Development and validation of machine learning models and nomograms for predicting the surgical difficulty of laparoscopic resection in rectal cancer.

BACKGROUND: The objective of this study is to develop and validate a machine learning (ML) prediction model for the assessment of laparoscopic total mesorectal excision (LaTME) surgery difficulty, as well as to identify independent risk factors that influence surgical difficulty. Establishing a nomogram aims to assist clinical practitioners in formulating more effective surgical plans before the procedure. METHODS: This study included 186 patients with rectal cancer who underwent LaTME from January 2018 to December 2020. They were divided into a training cohort (n = 131) versus a validation cohort (n = 55). The difficulty of LaTME was defined based on Escal's et al. scoring criteria with modifications. We utilized Lasso regression to screen the preoperative clinical characteristic variables and intraoperative information most relevant to surgical difficulty for the development and validation of four ML models: logistic regression (LR), support vector machine (SVM), random forest (RF), and decision tree (DT). The performance of the model was assessed based on the area under the receiver operating characteristic curve(AUC), sensitivity, specificity, and accuracy. Logistic regression-based column-line plots were created to visualize the predictive model. Consistency statistics (C-statistic) and calibration curves were used to discriminate and calibrate the nomogram, respectively. RESULTS: In the validation cohort, all four ML models demonstrate good performance: SVM AUC = 0.987, RF AUC = 0.953, LR AUC = 0.950, and DT AUC = 0.904. To enhance visual evaluation, a logistic regression-based nomogram has been established. Predictive factors included in the nomogram are body mass index (BMI), distance between the tumor to the dentate line ≤ 10 cm, radiodensity of visceral adipose tissue (VAT), area of subcutaneous adipose tissue (SAT), tumor diameter >3 cm, and comorbid hypertension. CONCLUSION: In this study, four ML models based on intraoperative and preoperative risk factors and a nomogram based on logistic regression may be of help to surgeons in evaluating the surgical difficulty before operation and adopting appropriate responses and surgical protocols.

Simple pelvimetry predicts the pelvic manipulation time in robot-assisted low and ultra-low anterior resection for rectal cancer.

PURPOSE: This study explored the difficulty factors in robot-assisted low and ultra-low anterior resection, focusing on simple measurements of the pelvic anatomy. METHODS: This was a retrospective analysis of the clinical data of 61 patients who underwent robot-assisted low and ultra-low anterior resection for rectal cancer between October 2018 and April 2023. The relationship between the operative time in the pelvic phase and clinicopathological data, especially pelvic anatomical parameters measured on X-ray and computed tomography (CT), was evaluated. The operative time in the pelvic phase was defined as the time between mobilization from the sacral promontory and rectal resection. RESULTS: Robot-assisted low and ultra-low anterior resections were performed in 32 and 29 patients, respectively. The median operative time in the pelvic phase was 126 (range, 31-332) min. A multiple linear regression analysis showed that a short distance from the anal verge to the lower edge of the cancer, a narrow area comprising the iliopectineal line, short anteroposterior and transverse pelvic diameters, and a small angle of the pelvic mesorectum were associated with a prolonged operative time in the pelvic phase. CONCLUSION: Simple pelvic anatomical measurements using abdominal radiography and CT may predict the pelvic manipulation time in robot-assisted surgery for rectal cancer.

Prediction of extraction difficulty for impacted maxillary third molars with deep learning approach.

OBJECTIVE: The aim of this study is to determine if a deep learning (DL) model can predict the surgical difficulty for impacted maxillary third molar tooth using panoramic images before surgery. MATERIALS AND METHODS: The dataset consists of 708 panoramic radiographs of the patients who applied to the Oral and Maxillofacial Surgery Clinic for various reasons. Each maxillary third molar difficulty was scored based on dept (V), angulation (H), relation with maxillary sinus (S), and relation with ramus (R) on panoramic images. The YoloV5x architecture was used to perform automatic segmentation and classification. To prevent re-testing of images, participate in the training, the data set was subdivided as: 80 % training, 10 % validation, and 10 % test group. RESULTS: Impacted Upper Third Molar Segmentation model showed best success on sensitivity, precision and F1 score with 0,9705, 0,9428 and 0,9565, respectively. S-model had a lesser sensitivity, precision and F1 score than the other models with 0,8974, 0,6194, 0,7329, respectively. CONCLUSION: The results showed that the proposed DL model could be effective for predicting the surgical difficulty of an impacted maxillary third molar tooth using panoramic radiographs and this approach might help as a decision support mechanism for the clinicians in peri­surgical period.

Nomogram for predicting the surgical difficulty of laparoscopic total mesorectal excision and exploring the technical advantages of robotic surgery.

