Objective: To determine the clinical impact of the baseline sagittal imbalance severity in patients with adult spinal deformity (ASD). Methods: We retrospectively reviewed patients who underwent ≥ 5-level fusion including the pelvis, for ASD with a ≥ 2-year follow-up. Using the Scoliosis Research Society-Schwab classification system, patients were classified into 3 groups according to the severity of the preoperative sagittal imbalance: mild, moderate, and severe. Postoperative clinical and radiographic results were compared among the 3 groups. Results: A total of 259 patients were finally included. There were 42, 62, and 155 patients in the mild, moderate, and severe groups, respectively. The perioperative surgical burden was greatest in the severe group. Postoperatively, this group also showed the largest pelvic incidence minus lumbar lordosis mismatch, suggesting a tendency towards undercorrection. No statistically significant differences were observed in proximal junctional kyphosis, proximal junctional failure, or rod fractures among the groups. Visual analogue scale for back pain and Scoliosis Research Society-22 scores were similar across groups. However, severe group’s last follow-up Oswestry Disability Index (ODI) scores significantly lower than those of the severe group. Conclusion Patients with severe sagittal imbalance were treated with more invasive surgical methods along with increased the perioperative surgical burden. All patients exhibited significant radiological and clinical improvements after surgery. However, regarding ODI, the severe group demonstrated slightly worse clinical outcomes than the other groups, probably due to relatively higher proportion of undercorrection. Therefore, more rigorous correction is necessary to achieve optimal sagittal alignment specifically in patients with severe baseline sagittal imbalance.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

Objective: To determine the clinical impact of the baseline sagittal imbalance severity in patients with adult spinal deformity (ASD). Methods: We retrospectively reviewed patients who underwent ≥ 5-level fusion including the pelvis, for ASD with a ≥ 2-year follow-up. Using the Scoliosis Research Society-Schwab classification system, patients were classified into 3 groups according to the severity of the preoperative sagittal imbalance: mild, moderate, and severe. Postoperative clinical and radiographic results were compared among the 3 groups. Results: A total of 259 patients were finally included. There were 42, 62, and 155 patients in the mild, moderate, and severe groups, respectively. The perioperative surgical burden was greatest in the severe group. Postoperatively, this group also showed the largest pelvic incidence minus lumbar lordosis mismatch, suggesting a tendency towards undercorrection. No statistically significant differences were observed in proximal junctional kyphosis, proximal junctional failure, or rod fractures among the groups. Visual analogue scale for back pain and Scoliosis Research Society-22 scores were similar across groups. However, severe group’s last follow-up Oswestry Disability Index (ODI) scores significantly lower than those of the severe group. Conclusion Patients with severe sagittal imbalance were treated with more invasive surgical methods along with increased the perioperative surgical burden. All patients exhibited significant radiological and clinical improvements after surgery. However, regarding ODI, the severe group demonstrated slightly worse clinical outcomes than the other groups, probably due to relatively higher proportion of undercorrection. Therefore, more rigorous correction is necessary to achieve optimal sagittal alignment specifically in patients with severe baseline sagittal imbalance.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

Objective: To determine the clinical impact of the baseline sagittal imbalance severity in patients with adult spinal deformity (ASD). Methods: We retrospectively reviewed patients who underwent ≥ 5-level fusion including the pelvis, for ASD with a ≥ 2-year follow-up. Using the Scoliosis Research Society-Schwab classification system, patients were classified into 3 groups according to the severity of the preoperative sagittal imbalance: mild, moderate, and severe. Postoperative clinical and radiographic results were compared among the 3 groups. Results: A total of 259 patients were finally included. There were 42, 62, and 155 patients in the mild, moderate, and severe groups, respectively. The perioperative surgical burden was greatest in the severe group. Postoperatively, this group also showed the largest pelvic incidence minus lumbar lordosis mismatch, suggesting a tendency towards undercorrection. No statistically significant differences were observed in proximal junctional kyphosis, proximal junctional failure, or rod fractures among the groups. Visual analogue scale for back pain and Scoliosis Research Society-22 scores were similar across groups. However, severe group’s last follow-up Oswestry Disability Index (ODI) scores significantly lower than those of the severe group. Conclusion Patients with severe sagittal imbalance were treated with more invasive surgical methods along with increased the perioperative surgical burden. All patients exhibited significant radiological and clinical improvements after surgery. However, regarding ODI, the severe group demonstrated slightly worse clinical outcomes than the other groups, probably due to relatively higher proportion of undercorrection. Therefore, more rigorous correction is necessary to achieve optimal sagittal alignment specifically in patients with severe baseline sagittal imbalance.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

Objective: To determine the clinical impact of the baseline sagittal imbalance severity in patients with adult spinal deformity (ASD). Methods: We retrospectively reviewed patients who underwent ≥ 5-level fusion including the pelvis, for ASD with a ≥ 2-year follow-up. Using the Scoliosis Research Society-Schwab classification system, patients were classified into 3 groups according to the severity of the preoperative sagittal imbalance: mild, moderate, and severe. Postoperative clinical and radiographic results were compared among the 3 groups. Results: A total of 259 patients were finally included. There were 42, 62, and 155 patients in the mild, moderate, and severe groups, respectively. The perioperative surgical burden was greatest in the severe group. Postoperatively, this group also showed the largest pelvic incidence minus lumbar lordosis mismatch, suggesting a tendency towards undercorrection. No statistically significant differences were observed in proximal junctional kyphosis, proximal junctional failure, or rod fractures among the groups. Visual analogue scale for back pain and Scoliosis Research Society-22 scores were similar across groups. However, severe group’s last follow-up Oswestry Disability Index (ODI) scores significantly lower than those of the severe group. Conclusion Patients with severe sagittal imbalance were treated with more invasive surgical methods along with increased the perioperative surgical burden. All patients exhibited significant radiological and clinical improvements after surgery. However, regarding ODI, the severe group demonstrated slightly worse clinical outcomes than the other groups, probably due to relatively higher proportion of undercorrection. Therefore, more rigorous correction is necessary to achieve optimal sagittal alignment specifically in patients with severe baseline sagittal imbalance.