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Kamran Baveicy,1 Shayan Mostafaei,2,3 Mitra Darbandi,4 Behrooz Hamzeh,4,5 Farid Najafi,4,6 Yahya Pasdar4,5 1Student Research Committee, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran; 2Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran; 3Epidemiology and Biostatistics Unit, Rheumatology Research Center, Tehran University of Medical Sciences, Tehran, Iran; 4Research Center for Environmental Determinants of Health (RCEDH), Health Institute, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran; 5Social Development and Health Promotion Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran; 6Cardiovascular Research Center, Kermanshah University of Medical Sciences, Kermanshah, IranCorrespondence: Yahya Pasdar Tel +98 83 38262005Fax +98 83 38263048Email yahya.pasdar@kums.ac.irBackground: The use of anthropometric indices is one of the new and low-cost diagnostic methods of metabolic syndrome (MetS). The present study aimed to determine optimal cutoff points for the visceral adiposity index (VAI), body roundness index (BRI), and a body shape index (ABSI) in the prediction of MetS.Methods: This cross-sectional study was performed on 10,000 individuals aged from 35 to 65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort study, in the west region of Iran, in 2019. MetS was defined according to International Diabetes Federation (IDF) criteria. The receiver operating characteristic (ROC) curve analysis was used to assess predictive anthropometric indices and determine optimal cutoff values.Results: The optimal cutoff points for VAI were 4.11 (AUC: 0.82; 95% CI: 0.81– 0.84) in men and 4.28 (AUC: 0.86; 95% CI: 0.85– 0.87) in women to prediction of MetS. The optimal cutoff points for BRI were 4.75 (AUC: 0.75; 95% CI: 0.74– 0.77) in men and 6.17 (AUC: 0.62; 95% CI: 0.61– 0.64) in women to prediction of MetS. The optimal cutoff points for ABSI were 0.12 (AUC: 0.49; 95% CI: 0.47– 0.51) in men and 0.13 (AUC: 0.49; 95% CI: 0.47– 0.51) in women to prediction of MetS. The risk of MetS in men and women with a VAI higher than the optimal cutoff point was, respectively, 9.82 and 11.44 times higher than that in those with a VAI lower than the cutoff point.Conclusion: Although VAI might not be very cost-beneficial compared to IDF, our study showed VAI is a better predictor of MetS than BRI in adults. ABSI was not a suitable predictor for MetS.Keywords: metabolic syndrome, body shape index, body roundness index, visceral adiposity index, ROC curve analysis

Background and Aim: Rheumatoid arthritis (RA) is an autoimmune disease. It seems that the function of regulatory T cells (Tregs) is compromised in RA. Foxp3 is a critical transcription factor of these cells. The aim of this study was to determine the relationship of vitamin D plasma level with Foxp3 gene expression in the patients with RA. Material and Methods: 18 untreated RA patients and 41 healthy people participated in this study. Plasma levels of vitamin D were measured by competitive ELISA method. Foxp3 gene expression was also determined by using realtime PCR technique. Results: The expression of Foxp3 gene was significantly lower in RA patients compared to that in the healthy controls (p

Diabetes mellitus type 2 (T2D) is associated with accelerated biological aging and the increased risk of onset of other age-related diseases. Epigenetic changes in DNA methylation levels have been found to serve as reliable biomarkers for biological aging. This study explores the relationship between various epigenetic biomarkers of aging and diabetes risk using longitudinal data. Data from the Swedish Adoption/Twin Study of Aging (SATSA) was collected from 1984 to 2014 and included 536 individuals with at least one epigenetic measurement. The following epigenetic biomarkers of aging were employed: DNAm PAI-1, DNAmTL, DunedinPACE, PCHorvath1, PCHorvath2, PCHannum, PCPhenoAge, and PCGrimAge. Firstly, longitudinal analysis of biomarker trajectories was done. Secondly, linear correlations between the biomarkers and time to diabetes were studied within individuals developing diabetes. Thirdly, Cox proportional hazards (PH) models were used to assess the associations between these biomarkers and time of diabetes diagnosis, with adjustments for chronological age, sex, education, smoking, blood glucose, and BMI. The longitudinal trajectories of the biomarkers revealed differences between individuals with and without diabetes. Smoothened average curves for DunedinPACE and DNAm PAI-1 were higher for individuals with diabetes around the age 60-70, compared to controls. Likewise, DunedinPACE and DNAm PAI-1 were higher closer to diabetes onset. However, no significant associations were found between the epigenetic biomarkers of aging and risk of diabetes in Cox PH models. Our findings suggest the potential value of developing epigenetic biomarkers specifically tailored to T2D, should we wish to model and explore the potential for predicting the disease., (© 2024. The Author(s).)