Background: Total mesorectal excision (TME), represents a key technique in radical surgery for rectal cancer. This study aimed to construct a preoperative nomogram for predicting the surgical difficulty of laparoscopic total mesorectal excision (L-TME) and to investigate whether there were potential benefits of robotic TME (R-TME) for patients with technically challenging rectal cancer. Methods: Consecutive mid-low rectal cancer patients receiving total mesorectal excision were included. A preoperative nomogram to predict the surgical difficulty of L-TME was established and validated. Patients with technically challenging rectal cancer were screened by calculating the prediction score of the nomogram. Then patients with technically challenging rectal cancer who underwent different types of surgery, R-TME or L-TME, were analyzed for comparison. Results: A total of 533 consecutive patients with mid-low rectal cancer who underwent TME at a single tertiary medical center between January 2018 and January 2021 were retrospectively enrolled. Multivariable analysis demonstrated that mesorectal fat area, intertuberous distance, tumor size, and tumor height were independent risk factors for surgical difficulty. Subsequently, these variables were used to construct the nomogram model to predict the surgical difficulty of L-TME. The area under the receiver operating characteristic curve of the nomogram was 0.827 (95% CI 0.745 - 0.909) and 0.809 (95% CI 0.674- 0.944) in the training and validation cohort, respectively. For patients with technically challenging rectal cancer, R-TME was associated with a lower diverting ileostomy rate (p = 0.003), less estimated blood loss (p < 0.043), shorter procedure time (p = 0.009) and shorter postoperative hospital stay (p = 0.037). Conclusion: In this study, we established a preoperative nomogram to predict the surgical difficulty of L-TME. Furthermore, this study also indicated that R-TME has potential technical advantages for patients with technically challenging rectal cancer.

Interpretable machine learning model to predict surgical difficulty in laparoscopic resection for rectal cancer.

Background: Laparoscopic total mesorectal excision (LaTME) is standard surgical methods for rectal cancer, and LaTME operation is a challenging procedure. This study is intended to use machine learning to develop and validate prediction models for surgical difficulty of LaTME in patients with rectal cancer and compare these models' performance. Methods: We retrospectively collected the preoperative clinical and MRI pelvimetry parameter of rectal cancer patients who underwent laparoscopic total mesorectal resection from 2017 to 2022. The difficulty of LaTME was defined according to the scoring criteria reported by Escal. Patients were randomly divided into training group (80%) and test group (20%). We selected independent influencing features using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression method. Adopt synthetic minority oversampling technique (SMOTE) to alleviate the class imbalance problem. Six machine learning model were developed: light gradient boosting machine (LGBM); categorical boosting (CatBoost); extreme gradient boost (XGBoost), logistic regression (LR); random forests (RF); multilayer perceptron (MLP). The area under receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity and F1 score were used to evaluate the performance of the model. The Shapley Additive Explanations (SHAP) analysis provided interpretation for the best machine learning model. Further decision curve analysis (DCA) was used to evaluate the clinical manifestations of the model. Results: A total of 626 patients were included. LASSO regression analysis shows that tumor height, prognostic nutrition index (PNI), pelvic inlet, pelvic outlet, sacrococcygeal distance, mesorectal fat area and angle 5 (the angle between the apex of the sacral angle and the lower edge of the pubic bone) are the predictor variables of the machine learning model. In addition, the correlation heatmap shows that there is no significant correlation between these seven variables. When predicting the difficulty of LaTME surgery, the XGBoost model performed best among the six machine learning models (AUROC=0.855). Based on the decision curve analysis (DCA) results, the XGBoost model is also superior, and feature importance analysis shows that tumor height is the most important variable among the seven factors. Conclusions: This study developed an XGBoost model to predict the difficulty of LaTME surgery. This model can help clinicians quickly and accurately predict the difficulty of surgery and adopt individualized surgical methods.

Validation of a surgical difficulty grading system in laparoscopic cholecystectomy for acute cholecystitis.

BACKGROUND: The surgical difficulty of laparoscopic cholecystectomy (LC) for acute cholecystitis varies from case to case, and appropriate intraoperative evaluation would help prevent bile duct injury (BDI). METHODS: We analyzed 178 patients who underwent LC for acute cholecystitis. Expert surgeons and trainees individually evaluated the surgical difficulty. The inter-rater agreement was analyzed using Conger's κ and Gwet's agreement coefficient (AC). Furthermore, we analyzed the predictive surgical difficulty item for performing subtotal cholecystectomy (STC). RESULTS: Regarding the inter-rater agreement between expert surgeons and trainees, 15 of the 17 surgical difficulty items had a Gwet's AC of 0.5 or higher, indicating "moderate" agreement or higher. Furthermore, the highest and total surgical difficulty scores were deemed "substantial" agreement. Scarring and dense fibrotic changes around the Calot's triangle area with easy bleeding with/without necrotic changes were predictive of whether STC should be performed. CONCLUSIONS: This surgical difficulty grading system is expected to be a tool that can be used by any surgeon with LC experience. STC should be performed to prevent BDI according to the changes around the Calot's triangle area.

