PURPOSE: Robotic surgery (RS) overcomes the limitations of previous conventional laparoscopic surgery (CLS). Although meta-analyses have been published recently, our study evaluated the latest comparative surgical, urologic, and sexual results for rectal cancer and compares RS with CLS in patients with rectal cancer only. METHODS: We searched three foreign databases (Ovid-MEDLINE, Ovid-Embase, and Cochrane Library) and five Korean databases (KoreaMed, KMbase, KISS, RISS, and KisTi) during July 2013. The Cochrane Risk of Bias and the Methodological Index for Non-Randomized were utilized to evaluate quality of study. Dichotomous variables were pooled using the risk ratio (RR), and continuous variables were pooled using the mean difference (MD). All meta-analyses were conducted with Review Manager, V. 5.3. RESULTS: Seventeen studies involving 2,224 patients were included. RS was associated with a lower rate of intraoperative conversion than that of CLS (RR, 0.28; 95% confidence interval [CI], 0.15-0.54). Time to first flatus was short (MD, -0.13; 95% CI, -0.25 to -0.01). Operating time was longer for RS than that for CLS (MD, 49.97; 95% CI, 20.43-79.52, I2 = 97%). International Prostate Symptom Score scores at 3 months better RS than CLS (MD, -2.90; 95% CI, -5.31 to -0.48, I2 = 0%). International Index of Erectile Function scores showed better improvement at 3 months (MD, -2.82; 95% CI, -4.78 to -0.87, I2 = 37%) and 6 months (MD, -2.15; 95% CI, -4.08 to -0.22, I2 = 0%). CONCLUSION: RS appears to be an effective alternative to CLS with a lower conversion rate to open surgery, a shorter time to first flatus and better recovery in voiding and sexual function. RS could enhance postoperative recovery in patients with rectal cancer.
Bias (Epidemiology) ; Flatulence ; Humans ; Laparoscopy* ; Odds Ratio ; Prostate ; Rectal Neoplasms*

BACKGROUND/AIMS: As a result of the rapid development of medical diagnostic tools, physicians require concrete evidence to evaluate the effectiveness of the tools. We aimed to investigate the effectiveness and additional diagnostic benefits of capsule endoscopy (CE) in patients with small bowel Crohn’s disease (CD). METHODS: We performed a systematic search of databases, including MEDLINE, EMBASE, and the Cochrane Library, as well as eight domestic databases. Two reviewers independently screened all references. Diagnostic data from the studies were collected, and a meta-analysis was performed. RESULTS: Twenty-four studies were included. In cases of suspected CD, CE demonstrated a superior diagnostic yield compared with small bowel follow-through (SBFT) and enteroclysis (EC); however, there was no difference compared with computed tomography enterography or magnetic resonance enterography. In cases with established CD, CE demonstrated a higher diagnostic yield only compared with EC. In the detection of terminal ileum lesions, CE exhibited a significantly increased detection rate compared with ileoscopy. CONCLUSIONS: The findings of our meta-analysis indicate that CE is superior to SBFT and EC in the evaluation of suspected CD cases. CE is also a more effective diagnostic modality in patients with established CD compared with EC.
Capsule Endoscopy* ; Crohn Disease ; Humans ; Ileum ; Intestines

PURPOSE: Reports from several case series have described the feasibility and safety of robotic surgery (RS) for colonic cancer. Experience is still limited in robotic colonic surgery, and a few meta-analysis has been conducted to integrate the results for colon cancer specifically. We conducted a systematic review of the available evidence comparing the surgical safety and efficacy of RS with that of conventional laparoscopic surgery (CLS) for colonic cancer. METHODS: We searched English databases (MEDLINE, Embase, and Cochrane Library), and Korean databases (KoreaMed, KMbase, KISS, RISS, and KisTi). Dichotomous variables were pooled using the risk ratio, and continuous variables were pooled using the mean difference (MD). RESULTS: The present study found that the RS group had a shorter time to resumption of a regular diet (MD, -0.62 days; 95% CI, -0.97 to -0.28), first passage of flatus (MD, -0.44 days; 95% CI, -0.66 to -0.23) and defecation (MD, -0.62 days; 95% CI, -0.77 to -0.47). Also, RS was associated with a shorter hospital stay (MD, -0.69 days; 95% CI, -1.12 to -0.26), a lower estimated blood loss (MD, -19.49 mL; 95% CI, -27.10 to -11.89) and a longer proximal margin (MD, 2.29 cm; 95% CI, 1.11-3.47). However, RS was associated with a longer surgery time (MD, 51.00 minutes; 95% CI, 39.38-62.62). CONCLUSION: We found that the potential benefits of perioperative and short-term outcomes for RS than for CLS. For a more accurate understanding of RS for colonic cancer patients, robust comparative studies and randomized clinical trials are required.
Colon* ; Colonic Neoplasms* ; Defecation ; Diet ; Flatulence ; Humans ; Laparoscopy* ; Length of Stay ; Odds Ratio ; Robotic Surgical Procedures

Artificial intelligence (AI) is expected to affect various fields of medicine substantially and has the potential to improve many aspects of healthcare. However, AI has been creating much hype, too. In applying AI technology to patients, medical professionals should be able to resolve any anxiety, confusion, and questions that patients and the public may have. Also, they are responsible for ensuring that AI becomes a technology beneficial for patient care. These make the acquisition of sound knowledge and experience about AI a task of high importance for medical students. Preparing for AI does not merely mean learning information technology such as computer programming. One should acquire sufficient knowledge of basic and clinical medicines, data science, biostatistics, and evidence-based medicine. As a medical student, one should not passively accept stories related to AI in medicine in the media and on the Internet. Medical students should try to develop abilities to distinguish correct information from hype and spin and even capabilities to create thoroughly validated, trustworthy information for patients and the public.