Introduction: Death due to covid-19 is one of the biggest health challenges in the world. There are many models that can predict death due to COVID-19. This study aimed to fit and compare Decision Tree (DT), Support Vector Machine (SVM), and AdaBoost models to predict death due to COVID-19., Methods: To describe the variables, mean (SD) and frequency (%) were reported. To determine the relationship between the variables and the death caused by COVID-19, chi-square test was performed with a significance level of 0.05. To compare DT, SVM and AdaBoost models for predicting death due to COVID-19 from sensitivity, specificity, accuracy and the area under the rock curve under R software using psych, caTools, random over-sampling examples, rpart, rpartplot packages was done., Results: Out of the total of 23,054 patients studied, 10,935 cases (46.5%) were women, and 12,569 cases (53.5%) were men. Additionally, the mean age of the patients was 54.9 ± 21.0 years. There is a statistically significant relationship between gender, fever, cough, muscle pain, smell and taste, abdominal pain, nausea and vomiting, diarrhea, anorexia, dizziness, chest pain, intubation, cancer, diabetes, chronic blood disease, Violation of immunity, pregnancy, Dialysis, chronic lung disease with the death of covid-19 patients showed ( p  < 0.05). The results showed that the sensitivity, specificity, accuracy and the area under the receiver operating characteristic curve were respectively 0.60, 0.68, 0.71, and 0.75 in the DT model, 0.54, 0.62, 0.63, and 0.71 in the SVM model, and 0.59, 0.65, 0.69 and 0.74 in the AdaBoost model., Conclusion: The results showed that DT had a high predictive power compared to other data mining models. Therefore, it is suggested to researchers in different fields to use DT to predict the studied variables. Also, it is suggested to use other approaches such as random forest or XGBoost to improve the accuracy in future studies., Competing Interests: The authors declare no conflict of interest., (© 2024 The Author(s). Health Science Reports published by Wiley Periodicals LLC.)

Objectives: The primary objective of this study was to examine the impact of the COVID-19 pandemic on the quality of stroke care for patients with preexisting dementia, compared with patients who had only stroke. The secondary aim was to investigate how the quality of stroke care changed during the pandemic and post-pandemic periods compared with the pre-pandemic period in patients with preexisting dementia., Design: A registry-based, nationwide cohort study in Sweden., Setting and Participants: We included patients with a first stroke between 2019 and 2022, both with and without dementia. The study periods were defined as follows: pre-pandemic (January 1, 2019, to February 29, 2020), COVID-19 pandemic (March 1, 2020, to February 24, 2022), and post-COVID-19 pandemic period (February 25, 2022, to September 19, 2022). The outcomes examined were the following quality indicators of stroke care, suggested by the national guideline of stroke care in Sweden: stroke admission site, performance of swallowing assessment, reperfusion treatment, assessment for rehabilitation, and early supported discharge., Methods: The associations were studied through group comparisons and binary logistic regressions., Results: Of the 21,795 patients with strokes, 1357 had documented preexisting dementia, and 20,438 had stroke without a dementia diagnosis. Throughout all study periods, a significantly lower proportion of patients with stroke with preexisting dementia, compared with stroke-only patients, received reperfusion treatment, assessments for rehabilitation, and early supported discharge from stroke units. In the subgroup of stroke patients with preexisting dementia, no significant associations were found regarding the quality indicators of stroke care before, during, and after the pandemic., Conclusions and Implications: Disparities in quality of stroke care were observed between stroke patients with preexisting dementia and those with only stroke during the COVID-19 pandemic. However, there were no statistically significant differences in stroke care for patients with dementia across the pandemic., Competing Interests: Disclosures The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Systemic sclerosis (SSc) is an autoimmune systemic disease that is characterized by immune dysregulation, inflammation, vasculopathy, and fibrosis. Tissue fibrosis plays an important role in SSc and can affect several organs such as the dermis, lungs, and heart. Dysregulation of interferon (IFN) signaling contributes to the SSc pathogenesis and interferon regulatory factor 1 (IRF1) has been indicated as the main regulator of type I IFN. This study aimed to clarify the effect of IFN-gamma (-γ) and dexamethasone (DEX) on the IRF1, extracellular signal-regulated kinase 1/2 (ERK1/2), and the expression of alpha-smooth muscle actin (α-SMA) in myofibroblasts and genes involved in the inflammation and fibrosis processes in early diffuse cutaneous systemic sclerosis (dcSSc). A total of 10 early dcSSc patients (diffuse cutaneous form) and 10 unaffected control dermis biopsies were obtained to determine IFNγ and DEX effects on inflammation and fibrosis. Fibroblasts were treated with IFNγ and DEX at optimum time and dose. The expression level of genes and proteins involved in the fibrosis and inflammation processes have been quantified by quantitative real-time PCR (RT-qPCR) and western blot, respectively. IFNγ could up-regulate some of the inflammation-related genes (Interleukin-6; IL6) and down-regulate some of the fibrosis-related genes (COL1A1) in cultured fibroblasts of patients with early dcSSc compared to the untreated group. Besides, it has been revealed that IFNγ can induce fibroblast differentiation to the myofibroblast that expresses α-SMA. Concerning the inhibitory effect of IFNγ on some fibrotic genes and its positive effect on the inflammatory genes and myofibroblast differentiation, it seems that IFNγ may play a dual role in SSc.

Objective: The incidence of preterm delivery is much higher in twin pregnancies than in singletons and even higher if a short cervical length is detected in the second trimester. Studies are contradictory regarding the efficacy of a cervical pessary to decrease preterm birth in twin pregnancies and short cervical length. To conduct a systematic review and meta-analysis investigating the efficacy of cervical pessary in prolonging gestation, preventing preterm birth, and reducing adverse neonatal outcomes in twin pregnancies with an asymptomatic short cervix., Data Sources: PubMed, Scopus, Web of Science, and ClinicalTrials.org were searched for randomized controlled trials from inception to June 2023., Study Eligibility Criteria: In this study, randomized controlled trials comparing the cervical pessary to expectant management in the pregnant population with twin gestations and asymptomatic short cervix were included., Methods: The Cochrane risk-of-bias-2 tool for randomized controlled trials was used for the evaluation of the risk of bias in included studies. A meta-analysis was performed by calculating risk ratio and mean difference with their 95% confidence interval using the random effects model or fixed effect model on the basis of heterogeneity and accounting for potential covariates among the included randomized controlled trials., Results: A total of 6 randomized controlled trials were included in the analysis. Cervical pessary did not significantly increase the gestational age at delivery in twin pregnancies with asymptomatic patients (mean difference, 0.36 weeks [-0.27 to 0.99]; P =.270; I 2 =72.0%). Moreover, the cervical pessary use did not result in a reduction of spontaneous or all-preterm birth before 37 weeks of gestation (risk ratio, 0.88 [0.77-1.00]; P =.061; I 2 =0.0%). There was no statistically significant difference in the composite neonatal adverse outcomes (risk ratio, 1.001 [0.86-1.16]; P =.981; I 2 =20.9%), including early respiratory morbidity, intraventricular hemorrhage, necrotizing enterocolitis, and confirmed sepsis., Conclusion: The use of cervical pessary in twin pregnancies with asymptomatic short cervix does not seem to be effective in increasing the gestational age at delivery, preventing preterm birth, or reducing adverse neonatal outcomes. This indicates that alternative interventions should be sought for the management of this patient population., (© 2024 The Authors.)

