• Journal of Korean Neurosurgical Society
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• v.59 no.5
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• pp.458-465
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• 2016

Objective : The aim of this study is to analyze the differences in the incidence, predicting factors, and clinical course of chronic subdural hematoma (CSDH) following surgical clipping between unruptured (UIA) and ruptured intracranial aneurysm (RIA). Methods : We conducted a retrospective analysis of 752 patients (UIA : 368 and RIA : 384) who underwent surgical clipping during 8 years. The incidence and predicting factors of CSDH development in the UIA and RIA were compared according to medical records and radiological data. Results : The incidence of postoperative CSDH was higher in the UIA (10.9%) than in the RIA (3.1%) (p=0.000). In multivariate analysis, a high Hounsfield (HF) unit (blood clots) for subdural fluid collection (SFC), persistence of SFC ${\geq}5mm$ and male sex in the UIA and A high HF unit for SFC and SFC ${\geq}5mm$ without progression to hydrocephalus in the RIA were identified as the independent predicting factors for CSDH development (p<0.05). Conclusion : There were differences in the incidence and predicting factors for CSDH following surgical clipping between UIA and RIA. Blood clots in the subdural space and persistence of SFC ${\geq}5mm$ were predicting factors in both UIA and RIA. However, progression to hydrocephalus may have in part contributed to low CSDH development in the RIA. We suggest that cleaning of blood clots in the subdural space and efforts to minimize SFC ${\geq}5mm$ at the end of surgery is helpful to prevent CSDH following aneurysmal clipping.

• Asian Spine Journal
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• v.12 no.6
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• pp.1085-1091
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• 2018

Study Design: Case-control. Purpose: To determine optimal cut-off value for body mass index (BMI) in predicting surgical success in patients with lumbar spinal canal stenosis (LSCS). Overview of Literature: BMI is an essential variable in the assessment of patients with LSCS. Methods: We conducted a prospective study with obese and non-obese LSCS surgical patients and analyzed data on age, sex, duration of symptoms, walking distance, morphologic grade of stenosis, BMI, postoperative complications, and functional disability. Obesity was defined as BMI of ${\geq}30kg/m^2$. Patients completed the Oswestry Disability Index (ODI) questionnaire before surgery and 2 years after surgery. Surgical success was defined as ${\geq}30%$ improvement from the baseline ODI score. Receiver operating characteristic (ROC) analysis was used to estimate the optimal cut-off values of BMI to predict surgical success. In addition, correlation was assessed between BMI and stenosis grade based on morphology as defined by Schizas and colleague in total, 189 patients were eligible to enter the study. Results: Mean age of patients was $61.5{\pm}9.6years$. Mean follow-up was $36{\pm}12months$. Most patients (88.4%) were classified with grades C (severe stenosis) and D (extreme stenosis). Post-surgical success was 85.7% at the 2-year follow-up. A weak correlation was observed between morphologic grade of stenosis and BMI. Rates of postoperative complications were similar between patients who were obese and those who were non-obese. Both cohorts had similar degree of improvement in the ODI at the 2-year followup. However, patients who were non-obese presented significantly higher surgical success than those who were obese. In ROC curve analysis, a cut-off value of ${\leq}29.1kg/m^2$ for BMI in patients with LSCS was suggestive of surgical success, with 81.1% sensitivity and 82.2% specificity (area under the curve, 0.857; 95% confidence interval, 0.788-0.927). Conclusion: This study showed that the BMI can be considered a parameter for predicting surgical success in patients with LSCS and can be useful in clinical practice.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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• pp.2211-2215
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• 2014

Background: To examine the incidence of positive vaginal surgical margins and determine the predicting factors following radical hysterectomy for stage IB1 carcinoma of the cervix. Materials and Methods: The clinical and histological data of 656 FIGO stage IB1 cervical cancer patients who had radical hysterectomy with bilateral pelvic lymphadenectomy (RHPL) from January 2003 to December 2012 were retrospectively reviewed and were analyzed for their association with a positive vaginal surgical margin. A p-value of < 0.05 was considered significant. Results: Thirty-five patients (5.3%) had positive vaginal surgical margins following RHPL; 24 (3.7%) for intraepithelial lesions and 11 (1.7%) for carcinoma. On multivariate analysis, microscopic vaginal involvement by high-grade squamous intraepithelial lesion and/or carcinoma (adjusted odd ratio (OR) 186.8; 95% confidence interval (CI) 48.5-718.5) and squamous histology (OR 8.7; 95% CI 1.7-44.0), were significantly associated with positive vaginal surgical margin. Conclusions: Microscopic vaginal involvement by HSIL and/or carcinoma are strong predictors for positive vaginal surgical margins for stage IB1 cervical cancer patients undergoing radical hysterectomy. Preoperative 'mapping' colposcopy or other strategies should be considered to ensure optimal vaginal resection.

