9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMerchant AAH, Shaukat N, Ashraf N, Hassan S, Jarrar Z, Abbasi A et al. Which curve is better? A comparative analysis of trauma scoring systems in a South Asian country. Trauma Surg Acute Care Open. 2023;8(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMilton M, Engelbrecht A, Geyser M. Predicting mortality in trauma patients-A retrospective comparison of the performance of six scoring systems applied to polytrauma patients from the emergency centre of a South African central hospital. Afr J Emerg Med. 2021;11(4):453\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Trauma Severity Indices, Multiple Trauma, Abbreviated Injury Scale","lastPublishedDoi":"10.21203/rs.3.rs-6841438/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6841438/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Trauma remains a leading cause of morbidity and mortality, necessitating the use of trauma scoring systems to assess injury severity, guide clinical management, and predict patient outcomes. Various trauma scoring models exist, but their accuracy in predicting mortality among polytraumatized patients remains debated. This study aimed to evaluate and compare the predictive accuracy of different trauma scoring systems in polytraumatized patients with injuries across multiple anatomical regions admitted to Tanta University Hospitals. The study further explored the correlation between trauma scores and patient outcomes, including survival and mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A prospective study was conducted on 300 polytrauma patients admitted between December 2024 and May 2025. Patients were evaluated using multiple trauma scoring systems, including the Injury Severity Score (ISS), Abbreviated Injury Scale (AIS), Revised Trauma Score (RTS), Trauma and Injury Severity Score (TRISS), and Kampala Trauma Score (KTS). Physiological parameters such as heart rate, respiratory rate, blood pressure, and capillary refill time were recorded. The predictive performance of these scoring systems was assessed using regression analysis and Receiver Operating Characteristic (ROC) curve analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The majority of the study population (79.67%) were male, with a mean age of 32.87 ± 12.06 years. Falls from heights (24%) and road traffic collisions (23%) were the leading causes of polytrauma. Among the trauma scores, TRISS (AUC = 0.99), RTS (AUC = 0.99), and Glasgow Coma Scale (GCS) (AUC = 0.99) demonstrated the highest predictive accuracy for mortality, while ISS showed poor performance (AUC = 0.18). Regression analysis confirmed that TRISS had the strongest predictive value for survival, followed by RTS and GCS, whereas ISS and KTS were less reliable predictors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e TRISS, RTS, and GCS demonstrated the highest predictive accuracy for mortality (AUC = 0.99), whereas ISS showed limited predictive ability (AUC = 0.18). Our findings highlight the critical role of integrating physiological parameters in trauma scoring for improved clinical decision-making.\u003c/p\u003e","manuscriptTitle":"Comparative Analysis of Trauma Scoring Systems Across Body Regions in Polytraumatized Patients: Outcomes from Tanta University Hospitals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 15:47:22","doi":"10.21203/rs.3.rs-6841438/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c214f935-98b7-4000-8319-9bd29b6f3c0a","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T18:53:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-17 15:47:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6841438","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6841438","identity":"rs-6841438","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}