Background: COVID-19 now is a serious concern for the world healthcare system. This study aimed to investigate possible therapeutic effect of colchicine and phenolic monoterpenes accompanied by standard care of treatment (SCT) in patients diagnosed with COVID-19., Methods: In this randomized controlled parallel clinical trial, a total number of 179 (of 200) patients with confirmed COVID-19 were enrolled according to the inclusion and exclusion criteria. The patients were allocated by simple randomization method into two groups control (receiving SCT with 71 patients) and intervention (receiving SCT plus colchicine and phenolic monoterpenes with 107 patients). The mortality ratio during hospitalization as well as a 2-week follow-up, ICU admission rate, and hospitalization duration were assessed as main outcomes., Results: The mortality ratio was 0.9% (1/108) and 8.45% (6/71) in the intervention and the control groups (p-value = 0.035) respectively, these ratios after a 14-day follow-up were 1.85% (2/108), and 9.85 (7/71) respectively (p-value = 0.031). Also, the ICU admission was significantly lower (p-value = 0.006) in the intervention group 2/108 (1.85%) compared with controls 10/71 (14.08%). Moreover, the duration of hospitalization followed a similar pattern to ICU admission with 4.17 ± 1.34 vs. 6.39 ± 2.59 days in the intervention and control groups respectively (p-value< 0.001). Furthermore, no significant side effect was found between the groups., Conclusion: According to the results, the combination of colchicine plus phenolic monoterpenes could be an additive treatment for the SCT. The authors strongly recommend further trials on this combination with other SCTs., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The severe coronavirus disease 2019 (COVID-19) is associated with increased levels of blood interleukin (IL)-6. Therefore, it is hypothesized that modulating the levels or effects of IL-6  could diminish airway inflammation and alter the course of COVID-19. We conducted a controlled, randomized, double-blind clinical trial on hospitalized patients with severe COVID-19 in Iran. The patients were randomly distributed by block randomization to take either standard-of-care (SOC) plus 1 or 2 doses of tocilizumab 8 mg/kg or SOC alone. The endpoint was defined by clinical improvement and discharge. We enrolled 40 patients (20 patients in each group) from 10 July to 10 December 2020. After randomization, 1 patient in the SOC arm and 3 patients in the tocilizumab arm refused to participate and were eliminated from the study. The mean age of participants was 59.62±15.80 in the tocilizumab group (8 women and 9 men) and 63.52±12.83 years old in the SOC group (9 women and 10 men) groups. The number of patients who recovered did not differ significantly between the tocilizumab and SOC groups (12 [70.6%][70.6%] vs. 15 [78.9%]), respectively). Hospitalization rates were also similar between the groups (Log-rank test, p=0.615; hazard ratio, 0.83; 95% C‎‎I [0.‎39-1.78]). The results show that tocilizumab could not be a beneficial agent for treating severe cases of COVID-19 patients and would not significantly improve clinical outcomes.

Background: Disturbances in brain cholesterol homeostasis may be involved in the pathogenesis of Alzheimer's disease (AD). Lipid-lowering medications could interfere with neurodegenerative processes in AD through cholesterol metabolism or other mechanisms., Objective: To explore the association between the use of lipid-lowering medications and cognitive decline over time in a cohort of patients with AD or mixed dementia with indication for lipid-lowering treatment., Methods: A longitudinal cohort study using the Swedish Registry for Cognitive/Dementia Disorders, linked with other Swedish national registries. Cognitive trajectories evaluated with mini-mental state examination (MMSE) were compared between statin users and non-users, individual statin users, groups of statins and non-statin lipid-lowering medications using mixed-effect regression models with inverse probability of drop out weighting. A dose-response analysis included statin users compared to non-users., Results: Our cohort consisted of 15,586 patients with mean age of 79.5 years at diagnosis and a majority of women (59.2 %). A dose-response effect was demonstrated: taking one defined daily dose of statins on average was associated with 0.63 more MMSE points after 3 years compared to no use of statins (95% CI: 0.33;0.94). Simvastatin users showed 1.01 more MMSE points (95% CI: 0.06;1.97) after 3 years compared to atorvastatin users. Younger (< 79.5 years at index date) simvastatin users had 0.80 more MMSE points compared to younger atorvastatin users (95% CI: 0.05;1.55) after 3 years. Simvastatin users had 1.03 more MMSE points (95% CI: 0.26;1.80) compared to rosuvastatin users after 3 years. No differences regarding statin lipophilicity were observed. The results of sensitivity analysis restricted to incident users were not consistent., Conclusions: Some patients with AD or mixed dementia with indication for lipid-lowering medication may benefit cognitively from statin treatment; however, further research is needed to clarify the findings of sensitivity analyses., (© 2023. The Author(s).)