• Neurospine
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• v.15 no.4
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• pp.329-337
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• 2018

Objective: Machine learning algorithms excel at leveraging big data to identify complex patterns that can be used to aid in clinical decision-making. The objective of this study is to demonstrate the performance of machine learning models in predicting postoperative complications following anterior cervical discectomy and fusion (ACDF). Methods: Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), and random forest decision tree (RF) models were trained on a multicenter data set of patients undergoing ACDF to predict surgical complications based on readily available patient data. Following training, these models were compared to the predictive capability of American Society of Anesthesiologists (ASA) physical status classification. Results: A total of 20,879 patients were identified as having undergone ACDF. Following exclusion criteria, patients were divided into 14,615 patients for training and 6,264 for testing data sets. ANN and LR consistently outperformed ASA physical status classification in predicting every complication (p < 0.05). The ANN outperformed LR in predicting venous thromboembolism, wound complication, and mortality (p < 0.05). The SVM and RF models were no better than random chance at predicting any of the postoperative complications (p < 0.05). Conclusion: ANN and LR algorithms outperform ASA physical status classification for predicting individual postoperative complications. Additionally, neural networks have greater sensitivity than LR when predicting mortality and wound complications. With the growing size of medical data, the training of machine learning on these large datasets promises to improve risk prognostication, with the ability of continuously learning making them excellent tools in complex clinical scenarios.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.2
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• pp.195-200
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• 2023

Backgrounds/Aims: We aimed to build a machine learning tool to help predict low-grade intraductal papillary mucinous neoplasms (IPMNs) in order to avoid unnecessary surgical resection. IPMNs are precursors to pancreatic cancer. Surgical resection remains the only recognized treatment for IPMNs yet carries some risks of morbidity and potential mortality. Existing clinical guidelines are imperfect in distinguishing low-risk cysts from high-risk cysts that warrant resection. Methods: We built a linear support vector machine (SVM) learning model using a prospectively maintained surgical database of patients with resected IPMNs. Input variables included 18 demographic, clinical, and imaging characteristics. The outcome variable was the presence of low-grade or high-grade IPMN based on post-operative pathology results. Data were divided into a training/validation set and a testing set at a ratio of 4:1. Receiver operating characteristics analysis was used to assess classification performance. Results: A total of 575 patients with resected IPMNs were identified. Of them, 53.4% had low-grade disease on final pathology. After classifier training and testing, a linear SVM-based model (IPMN-LEARN) was applied on the validation set. It achieved an accuracy of 77.4%, with a positive predictive value of 83%, a specificity of 72%, and a sensitivity of 83% in predicting low-grade disease in patients with IPMN. The model predicted low-grade lesions with an area under the curve of 0.82. Conclusions: A linear SVM learning model can identify low-grade IPMNs with good sensitivity and specificity. It may be used as a complement to existing guidelines to identify patients who could avoid unnecessary surgical resection.

• Archives of Plastic Surgery
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• v.51 no.3
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• pp.337-341
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• 2024

Nipple-areolar complex (NAC) necrosis is a devastating complication in nipple-sparing mastectomies (NSMs) that significantly impacts patient's quality of life. The use of fluorescence angiography for intraoperative assessment of mastectomy skin flap perfusion in NSM has been successfully described and can be utilized to help guide surgical decision-making. Recently, a novel fluorescence-guided surgical imager was developed, OnLume Avata System (OnLume Surgical, Madison, WI), which provides intraoperative evaluation of vascular perfusion in ambient light. In this case report, we describe the use of OnLume fluorescence-guided surgery technology to help aid in clinical decision-making for two breast reconstruction cases with concern for intraoperative nipple hypoperfusion.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.44 no.4
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• pp.174-181
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• 2018

