A Novel Machine Learning Approach to Predict Textbook Outcome in Colectomy.

BACKGROUND: Several calculators exist to predict risk of postoperative complications. However, in low-risk procedures such as colectomy, a tool to determine the probability of achieving the ideal outcome could better aid clinical decision-making, especially for high-risk patients. A textbook outcome is a composite measure that serves as a surrogate for the ideal surgical outcome. OBJECTIVE: To identify the most important factors for predicting textbook outcomes in patients with nonmetastatic colon cancer undergoing colectomy and to create a textbook outcome decision support tool using machine learning algorithms. DESIGN: This was a retrospective analysis study. SETTINGS: Data were collected from the American College of Surgeons National Surgical Quality Improvement Program database. PATIENTS: Adult patients undergoing elective colectomy for nonmetastatic colon cancer (2014-2020) were included. MAIN OUTCOME MEASURES: Textbook outcome was the main outcome, defined as no mortality, no 30-day readmission, no postoperative complications, no 30-day reinterventions, and a hospital length of stay of ≤5 days. Four models (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting) were trained and validated. Ultimately, a web-based calculator was developed as proof of concept for clinical application. RESULTS: A total of 20,498 patients who underwent colectomy for nonmetastatic colon cancer were included. Overall, textbook outcome was achieved in 66% of patients. Textbook outcome was more frequently achieved after robotic colectomy (77%), followed by laparoscopic colectomy (68%) and open colectomy (39%, p < 0.001). eXtreme Gradient Boosting was the best performing model (area under the curve = 0.72). The top 5 preoperative variables to predict textbook outcome were surgical approach, patient age, preoperative hematocrit, preoperative oral antibiotic bowel preparation, and patient sex. LIMITATIONS: This study was limited by its retrospective nature of the analysis. CONCLUSIONS: Using textbook outcome as the preferred outcome may be a useful tool in relatively low-risk procedures such as colectomy, and the proposed web-based calculator may aid surgeons in preoperative evaluation and counseling, especially for high-risk patients. See Video Abstract . UN NUEVO ENFOQUE DE APRENDIZAJE AUTOMTICO PARA PREDECIR EL RESULTADO DE LOS LIBROS DE TEXTO EN COLECTOMA: ANTECEDENTES:Existen varias calculadoras para predecir el riesgo de complicaciones posoperatorias. Sin embargo, en procedimientos de bajo riesgo como la colectomía, una herramienta para determinar la probabilidad de lograr el resultado ideal podría ayudar mejor a la toma de decisiones clínicas, especialmente para pacientes de alto riesgo. Un resultado de libro de texto es una medida compuesta que sirve como sustituto del resultado quirúrgico ideal.OBJETIVO:Identificar los factores más importantes para predecir el resultado de los libros de texto en pacientes con cáncer de colon no metastásico sometidos a colectomía y crear una herramienta de apoyo a la toma de decisiones sobre los resultados de los libros de texto utilizando algoritmos de aprendizaje automático.DISEÑO:Este fue un estudio de análisis retrospectivo.AJUSTES:Los datos se obtuvieron de la base de datos del Programa Nacional de Mejora de la Calidad del Colegio Americano de Cirujanos.PACIENTES:Se incluyeron pacientes adultos sometidos a colectomía electiva por cáncer de colon no metastásico (2014-2020).MEDIDAS PRINCIPALES DE RESULTADO:El resultado de los libros de texto fue el resultado principal, definido como ausencia de mortalidad, reingreso a los 30 días, complicaciones posoperatorias, reintervenciones a los 30 días y una estancia hospitalaria ≤5 días. Se entrenaron y validaron cuatro modelos (regresión logística, árbol de decisión, bosque aleatorio y XGBoost). Finalmente, se desarrolló una calculadora basada en la web como prueba de concepto para su aplicación clínica.RESULTADOS:Se incluyeron un total de 20.498 pacientes sometidos a colectomía por cáncer de colon no metastásico. En general, el resultado de los libros de texto se logró en el 66% de los pacientes. Los resultados de los libros de texto se lograron con mayor frecuencia después de la colectomía robótica (77%), seguida de la colectomía laparoscópica (68%) y la colectomía abierta (39%) (p<0,001). XGBoost fue el modelo con mejor rendimiento (AUC=0,72). Los cinco principales variables preoperatorias para predecir el resultado en los libros de texto fueron el abordaje quirúrgico, la edad del paciente, el hematocrito preoperatorio, la preparación intestinal con antibióticos orales preoperatorios y el sexo femenino.LIMITACIONES:Este estudio estuvo limitado por la naturaleza retrospectiva del análisis.CONCLUSIONES:El uso de los resultados de los libros de texto como resultado preferido puede ser una herramienta útil en procedimientos de riesgo relativamente bajo, como la colectomía, y la calculadora basada en la web propuesta puede ayudar a los cirujanos en la evaluación y el asesoramiento preoperatorios, especialmente para pacientes de alto riesgo. (Traducción-Yesenia Rojas-Khalil ).

