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Background: Sepsis is a leading cause of mortality in polytrauma patients, especially beyond the first week, and its management is vital for reducing multiorgan failure and improving survival rates. This is particularly critical in geriatric polytrauma patients due to factors such as age-related physiological alterations and weakened immune systems. This study aimed to investigate various clinical and laboratory parameters associated with sepsis in polytrauma patients aged < 65 years and ≥65 years, with the secondary objective of comparing sources of infection in these patient groups. Methods: A retrospective cohort study was conducted at the University Hospital Zurich from August 1996 to December 2012. Participants included trauma patients aged ≥16 years with an Injury Severity Score (ISS) ≥ 16 who were diagnosed with sepsis within 31 days of admission. Patients in the age groups < 65 and ≥65 years were compared in terms of sepsis development. The parameters examined included patient and clinical data as well as laboratory values. The statistical methods encompassed group comparisons with Welch's t-test and logistic regression. Results: A total of 3059 polytrauma patients were included in the final study. The median age in the group < 65 years was 37 years, with a median ISS of 28. In the patient group ≥ 65 years, the median age was 75 years, with a median ISS of 27. Blunt trauma mechanism, ISS, leucocytosis at admission, and anaemia at admission were associated with sepsis in younger patients but not in geriatric patients, whereas sex, pH at admission, lactate at admission, and Quick values at admission were not significantly linked with sepsis in either age group. Pneumonia was the most common cause of sepsis in both age groups. Conclusions: Various parameters linked to sepsis in younger polytrauma patients do not necessarily correlate with sepsis in geriatric individuals with polytrauma. Hence, it becomes critical to recognize imminent danger, particularly in geriatric patients. In this context, the principle of "HIT HARD and HIT EARLY" is highly important as a proactive approach to effectively address sepsis in the geriatric trauma population, including the preclinical setting.
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The Watson Trauma Pathway Explorer ® is an outcome prediction tool invented by the University Hospital of Zurich in collaboration with IBM®, representing an artificial intelligence application to predict the most adverse outcome scenarios in polytrauma patients: Systemic Inflammatory Respiratory Syndrome (SIRS), sepsis within 21 days and death within 72 h. The hypothesis was how lactate values woud be associated with the incidence of sepsis. Data from 3653 patients in an internal database, with ongoing implementation, served for analysis. Patients were split in two groups according to sepsis presence, and lactate values were measured at formerly defined time points from admission until 21 days after admission for both groups. Differences between groups were analyzed; time points with lactate as independent predictor for sepsis were identified. The predictive quality of lactate at 2 and 12 h after admission was evaluated. Threshold values between groups at all timepoints were calculated. Lactate levels differed from less than 2 h after admission until the end of the observation period (21 d). Lactate represented an independent predictor for sepsis from 12 to 48 h and 14 d to 21 d after admission relative to ISS levels. AUROC was poor at 2 and 12 h after admission with a slight improvement at the 12 h mark. Lactate levels decreased over time at a range of 2 [mmol/L] for 6-8 h after admission. These insights may allow for time-dependent referencing of lactate levels and anticipation of subsequent sepsis, although further parameters must be considered for a higher predictability.
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IBM and the University Hospital Zurich have developed an online tool for predicting outcomes of a patient with polytrauma, the IBM WATSON Trauma Pathway Explorer® . The three predicted outcomes are Systemic Inflammatory Response Syndrome (SIRS) and sepsis within 21 days as well as early death within 72 hours since the admission of the patient. The validated Trauma Pathway Explorer® offers insights into the most common laboratory parameters, such as procalcitonin (PCT). Sepsis is one of the most important complications after polytrauma, which is why it is crucial to detect it early. This study aimed to examine the time-dependent relationship between PCT values and sepsis, based on the WATSON technology. A total of 3653 patients were included, and ongoing admissions are incorporated continuously. Patients were split into two groups (sepsis and non-sepsis), and the PCT value was assessed for 21 days (1, 2, 3, 4, 6, 8, 12, 24, 48 hours, and 3, 4, 5, 7, 10, 14 and 21 days). The Mann-Whitney U-Test was used to evaluate the difference between the two groups. Binary logistic regression was utilized to examine the dependency of prediction. The Closest Top-left Threshold Method provided time-specific thresholds at which the PCT level is predictive for sepsis. At p <0.05, the data were declared significant. R was used to conduct all statistical analyses. The Mann-Whitney U-test showed a significant difference in PCT values in sepsis and non-sepsis patients between 12 and 24 hours, including post-hoc analysis (p <0.05). Likewise, the p-value started to be significant between 12 and 24 hours in the binary logistic regression (p <0.05). The threshold value of PCT to predict sepsis at 24 hours is 0.7µg/l, and at 48 hours 0.5µg/l. The presented time course of PCT levels in polytrauma patients shows the PCT as a separate predictor for sepsis relatively early. Even later, during the 21-day observation period, time-dependent PCT values may be utilized as a benchmark for the early and preemptive detection of sepsis, which may reduce death from septic shock and other deadly infectious episodes.