Objectives: The number of patients with medication-related osteonecrosis of the jaw (MRONJ) is increasing, but treatment remains controversial. Published papers and systematic reviews have suggested that surgical treatment is effective in patients with MRONJ. The purpose of this study was to determine whether preoperative University of Connecticut Osteonecrosis Numerical Scale (UCONNS), other serologic biomarkers, and size of necrosis are prognostic factors for outcome of surgical treatment in MRONJ. Materials and Methods: From January 2008 to December 2016, 65 patients diagnosed with MRONJ at the Department of Oral and Maxillofacial Surgery in College of Dentistry, Dankook University who required hospitalization and surgical treatment were investigated. Patient information, systemic factors, and UCONNS were investigated. In addition, several serologic values were examined through blood tests one week before surgery. The size of osteolysis was measured by panoramic view and cone-beam computed tomography in all patients. With this information, multivariate logistic regression analysis with backward elimination was used to examine factors affecting postoperative outcome. Results: In multivariate logistic analysis, higher UCONNS, higher C-reactive protein (CRP), larger size of osteolysis, and lower serum alkaline phosphate were associated with higher incidence of incomplete recovery after operation. This shows that UCONNS, CRP, serum alkaline phosphate, and size of osteolysis were statistically significant as factors for predicting postoperative prognosis. Conclusion: This study demonstrated that CRP, UCONNS, serum alkaline phosphate, and size of osteolysis were statistically significant factors in predicting the prognosis of surgical outcome of MRONJ. Among these factors, UCONNS can predict the prognosis of MRONJ surgery as a scale that includes various influencing factors, and UCONNS should be used first as a predictor. More aggressive surgical treatment and more definite surgical margins are needed when the prognosis is poor.

• Genomics & Informatics
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• v.8 no.4
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• pp.212-218
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• 2010

An accurate system for predicting the survival of patients with oral squamous cell carcinoma (OSCC) will be useful for selecting appropriate therapies. A nomogram for predicting survival was constructed from 96 patients with primary OSCC who underwent surgical resection between January 1994 and June 2003 at the Yonsei Dental Hospital in Seoul, Korea. We performed univariate and multivariate Cox regression to identify survival prognostic factors. For the early stage patients group, the nomogram was able to predict the 5 and 10 year survival from OSCC with a concordance index of 0.72. The total point assigned by the nomogram was a significant factor for predicting survival. This nomogram was able to accurately predict the survival after treatment of an individual patient with OSCC and may have practical utility for deciding adjuvant treatment.

• Archives of Craniofacial Surgery
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• v.25 no.5
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• pp.217-233
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• 2024

Background: This study investigated the predictive value of orthopantomography (OPG) for the difficulty of extracting impacted mandibular third molars, in comparison with cone-beam computed tomography (CBCT). Methods: In this descriptive quantitative investigation, two oral and maxillofacial radiologists evaluated OPG and three-dimensional CBCT images according to the Pell-Gregory and Winter classifications. The results for the classification were compared using the chi-square test, and the prediction of difficulty was assessed using the Pederson scale, with a significance level of p< 0.05. Results: The study included 30 patients (14 men and 16 women), providing a total of 53 samples of impacted mandibular third molars. Of these, 30 (56.6%) were from the right side and 23 (43.4%) from the left. There was a statistically significant difference between the OPG and CBCT images concerning their relation to the mandibular ramus (p< 0.05). However, evaluations based on occlusal lines and angulation showed no significant differences (p> 0.05). According to the Pederson scale, significant differences were observed between OPG and CBCT in predicting extraction difficulty (p< 0.05). Conclusion: CBCT offered a more accurate assessment of the surgical difficulty associated with mandibular third molars than OPG. OPG views frequently failed to adequately visualize the region of the mandibular ramus, influencing the perceived difficulty of mandibular third molar surgery. In certain cases, the use of CBCT imaging is crucial.

• Journal of Gastric Cancer
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• v.20 no.3
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• pp.267-276
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• 2020

Purpose: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) risk calculator is useful in predicting postoperative adverse events. However, its accuracy in specific disorders is unclear. We validated the ACS NSQIP risk calculator in patients with gastric cancer undergoing curative laparoscopic surgery. Materials and Methods: We included 207 consecutive early gastric cancer patients who underwent laparoscopic gastrectomy between January 2018 and January 2019. The preoperative characteristics and risks of the patients were reviewed and entered into the ACS NSQIP calculator. The estimated risks of postoperative outcomes were compared with the observed outcomes using C-statistics and Brier scores. Results: Most of the patients underwent distal gastrectomy with Roux-en-Y reconstruction (74.4%). We did not observe any cases of mortality, venous thromboembolism, urinary tract infection, renal failure, or cardiac complications. The other outcomes assessed were complications such as pneumonia, surgical site infections, any complications requiring re-operation or hospital readmission, the rates of discharge to nursing homes/rehabilitation centers, and the length of stay. All C-statistics were <0 and the highest was for pneumonia (0.65; 95% confidence interval: 0.58-0.71). Brier scores ranged from 0.01 for pneumonia to 0.155 for other complications. Overall, the risk calculator was inconsistent in predicting the outcomes. Conclusions: The ACS NSQIP surgical risk calculator showed low predictive ability for postoperative adverse events after laparoscopic gastrectomy for patients with early gastric cancer. Further research to adjust the risk calculator for these patients may improve its predictive ability.