A machine learning approach for predicting textbook outcome after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy.

INTRODUCTION: Peritoneal carcinomatosis is considered a late-stage manifestation of neoplastic diseases. Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) can be an effective treatment for these patients. However, the procedure is associated with significant morbidity. Our aim was to develop a machine learning model to predict the probability of achieving textbook outcome (TO) after CRS-HIPEC using only preoperatively known variables. METHODS: Adult patients with peritoneal carcinomatosis and who underwent CRS-HIPEC were included from a large, single-center, prospectively maintained dataset (2001-2020). TO was defined as a hospital length of stay ≤14 days and no postoperative adverse events including any complications, reoperation, readmission, and mortality within 90 days. Four models (logistic regression, neural network, random forest, and XGBoost) were trained, validated, and a user-friendly risk calculator was then developed. RESULTS: A total of 1954 CRS-HIPEC procedures for peritoneal carcinomatosis were included. Overall, 13% (n = 258) achieved TO following CRS-HIPEC procedure. XGBoost and logistic regression had the highest area under the curve (AUC) (0.76) after model optimization, followed by random forest (AUC 0.75) and neural network (AUC 0.74). The top preoperative variables associated with achieving a TO were lower peritoneal cancer index scores, not undergoing proctectomy, splenectomy, or partial colectomy and being asymptomatic from peritoneal metastases prior to surgery. CONCLUSION: This is a data-driven study to predict the probability of achieving TO after CRS-HIPEC. The proposed pipeline has the potential to not only identify patients for whom surgery is not associated with prohibitive risk, but also aid surgeons in communicating this risk to patients.

Development and Validation of Prediction Models and Risk Calculators for Posthepatectomy Liver Failure and Postoperative Complications Using a Diverse International Cohort of Major Hepatectomies.

OBJECTIVE: The study aim was to develop and validate models to predict clinically significant posthepatectomy liver failure (PHLF) and serious complications [a Comprehensive Complication Index (CCI)>40] using preoperative and intraoperative variables. BACKGROUND: PHLF is a serious complication after major hepatectomy but does not comprehensively capture a patient's postoperative course. Adding the CCI as an additional metric can account for complications unrelated to liver function. METHODS: The cohort included adult patients who underwent major hepatectomies at 12 international centers (2010-2020). After splitting the data into training and validation sets (70:30), models for PHLF and a CCI>40 were fit using logistic regression with a lasso penalty on the training cohort. The models were then evaluated on the validation data set. RESULTS: Among 2192 patients, 185 (8.4%) had clinically significant PHLF and 160 (7.3%) had a CCI>40. The PHLF model had an area under the curve (AUC) of 0.80, calibration slope of 0.95, and calibration-in-the-large of -0.09, while the CCI model had an AUC of 0.76, calibration slope of 0.88, and calibration-in-the-large of 0.02. When the models were provided only preoperative variables to predict PHLF and a CCI>40, this resulted in similar AUCs of 0.78 and 0.71, respectively. Both models were used to build 2 risk calculators with the option to include or exclude intraoperative variables ( PHLF Risk Calculator; CCI>40 Risk Calculator ). CONCLUSIONS: Using an international cohort of major hepatectomy patients, we used preoperative and intraoperative variables to develop and internally validate multivariable models to predict clinically significant PHLF and a CCI>40 with good discrimination and calibration.