Validación de un Nuevo Indice de Dificultad para la Exodoncia de Terceros Molares Mandibulares Impactados

El objetivo del presente estudio fue el determinar la validez de un nuevo índice de dificultad para la exodoncia de terceros molares mandibulares impactados. El presente es un estudio descriptivo, comparativo y transversal. Se llevó a cabo en la Clínica Estomatológica de la Universidad Nacional de Trujillo-Perú, durante el año 2015. La muestra estuvo conformada por 42 pacientes ASA I, de 18 a 65 años, con indicación de extracción de tercera molar mandibular impactada asintomática, con corona clínica íntegra. Cada paciente firmó un consentimiento informado para así poder participar en el estudio. Antes de la realización de la exodoncia, a cada paciente, se le valoró su grado de dificultad quirúrgica según la clasificación de Winter-Pell y Gregory y el nuevo índice de dificultad propuesto. Para la comparación del grado de dificultad entre los índices con el número de complicaciones, la dificultad quirúrgica entre los índices con la dificultad quirúrgica real y el tiempo quirúrgico entre los índices; se utilizaron la prueba estadística de Chi cuadrado, el Test de Mc Nemar y la T de Student, respectivamente. La significación estadística fue del 5 %. Al comparar los índices con el grado de dificultad real, se obtuvo que existe una alta diferencia estadística significativa (p < 0.001). Al realizar las pruebas de sensibilidad y especificidad de ambos índices, se obtuvo que el nuevo índice y el índice de Winter-Pell y Gregory tuvieron una sensibilidad del 100 % y 55 % y una especificidad del 10 % y 100 %, respectivamente. Se concluye que el nuevo índice propuesto en este estudio pronostica de manera más exacta la dificultad quirúrgica de las exodoncias de terceros molares mandibulares impactados.

The aim of this study was to determine the validity of a new difficulty index for the extraction of impacted mandibular third molars. This is a descriptive, comparative and cross-sectional study. It was carried out at the Clinica Estomatológica of the Universidad Nacional de Trujillo - Peru, during the year 2015. The sample consisted of 42 ASA I patients, from 18 to 65 years old, with an indication for extraction of an asymptomatic impacted mandibular third molar, with complete clinical crown. Each patient signed an informed consent in order to participate in the study. Before performing the extraction, each patient was assessed their degree of surgical difficulty according to the Winter-Pell and Gregory classification and the new difficulty index proposed. For the comparison of the degree of difficulty between the indices with the number of complications, the surgical difficulty between the indices with the actual surgical difficulty and the surgical time between the indices; the Chi-square statistical test, the Mc Nemar Test and the Student's T test were used, respectively. Statistical significance was 5 %. When comparing the indices with the actual degree of difficulty, it was found that there is a highly significant statistical difference (p < 0.001). When carrying out the sensitivity and specificity tests of both indices, it was found that the new index and the Winter-Pell and Gregory index had a sensitivity of 100 % and 55 % and a specificity of 10 % and 100 %, respectively. It is concluded that the new index proposed in this study more accurately predicts the surgical difficulty of extractions of impacted mandibular third molars.

Effect of thoracic cage width on surgery time and postoperative outcome in minimally invasive esophagectomy.

INTRODUCTION: Minimally invasive esophagectomy (MIE) for esophageal cancer is a complex procedure that reduces postoperative morbidity in comparison to open approach. In this study, thoracic cage width as a factor to predict surgical difficulty in MIE was evaluated. METHODS: All patients of our institution receiving either total MIE or robotic-assisted MIE (RAMIE) with intrathoracic anastomosis between February 2016 and April 2021 for esophageal cancer were included in this study. Right unilateral thoracic cage width on the level of vena azygos crossing the esophagus was measured by the horizontal distance between the esophagus and parietal pleura on preoperative computer tomography. Patients' data as well as operative and postoperative details were collected in a prospective database. Correlation between thoracic cage width with duration of the thoracic procedure and postoperative complication rates was analyzed. RESULTS: Overall, 313 patients were eligible for this study. Thoracic width on vena azygos level ranged from 85 to 149 mm with a mean of 116.5 mm. In univariate analysis, a small thoracic width significantly correlated with longer duration of the thoracic procedure (p = 0.014). In multivariate analysis, small thoracic width and neoadjuvant therapy were identified as independent factors for long duration of the thoracic procedure (p = 0.006). Regarding postoperative complications, thoracic cage width was a significant risk factor for occurrence of postoperative pneumonia in the multivariate analysis (p = 0.045). Dividing the cohort into two groups of patients with narrow (≤ 107 mm, 19.5%) and wide thoraces (≥ 108 mm, 80.5%), the thoracic procedure was significantly prolonged by 17 min (204 min vs. 221 min, p = 0.014). CONCLUSION: A small thoracic cage width is significantly correlated with longer operation time during thoracic phase of a MIE in Europe, which suggests increased surgical difficulty. Patients with small thoracic cage width may preferably be operated by MIE-experienced surgeons.

