Caustic substance ingestion is frequently life-threatening, and its pathological mechanisms of tissue damage are well documented. However, few studies have assessed the combined effects of pH and t...

Objective: To identify the feasibility and efficiency of deep convolutional neural networks (DCNNs) in the detection of ankle fractures and to explore ensemble strategies that applied multiple projections of radiographs. Ankle radiographs (AXRs) are the primary tool used to diagnose ankle fractures. Applying DCNN algorithms on AXRs can potentially improve the diagnostic accuracy and efficiency of detecting ankle fractures. Methods: A DCNN was trained using a trauma image registry, including 3102 AXRs. We separately trained the DCNN on anteroposterior (AP) and lateral (Lat) AXRs. Different ensemble methods, such as “sum-up,” “severance-OR,” and “severance-Both,” were evaluated to incorporate the results of the model using different projections of view. Results: The AP/Lat model’s individual sensitivity, specificity, positive-predictive value, accuracy, and F1 score were 79%/84%, 90%/86%, 88%/86%, 83%/85%, and 0.816/0.850, respectively. Furthermore, the area under the receiver operating characteristic curve (AUROC) of the AP/Lat model was 0.890/0.894 (95% CI: 0.826–0.954/0.831–0.953). The sum-up method generated balanced results by applying both models and obtained an AUROC of 0.917 (95% CI: 0.863–0.972) with 87% accuracy. The severance-OR method resulted in a better sensitivity of 90%, and the severance-Both method obtained a high specificity of 94%. Conclusion: Ankle fracture in the AXR could be identified by the trained DCNN algorithm. The selection of ensemble methods can depend on the clinical situation which might help clinicians detect ankle fractures efficiently without interrupting the current clinical pathway. Advances in knowledge: This study demonstrated different ensemble strategies of AI algorithms on multiple view AXRs to optimize the performance in various clinical needs.

(1) Background: Design thinking is a problem-solving approach that has been applied in various sectors, including healthcare and medical education. While deep learning (DL) algorithms can assist in clinical practice, integrating them into clinical scenarios can be challenging. This study aimed to use design thinking steps to develop a DL algorithm that accelerates deployment in clinical practice and improves its performance to meet clinical requirements. (2) Methods: We applied the design thinking process to interview clinical doctors and gain insights to develop and modify the DL algorithm to meet clinical scenarios. We also compared the DL performance of the algorithm before and after the integration of design thinking. (3) Results: After empathizing with clinical doctors and defining their needs, we identified the unmet need of five trauma surgeons as “how to reduce the misdiagnosis of femoral fracture by pelvic plain film (PXR) at initial emergency visiting”. We collected 4235 PXRs from our hospital, of which 2146 had a hip fracture (51%) from 2008 to 2016. We developed hip fracture DL detection models based on the Xception convolutional neural network by using these images. By incorporating design thinking, we improved the diagnostic accuracy from 0.91 (0.84–0.96) to 0.95 (0.93–0.97), the sensitivity from 0.97 (0.89–1.00) to 0.97 (0.94–0.99), and the specificity from 0.84 (0.71–0.93) to 0.93(0.990–0.97). (4) Conclusions: In summary, this study demonstrates that design thinking can ensure that DL solutions developed for trauma care are user-centered and meet the needs of patients and healthcare providers.

This study aimed to assess current evidence regarding the effect of selenium (Se) supplementation on the prognosis in patients sustaining trauma. MEDLINE, Embase, and Web of Science databases were searched with the following terms: “trace element”, “selenium”, “copper”, “zinc”, “injury”, and “trauma”. Seven studies were included in the meta-analysis. The pooled results showed that Se supplementation was associated with a lower mortality rate (OR 0.733, 95% CI: 0.586, 0.918, p = 0.007; heterogeneity, I² = 0%). Regarding the incidence of infectious complications, there was no statistically significant benefit after analyzing the four studies (OR 0.942, 95% CI: 0.695, 1.277, p = 0.702; heterogeneity, I² = 14.343%). The patients with Se supplementation had a reduced ICU length of stay (standard difference in means (SMD): −0.324, 95% CI: −0.382, −0.265, p < 0.001; heterogeneity, I² = 0%) and lesser hospital length of stay (SMD: −0.243, 95% CI: −0.474, −0.012, p < 0.001; heterogeneity, I² = 45.496%). Se supplementation after trauma confers positive effects in decreasing the mortality and length of ICU and hospital stay.

Purpose: High prevalence of psychiatric comorbidities (PCs) has been widely documented in caustic substance ingestion cases. However, their effect on the clinical features and prognostic outcomes remains unclear due to the paucity of discussion. We report on detailed clinical courses with long-term multifaceted outcomes and review the association between caustic ingestion and each specific PC. Patients and Methods: The retrospective chart review included 396 adults (median follow-up, 16.6 months) with and 377 without (control group) PCs treated between 1999 and 2018 at Chang Gung Memorial Hospital. All PCs were diagnosed/confirmed by psychiatrists through face-to-face interviews. Results: The PCs predicted serious esophagogastroduodenoscopy grading, higher rates of admission/surgery/intensive care unit stay, increments of systemic/gastrointestinal complications, and poorer 5-year overall survival rates. The poor survival among patients with PCs was highly consistent with their baseline characteristics. Significantly advanced age, more non-PCs, alcoholism, illicit drug abuse, and baseline unhealthy status resulted in statistically higher risks of severe complications and limited recovery. Conclusion: PCs changed clinical patterns and had critical roles in the survival outcomes of caustic injury victims. Clinical awareness achieves benefit by limiting injuries in mild cases or allowing emergent interventions in severe cases. Future studies based on worldwide populations are essential for realizing geographic differences.