A Machine Learning Approach to Predict Postoperative Pancreatic Fistula After Pancreaticoduodenectomy Using Only Preoperatively Known Data.

BACKGROUND: Clinically-relevant postoperative pancreatic fistula (CR-POPF) following pancreaticoduodenectomy (PD) is a major postoperative complication and the primary determinant of surgical outcomes. However, the majority of current risk calculators utilize intraoperative and postoperative variables, limiting their utility in the preoperative setting. Therefore, we aimed to develop a user-friendly risk calculator to predict CR-POPF following PD using state-of-the-art machine learning (ML) algorithms and only preoperatively known variables. METHODS: Adult patients undergoing elective PD for non-metastatic pancreatic cancer were identified from the ACS-NSQIP targeted pancreatectomy dataset (2014-2019). The primary endpoint was development of CR-POPF (grade B or C). Secondary endpoints included discharge to facility, 30-day mortality, and a composite of overall and significant complications. Four models (logistic regression, neural network, random forest, and XGBoost) were trained, validated and a user-friendly risk calculator was then developed. RESULTS: Of the 8666 patients who underwent elective PD, 13% (n = 1160) developed CR-POPF. XGBoost was the best performing model (AUC = 0.72), and the top five preoperative variables associated with CR-POPF were non-adenocarcinoma histology, lack of neoadjuvant chemotherapy, pancreatic duct size less than 3 mm, higher BMI, and higher preoperative serum creatinine. Model performance for 30-day mortality, discharge to a facility, and overall and significant complications ranged from AUC 0.62-0.78. CONCLUSIONS: In this study, we developed and validated an ML model using only preoperatively known variables to predict CR-POPF following PD. The risk calculator can be used in the preoperative setting to inform clinical decision-making and patient counseling.

Immediate Breast Reconstruction Using the Autologous Dermal Flap.

INTRODUCTION: Despite the development of breast-conserving surgery in breast cancer treatment, there still remain indications for total mastectomy. Since mastectomy has a significant negative impact on the patients' quality of life, breast reconstruction is increasingly popular. However, for patients with large ptotic breasts who do not choose tissue-based reconstruction techniques and prefer implant-based breast reconstruction, there is no single-stage breast reconstruction technique other than the classic technique using Acellular Dermal Matrix (ADM). METHODS: This study presents a novel technique for Nipple-Sparing Mastectomy (NSM) and Immediate Breast reconstruction (IBR) in 11 operations (in seven patients) whose treatment decision-making was based on NCCN guidelines. In this technique, the implant/tissue expander is covered by the pectoral muscle in the upper part and an autologous dermal flap in the lower part, replacing an ADM. The dermal flap is created from the de-epithelialized lower mastectomy flap in these large ptotic breasts. Maintaining the nipple-areola complex (NAC) is possible by re-implanting a free nipple split-thickness graft from the NAC of the ipsilateral breast prepared at the beginning of the operation. RESULTS: All seven patients had large ptotic breasts ranging from C cup to double D in size and grade 2 and higher breast ptosis. The mean BMI of the patients was 28 (range: 26-33). No major complications occurred postoperatively. There were three minor complications, all managed conservatively. Surgical indications were risk reduction surgery in three patients with BRCA mutations and therapeutic in the remaining patients (three multifocal invasive ductal carcinomas and one diffused ductal carcinoma in situ). None of the patients had a previous reduction mammoplasty as preparation for NSM, and all the patients underwent a single operation. No breast tissue remained under the NAC, which is ideal with the NSM technique. CONCLUSIONS: The proposed technique is excellent for implant-based IBR in patients with large ptotic breasts. It eliminates the use of ADM mesh and reduces the cost and postoperative complication rate associated with ADM. Furthermore, using a free nipple graft technique can eliminate the need for a preparatory mastopexy. This technique can also theoretically reduce the risk of recurrence or new primary breast cancer as there are no remaining ducts beneath the nipple-areola complex.

