Machine learning for predicting cognitive decline within five years in Parkinson's disease: Comparing cognitive assessment scales with DAT SPECT and clinical biomarkers.

OBJECTIVE: Parkinson's disease (PD) is an age-related neurodegenerative condition characterized mostly by motor symptoms. Although a wide range of non-motor symptoms (NMS) are frequently experienced by PD patients. One of the important and common NMS is cognitive impairment, which is measured using different cognitive scales. Monitoring cognitive impairment and its decline in PD is essential for patient care and management. In this study, our goal is to identify the most effective cognitive scale in predicting cognitive decline over a 5-year timeframe initializing clinical biomarkers and DAT SPECT. METHODS: Machine Learning has previously shown superior performance in image and clinical data classification and detection. In this study, we propose to use machine learning with different types of data, such as DAT SPECT and clinical biomarkers, to predict PD-CD based on various cognitive scales. We collected 330 DAT SPECT images and their clinical data in baseline, years 2,3,4, and 5 from Parkinson's Progression Markers Initiative (PPMI). We then designed a 3D Autoencoder to extract deep radiomic features (DF) from DAT SPECT images, and we then concatenated it with 17 clinical features (CF) to predict cognitive decline based on Montreal Cognitive Assessment (MoCA) and The Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS-I). RESULTS: The utilization of MoCA as a cognitive decline scale yielded better performance in various years compared to MDS-UPDRS-I. In year 4, the application of the deep radiomic feature resulted in the highest achievement, with a cross-validation AUC of 89.28, utilizing the gradient boosting classifier. For the MDS-UPDRS-I scale, the highest achievement was obtained by utilizing the deep radiomic feature, resulting in a cross-validation AUC of 81.34 with the random forest classifier. CONCLUSIONS: The study findings indicate that the MoCA scale may be a more effective predictor of cognitive decline within 5 years compared to MDS-UPDRS-I. Furthermore, deep radiomic features had better performance compared to sole clinical biomarkers or clinical and deep radiomic combined. These results suggest that using the MoCA score and deep radiomic features extracted from DAT SPECT could be a promising approach for identifying individuals at risk for cognitive decline in four years. Future research is needed to validate these findings and explore their utility in clinical practice.

World addiction medicine reports: formation of the International Society of Addiction Medicine Global Expert Network (ISAM-GEN) and its global surveys.

Addiction medicine is a dynamic field that encompasses clinical practice and research in the context of societal, economic, and cultural factors at the local, national, regional, and global levels. This field has evolved profoundly during the past decades in terms of scopes and activities with the contribution of addiction medicine scientists and professionals globally. The dynamic nature of drug addiction at the global level has resulted in a crucial need for developing an international collaborative network of addiction societies, treatment programs and experts to monitor emerging national, regional, and global concerns. This protocol paper presents methodological details of running longitudinal surveys at national, regional, and global levels through the Global Expert Network of the International Society of Addiction Medicine (ISAM-GEN). The initial formation of the network with a recruitment phase and a round of snowball sampling provided 354 experts from 78 countries across the globe. In addition, 43 national/regional addiction societies/associations are also included in the database. The surveys will be developed by global experts in addiction medicine on treatment services, service coverage, co-occurring disorders, treatment standards and barriers, emerging addictions and/or dynamic changes in treatment needs worldwide. Survey participants in categories of (1) addiction societies/associations, (2) addiction treatment programs, (3) addiction experts/clinicians and (4) related stakeholders will respond to these global longitudinal surveys. The results will be analyzed and cross-examined with available data and peer-reviewed for publication.

Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review.

Importance: In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers. Objective: To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts. Evidence Review: The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders. Findings: There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes. Conclusions and Relevance: Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.

PerPsych: An iPadOS-based open-source neuropsychological software for time perception assessment.

Time perception is an important aspect of cognitive function that can be affected by mental illness and brain disease. Neuropsychological tests often assess time perception using computer displays, but smartphone or tablet software may offer some advantages. In this study, we present PerPsych, an open-source, iPadOS-based neuropsychological tool for testing time perception. PerPsych has the following features:•It is designed natively for iPadOS, using the low-level Metal interface to access the graphics processing unit for high-timing performance.•It allows researchers to conduct studies on time perception in individuals with cognitive impairment using a simple and user-friendly interface.•It supports various experimental paradigms and parameters for measuring time perception, such as duration estimation, production, and reproduction.

