Background: Delayed hemothorax (dHTX) can occur unexpectedly, even in patients who initially present without signs of hemothorax (HTX), potentially leading to death. We aimed to develop a predictive model for dHTX requiring intervention, specifically targeting those with no or occult HTX. Methods: This retrospective study was conducted at a level 1 trauma center. The primary outcome was the occurrence of dHTX requiring intervention in patients who had no HTX or occult HTX and did not undergo closed thoracostomy post-injury. To minimize overfitting, we employed the least absolute shrinkage and selection operator (LASSO) logistic regression model for feature selection. Thereafter, we developed a multivariable logistic regression (MLR) model and a nomogram. Results: In total, 688 patients were included in the study, with 64 cases of dHTX (9.3%).The LASSO and MLR analyses revealed that the depth of HTX (adjusted odds ratio [aOR], 3.79; 95% confidence interval [CI], 2.10–6.85; p<0.001) and the number of totally displaced rib fractures (RFX) (aOR, 1.90; 95% CI, 1.56–2.32; p<0.001) were significant predictors. Based on these parameters, we developed a nomogram to predict dHTX, with a sensitivity of 78.1%, a specificity of 76.0%, a positive predictive value of 25.0%, and a negative predictive value of 97.1% at the optimal cut-off value. The area under the receiver operating characteristic curve was 0.832. Conclusion The depth of HTX on initial chest computed tomography and the number of totally displaced RFX emerged as significant risk factors for dHTX. We propose a novel nomogram that is easily applicable in clinical settings.

Background: Delayed hemothorax (dHTX) can occur unexpectedly, even in patients who initially present without signs of hemothorax (HTX), potentially leading to death. We aimed to develop a predictive model for dHTX requiring intervention, specifically targeting those with no or occult HTX. Methods: This retrospective study was conducted at a level 1 trauma center. The primary outcome was the occurrence of dHTX requiring intervention in patients who had no HTX or occult HTX and did not undergo closed thoracostomy post-injury. To minimize overfitting, we employed the least absolute shrinkage and selection operator (LASSO) logistic regression model for feature selection. Thereafter, we developed a multivariable logistic regression (MLR) model and a nomogram. Results: In total, 688 patients were included in the study, with 64 cases of dHTX (9.3%).The LASSO and MLR analyses revealed that the depth of HTX (adjusted odds ratio [aOR], 3.79; 95% confidence interval [CI], 2.10–6.85; p<0.001) and the number of totally displaced rib fractures (RFX) (aOR, 1.90; 95% CI, 1.56–2.32; p<0.001) were significant predictors. Based on these parameters, we developed a nomogram to predict dHTX, with a sensitivity of 78.1%, a specificity of 76.0%, a positive predictive value of 25.0%, and a negative predictive value of 97.1% at the optimal cut-off value. The area under the receiver operating characteristic curve was 0.832. Conclusion The depth of HTX on initial chest computed tomography and the number of totally displaced RFX emerged as significant risk factors for dHTX. We propose a novel nomogram that is easily applicable in clinical settings.

Background: Delayed hemothorax (dHTX) can occur unexpectedly, even in patients who initially present without signs of hemothorax (HTX), potentially leading to death. We aimed to develop a predictive model for dHTX requiring intervention, specifically targeting those with no or occult HTX. Methods: This retrospective study was conducted at a level 1 trauma center. The primary outcome was the occurrence of dHTX requiring intervention in patients who had no HTX or occult HTX and did not undergo closed thoracostomy post-injury. To minimize overfitting, we employed the least absolute shrinkage and selection operator (LASSO) logistic regression model for feature selection. Thereafter, we developed a multivariable logistic regression (MLR) model and a nomogram. Results: In total, 688 patients were included in the study, with 64 cases of dHTX (9.3%).The LASSO and MLR analyses revealed that the depth of HTX (adjusted odds ratio [aOR], 3.79; 95% confidence interval [CI], 2.10–6.85; p<0.001) and the number of totally displaced rib fractures (RFX) (aOR, 1.90; 95% CI, 1.56–2.32; p<0.001) were significant predictors. Based on these parameters, we developed a nomogram to predict dHTX, with a sensitivity of 78.1%, a specificity of 76.0%, a positive predictive value of 25.0%, and a negative predictive value of 97.1% at the optimal cut-off value. The area under the receiver operating characteristic curve was 0.832. Conclusion The depth of HTX on initial chest computed tomography and the number of totally displaced RFX emerged as significant risk factors for dHTX. We propose a novel nomogram that is easily applicable in clinical settings.