Conventional MRI-derived subchondral trabecular biomarkers and their association with knee cartilage volume loss as early as 1 year: a longitudinal analysis from Osteoarthritis Initiative.

OBJECTIVE: To study associations between MRI-derived subchondral trabecular biomarkers obtained from conventional MRI sequences and knee cartilage loss over 12 and 24 months, using the FNIH osteoarthritis (OA) biomarkers consortium. MATERIALS AND METHODS: Data of the 600 subjects in the FNIH OA biomarkers consortium (a nested case-control study within Osteoarthritis Initiative [OAI]) were extracted from the online database. Baseline knee MRI (intermediate-weighted (IW) sequences) were evaluated to determine conventional MRI-derived trabecular thickness (cTbTh) and bone-to-total ratio (cBV/TV). The measurements for medial and lateral volumes of cartilages using baseline, 12-, and 24-month knee MRI were extracted from the OAI database, and cartilage volume loss over 12 and 24 months of follow-up were determined using Relative Change Index. The association between conventional MRI-based subchondral trabecular biomarkers and cartilage volume loss were studied using logistic regression models, adjusted for relevant confounders including age, sex, body mass index (BMI), vitamin D use, Kellgren Lawrence grade (KLG), and tibiofemoral alignment. RESULTS: Higher medial cTbTh and cBV/TV at baseline were associated with increased odds of medial tibial cartilage volume loss over 12 months (ORs: 1.01 [1.00-1.02] and 1.24 [1.10-1.39] per 1-SD change) and 24 months (ORs: 1.01 [1.00-1.02] and 1.22 [1.08-1.37], per 1-SD change). No significant association was observed between medial subchondral trabecular biomarkers and lateral tibial or femoral (medial or lateral) cartilage volume loss over the first and second follow-up years. CONCLUSIONS: Conventional MRI-derived subchondral trabecular biomarkers (higher medial cTbTh and cBV/TV) may be associated with increased medial tibial cartilage volume loss as early as 1 year.

Association between Patellofemoral and medial Tibiofemoral compartment osteoarthritis progression: exploring the effect of body weight using longitudinal data from osteoarthritis initiative (OAI).

OBJECTIVES: To investigate the associations of medial and lateral patellofemoral osteoarthritis (PF-OA) at baseline with symptomatic and radiographic OA outcomes in the medial tibiofemoral compartment (MTFC) over 4 years, according to baseline overweight status. METHODS: Data and MRI images of 600 subjects in the FNIH-OA biomarkers consortium were used. Symptomatic worsening and radiographic progression of MTFC-OA were defined using Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain scores and MTFC joint space narrowing (JSN) from baseline to 4-year follow-up. Baseline MRIs were read to establish PF-OA diagnosis. The association between baseline regional PF-OA pattern and odds for MTFC-OA progression was evaluated using regression models (adjusted for relevant confounding covariates including body mass index (BMI), age, sex, PF alignment measurements, KL grade, and knee alignment). To evaluate the effect modifying role for overweight status, stratification analysis was performed (BMI ≥ 25 vs. < 25 kg/m2). RESULTS: At baseline, 340 (56.7%), 255 (42.5%), and 199 (33.2%) subjects had OA in the medial, lateral, and both PF compartments. Baseline medial PF-OA was associated with WOMAC pain score and MTFC JSN progression at 4 years (Adjusted OR:1.56[95%CI:1.09-2.23] and 1.59[1.11-2.28], respectively) but not lateral PF-OA. In stratification analysis, overweight status was found to be an effect modifier for medial PF-OA and WOMAC pain (OR in overweight vs. non-overweight subjects:1.65[1.13-2.42] vs. 0.50[0.12-1.82]) as well as MTFC-JSN progression (1.63[1.12-2.4] vs. 0.75[0.19-2.81]). CONCLUSIONS: In addition to the known confounding effect of BMI for PF-OA and MTFC-OA, the overweight status may also play an effect modifier role in the association between baseline medial PF-OA and MTFC-OA progression, which is amenable to secondary prevention.