Perioperative and oncologic outcomes of pulmonary resection for synchronous oligometastatic non-small cell lung cancer: Evidence for surgery in advanced disease.

OBJECTIVES: Recent randomized trials have demonstrated a survival advantage with the use of local consolidative therapy in oligometastatic non-small cell lung cancer; however, the indications for and outcomes after pulmonary resection as a component of local consolidative therapy remain ill defined. We sought to characterize the perioperative and long-term survival outcomes among patients with resected oligometastatic non-small cell lung cancer. METHODS: Patients presenting to a single center (2000-2017) with oligometastatic non-small cell lung cancer (≤3 synchronous metastases, intrathoracic nodal disease counted as a single site) who underwent resection of the primary tumor were retrospectively identified. Charts were reviewed, and demographic, clinical, pathologic, oncologic, and survival outcomes were recorded. Survival outcomes were analyzed from the date of surgery. RESULTS: A total of 52 patients met inclusion criteria, among whom most (38, 73.1%) were ever smokers, had nonsquamous tumors (48, 92.3%), had no intrathoracic nodal disease (33, 63.5%), and had 1 to 2 sites of metastases (49, 94.2%). The majority (41, 78.9%) received systemic therapy, predominantly in the neoadjuvant setting (24/41, 58.5%). After resection, there were no 30- or 90-day deaths. After a median follow-up of 94.6 months (95% CI, 69.0-139.1), 37 patients (71.2%) progressed and 38 patients (73.1%) died. Median postoperative progression-free survival and overall survival were 9.4 (5.5-11.6) months and 51.7 (22.3-65.3) months, respectively. CONCLUSIONS: Pulmonary resection as a means of maximum locoregional control in oligometastatic non-small cell lung cancer is feasible and safe, and may be associated with durable long-term survival benefits. The frequency of systemic postoperative progression highlights an urgent need to characterize perioperative and oncologic outcomes after pulmonary resection in the current era of novel systemic therapies.

Establishment of Surgical Difficulty Grading System and Application of MRI-Based Artificial Intelligence to Stratify Difficulty in Laparoscopic Rectal Surgery.

(1) Background: The difficulty of pelvic operation is greatly affected by anatomical constraints. Defining this difficulty and assessing it based on conventional methods has some limitations. Artificial intelligence (AI) has enabled rapid advances in surgery, but its role in assessing the difficulty of laparoscopic rectal surgery is unclear. This study aimed to establish a difficulty grading system to assess the difficulty of laparoscopic rectal surgery, as well as utilize this system to evaluate the reliability of pelvis-induced difficulties described by MRI-based AI. (2) Methods: Patients who underwent laparoscopic rectal surgery from March 2019 to October 2022 were included, and were divided into a non-difficult group and difficult group. This study was divided into two stages. In the first stage, a difficulty grading system was developed and proposed to assess the surgical difficulty caused by the pelvis. In the second stage, AI was used to build a model, and the ability of the model to stratify the difficulty of surgery was evaluated at this stage, based on the results of the first stage; (3) Results: Among the 108 enrolled patients, 53 patients (49.1%) were in the difficult group. Compared to the non-difficult group, there were longer operation times, more blood loss, higher rates of anastomotic leaks, and poorer specimen quality in the difficult group. In the second stage, after training and testing, the average accuracy of the four-fold cross validation models on the test set was 0.830, and the accuracy of the merged AI model was 0.800, the precision was 0.786, the specificity was 0.750, the recall was 0.846, the F1-score was 0.815, the area under the receiver operating curve was 0.78 and the average precision was 0.69; (4) Conclusions: This study successfully proposed a feasible grading system for surgery difficulty and developed a predictive model with reasonable accuracy using AI, which can assist surgeons in determining surgical difficulty and in choosing the optimal surgical approach for rectal cancer patients with a structurally difficult pelvis.