Background: This study aimed to validate the Geriatric Trauma Outcome Score (GTOS) for predicting mortality associated with trauma in older Korean adults and compare the GTOS with the Trauma and Injury Severity Score (TRISS). Methods: This study included patients aged ≥65 years who visited the Chungbuk National University Hospital Regional Trauma Center between January 2016 and December 2022. We used receiver operating characteristic curves and calibration plots to assess the discrimination and calibration of the scoring systems. Results: Among 3,053 patients, the median age was 77 years, and the mortality rate was 5.2%. The overall GTOS-predicted mortality and 1–TRISS were 5.4% (interquartile range [IQR], 3.7–9.5) and 4.7% (IQR, 4.7–4.7), respectively. The areas under the curves (AUCs) of 1–TRISS and GTOS for the total population were 0.763 (95% confidence interval [CI], 0.719–0.806) and 0.794 (95% CI, 0.755–0.833), respectively. In the Glasgow Coma Scale (GCS) ≤12 group, the in-hospital mortality rate was 27.5% (79 deaths). The GTOS-predicted mortality and 1–TRISS in this group were 18.6% (IQR, 7.5–34.7) and 26.9% (IQR, 11.9–73.1), respectively. The AUCs of 1–TRISS and GTOS for the total population were 0.800 (95% CI, 0.776–0.854) and 0.744 (95% CI, 0.685–0.804), respectively. Conclusion The GTOS and TRISS demonstrated comparable accuracy in predicting mortality, while the GTOS offered the advantage of simpler calculations. However, the GTOS tended to underestimate mortality in patients with GCS ≤12; thus, its application requires care in such cases.

Background: This study aimed to validate the Geriatric Trauma Outcome Score (GTOS) for predicting mortality associated with trauma in older Korean adults and compare the GTOS with the Trauma and Injury Severity Score (TRISS). Methods: This study included patients aged ≥65 years who visited the Chungbuk National University Hospital Regional Trauma Center between January 2016 and December 2022. We used receiver operating characteristic curves and calibration plots to assess the discrimination and calibration of the scoring systems. Results: Among 3,053 patients, the median age was 77 years, and the mortality rate was 5.2%. The overall GTOS-predicted mortality and 1–TRISS were 5.4% (interquartile range [IQR], 3.7–9.5) and 4.7% (IQR, 4.7–4.7), respectively. The areas under the curves (AUCs) of 1–TRISS and GTOS for the total population were 0.763 (95% confidence interval [CI], 0.719–0.806) and 0.794 (95% CI, 0.755–0.833), respectively. In the Glasgow Coma Scale (GCS) ≤12 group, the in-hospital mortality rate was 27.5% (79 deaths). The GTOS-predicted mortality and 1–TRISS in this group were 18.6% (IQR, 7.5–34.7) and 26.9% (IQR, 11.9–73.1), respectively. The AUCs of 1–TRISS and GTOS for the total population were 0.800 (95% CI, 0.776–0.854) and 0.744 (95% CI, 0.685–0.804), respectively. Conclusion The GTOS and TRISS demonstrated comparable accuracy in predicting mortality, while the GTOS offered the advantage of simpler calculations. However, the GTOS tended to underestimate mortality in patients with GCS ≤12; thus, its application requires care in such cases.

Background: This study aimed to validate the Geriatric Trauma Outcome Score (GTOS) for predicting mortality associated with trauma in older Korean adults and compare the GTOS with the Trauma and Injury Severity Score (TRISS). Methods: This study included patients aged ≥65 years who visited the Chungbuk National University Hospital Regional Trauma Center between January 2016 and December 2022. We used receiver operating characteristic curves and calibration plots to assess the discrimination and calibration of the scoring systems. Results: Among 3,053 patients, the median age was 77 years, and the mortality rate was 5.2%. The overall GTOS-predicted mortality and 1–TRISS were 5.4% (interquartile range [IQR], 3.7–9.5) and 4.7% (IQR, 4.7–4.7), respectively. The areas under the curves (AUCs) of 1–TRISS and GTOS for the total population were 0.763 (95% confidence interval [CI], 0.719–0.806) and 0.794 (95% CI, 0.755–0.833), respectively. In the Glasgow Coma Scale (GCS) ≤12 group, the in-hospital mortality rate was 27.5% (79 deaths). The GTOS-predicted mortality and 1–TRISS in this group were 18.6% (IQR, 7.5–34.7) and 26.9% (IQR, 11.9–73.1), respectively. The AUCs of 1–TRISS and GTOS for the total population were 0.800 (95% CI, 0.776–0.854) and 0.744 (95% CI, 0.685–0.804), respectively. Conclusion The GTOS and TRISS demonstrated comparable accuracy in predicting mortality, while the GTOS offered the advantage of simpler calculations. However, the GTOS tended to underestimate mortality in patients with GCS ≤12; thus, its application requires care in such cases.