Efficacy and safety of sulforaphane for treatment of mild to moderate depression in patients with history of cardiac interventions: A randomized, double-blind, placebo-controlled clinical trial.

AIM: Depression has been recognized as one of the disorders associated with cardiac interventions such as percutaneous coronary intervention (PCI) or coronary artery bypass graft surgery (CABG). In the present study, we evaluated the efficacy and safety of sulforaphane in treatment of depression induced by cardiac interventions. METHODS: After initial screening, 66 patients with previous history of at least one cardiac intervention and current mild to moderate depression were randomly assigned to two parallel groups receiving either sulforaphane (n = 33) or placebo (n = 33) for six successive weeks. Efficacy was assessed using the Hamilton Rating Scale for Depression (HAM-D) at baseline and week 2, 4, and 6. Safety of the treatments was checked during the trial period. RESULTS: Sixty participants completed the clinical trial (n = 30 in each group). Baseline demographic and clinical parameters were all similar among groups. Repeated measures analysis indicated that the sulforaphane group exhibited greater improvement in HAM-D scores throughout the trial (P < 0.001). Response to treatment (≥50% reduction in the HAM-D score) rate was higher in the sulforaphane group at trial endpoint (30% vs 6.67%, P = 0.042). Remission (HAM-D score ≤ 7) rate was also higher in the sulforaphane group; however, the difference was not significant (23.33% vs 3.33%, P = 0.052). Finally, no significant difference was observed between the two groups in terms of frequency of side effects. CONCLUSIONS: Sulforaphane could safely improve depressive symptoms induced by cardiac interventions. Further clinical trials with larger sample sizes and longer follow-up periods are warranted to confirm our results.

Resveratrol adjunct to methylphenidate improves symptoms of attention-deficit/hyperactivity disorder: a randomized, double-blinded, placebo-controlled clinical trial.

Current pharmacological approaches have failed to provide complete remission for patients with Attention-Deficit/Hyperactivity Disorder (ADHD). This study aimed to evaluate the efficacy and tolerability of resveratrol (that have been shown to have antioxidative, anti-inflammatory, and anti-apoptotic effects) as an adjunct to methylphenidate in pharmacologic treatment of ADHD. This 8-week, double-blinded, placebo-controlled trial randomized 66 participants to receive either 500 mg/day resveratrol or matched placebo in addition to methylphenidate. ADHD symptoms were evaluated in the patients using the Parent and Teacher versions of ADHD-Rating Scale (ADHD-RS) at three measurement points with time intervals of 4 weeks. Furthermore, the tolerability of the treatment strategies was systematically compared. Repeated measures analysis demonstrated a significant effect for time-treatment interaction on all three subscales of the Parent ADHD-RS during the trial period (total: p = 0.015; inattention: p = 0.032; hyperactivity/impulsivity: p = 0.036). Nevertheless, the effect for time-treatment interaction was not significant for the Teacher version of ADHD-RS (total: F = 0.81, df = 1.33, p = 0.401; inattention: F = 0.57, df = 1.37, p = 0.507; hyperactivity/impulsivity: F = 0.65, df = 1.34, p = 0.466). The frequencies of complications in the treatment groups were similar. Resveratrol administration for a duration of 8 weeks improved characteristic symptoms in patients with ADHD according to their parents. Further investigations containing larger sample sizes, longer supplementation periods, and dose-response evaluations are required to replicate these findings in ADHD children more confidently.