Background and Aim: Preterm birth (PTB) accompanies with morbidities and mortality among newborns. This study aimed to show that different factors such as economic (adjusted net national income and gross domestic product [GDP] per capita), human developmental (human developmental index), and health (overall health performance, pregnancy prenatal care rate, and modeled estimated maternal mortality rate) indexes might influence the prevalence of PTB., Methods: To this, the top 10 countries with the highest and lowest prevalence of PTB were extracted from the Global Burden of Disease report for PTB. Then, we have gathered some common indexes for economic (adjusted net national income and GDP per capita), health-related (overall health performance, pregnancy prenatal care rate, and modeled estimated maternal mortality rate), and combined developmental (human developmental index) factors from different resources including World Bank and United Nations for those countries. The truncated Bayesian linear regression model, decision tree, and k-means clustering algorithms were used for data analysis., Results: The results showed Pregnancy Prenatal Care Rate index has a significant effect on the PTB rate in the top 10 countries with the highest prevalence of PTB. Also, for the top 10 less prevalent countries for PTB, it was shown that modeled estimated maternal mortality rate, human developmental index rank, and pregnancy prenatal care rate have significant effects on PTB rate. In addition, the clustering based on the similarities in socioeconomic, human developmental, and health indexes were approximately like with the clustering of the countries based on the PTB rates (Rand index = 0.823)., Conclusion: The results showed studies on the epidemiology of PTB (either worldwide or nation-based) should consider these confounder factors to obtain accurate results., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Purpose: Image artefacts continue to pose challenges in clinical molecular imaging, resulting in misdiagnoses, additional radiation doses to patients and financial costs. Mismatch and halo artefacts occur frequently in gallium-68 ( 68 Ga)-labelled compounds whole-body PET/CT imaging. Correcting for these artefacts is not straightforward and requires algorithmic developments, given that conventional techniques have failed to address them adequately. In the current study, we employed differential privacy-preserving federated transfer learning (FTL) to manage clinical data sharing and tackle privacy issues for building centre-specific models that detect and correct artefacts present in PET images., Methods: Altogether, 1413 patients with 68 Ga prostate-specific membrane antigen (PSMA)/DOTA-TATE (TOC) PET/CT scans from 3 countries, including 8 different centres, were enrolled in this study. CT-based attenuation and scatter correction (CT-ASC) was used in all centres for quantitative PET reconstruction. Prior to model training, an experienced nuclear medicine physician reviewed all images to ensure the use of high-quality, artefact-free PET images (421 patients' images). A deep neural network (modified U2Net) was trained on 80% of the artefact-free PET images to utilize centre-based (CeBa), centralized (CeZe) and the proposed differential privacy FTL frameworks. Quantitative analysis was performed in 20% of the clean data (with no artefacts) in each centre. A panel of two nuclear medicine physicians conducted qualitative assessment of image quality, diagnostic confidence and image artefacts in 128 patients with artefacts (256 images for CT-ASC and FTL-ASC)., Results: The three approaches investigated in this study for 68 Ga-PET imaging (CeBa, CeZe and FTL) resulted in a mean absolute error (MAE) of 0.42 ± 0.21 (CI 95%: 0.38 to 0.47), 0.32 ± 0.23 (CI 95%: 0.27 to 0.37) and 0.28 ± 0.15 (CI 95%: 0.25 to 0.31), respectively. Statistical analysis using the Wilcoxon test revealed significant differences between the three approaches, with FTL outperforming CeBa and CeZe (p-value < 0.05) in the clean test set. The qualitative assessment demonstrated that FTL-ASC significantly improved image quality and diagnostic confidence and decreased image artefacts, compared to CT-ASC in 68 Ga-PET imaging. In addition, mismatch and halo artefacts were successfully detected and disentangled in the chest, abdomen and pelvic regions in 68 Ga-PET imaging., Conclusion: The proposed approach benefits from using large datasets from multiple centres while preserving patient privacy. Qualitative assessment by nuclear medicine physicians showed that the proposed model correctly addressed two main challenging artefacts in 68 Ga-PET imaging. This technique could be integrated in the clinic for 68 Ga-PET imaging artefact detection and disentanglement using multicentric heterogeneous datasets., (© 2023. The Author(s).)

Purpose: Metformin is considered as radiation modulator in both tumors and healthy tissues. Radiomics has the potential to decode biological mechanisms of radiotherapy response. The aim of this study was to apply radiomics analysis in metformin-induced radiosensitivity and finding radioproteomics associations of computed tomography (CT) imaging features and proteins involved in metformin radiosensitivity signaling pathways., Materials and Methods: A total of 32 female BALB/c mice were used in this study and were subjected to injection of breast cancer cells. When tumors reached a mean volume of 150 mm 3 , mice were randomly divided into the four groups including Control, Metformin, Radiation, and Radiation + Metformin. Western blot analysis was performed after treatment to measure expression of proteins including AMPK-alpha, phospho-AMPK-alpha (Thr172), mTOR, phospho-mTOR (Ser2448), phospho-4EBP1 (Thr37/46), phospho-ACC (Ser79), and β-actin. CT imaging was performed before treatment and at the end of treatment in all groups. Radiomics features extracted from segmented tumors were selected using Elastic-net regression and were assessed in terms of correlation with expression of the proteins., Results: It was observed that proteins including phospho-mTOR, phospho-4EBP1, and mTOR had positive correlations with changes in tumor volumes in days 28, 24, 20, 16, and 12, while tumor volume changes at these days had negative correlations with AMPK-alpha, phospho-AMPK-alpha, and phospho-ACC proteins. Furthermore, median feature had a positive correlation with AMPK-alpha, phospho-ACC, and phospho-AMPK-alpha proteins. Also, Cluster shade feature had positive correlations with mTOR and p-mTOR. On the other hand, LGLZE feature had negative correlations with AMPK-alpha and phospho-AMPK-alpha., Conclusion: Radiomics features can decode proteins that involved in response to metformin and radiation, although further studies are warranted to investigate the optimal way to integrate radiomics into biological experiments., (© 2023. The Author(s) under exclusive licence to Japan Radiological Society.)

