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Evaluation of Inpatient Surveillance After High-Energy Accident Without Apparent Serious Injury: Retrospective
Andreas Gather1, Alexandra Braun2, Matthias K Jung von Landenberg2
1Department of Interdisciplinary Emergency and Acute Medicine (IRN), BG Klinik Ludwigshafen, Ludwig-Guttmann-Str. 13, 67071 Ludwigshafen, Germany.
Abstract:
Background/Objectives: Patients involved in high-energy accidents (HEAs) are frequently admitted for inpatient surveillance despite normal clinical examination and imaging, although the yield of this practice is uncertain. This study evaluated the frequency and nature of clinical events, interventions during surveillance and missed injuries in such low-risk patients and explored potential predictors. Methods: Retrospective study at a Level I trauma center including patients ≥18 years admitted between January 2022 and September 2023 solely due to HEA mechanism, without apparent injury requiring inpatient treatment. Baseline characteristics, clinical presentation, imaging findings, and laboratory values were extracted. Outcomes included additional diagnostics, new diagnoses, therapeutic interventions, and missed injuries. Patients with eventful and uneventful stays were compared using univariate statistical tests. Results: Among 363 included patients, 86.0% experienced an uneventful stay. Fifty-one patients (14.0%) had an eventful stay, most commonly requiring additional radiological examinations (8.5%) or blood tests (6.9%). New diagnoses occurred in 6.6%, and 6.1% received additional therapeutic interventions. Missed injuries were detected in 3.9%, including two potentially life-threatening injuries (0.6%). No robust predictors for missed injuries were identified. Established predictors of missed injuries from broader trauma populations were absent in this selected low-risk cohort. However, individuals after bicycle accidents were significantly more likely to experience any event during their stay (p = 0.009). Conclusions: Inpatient surveillance of patients without apparent injury after HEAs has a low overall yield but occasionally identifies clinically significant conditions. As no reliable predictors for adverse events were found, selective admission remains challenging. Hybrid models combining short-term observation with structured outpatient reassessment may represent a resource-efficient alternative for low-risk patients.
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