Activation of adenosine A2A receptor induced interleukin-23 mRNA expression in macrophages of ankylosing spondylitis patients.

BACKGROUND: Ankylosing spondylitis (AS) is an auto-inflammatory debilitating disorder with a complex pathogenesis. The adenosinergic pathway is an immunologic regulating pathway with a potential role in AS pathophysiology. In the present study, we have aimed to investigate the influence of A2A adenosine receptor (A2AAR) activation on tumor necrosis factor-α (TNF-α) and interleukin-23 (IL-23) expression and secretion by monocyte-generated macrophages of AS patients. METHODS: Whole-blood separated monocytes were extracted from 14 AS patients and 14 healthy controls. Macrophages were differentiated by macrophage colony-stimulating factor (M-CSF), and surface markers were confirmed by flow cytometer. Cells were treated with CGS-21680 as a known agonist of A2AAR. Analysis of ADORA2A, TNFA, and IL23A gene expression was performed by SYBR green real-time PCR. The concentration of secreted cytokines was also measured by ELISA kits. RESULTS: Based on our analysis, CGS-21680 significantly decreased TNF-α secretion by monocyte-derived macrophages of AS patients. Moreover, A2AAR agonist increased the IL23A mRNA expression level in monocyte-derived macrophages of AS patients considerably. Whereas, CGS-21680 did not have any influence on macrophages of healthy individuals. CONCLUSION: According to our results, it appears that A2AAR activation can increase IL-23 secretion by monocyte-derived macrophages of AS patients. Although the TNF-α reducing effect of A2AAR agonists can be a potential target in AS treatment, robust increasing of IL-23 should be considered as the undesirable effect of these agents.

Resveratrol Adjunct Therapy for Negative Symptoms in Patients With Stable Schizophrenia: A Double-Blind, Randomized Placebo-Controlled Trial.

BACKGROUND: Patients with schizophrenia can generally manifest a broad variety of primary negative symptoms. The current study aimed to assess the efficacy and tolerability of resveratrol add-on therapy in the treatment of negative symptoms in patients with stable schizophrenia. METHODS: In a randomized, double-blind, and placebo-controlled setting, schizophrenia patients were assigned to receive either 200 mg/d resveratrol or matched placebo in addition to a stable dose of risperidone for 8 weeks. Patients were assessed using the positive and negative syndrome scale, the extrapyramidal symptom rating scale, and Hamilton Depression Rating Scale over the trial period. The primary outcome was considered as the change in positive and negative subscale score from baseline to week 8 between the treatment arms. RESULTS: A total 52 patients completed the trial (26 in each arm). Baseline characteristics of both groups were statistically similar (P > .05). Despite the statistically similar behavior of positive symptoms between the groups across time (Greenhouse-Geisser corrected: F = 1.76, df = 1.88, P = .180), the resveratrol group demonstrated greater improvement in negative, general psychopathology, and total scores (Greenhouse-Geisser corrected: F = 12.25, df = 2.04, P < .001; F = 5.42, df = 1.56, P = .011; F = 7.64, df = 1.48, P = .003). HDRS scores and its changes, ESRS score, and frequency of other complications were not significantly different between resveratrol and placebo groups. CONCLUSION: Adding resveratrol to risperidone can exhibit remarkable efficacy and safety in terms of management of schizophrenia-related negative symptoms.

Application of muscle ultrasound for the evaluation of patients with amyotrophic lateral sclerosis: An observational cross-sectional study.