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The University Hospital Zurich together with IBM® invented an outcome prediction tool based on the IBM Watson technology, the Watson Trauma Pathway Explorer®. This tool is an artificial intelligence to predict three outcome scenarios in polytrauma patients: the Systemic Inflammatory Response Syndrome (SIRS) and sepsis within 21 days as well as death within 72 h. The knowledge of a patient's future under standardized trauma treatment might be of utmost importance. Here, new time-related insights on the C-reactive protein (CRP) and sepsis are presented. Meanwhile, the validated IBM Watson Trauma Pathway Explorer® offers a time-related insight into the most frequent laboratory parameters. In total, 3653 patients were included in the databank used by the application, and ongoing admissions are constantly implemented. The patients were grouped according to sepsis, and the CRP was analyzed according to the point of time at which the value was acquired (1, 2, 3, 4, 6, 8, 12, 24, and 48 h and 3, 4, 5, 7, 10, 14, and 21 days). The differences were analyzed using the Mann-Whitney U-Test; binary logistic regression was used to determine the dependency of prediction, and the Closest Top-left Threshold Method presented time-specific thresholds at which CRP is predictive for sepsis. The data were considered as significant at p < 0.05, all analyses were performed in R. The differences in the CRP value of the non-sepsis and sepsis groups are starting to be significant between 6 and 8 h (p < 0.05) after admission inclusive of post hoc analysis, and the binary logistic regression depicts a similar picture. The level of significance is reached between 6 and 8 h (p < 0.05) after admission. The knowledge of the outcome reflected by the CRP in polytrauma patients improves the surgeon's tactical position to indicate operations to reduce antigenic load and avoid an infectious adverse outcome.
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Introduction: Big data-based artificial intelligence (AI) has become increasingly important in medicine and may be helpful in the future to predict diseases and outcomes. For severely injured patients, a new analytics tool has recently been developed (WATSON Trauma Pathway Explorer) to assess individual risk profiles early after trauma. We performed a validation of this tool and a comparison with the Trauma and Injury Severity Score (TRISS), an established trauma survival estimation score. Methods: Prospective data collection, level I trauma centre, 1 January 2018-31 December 2019. INCLUSION CRITERIA: Primary admission for trauma, injury severity score (ISS) ≥ 16, age ≥ 16. PARAMETERS: Age, ISS, temperature, presence of head injury by the Glasgow Coma Scale (GCS). OUTCOMES: SIRS and sepsis within 21 days and early death within 72 h after hospitalisation. STATISTICS: Area under the receiver operating characteristic (ROC) curve for predictive quality, calibration plots for graphical goodness of fit, Brier score for overall performance of WATSON and TRISS. Results: Between 2018 and 2019, 107 patients were included (33 female, 74 male; mean age 48.3 ± 19.7; mean temperature 35.9 ± 1.3; median ISS 30, IQR 23-36). The area under the curve (AUC) is 0.77 (95% CI 0.68-0.85) for SIRS and 0.71 (95% CI 0.58-0.83) for sepsis. WATSON and TRISS showed similar AUCs to predict early death (AUC 0.90, 95% CI 0.79-0.99 vs. AUC 0.88, 95% CI 0.77-0.97; p = 0.75). The goodness of fit of WATSON (X2 = 8.19, Hosmer-Lemeshow p = 0.42) was superior to that of TRISS (X2 = 31.93, Hosmer-Lemeshow p < 0.05), as was the overall performance based on Brier score (0.06 vs. 0.11 points). Discussion: The validation supports previous reports in terms of feasibility of the WATSON Trauma Pathway Explorer and emphasises its relevance to predict SIRS, sepsis, and early death when compared with the TRISS method.
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INTRODUCTION: Early physiological assessment of multiple injured patients is crucial for decision making and has relied on personal experience of trauma experts. We have developed a new visual analytics tool (Sankey diagram, Watson Trauma Health care tool) that includes known prognostic parameters for polytrauma patients to help guide assessment and treatment decisions for physicians involved in trauma care. METHODS: A prospectively collected trauma database of a single level I trauma center (3655 patients) was used. INCLUSION CRITERIA: age >16 years, an injury severity score (ISS) >16 and presence of a complete data set in the database. Data collected included admission values of patient age, injury scoring, shock classification, temperature, acid-base and hemostasis parameters. All of these parameters were collected daily as longitudinal parameters. Endpoints of the clinical course we considered were sepsis, SIRS and early in hospital mortality (<72 h). A proof of concept of the visualization was developed over a 2-year period in a cooperation between physicians and engineers. Statistically, the most predictive parameters were selected by binary logistic regression and ROC analysis. RESULTS: A dynamic interactive multilayer Sankey diagram, based on cohort similarities, was developed in a collaboration between the University Hospital of Zurich, Department of Trauma and IBM, from August 2017 until January 2018. It is a modular tool and allows any user to add a new patient, or work with an existing case. The visualization used the data-driven documents (D3) interactive visualization library to create a responsive graphic. CONCLUSIONS: This application summarizes the experience of 3655 polytrauma patients and might serve as a guide for clinical decisions and educative purposes, as well as new scientific questions for the polytrauma patient. LEVEL OF EVIDENCE: IV.