Objective: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) in detecting liver metastasis with that of radiologists. Materials and Methods: This clinical retrospective study used 4386-slice computed tomography (CT) images and labels from a training cohort (502 patients with colorectal cancer [CRC] from November 2005 to December 2010) to train the DLLD for detecting liver metastasis, and used CT images of a validation cohort (40 patients with 99 liver metastatic lesions and 45 patients without liver metastasis from January 2011 to December 2011) for comparing the performance of the DLLD with that of readers (three abdominal radiologists and three radiology residents). For per-lesion binary classification, the sensitivity and false positives per patient were measured. Results: A total of 85 patients with CRC were included in the validation cohort. In the comparison based on per-lesion binary classification, the sensitivity of DLLD (81.82%, [81/99]) was comparable to that of abdominal radiologists (80.81%, p = 0.80) and radiology residents (79.46%, p = 0.57). However, the false positives per patient with DLLD (1.330) was higher than that of abdominal radiologists (0.357, p < 0.001) and radiology residents (0.667, p < 0.001). Conclusion DLLD showed a sensitivity comparable to that of radiologists when detecting liver metastasis in patients initially diagnosed with CRC. However, the false positives of DLLD were higher than those of radiologists. Therefore, DLLD could serve as an assistant tool for detecting liver metastasis instead of a standalone diagnostic tool.

Objective: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) in detecting liver metastasis with that of radiologists. Materials and Methods: This clinical retrospective study used 4386-slice computed tomography (CT) images and labels from a training cohort (502 patients with colorectal cancer [CRC] from November 2005 to December 2010) to train the DLLD for detecting liver metastasis, and used CT images of a validation cohort (40 patients with 99 liver metastatic lesions and 45 patients without liver metastasis from January 2011 to December 2011) for comparing the performance of the DLLD with that of readers (three abdominal radiologists and three radiology residents). For per-lesion binary classification, the sensitivity and false positives per patient were measured. Results: A total of 85 patients with CRC were included in the validation cohort. In the comparison based on per-lesion binary classification, the sensitivity of DLLD (81.82%, [81/99]) was comparable to that of abdominal radiologists (80.81%, p = 0.80) and radiology residents (79.46%, p = 0.57). However, the false positives per patient with DLLD (1.330) was higher than that of abdominal radiologists (0.357, p < 0.001) and radiology residents (0.667, p < 0.001). Conclusion DLLD showed a sensitivity comparable to that of radiologists when detecting liver metastasis in patients initially diagnosed with CRC. However, the false positives of DLLD were higher than those of radiologists. Therefore, DLLD could serve as an assistant tool for detecting liver metastasis instead of a standalone diagnostic tool.

PURPOSE: This study was designed to validate the usefulness of the Acute Physiology and Chronic Health Evaluation (APACHE) II for predicting hospital mortality of critically ill Korean patients. MATERIALS AND METHODS: We analyzed data on 826 patients who had been admitted to nine intensive care units and were included in the Fever and Antipyretics in Critical Illness Evaluation study cohort. RESULTS: Among the patients enrolled, 62% (512/826) were medical and 38% (314/826) were surgical patients. The median APACHE II score was 17 (11 to 23 interquartile range), and the hospital mortality rate was 19.5%. Age, underlying diseases, medical patients, mechanical ventilation, and renal replacement therapy were independently associated with hospital mortality. The calibration of APACHE II was poor (H=57.54, p<0.0001; C=55.99, p<0.0001), and the discrimination was modest [area under the receiver operating characteristic (aROC)=0.729]. Calibration was poor for both medical and surgical patients (H=63.56, p<0.0001; C=73.83, p<0.0001, and H=33.92, p<0.0001; C=33.34, p=0.0001, respectively), while discrimination was poor for medical patients (aROC=0.651) and modest for surgical patients (aROC=0.704). At the predicted risk of 50%, APACHE II had a sensitivity of 36.6% and a specificity of 87.4% for hospital mortality. CONCLUSION: For Koreans, the APACHE II exhibits poor calibration and modest discrimination for hospital mortality. Therefore, a new model is needed to accurately predict mortality in critically ill Korean patients.
*APACHE ; Aged ; Cohort Studies ; Critical Illness/mortality ; Hospital Mortality ; Humans ; *Intensive Care Units ; Middle Aged ; Risk Factors