INTRODUCTION: We evaluated the association between muscle ultrasound, number of motor units, and clinical parameters, and assessed their utility for distinguishing amyotrophic lateral scleorisis (ALS) patients from healthy individuals. METHODS: Three muscle pairs (abductor pollicis brevis, abductor digiti minimi, and tibialis anterior) of 18 ALS patients and 18 controls underwent muscle ultrasound (echointensity and thickness) and assessment of motor unit number index (MUNIX). The clinical and functional status of participants were also assessed. RESULTS: Mean age of the patients was 53.8 ± 12.1 years, and score on the ALS Functional Rating Scale-Revised was 38.9 ± 4.1. Echointensity of all tested muscles of ALS participants was significantly higher than that of controls, but there was no significant difference in muscle thickness. Muscle echointensity correlated significantly with clinical and electrophysiological parameters. CONCLUSION: Echointensity of muscles was highly associated with clinical scales and MUNIX, confirming its relevance as an ancillary diagnostic test in ALS patients.

Exploring the etiopathogenesis of systemic lupus erythematosus: a genetic perspective.

Systemic lupus erythematosus (SLE) is an autoimmune multi-organ disorder that presents itself in a thousand ways. Its clinical course is extremely unpredictable, which makes diagnosis and treatment a challenge for clinicians. It appears that the clinical course of SLE is determined by genetic material in combination with environmental factors. In this article, we review recent findings on the pathogenesis of SLE from the perspective of genetics, focusing on defects in the clearance of apoptotic bodies and immune complexes, on alterations in the innate immune system response, and on impaired pathways in the adaptive immune system. Furthermore, the major histocompatibility complex (MHC) and non-MHC genes discovered during genome-wide association studies (GWASs) in SLE patients are also evaluated. In addition, the effect of these polymorphisms on the function of their related transcripts and their association with the clinical manifestations of SLE and its pathophysiology are explained. Finally, the association of genetic polymorphisms with clinical responses to common medications used in the treatment of SLE is also discussed.

White matter correlates of disease duration in patients with temporal lobe epilepsy: updated review of literature.

BACKGROUND: Medial temporal lobe epilepsy (mTLE) has been associated with widespread white mater (WM) alternations in addition to mesial temporal sclerosis (MTS). Herein, we aimed to investigate the correlation between disease duration and WM structural abnormalities in mTLE using diffusion MRI (DMRI) connectometry approach. METHOD: DMRI connectometry was conducted on 24 patients with mTLE. A multiple regression model was used to investigate white matter tracts with microstructural correlates to disease duration, controlling for age and sex. DMRI data were processed in the MNI space using q-space diffeomorphic reconstruction to obtain the spin distribution function (SDF). The SDF values were converted to quantitative anisotropy (QA) and used in further analyses. RESULTS: Connectometry analysis identified impaired white matter QA of the following fibers to be correlated with disease duration: bilateral retrosplenial cingulum, bilateral fornix, right inferior longitudinal fasciculus (ILF), and genu of corpus callosum (CC) (FDR = 0.009). CONCLUSION: Our results were obtained from DMRI connectometry, which indicates the connectivity and the level of diffusion in nerve fibers rather just the direction of diffusion. Compared to previous studies investigating the correlation between duration of epilepsy and white matter integrity in mTLE patients, we detected broader and somewhat different associations in midline structures and component of limbic system. However, further studies with larger sample sizes are required to elucidate previous and current results.

HBV reactivation in rheumatic diseases patients under therapy: A meta-analysis.