Importance: Little is known about the specific timing and sequence of incident psychiatric comorbidities at different stages of dementia diagnosis., Objectives: To examine the temporal risk patterns of psychiatric disorders, including depression, anxiety, stress-related disorders, substance use disorders, sleep disorders, somatoform/conversion disorders, and psychotic disorders, among patients with dementia before, at the time of, and after receipt of a diagnosis., Design, Setting, and Participants: This population-based, nationwide cohort study analyzed data from 796 505 participants obtained from 6 registers between January 1, 2000, and December 31, 2017, including the Swedish registry for cognitive/dementia disorders. Patients with dementia were matched on year of birth (±3 years), sex, and region of residence with up to 4 controls. Data were analyzed between March 1, 2023, and August 31, 2023., Exposures: Any cause of dementia and dementia subtypes., Main Outcomes and Measures: Flexible parametric survival models to determine the time-dependent risk of initial diagnosis of psychiatric disorders, from 7 years prior to dementia diagnosis to 10 years after diagnosis. Subgroup analysis was conducted for psychiatric drug use among persons receiving a diagnosis of dementia from January 1, 2011, to December 31, 2012., Results: Of 796 505 patients included in the study (mean [SD] age at diagnosis, 80.2 [8.3] years; 448 869 (56.4%) female), 209 245 had dementia, whereas 587 260 did not, across 7 824 616 person-years. The relative risk of psychiatric disorders was consistently higher among patients with dementia compared with control participants and began to increase from 3 years before diagnosis (hazard ratio, [HR], 1.72; 95% CI, 1.67-1.76), peaked during the week after diagnosis (HR, 4.74; 95% CI, 4.21-5.34), and decreased rapidly thereafter. Decreased risk relative to controls was observed from 5 years after diagnosis (HR, 0.93; 95% CI, 0.87-0.98). The results were similar for Alzheimer disease, mixed dementia, vascular dementia and unspecified dementia. Among patients with dementia, markedly elevated use of psychiatric medications was observed in the year leading up to the dementia diagnosis and peaked 6 months after diagnosis. For example, antidepressant use was persistently higher among patients with dementia compared with controls, and the difference increased from 2 years before dementia diagnosis (15.9% vs 7.9%, P < .001), peaked approximately 6 months after dementia diagnosis (29.1% vs 9.7%, P < .001), and then decreased slowly from 3 years after diagnosis but remained higher than controls 5 years after diagnosis (16.4% vs 6.9%, P < .001)., Conclusions and Relevance: The findings of this cohort study that patients with dementia had markedly increased risks of psychiatric disorders both before and after dementia diagnosis highlight the significance of incorporating psychiatric preventative and management interventions for individuals with dementia across various diagnostic stages.

Purpose: We aimed to study insertion/deletion (I/D) variation (rs4646994) of ACE gene in a group of SLE patients in west of Iran and its possible relationship with oxidative stress., Method and Results: Genotypes and allele frequencies related to ACE (I/D) variation were determined in 108 SLE patients and 110 gender and age-matched healthy controls using PCR. Neopterin, malondialdehyde (MDA), and serum lipid concentrations were determined by HPLC and enzyme assay respectively. The overall distribution of ACE I/D genotypes in SLE patients was different from that of the control group (P = 0.005). DD genotype compared to ID genotype increased the risk of SLE (OR = 2.57, 95% CI 1.4-4.8, P = 0.003). ID genotype compared to the II genotype decreased the risk of disease (OR = 0.45, 95% CI 0.2-0.99, p = 0.042). SLE patients with DD, ID, and II genotypes had lower paraoxonase (PON) activity and higher serum levels of MDA and neopterin versus control patients. We also detected a significant protective effect against SLE in presence of ACE I alleles and lack of angiotensin II receptor, type 1 (AGTR1) A1166C (NCBI reference SNP id: rs5186), C alleles in this study (OR = 0.31, 95% CI 0.14-0.68, P = 0.002)., Conclusions: Carriers of the DD genotype of ACE gene with higher serum concentrations of neopterin and MDA, and lower PON activity had a high risk to develop SLE, while ID genotype decreased the risk of disease development by 2.22 times compared to II genotype., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Objectives: We aim to analyze the risk of death from specific external causes, including falls, complications of medical and surgical care, unintentional injuries, and suicide, in dementia patients., Design: Swedish nationwide cohort study integrating 6 registers from May 1, 2007, through December 31, 2018, including the Swedish Registry for Cognitive/Dementia Disorders (SveDem)., Setting and Participants: Population-based study. Patients diagnosed with dementia from 2007 to 2018 and up to 4 controls matched on year of birth (±3 years), sex, and region of residence., Methods: The exposures of this study were diagnosis of dementia and dementia subtypes. Number of deaths and causes of mortality were obtained from death certificates compiled into the Cause of Death Register. Hazard ratios (HRs) and 95% CIs were estimated using Cox and flexible models, adjusted for sociodemographics, medical and psychiatric disorders., Results: The study population included 235,085 patients with dementia [96,760 men (41.2%); mean age 81.5 (SD 8.5) years] and 771,019 control participants [341,994 men (44.4%); mean age 79.9 (SD 8.6) years], over 3,721,687 person-years. Compared with control participants, patients with dementia presented increased risk for unintentional injuries (HR 3.30, 95% CI 3.19-3.40) and falls (HR 2.67, 95% CI 2.54-2.80) during old age (≥75 y), and suicide (HR 1.56, 95% CI 1.02-2.39) in middle age (<65 y). Suicide risk was 5.04 times higher (HR 6.04, 95% CI 4.22-8.66) in patients with both dementia and 2 or more psychiatric disorders relative to controls (incidence rate per person-years, 1.6 vs 0.3). For dementia subtypes, frontotemporal dementia had the highest risks of unintentional injuries (HR 4.28, 95% CI 2.80-6.52) and falls (HR 3.83, 95% CI 1.98-7.41), whereas subjects with mixed dementia were less likely to die from suicide (HR 0.11, 95% CI 0.03-0.46) and complications of medical and surgical care (HR 0.53, 95% CI 0.40-0.70) compared to controls., Conclusions and Implications: Suicide risk screening and psychiatric disorders management in early-onset dementia and early interventions for unintentional injuries and falls prevention in older dementia patients should be provided., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