Development of artificial blood loss and duration of excision score to evaluate surgical difficulty of total laparoscopic anterior resection in rectal cancer.

Purpose: Total laparoscopic anterior resection (tLAR) has been gradually applied in the treatment of rectal cancer (RC). This study aims to develop a scoring system to predict the surgical difficulty of tLAR. Methods: RC patients treated with tLAR were collected. The blood loss and duration of excision (BLADE) scoring system was built to assess the surgical difficulty by using restricted cubic spline regression. Multivariate logistic regression was used to evaluate the effect of the BLADE score on postoperative complications. The random forest (RF) algorithm was used to establish a preoperative predictive model for the BLADE score. Results: A total of 1,994 RC patients were randomly selected for the training set and the test set, and 325 RC patients were identified as the external validation set. The BLADE score, which was built based on the thresholds of blood loss (60 ml) and duration of surgical excision (165 min), was the most important risk factor for postoperative complications. The areas under the curve of the predictive RF model were 0.786 in the training set, 0.640 in the test set, and 0.665 in the external validation set. Conclusion: This preoperative predictive model for the BLADE score presents clinical feasibility and reliability in identifying the candidates to receive tLAR and in making surgical plans for RC patients.

Identifying the preoperative factors predicting the surgical difficulty of robotic distal pancreatectomy.

BACKGROUND: Few studies have evaluated the preoperative factors predicting the surgical difficulty of robotic distal pancreatectomy (RDP). This study aims to explore such factors and provide guidance on the selection of suitable patients to aid surgeons lacking extensive experience in RDP. METHODS: A retrospective study was conducted on consecutive patients who underwent RDP to identify preoperative factors predicting surgical difficulty. High surgical difficulty was defined by both operation time and intraoperative estimated blood loss exceeding their median, or by conversion to laparotomy. RESULTS: A total of 161 patients were ultimately enrolled, including 51 patients with high levels of surgical difficulty. Multivariate analysis revealed that male sex [OR (95% CI): 4.07 (1.77,9.40), p = 0.001], body mass index (BMI) ≥ 25 kg/m2 OR (95% CI): 2.27 (1.03,5.00), p = 0.042], tumors located at the neck of the pancreas [OR (95% CI): 4.15 (1.49,11.56), p = 0.006] and splenic artery type B [OR (95% CI): 3.28 (1.09,9.91), p = 0.035] were independent risk factors for surgical difficulty. Regarding postoperative complications, high surgical difficulty was associated with the risk of overall complications and pancreatic fistula (grade B/C) (49.0% vs. 22.7%, p < 0.001; 39.2% vs. 19.1%, p = 0.006). CONCLUSION: Male sex, body mass index ≥ 25 kg/m2, tumor located at the neck of the pancreas and splenic artery type B are associated with a high RDP difficulty level. These factors can be used preoperatively to assess the difficulty level of surgery, to help surgeons choose patients suitable for them and ensure surgical safety.

Clinical evaluation of a surgical difficulty score for laparoscopic cholecystectomy for acute cholecystitis proposed in the Tokyo Guidelines 2018.

BACKGROUND/PURPOSE: We evaluated the difficulty score of laparoscopic cholecystectomy (LC) for acute cholecystitis (AC) proposed in the Tokyo guidelines 2018 (TG18) and analyzed the most appropriate scoring method. METHODS: We reviewed 127 patients who underwent LC for AC from January 2018 to March 2022. According to TG18, surgical difficulty was scored for five categories consisting of 25 intraoperative findings. The median, highest, and mean score of the five categories were analyzed for their association with surgical outcomes. RESULTS: The difficulty score distribution (0/1/2/3/4/5/6) was as follows: median (8/34/43/30/12/0/0), highest (1/1/32/42/36/15/0) and mean (19/49/49/10/0/0/0). In all three scoring methods, higher difficulty scores were significantly correlated with longer operative time, more blood loss, and higher occurrence of subtotal cholecystectomy in trend tests. The areas under the curve (AUCs) for prediction of prolonged operative time minutes and increased blood loss were similar in all three scoring methods. For conversion to subtotal cholecystectomy, the AUC was significantly better for the highest than median and mean score (p = .015 and p = .002, respectively). CONCLUSIONS: The difficulty score in TG18 appropriately reflects the surgical difficulty of LC for AC. The median, highest, and mean scores of the five categories are all available, and the highest scores are simple and versatile.

The preoperative M2BPGi score predicts operative difficulty and the incidence of postoperative complications in laparoscopic liver resection.

