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.

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.

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 ).

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.

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.

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.

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.

Prototypic P2X7 Receptor Agonist, BzATP, Induced the Expression of Unfolded Protein Response Genes in Human M1 Macrophages.

Purinergic receptors stimulation by adenosine triphosphate (ATP) contributes significantly to macrophage activation, and also macrophage cell death. Upon the macrophage activation, the protein load of the endoplasmic reticulum is increased which is resulted in the activation of unfolded protein response (UPR). In the current study, we aimed to evaluate the connection between prototypic P2X7 receptor agonist, extracellular 2'(3')-O-(4-Benzoylbenzoyl)-ATP (BzATP), and the UPR pathway in macrophages. The monocyte-derived macrophages from blood samples of 14 healthy volunteers were skewed toward M1 macrophages after incubation with LPS and IFN-γ. M1 macrophages were treated with 200 µM BzATP. The expression levels of UPR genes, including CHOP, HERP, GADD34, XBP1, and ATF6 in macrophages before and after treatment were measured using real-time polymerase chain reaction. The results demonstrated that the expression of CHOP, HERP, and ATF6 is significantly decreased and the expression level of GADD34 and XBP1 is significantly increased after M1 polarization. BzATP not only significantly increased the expression levels of CHOP, GADD34, ATF6, and HERP but also significantly decreases the XBP1 expression level in M1 macrophages. The present study showed that BzATP induces cellular stress in M1 macrophages by elevating the expression levels of UPR genes including CHOP, GADD34, ATF6, and reducing cell viability.

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.

The Transition of Mild Cognitive Impairment Over Time: An AV45- and FDG-PET Study of Reversion and Conversion Phenomena.

BACKGROUND: Mild cognitive impairment (MCI) is a state between normal cognition and dementia. However, MCI diagnosis does not necessarily guarantee the progression to dementia. Since no previous study investigated brain positron emission tomography (PET) imaging of MCI-- to-normal reversion, we provided PET imaging of MCI- to-normal reversion using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. METHODS: We applied comprehensive neuropsychological criteria (NP criteria), consisting of memory, language, and attention/executive function domains, to include patients with a baseline diagnosis of MCI (n=613). According to the criteria, the year 1 status of the patients was categorized into three groups (reversion: n=105, stable MCI: n=422, conversion: n=86). Demographic, neuropsychological, genetic, CSF, and cognition biomarker variables were compared between the groups. Additionally, after adjustment for confounding variables, the deposition pattern of amyloid-ß and cerebral glucose metabolism were compared between three groups via AV45- and FDG-PET modalities, respectively. RESULTS: MCI reversion rate was 17.1% during one year of follow-up. The reversion group had the lowest frequency of APOE ε4+ subjects, the highest CSF level of amyloid-ß, and the lowest CSF levels of t-tau and p-tau. Neuropsychological assessments were also suggestive of better cognitive performance in the reversion group. Patients with reversion to normal state had higher glucose metabolism in bilateral angular and left middle/inferior temporal gyri, when compared to those with stable MCI state. Meanwhile, lower amyloid-ß deposition at baseline was observed in the frontal and parietal regions of the reverted subjects. On the other hand, the conversion group showed lower cerebral glucose metabolism in bilateral angular and bilateral middle/inferior temporal gyri compared to the stable MCI group, whereas the amyloid-ß accumulation was similar between the groups. CONCLUSION: This longitudinal study provides novel insight regarding the application of PET imaging in predicting MCI transition over time.

White matter changes in drug-naïve Parkinson's disease patients with impulse control & probable REM sleep behavior disorders.

BACKGROUND: According to epidemiological studies, Parkinson's disease (PD) patients with probable REM sleep behavior disorder (pRBD) are more prone to develop impulse control disorders (ICDs), which is shown to be present in drug-naïve PD patients, and vice versa. OBJECTIVES: To investigate white-matter integrity differences, with and without comorbid pRBD and ICDs. METHODS: 149 de-novo PD patients and 30 age- and gender-matched controls from the Parkinson's Progression Markers Initiative were studied. PD subjects were categorized into four groups with and without these comorbidities. We investigated the white matter integrity differences between these groups. RESULTS: PDs with only ICDs manifested greater fractional anisotropy (FA) and lower mean diffusivity (MD) in ipsilateral cerebellar connections when compared to controls and to Parkinson's with both comorbid disorders. In contrast, significantly lower FA and higher MD in the ipsilateral fornix-stria-terminalis was observed in PDs with only pRBD compared to controls and to PDs without either comorbid disorder. Also, PDs with only pRBD manifested greater FA in contralateral putamen when compared to controls. CONCLUSIONS: Our results suggest the presence of an underlying neural network in PDs with ICDs, particularly involving cerebellar connections, which makes the subjects susceptible to pRBD. Lower white-matter integrity in the fornix of PDs with only pRBD suggests a neuropathological pathway specific to sleep behavior disorder, independent of impulse control disorders. Greater white-matter integrity observed in PDs without comorbid ICDs, regardless of their comorbid pRBD status, might reflect compensatory mechanisms. Targeted therapies for this particular neuropathology may help prevent these comorbidities.