Prediction of Cognitive Decline in Parkinson's Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems.

BACKGROUND: We aimed to predict Montreal Cognitive Assessment (MoCA) scores in Parkinson's disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and clinical (CF) features at year 0 (baseline) applied to hybrid machine learning systems (HMLSs). METHODS: 297 patients were selected from the Parkinson's Progressive Marker Initiative (PPMI) database. The standardized SERA radiomics software and a 3D encoder were employed to extract RFs and DFs from single-photon emission computed tomography (DAT-SPECT) images, respectively. The patients with MoCA scores over 26 were indicated as normal; otherwise, scores under 26 were indicated as abnormal. Moreover, we applied different combinations of feature sets to HMLSs, including the Analysis of Variance (ANOVA) feature selection, which was linked with eight classifiers, including Multi-Layer Perceptron (MLP), K-Neighbors Classifier (KNN), Extra Trees Classifier (ETC), and others. We employed 80% of the patients to select the best model in a 5-fold cross-validation process, and the remaining 20% were employed for hold-out testing. RESULTS: For the sole usage of RFs and DFs, ANOVA and MLP resulted in averaged accuracies of 59 ± 3% and 65 ± 4% for 5-fold cross-validation, respectively, with hold-out testing accuracies of 59 ± 1% and 56 ± 2%, respectively. For sole CFs, a higher performance of 77 ± 8% for 5-fold cross-validation and a hold-out testing performance of 82 + 2% were obtained from ANOVA and ETC. RF+DF obtained a performance of 64 ± 7%, with a hold-out testing performance of 59 ± 2% through ANOVA and XGBC. Usage of CF+RF, CF+DF, and RF+DF+CF enabled the highest averaged accuracies of 78 ± 7%, 78 ± 9%, and 76 ± 8% for 5-fold cross-validation, and hold-out testing accuracies of 81 ± 2%, 82 ± 2%, and 83 ± 4%, respectively. CONCLUSIONS: We demonstrated that CFs vitally contribute to predictive performance, and combining them with appropriate imaging features and HMLSs can result in the best prediction performance.

The Antimicrobial and Healing Effect of Scrophularia striata Boiss Hydroalcoholic Extract on First- and Second-Grade Pressure Wounds in Patients with Brain and Spinal Cord Injury: A Randomized Clinical Trial.

Materials and Methods: This double-blind clinical trial study was performed on grade 1 and 2 pressure wounds in 120 patients with cerebral-spinal cord lesions. The patients were randomly divided into four groups (n = 30). Topical treatments in all groups were performed twice a day. These groups included experiment 1 (SHE + phenytoin), experiment 2 (SHE + SHE), control (phenytoin + phenytoin), and placebo (eucerin + phenytoin). After evaluating the effect of SHE on wound healing, its antibacterial activity was determined by the standard agar well diffusion method. Results: Patients in each group in this study did not significantly differ in demographic and clinical variables. Complete wound healing by the 10th day of the intervention occurred in 63%, 100%, and 27% of patients in experimental 1, experimental 2, and control groups, respectively. In contrast, the placebo group had no complete wound healing until the 10th day. Topical application of SHE, twice a day in the experimental 2 groups, had a higher potency to heal wounds and reduce the duration of complete wound healing in patients compared with other groups. Conclusion: SHE, as a novel treatment option, has good potential to accelerate the healing of first- and second-degree pressure wounds in patients with brain-spinal cord injuries.

Nanocurcumin Improves Lipid Status, Oxidative Stress, and Function of the Liver in Aluminium Phosphide-Induced Toxicity: Cellular and Molecular Mechanisms.