BACKGROUND: Liver fibrosis or cirrhosis frequently makes parenchymal transection more difficult, but the difficulty score of laparoscopic liver resection (LLR), including the IWATE criteria, does not include a factor related to liver fibrosis. Therefore, this study aimed to evaluate M2BPGi as a predictor of the difficulty of parenchymal transection and the incidence of postoperative complications in LLR. METHODS: Data from 54 patients who underwent laparoscopic partial liver resection (LLR-P) and 24 patients who underwent laparoscopic anatomical liver resection between 2017 and 2019 in our institution were retrospectively analyzed. All cases were classified according to M2BPGi scores, and reserve liver function, intraoperative blood loss, and postoperative complications were compared among these groups. RESULTS: Sixteen cases (29.6%) were M2BPGi negative (cut-off index < 1.0), 25 cases (46.3%) were 1+ (1.0 ≤ cut-off index < 3.0), and 13 cases (24.1%) were 2+ (cut-off index ≥ 3.0). M2BPGi-positive cases had significantly worse hepatic reserve function (K-ICG: 0.16 vs 0.14 vs 0.08, p < 0.0001). Intraoperative bleeding was significantly greater in M2BPGi-positive cases [50 ml vs 150 ml vs 200 ml, M2BPGi (-) or (1+) vs M2BPGi (2+), p = 0.045]. Postoperative complications (Clavien-Dindo ≥ II) were significantly more frequent in M2BPGi-positive cases [0% vs 4% vs 33%, M2BPGi (-) or (1+) vs M2BPGi (2+), p = 0.001]. CONCLUSION: M2BPGi could predict surgical difficulty and complications in LLR-P. In particular, it might be better not to select M2BPGi (2+) cases as teaching cases because of the massive bleeding during parenchymal transection.

Research progress in predicting the difficulty of surgery for middle and low rectal cancer based on pelvic measurement / 中华消化外科杂志

Total mesorectal excision (TME) has become the basic principle of surgical treat-ment for middle and low rectal cancer. Some of patients with ultra-low rectal cancer require under-going intersphincteric resection (ISR). Due to the limitation of the narrow pelvis, TME and ISR put forward higher requirements for the precise separation of the anatomical level and the protection of neurological function during the operation. At present, evaluation of the difficulty of surgery for middle and low rectal cancer is mainly based on the subjective judgment of chief surgeon, and there is no unified and objective scoring system or prediction model that can classify the difficulty of surgery for middle and low rectal cancer before surgery. The authors review relevant literatures and summarize the existing studies related to pelvic measurement for predicting the difficulty of surgery for middle and low rectal cancer, in order to provide significant guidance for the selection of surgical approach for patients with middle and low rectal cancer.

A Scoring System That Predicts Difficult Lipoma Resection: Logistic Regression and Tenfold Cross-Validation Analysis.

INTRODUCTION: Most lipomas are readily dissected and removed. However, some cases can pose surgical difficulties. This retrospective study sought to identify clinical and radiological risk factors that predict difficult lipoma resection and can be used in a clinically useful scoring system that predicts difficulty preoperatively. METHODS: The study cohort consisted of all consecutive patients who underwent resection of pathology-confirmed lipoma during 2016-2018 at a tertiary care referral center in Tokyo, Japan. Surgical difficulty was defined as difficulty separating some/all of the tumor from the surrounding tissue by hand and inability to extract the tumor in one piece. Descriptive, univariate, and multivariate logistic regression analyses were conducted to identify predictive factors. The predictive accuracy of the scoring system that included these factors was assessed by tenfold cross-validation analysis. Receiver-operating curve (ROC) analysis was conducted to identify the optimal cutoff score for predicting surgical difficulty. RESULTS: Of the 86 cases, 36% involved surgical difficulty. Multivariate analysis showed that subfascial intramuscular location (odds ratio 42.7, 95% confidence interval 3.0-608.0), broad touching of underlying structures (46.5, 3.7-586.0), in-flowing blood vessels (9.3, 1.1-78.5), and unclear boundaries (109.0, 1.1-1110.0) significantly predicted surgical difficulty. These factors were used to construct a 0-4 point scoring system (with one point per variable). On cross-validation, the accuracy of the scoring system was 82.4% (Cohen's kappa of 0.57). ROC analysis showed that scores ≥ 2 predicted surgical difficulty with sensitivity and specificity of 55% and 98%, respectively. CONCLUSIONS: Our scoring system accurately predicted lipoma resection difficulty and may help operators prepare, thereby facilitating surgery.

The StarvAnx Study-Comparison Between the Effects of Non-fasting Vs. Fasting Strategy on Surgical Outcomes, Anxiety and Pain in Patients Undergoing Cataract Surgery Under Topical Anesthesia: A Randomized, Crossover, Controlled Trial.