Melatonin improves learning and memory of mice with chronic social isolation stress via an interaction between microglia polarization and BDNF/TrkB/CREB signaling pathway.

Chronic social isolation stress (SIS) could impair learning and memory-related behaviors. Herein, we investigated the efficacy of Melatonin in treatment of memory despair and also its possible underlying mechanism of action in an animal model of SIS. For this purpose, mice were allocated to two opposing conditions, including social condition (SC) and isolated condition (IC), for five weeks. The study consisted of three groups, including saline-treated SC, saline-treated IC, Melatonin-treated IC (10 mg/kg/day for five successive days). At the end of the isolation period, mice underwent three neurobehavioral tests: passive avoidance (PA), Morris water maze (MWM), and Y maze (YM) tests. Hippocampus samples were obtained and the expressions of BDNF, TrkB, phosphorylated TrkB (pTrkB), CREB, phosphorylated CREB (pCREB), as well as M1 and M2 microglia were assessed. Interpreting the behavioral tests, we found that isolated mice showed lower freezing response in the PA test, lower number of novel arm visits in the YM, and higher escape latency and less time spent in the target quadrant in the MWM, when compared to SC rodents (P values < 0.001). The isolated group had higher M1/M2 relative ratio (P < 0.001), as well as lower concentrations of BDNF mRNA (p < 0.001) and protein (P < 0.001), TrkB protein (P = 0.035), CREB mRNA (P < 0.001) and protein (P = 0.012), pTrkB (P < 0.001), and pCREB (P = 0.035). However, Melatonin relatively reversed the behavioral, cellular, and molecular effects of SIS. Taken together, melatonin therapy could alleviate memory impairment through switching microglial polarization from M1 to M2 phenotype along with altered expression and function in the BDNF/TrkB/CREB signaling pathway.

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.

Biological Features of Reversion from Mild Cognitive Impairment to Normal Cognition: A Study of Cerebrospinal Fluid Markers and Brain Volume.

BACKGROUND: Mild cognitive impairment (MCI) is a transitional condition between normal cognition and dementia. Although a significant proportion of the population with MCI experience reversion to normal cognition, it is still poorly understood. OBJECTIVE: This study was designed to extend the present evidence regarding the difference between stable and reverting MCI by including whole brain atrophy measures as possible parameters involved. METHODS: 405 patients diagnosed with MCI at baseline were selected. After one-year follow-up period, 337 patients (83.2%) were categorized as stable MCI and 68 patients (16.8%) reverted to cognitively normal status (reversion group). Several baseline biomarkers including cerebrospinal fluid (CSF) biomarkers of AD, including Aß42, t-tau, and p-tau and MRI-based atrophy measurements were compared. RESULTS: Participants with stable MCI demonstrated greater brain atrophy as well as lower Aß and higher tau proteins in the CSF. The atrophy rate was found to be associated with CSF biomarkers merely in the stable group, after adjustment for confounding variables. CONCLUSION: These findings provide novel evidence regarding the biological perspective of the reversion phenomenon in individuals with MCI.

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.

The Association Between REM Sleep Behavior Disorder and Autonomic Dysfunction in Parkinson's Disease.

BACKGROUND: REM behavior disorder (RBD) can occur in the context of neurodegenerative alpha-synucleinopathies, such as Parkinson's disease (PD). PD patients with RBD (PD-pRBD) represent more severe symptoms and signs compared with those without RBD (PD-nRBD). On another note, autonomic dysfunction in PD patients is categorized as one of the most prominent non-motor symptoms and has been lately the field of interest in research. OBJECTIVE: In the current study, we longitudinally studied autonomic dysfunction in PD-pRBD and PD-nRBD groups. METHOD: This study was conducted on 420 drug-naïve PD patients selected from the Parkinson's Progression Markers Initiative database. The RBD Screening Questionnaire was used to define the presence of probable RBD. SCOPA-AUT was used to assess autonomic dysfunction. Additionally, dopamine transporter deficits on [123I] FP-CIT SPECT imaging was performed for all of the patients. RESULTS: Out of 420 PD patients, 158 individuals (37.6%) were considered to have probable RBD (PD-pRBD) and others without RBD (PD-nRBD). Except for pupillomotor function, all the autonomic symptoms were significantly more severe in PD-pRBD group. In PD-nRBD group, caudate striatal binding ratio was negatively correlated with SCOPA-AUT scores, while no significant correlation was observed in PD-pRBD group. Finally, there was a significant difference considering the longitudinal changes of SCOPA-AUT total between PD-pRBD and PD-nRBD groups, suggesting a more severe autonomic decline in PD-pRBD patients. CONCLUSION: Our results indicate that PD-pRBD patients have more severe autonomic dysfunction. These results support the theory that PD patients can be categorized based on the clinical presentation, possibly representing differences in the disease pathophysiology.

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.