BACKGROUND: Hepatitis B is one of the most common infectious diseases worldwide. In patients undergoing immunosuppressive therapy such as rheumatic diseases, reactivation of hepatitis B virus (HBV) is considered clinically important. This systematic review and meta-analysis were performed to determine the prevalence rate of HBV reactivation in rheumatic patients from different parts of the world. METHODS: The authors performed a systematic literature review from several reliable databases including Scopus, ISI Web of Science and PubMed. Furthermore, the keywords of this research were "Hepatitis B virus", "Rheumatic diseases", "HBV reactivation", "Anti-TNF", "DMARDs" and "Biologic agents". RESULTS: The authors selected 30 studies out of 983 for the present review. The overall estimation of the prevalence of HBV reactivation was 1.4 (95% confidence interval (CI): 1.3-1.6). Also, the heterogeneity in estimating the pooled prevalence among the studies was shown; Cochran Q test, P < 0.001, I2 = 99.9%. It should be noted that max and min reactivation rate of HBV were in Italy and France respectively. CONCLUSIONS: Rheumatic disease patients with resolved hepatitis B should be tightly monitored for possible HBV reactivation by elevation of liver enzymes and HBV DNA levels.

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical outcomes. However, it is unknown whether they are superior to traditional statistical methods such as logistic regression (LR). This study aimed to perform a systematic review and meta-analysis to compare the performance of ML vs LR models in predicting postoperative outcomes for patients undergoing gastrointestinal (GI) surgery. METHODS: A systematic search of Embase, MEDLINE, Cochrane, Web of Science, and Google Scholar was performed through December 2022. The primary outcome was the discriminatory performance of ML vs LR models as measured by the area under the receiver operating characteristic curve (AUC). A meta-analysis was then performed using a random effects model. RESULTS: A total of 62 LR models and 143 ML models were included across 38 studies. On average, the best-performing ML models had a significantly higher AUC than the LR models (ΔAUC, 0.07; 95% CI, 0.04-0.09; P < .001). Similarly, on average, the best-performing ML models had a significantly higher logit (AUC) than the LR models (Δlogit [AUC], 0.41; 95% CI, 0.23-0.58; P < .001). Approximately half of studies (44%) were found to have a low risk of bias. Upon a subset analysis of only low-risk studies, the difference in logit (AUC) remained significant (ML vs LR, Δlogit [AUC], 0.40; 95% CI, 0.14-0.66; P = .009). CONCLUSION: We found a significant improvement in discriminatory ability when using ML over LR algorithms in predicting postoperative outcomes for patients undergoing GI surgery. Subsequent efforts should establish standardized protocols for both developing and reporting studies using ML models and explore the practical implementation of these models.

Inadequate Lymph Node Yield: An Inadequate Indication for Adjuvant Chemotherapy in Stage II Colon Cancer.

Background: Optimal therapy for stage II colon cancer remains unclear, and national guidelines recommend "consideration" of adjuvant chemotherapy (ACT) in the presence of high-risk features, including inadequate lymph node yield (LNY, <12 nodes). This study aims to determine whether the survival benefit of ACT in stage II disease varies based on the adequacy of LNY. Methods: We used the National Cancer Database (NCDB) to identify adults who underwent resection for a single primary T3 or T4 colon cancer between 2006 and 2018. Multivariable logistic regression tested for associations between ACT and prespecified demographic and clinical characteristics, including the adequacy of LNY. We used Cox proportional hazards models to assess overall survival and restricted cubic splines to estimate the optimal LNY threshold to dichotomize patients based on overall survival. Results: Unadjusted 5- and 10-year survival rates were 84% and 75%, respectively, among patients who received ACT and 70% and 50% among patients who did not (log-rank P < 0.01). Inadequate LNY was independently associated with both receipt of ACT (odds ratios, 1.50; P < 0.01) and decreased overall survival [hazard ratio (HR), 1.56; P < 0.01]. ACT was independently associated with improved survival (HR, 0.67; P < 0.01); this effect size did not change based on the adequacy of LNY (interaction P = 0.41). Results were robust to re-analysis with our cohort-optimized threshold of 18 lymph nodes. Conclusions: Consistent with contemporary guidelines, patients with inadequate LNY are more likely to receive ACT. LNY adequacy is an independent prognostic factor but, in isolation, should not dictate whether patients receive ACT.