To investigate the outcomes of asymptomatic stage I twin-to-twin transfusion syndrome (stage I TTTS) among patients treated with fetoscopic laser photocoagulation (FLP) versus expectant management. Databases such as PubMed, Web of Science and Scopus were systematically searched from inception up to March 1st, 2022. The primary outcome was at least one fetal survival at birth and secondary outcomes included gestational age at delivery, preterm premature rupture of membranes < 32 weeks, preterm birth < 32 weeks, and single and dual fetal survival. Five studies were included in the meta-analysis. There was no significant difference in terms of at least one survival (odds ratio (OR) = 1.40, 95%CI= (0.26, 7.43), P = 0.70), single survival (OR = 0.87, 95%CI= (0.51, 1.48), P = 0.60) and dual survival (OR = 1.63, 95%CI= (0.74, 3.62), P = 0.23) among FLP and expectant groups. Gestational age at delivery (mean difference = 1.19, 95%CI= (-0.25, 2.63), P = 0.10), the risk of PTB<32 weeks (OR = 0.88, 95%CI= (0.50, 1.54), P = 0.65), and pPROM<32 weeks (OR = 1.80, 95% CI= (0.41, 7.98), P = 0.44) were also comparable between the groups. Routine FLP of the placental anastomoses before 26 weeks of gestation is unlikely to be beneficial among asymptomatic stable stage I TTTS patients without cervical shortening as the procedure does not offer a survival advantage compared with expectant management., (© 2023 John Wiley & Sons Ltd.)

Punica granatum (Family Lythraceae) comprises considerable content of phenolic components and it proves the antioxidant activity of pomegranate. Some clinical trial investigations display that consumption of pomegranate is able to boost the antioxidant status. This systematic review assessed the efficacy of pomegranate extract to reduce oxidative stress. Pomegranate was used in some studies as capsules (between 250 mg and 250 g) and some in liquid form (between 10 and 500 ml), and the follow-up duration varied from 3 weeks to 12 months. Standardized mean difference and its corresponding 95% confidence interval (CI) was used as the effect size of pomegranate supplementation on oxidative stress biomarkers. Based on the results, pomegranate decreased but it was not statistically significant and the same result was obtained for ox-LDL and POX 1. In addition, the results showed that pomegranate consumption can significantly increase GPX and TAC. Result of combination of on TBRAS showed significantly effect of pomegranate use on reduction of TBRAS. Since this study has evaluated mostly Eastern countries' studies it could be concluded that pomegranate supplements are effective in modifying oxidative stress in Eastern countries. The evidence to support this study is low, therefore, needs the future studies to confirm the results., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: In recent decades, more and more attention has been paid to the influence of nutrition on reproductive health. Nevertheless, the imminent association between diet-related inflammation and the risk of infertility has not yet been established. The aim of the current study was to investigate the ability of the Dietary Inflammatory Index (DII) to estimate infertility incidence in women., Methods: This cross-sectional study was conducted using data from Ravansar non-communicable diseases (RaNCD) cohort study on 4437 participants. The DII was calculated based on the reported consumption of up to 31 food parameters measured via a validated and reproducible 118-item food-frequency questionnaire (FFQ). Multiple logistic regression analysis was applied to estimate the multivariable odds ratio (OR) adjusted for potential confounding variables., Results: Out of all participants, 411 women (9.26%) were infertile. The mean ± SD age and weight of infertile women were 43.67 ± 7.47 years and 72.86 ± 13.02 kg, respectively. Statistical analyses showed the odds ratio of infertility in the fourth quartile (pro-inflammatory diet) was 1.76 times higher than in the first quartile (anti-inflammatory diet) of DII (95% CI: 1.57-2.02)., Conclusions: The findings of this study provide compelling evidence about the association between infertility and the quality of diet in women. Therefore, interventions and programs aimed at promoting a healthy lifestyle and using healthy diets can be considered as one of the effective approaches in the prevention and treatment of infertility in women., (© 2023. The Author(s).)

Background: Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first time, the function of the longitudinal regression tree algorithm as a non-parametric method after imputing missing data using SI and MI was investigated using simulated and real data., Method: Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing longitudinal data using parametric and non-parametric longitudinal models and the performance of the methods was assessed in real data. The real data included 3,645 participants older than 18 years within six waves obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling was conducted using systolic and diastolic blood pressure (SBP/DBP) as the outcome variables and included predictor variables such as age, gender, and BMI. The efficiency of imputation approaches was compared using mean squared error (MSE), root-mean-squared error (RMSE), median absolute deviation (MAD), deviance, and Akaike information criteria (AIC)., Results: The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the missing at random (MAR) mechanism. Overall, based on fitting the non-parametric model, the performance of the 27 imputation approaches was nearly similar. However, the SI traj-mean method improved performance compared with other imputation approaches., Conclusion: Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data, we recommend that researchers use the traj-mean method for imputing missing values of longitudinal data. Choosing the imputation method with the best performance is widely dependent on the models of interest and the data structure., (© 2023. The Author(s).)

Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to identify the most important variables associated with mortality after dementia diagnosis in the Swedish Registry for Cognitive/Dementia Disorders (SveDem). From SveDem, a longitudinal cohort of 28,023 dementia-diagnosed patients was selected for this study. Sixty variables were considered as potential predictors of mortality risk, such as age at dementia diagnosis, dementia type, sex, body mass index (BMI), mini-mental state examination (MMSE) score, time from referral to initiation of work-up, time from initiation of work-up to diagnosis, dementia medications, comorbidities, and some specific medications for chronic comorbidities (e.g., cardiovascular disease). We applied sparsity-inducing penalties for three ML algorithms and identified twenty important variables for the binary classification task in mortality risk prediction and fifteen variables to predict time to death. Area-under-ROC curve (AUC) measure was used to evaluate the classification algorithms. Then, an unsupervised clustering algorithm was applied on the set of twenty-selected variables to find two main clusters which accurately matched surviving and dead patient clusters. A support-vector-machines with an appropriate sparsity penalty provided the classification of mortality risk with accuracy = 0.7077, AUROC = 0.7375, sensitivity = 0.6436, and specificity = 0.740. Across three ML algorithms, the majority of the identified twenty variables were compatible with literature and with our previous studies on SveDem. We also found new variables which were not previously reported in literature as associated with mortality in dementia. Performance of basic dementia diagnostic work-up, time from referral to initiation of work-up, and time from initiation of work-up to diagnosis were found to be elements of the diagnostic process identified by the ML algorithms. The median follow-up time was 1053 (IQR = 516-1771) days in surviving and 1125 (IQR = 605-1770) days in dead patients. For prediction of time to death, the CoxBoost model identified 15 variables and classified them in order of importance. These highly important variables were age at diagnosis, MMSE score, sex, BMI, and Charlson Comorbidity Index with selection scores of 23%, 15%, 14%, 12% and 10%, respectively. This study demonstrates the potential of sparsity-inducing ML algorithms in improving our understanding of mortality risk factors in dementia patients and their application in clinical settings. Moreover, ML methods can be used as a complement to traditional statistical methods., (© 2023. The Author(s).)

Objective: This study aimed to introduce novel techniques for identifying the genes associated with developing chronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using regression methods., Materials and Methods: This is a secondary analysis of the data from an experimental study. We used penalized logistic regressions with three different types of penalties included least absolute shrinkage and selection operator (LASSO), minimax concave penalty (MCP), and smoothly clipped absolute deviation (SCAD). The models were trained using genome-wide expression profiling to define gene networks relevant to the COPD stages. A 10-fold cross-validation scheme was used to evaluate the performance of the methods. In addition, we validate our results by the external validity approach. We reported the sensitivity, specificity, and area under curve (AUC) of the models., Results: There were 21, 22, and 18 significantly associated genes for LASSO, SCAD, and MCP models, respectively. The most statistically conservative method (detecting less significant features) was MCP detected 18 genes that were all detected by the other two approaches. The most appropriate approach was a SCAD penalized logistic regression (AUC= 96.26, sensitivity= 94.2, specificity= 86.96). In this study, we have a common panel of 18 genes in all three models that show a significant positive and negative correlation with COPD, in which RNF130, STX6, PLCB1, CACNA1G, LARP4B, LOC100507634, SLC38A2, and STIM2 showed the odds ratio (OR) more than 1. However, there was a slight difference between penalized methods., Conclusion: Regularization solves the serious dimensionality problem in using this kind of regression. More exploration of how these genes affect the outcome and mechanism is possible more quickly in this manner. The regression-based approaches we present could apply to overcoming this issue.

Takayasu arteritis (TA) is a chronic inflammatory disorder characterized by vascular damage and fibrosis in the intima that commonly occurs in the aorta. In many damaged sites in TA patients, natural killer (NK) cells have been shown to be hyperactivated and produce inflammatory cytokines and toxic components. Killer cell immunoglobulin-like receptors (KIRs) are found on NK cells and interact with human leukocyte antigen (HLA) class I ligands to activate or suppress NK cells. The present study assessed the possible role of KIR and their HLA ligand genes in susceptibility to TA in Iranian patients. This case-control study included 50 TA patients and 50 healthy subjects. DNA was extracted from whole peripheral blood samples, and polymerase chain reaction with sequence-specific primers (PCR-SSP) was performed to recognize the presence or absence of polymorphism in 17 KIR genes and 5 HLA class I ligands in each participant. Among the KIR and HLA genes, a significant decrease was detected in the frequency of 2DS4 (full allele) in TA patients (38%) compared with healthy controls (82%) (OR=0.13, 95% CI=0.05-0.34). However, none of the KIR and HLA genotypes or the interactions between these genes were associated with susceptibility to TA. The KIR2DS4 gene might be involved in the regulation of activation as well as the production of cytotoxic mediators of NK cells in patients with TA.