Background: Fasting is usually recommended in patients undergoing cataract surgery under topical anesthesia. However, starving before surgery may increase preoperative anxiety and affect surgical outcomes. It is not known which fasting or non-fasting strategy is best for cataract surgery. The aim of this study was to compare non-fasting and fasting strategy in patients undergoing cataract surgery under topical anesthesia with regard to surgical outcomes, anxiety and pain. Methods: This randomized, crossover, controlled trial enrolled patients undergoing surgery for bilateral cataract under topical anesthesia at Cochin Hospital (Paris, France), from February to May 2021. Patients were randomly assigned to the non-fasting or fasting group for the first eye surgery and were switched to the other group for the second eye surgery. The primary endpoint was to compare the rate of anesthetist's interventions during surgery. The secondary endpoints included intra-operative complications, duration of surgery, surgeon perception of surgical difficulty, anesthesia-related complications and anxiety and pain level. Results: one hundred and nine consecutive patients were included, with 60 of them being fasted first and non-fasted for the second eye surgery, while the other 59 were non-fasted first and fasted for the next surgery. The number of patients requiring sedation was significantly lower in the non-fasting group compared with the fasting group [1%; 95%IC (0-3.2) vs. 6%; 95%IC (2.9-8.9), P = 0.04]. No anesthesia-related complications were observed. There was no difference in the number of intra-operative complications between the non-fasting and the fasting groups (,respectively, 0 and 1; P = 1). Anxiety level and surgical pain were significantly lower in the non-fasting group compared to the fasting group (,respectively, 2.3 ± 2.0 vs. 4.1 ± 2.4, P = 0.01 and 0.6 ± 0.6 vs. 2.6 ± 3.4, P = 0.003). The mean duration of surgery was significantly shorter in the non-fasting group compared with the fasting group (,respectively, 16.0 ± 5.9 vs. 22.3 ± 6.1 min; P = 0.03). Conclusion: In conclusion pre-operatory non-fasting strategy provides a better patient experience with regards to preoperative anxiety and surgical pain. It allows to reduce operating times and is safe and well-tolerated as regards the anesthetic intervention.

Establishment of Thoracic Surgical Difficulty Assessment Scale based on Delphi method. / 基于德尔菲法构建胸外科手术难度评价量表.

OBJECTIVES: The difficulty of surgery, which is related to surgical safety, has only been mentioned as a subjective perception for a long time. There are few studies to quantitatively and systematically evaluate the difficulty of thoracic surgery. This study aims to establish a quantitative evaluation index system for thoracic surgical difficulty, and to evaluate its reliability and validity. METHODS: During the 2 national thoracic surgery academic conferences, the factors that may affect the difficulty of thoracic surgery were evaluated by the thoracic surgeons via semi open questionnaires, and then the evaluation item pool of thoracic surgery difficulty was established. The importance of each indicator in the evaluation item pool was graded by 2 rounds of Delphi method. The average score, full score rate and coefficient of variation of each index were calculated, and the composite index method was used to decide whether to delete the indicator.Finally, the difficulty evaluation scale of thoracic surgery was constructed. The surgical data of patients with thoracic tumors were collected. The scale was used to evaluate the difficulty of thoracic surgery for lung, esophageal, and mediastinal tumors. The reliability and validity of the scale were evaluated by the commonly used difficulty evaluation indexes: Operation time, intraoperative estimated blood loss, Visual Analog Scale (VAS), side injury rate, and blood transfusion rate as standards. RESULTS: A total of 230 questionnaires were distributed in the 2 rounds of survey, and 149 valid questionnaires were collected after eliminating duplicate questionnaires. Through 2 rounds of Delphi consultation with 20 experts, the difficulty evaluation indexes were scored and screened, and the difficulty evaluation scale of thoracic surgery was established. It included 5 main indexes (surgical decision-making, operation space, separation interface, reconstruction method, and surgical materials) and 16 secondary indexes [American Society of Anesthesiologists (ASA) classification, surgical trauma, operator experience, space size, space depth, space source, space adjacent, interface content, anatomical gap, visual field, interface size, reconstruction complexity, reconstruction scope, autologous materials, artificial biomaterials and instruments]. After weighting, the total score of Thoracic Surgery Difficulty Evaluation Scale was from 1 to 3. A Score at 1 standed for simplicity, and score at 3 standed for difficulty. Further data were collected for 127 cases of thoracic tumor surgery. The difficulty scores of surgery for lung, esophageal, and mediastinal tumor were 1.69±0.26, 1.86±0.18, and 1.56±0.31, respectively, and the Cronbach's α coefficients of the scale in 3 tumor surgeries were 0.993, 0.974, and 0.989, repectively, and the Spearman Brown coefficients were 0.996, 0.984, and 0.996, respectively. The Spearman correlation coefficients of operation difficulty score with operation time, estimated blood loss, and VAS were 0.360 and 0.634, 0.632 and 0.578, 0.696 and 0.875, respectively (all P<0.05). The incidence of postoperative complications in the difficult operation group (difficulty score >1.85) was higher than that in the non-difficult operation group (P=0.02). CONCLUSIONS: The quantitative Thoracic Surgical Difficulty Assessment Scale has been successfully established, which shows good reliability and validity in thoracic tumor surgery. The Thoracic Surgical Difficulty Assessment Scale has broad application prospects in reducing the difficulty of the surgery, controlling surgical complications, and training surgeons.