Background: The present study aimed to evaluate the effect of nanocurcumin and curcumin on liver transaminases, lipid profile, oxidant and antioxidant system, and pathophysiological changes in aluminium phosphide (ALP) induced hepatoxicity. Material and Methods. In this experimental study, thirty-six male Wistar rats were randomly divided into six groups curcumin (Cur), nanocurcumin (Nanocur), ALP, ALP+Cur, and ALP+Nanocur. All treatments were performed by oral gavage for seven days. After treatment, animals were sacrificed, and liver and blood samples were taken. Serum levels of aspartate aminotransferase (AST), alanine transaminase (ALT), alkaline phosphatase (AP), total bilirubin, cholesterol, triglyceride, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and very-low-density lipoprotein (VLDL) were measured by photometric methods. Total antioxidant capacity (TAC) and malondialdehyde (MDA) as parameters of oxidative stress and mRNA expression of the nonenzyme protein including Sirtuin 1 (STR1), Forkhead box protein O1 (FOXO1) and protein O3 (FOXO3), catalase (CAT), and glutathione peroxidase (GPX) as the enzyme protein in homogenized tissues have been investigated. A histologist analyzed liver tissue sections after staining with hematoxylin-eosin. Results: In the aluminium phosphide group, there was a significant increase in MDA, ALT, AST, and AP and total bilirubin, cholesterol, triglyceride, LDL, and VLDL; AST, ALT, total bilirubin, LDL, VLDL, cholesterol, and MDA were significantly decreased; and HDL and TAC were significantly increased compared to ALP (P < 0.05). In the ALP+Nanocur group, ALT, AST, ALP, total bilirubin, cholesterol, LDL, VLDL, triglyceride, and MDA were significantly decreased and HDL and TAC were increased significantly (P < 0.05). The effect of nanocurcumin on controlling serum levels of LDL, VLDL, triglyceride, and MDA in ALP-poisoned rats was significantly more than curcumin (P < 0.05). The ALP group had significant changes in genes SIRT1, FOXO1a, FOXO3a, CAT, and GPX compared to healthy controls (P < 0.05). Nanocurcumin mice expressed more SIRT1, FOXO1a, CAT, and GPX genes than controls, and curcumin-treated mice expressed more SIRT1 and FOXO1a genes (P < 0.05). Histopathological findings also indicated a more significant protective effect of nanocurcumin relative to curcumin against ALP-induced hepatotoxicity. Conclusion: Nanocurcumin significantly protects the liver against aluminum phosphide toxicity. It is suggested that nanocurcumin-based drugs be developed to reduce the toxic effects of ALP in poisoned patients.

Effect of specific training course for competency in professional oral hygiene care in the intensive care unit: a quasi-experimental study for developing a standardized learning curve.

BACKGROUND: The development of evidence-based training standards can help improve the quality of educational programs for novice intensive care unit (ICU) nurses. This study was conducted to assess the application of a training course on competency development of nurses in relation to oral hygiene care in ICU patients and to develop a checklist for evaluating the competence performance. In addition, to achieve a certain level of oral hygiene competence, as well as to assess the relative importance of predicting factors and learning competency patterns in oral hygiene care, we used standard learning curve. METHODS: This quasi-experimental study with time series design was conducted on newly registered ICU nurses of a teaching hospital affiliated with Tehran University of Medical Sciences, Iran, between 2016 and 2018. In the first phase of this study, we designed a checklist to assess nurses' professional competence in oral hygiene care in three stages: before, during, and after care. Then, in the second phase, the level of competence of nurses in repeated times of oral hygiene care was determined based on checklist items and recorded in the learning curve. RESULTS: The greatest increase of oral hygiene care competency due to repetition was observed in the first and fourth times of repetition in comparison to the subsequent and previous steps. In the linear regression model, demographic variables predicted 12-19% of changes related to skill scores in repetitions. CONCLUSION: According to the learning curve, newly registered ICU nurses can reach an acceptable competency after 6 repetitions of oral hygiene care.

Incidence and Risk Factors of Ventilator-Associated Pneumonia among Patients with Delirium in the Intensive Care Unit: A Prospective Observational Study.