A retrospective and prospective study to establish a preoperative difficulty predicting model for video-assisted thoracoscopic lobectomy and mediastinal lymph node dissection.

BACKGROUND: In previous studies, the difficulty of surgery has rarely been used as a research object. Our study aimed to develop a predictive model to enable preoperative prediction of the technical difficulty of video-assisted thoracoscopic lobectomy and mediastinal lymph node dissection using retrospective data and to validate our findings prospectively. METHODS: Collected data according to the designed data table and took the operation time as the outcome variable. A nomogram to predict the difficulty of surgery was established through Lasso logistic regression. The prospective datasets were analyzed and the outcome was the operation time. RESULTS: This retrospective study enrolled 351 patients and 85 patients were included in the prospective datasets. The variables in the retrospective research were selected by Lasso logistic regression (only used for modeling and not screening), and four significantly related influencing factors were obtained: FEV1/FVC (forced expiratory volume in the first second/forced vital capacity) (p < 0.001, OR, odds ratio = 0.89, 95% CI, confidence interval = 0.84-0.94), FEV1/pred FEV1 (forced expiratory volume in the first second/forced expiratory volume in the first second in predicted) (p = 0.076, OR = 0.98, 95% CI = 0.95-1.00), history of lung disease (p = 0.027, OR = 4.00, 95% CI = 1.27-15.64), and mediastinal lymph node enlargement or calcification (p < 0.001, OR = 9.78, 95% CI = 5.10-19.69). We used ROC (receiver operating characteristic) curves to evaluate the model. The training set AUC (area under curve) value was 0.877, the test set's AUC was 0.789, and the model had a good calibration curve. In a prospective study, the data obtained in the research cohort were brought into the model again for verification, and the AUC value was 0.772. CONCLUSION: Our retrospective study identified four preoperative variables that are correlated with a longer surgical time and can be presumed to reflect more difficult surgical procedures. Our prospective study verified that the variables in the prediction model (including prior lung disease, FEV1/pred FEV1, FEV1/FVC, mediastinal lymph node enlargement or calcification) were related to the difficulty.

Perioperative factors influencing the difficulty of retroperitoneal laparoscopic adrenalectomy: a single-center retrospective study.

PURPOSE: Identifying patients in whom adrenalectomy may be more difficult can help with surgical decision-making. This study investigated the perioperative factors affecting the difficulty of retroperitoneal laparoscopic adrenalectomy (RLA). METHODS: Sixty-eight patients who underwent RLA at our hospital between December 1, 2020 and May 1, 2021 were included. The difficulty of RLA was assessed by operating time and intraoperative blood loss. We analyzed the relationship between surgical difficulty and patient sex, age, and body mass index, pathological type, tumor side, tumor size, distance from the lower pole of the adrenal tumor to the upper pole of the kidney (DAK), and distance from the lower pole of the adrenal tumor to the renal pedicle (DARP). RESULTS: Mean operating time was 105.38 ± 33.31 min and mean intraoperative blood loss was 32.28 ± 22.88 ml. Univariate linear regression analysis showed that age (P = 0.047), tumor size (P = 0.002), DAK (P = 0.002), and DARP (P < 0.001) were significantly correlated with a longer operating time. Univariate logistic regression analysis showed that DARP (P = 0.001), DAK (P = 0.001), tumor size (P = 0.002), and age (P = 0.033) were significantly correlated with a longer operating time. Multivariate logistic regression indicated that DARP (OR 5.341; 95% CI 1.704-16.739; P = 0.004), and tumor size (OR 4.433; 95% CI 1.434-13.709; P = 0.010) were independent predictors of operating time. CONCLUSION: Age, tumor size, DAK, and DARP were predictors of the difficulty of RLA. Older age, lower DARP and DAK, and a larger tumor size were associated with a longer operating time. DARP and tumor size were independent predictors of surgical difficulty.