INTRODUCTION: The incidence and risk factors for ventilator-related pneumonia (VAP) in patients with delirium are deficient, and there is a lack of in-depth knowledge of the impact of VAP on outcomes in this population. We investigated the incidence, risk factors, and outcomes of VAP in patients with delirium. MATERIALS AND METHODS: This prospective observational study was performed in a surgical ICU at Be'sat Hospital in Hamadan, Iran, between 2018 and 2019. A total of 108 patients with delirium were identified using the Confusion Assessment Method (CAM) for the ICU and Intensive Care Delirium Screening Checklist (ICDSC) and enrolled in this study. The association between VAP and delirium, risk factors, and outcomes (ICU length of stay and ICU mortality) for VAP were investigated using the Cox proportional hazards model and logistic and simple linear regression analyses with a 95% confidence interval. RESULTS: Of 108 delirium patients, 86 patients (79.6%) underwent mechanical ventilation (MV) and 16 patients (18.6%) experienced VAP during ICU stay. The median onset of VAP was 6.5 (IQR 4.2-7.7) days after intubation. Delirium patients with VAP stayed longer in the ICU (21.68 ± 4.26 vs.12.93 ± 1.71, P < 0.001) and also had higher ICU mortality (31.25% vs. 0%, P < 0.001) than subjects without VAP. According to multivariate cox regression, the expected HR for VAP was 53.5% lower for patients with early-onset delirium than in patients with late-onset delirium (HR: 0.465, 95% CI: 0.241-0.894, P=0.022). However, the expected hazard for VAP was 1.854 times and 4.604 times higher in patients with longer ICU stay (HR: 1.854, 95% CI: 1.689-3.059, P=0.032) and in patients with a prolonged MV duration (HR: 4.604, 95%CI: 1.567-6.708, P=0.023). CONCLUSION: According to the results, there seems to be an inverse relationship between early onset of delirium and VAP. This finding cannot be conclusively cited, and more studies in this filed should be conducted with a larger sample size. Furthermore, VAP in delirium patients is associated with increases in poor outcomes (higher ICU mortality) and the use of medical resources (longer stay in the ICU and MV duration).

How COVID-19 can cause autonomic dysfunctions and postural orthostatic syndrome? A Review of mechanisms and evidence.

Coronavirus disease 2019 (COVID-19) is a viral disease spread by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Because the recent pandemic has resulted in significant morbidity and mortality, understanding various aspects of this disease has become critical. SARS-CoV-2 can affect a variety of organs and systems in the body. The autonomic nervous system plays an important role in regulating body functions, and its dysfunction can cause a great deal of discomfort for patients. In this study, we focused on the effect of COVID-19 on the autonomic system and syndromes associated with it, such as postural orthostatic syndrome (POTS).

Hazard Ratio of 90-Day Mortality in ICU Patients with Abdominal Injuries Compared with Head Injuries.

BACKGROUND: Despite advances in the treatment of abdominal injuries in patients with trauma, it remains a major public health problem worldwide. Evaluation of hazard ratio (HR) of 90-day mortality in intensive care unit (ICU) patients with abdominal injuries compare with head injuries in trauma patients and non-trauma surgical ICU patients. METHODS: This single-center, prospective cohort study was conducted on 400 patients admitted to the ICU between 2018 and 2019 due to trauma or surgery in Hamadan, Iran. The main outcome was mortality at 90-day after ICU admission. Cox proportional hazards models were used to determine the HR and 95% confidence interval (CI) for 90-day mortality. RESULTS: The 90-day mortality was 21.9% in abdominal injuries patients. According to multivariate Cox regression, the expected hazard mortality was 2.758 times higher in patients with abdominal injuries compared to non-trauma patients (HR: 2.758, 95% CI: 1.077-7.063, P=0.034). About more than 50% of all deaths in the abdominal and head trauma groups occurred within 20 days after admission. Mean time to death was 27.85±20.1, 30.27±18.22 and 31.43±26.24 days for abdominal-trauma, surgical-ICU, and head-trauma groups, respectively. CONCLUSION: Difficulty in accurate diagnosis due to the complex physiological variability of abdominal trauma, less obvious clinical symptoms in blunt abdominal injuries, multi-organ dysfunction in abdominal injuries, failure to provide timely acute care, as well as different treatment methods all account for the high 90-day mortality rate in abdominal-trauma patients. Therefore, these patients need a multidisciplinary team to care for them both in the ICU and afterwards in the general ward.