This meta-analysis aims to compare the perinatal outcome of twin-twin transfusion syndrome (TTTS) pregnancies undergoing selective versus vascular equator (Solomon) fetoscopic laser photocoagulation (FLP). We performed a systematic search in PubMed and Web of Science from inception up to 25 July 2021. Studies comparing the Solomon and selective techniques of FLP for treatment of TTTS pregnancies were eligible. Random-effects or fixed-effect models were used to pool standardized mean differences (SMD) and log odds ratio. Seven studies with a total of 1664 TTTS pregnancies (n = 671 undergoing Solomon and n = 993 selective techniques) were included. As compared to the selective FLP, Solomon was associated with a lower risk of recurrent TTTS compared to the selective technique (Log odds ratio [OR]: -1.167; 95% credible interval [CrI]: -2.01, -0.33; p = 0.021; I 2 : 67%). In addition, Solomon was significantly associated with a higher risk of placental abruption than the selective technique (Log [OR]: 1.44; 95% CrI: 0.45, 2.47; p = 0.012; I 2 : 0.0%). Furthermore, a trend for the higher risk of preterm premature rupture of membranes was observed among those undergoing Solomon (Log [OR]: 0.581; 95% CrI: -0.43, 1.49; p = 0.131; I 2 : 17%). As compared to selective FLP, the Solomon technique for TTTS pregnancies is associated with a significantly lower recurrence of TTTS; however, it significantly increases the risk of placental abruption., (© 2022 John Wiley & Sons Ltd.)

The main aim of the present study was to predict myocardial function improvement in cardiac MR (LGE-CMR) images in patients after coronary artery bypass grafting (CABG) using radiomics and machine learning algorithms. Altogether, 43 patients who had visible scars on short-axis LGE-CMR images and were candidates for CABG surgery were selected and enrolled in this study. MR imaging was performed preoperatively using a 1.5-T MRI scanner. All images were segmented by two expert radiologists (in consensus). Prior to extraction of radiomics features, all MR images were resampled to an isotropic voxel size of 1.8 × 1.8 × 1.8 mm 3 . Subsequently, intensities were quantized to 64 discretized gray levels and a total of 93 features were extracted. The applied algorithms included a smoothly clipped absolute deviation (SCAD)-penalized support vector machine (SVM) and the recursive partitioning (RP) algorithm as a robust classifier for binary classification in this high-dimensional and non-sparse data. All models were validated with repeated fivefold cross-validation and 10,000 bootstrapping resamples. Ten and seven features were selected with SCAD-penalized SVM and RP algorithm, respectively, for CABG responder/non-responder classification. Considering univariate analysis, the GLSZM gray-level non-uniformity-normalized feature achieved the best performance (AUC: 0.62, 95% CI: 0.53-0.76) with SCAD-penalized SVM. Regarding multivariable modeling, SCAD-penalized SVM obtained an AUC of 0.784 (95% CI: 0.64-0.92), whereas the RP algorithm achieved an AUC of 0.654 (95% CI: 0.50-0.82). In conclusion, different radiomics texture features alone or combined in multivariate analysis using machine learning algorithms provide prognostic information regarding myocardial function in patients after CABG., (© 2022. The Author(s).)

Objectives: The aim of this study was to evaluate differences in clinical features and laboratory parameters in critically ill pregnant women with acute respiratory distress syndrome (ARDS) compared to moderate and severe pregnant women with coronavirus disease-2019 (COVID-19) but without ARDS., Methods: This was a retrospective multicenter study of all pregnant women with COVID-19 diagnosed with ARDS between February 15, and May 1, 2020 in nine level III maternity centers in Iran (ARDS group). The control COVID-19 pregnant women were selected from 3 of 9 level III maternity centers between March 15 and April 20, 2020. Univariate statistics were used to look at differences between groups. Cluster dendrograms were used to look at the correlations between clinical and laboratory findings in the groups. A value of p <.05 was considered statistically significant., Results: Fifteen COVID-19 infected women with ARDS were compared to 29 COVID-19 positive and ARDS negative control (moderate: ( n  = 26) 89.7% and severe: ( n  = 3)10.3%). The mean maternal age (35.6 vs. 29.4 years; p  = .002) and diagnosis of chronic hypertension (20.0% vs. 0%, p  = .034) were significantly higher in the ARDS group. There was no significant difference between the two groups in their presenting symptoms. The ARDS group had a significantly higher prevalence of tachypnea (66.6% vs. 10.3%, p  = .042) and blood oxygen saturation (SpO 2 ) <93% (66.6% vs. 10.3%, p  = .004) at presentation. Relative lymphopenia (lymphocyte ratio < 10.5%, 66.6% vs. 17.2%, p  = .002), lymphocytes to leukocytes ratio (11.3% vs. 17.7%, p  = .010), and neutrophils to lymphocytes ratio (NLR) >7.5 were significantly different between the two groups (all p  < .05)., Conclusion: Our data demonstrate that symptom-based strategies for identifying the critically ill pregnant women with SARS-CoV-2 are insufficient; however, vital signs and laboratory data might be helpful to predict ARDS in critically ill COVID-19 pregnant patients.

Objective: This systematic review and meta-analysis study was performed to assess the potential association between interleukin-1 beta (IL-1β) single nucleotide polymorphisms (SNPs) (rs1143634 and rs16944) and interleukin-6 (IL-6) SNP (rs1800795) and pre-eclampsia (PE)., Methods: A comprehensive literature search was conducted in the international search engines and databases, including MEDLINE (via PubMed), Scopus, and Web of Science (ISI) up to 9 March 2021. After retrieving relevant articles, data extraction was performed by four authors independently. Pooled ORs and corresponding 95% CIs were used to evaluate the association between IL-1β and IL-6 polymorphisms and PE risk. Cochran's Q test was used to check heterogeneity, and the I 2 index was calculated for measuring the heterogeneity between the estimations of included studies., Results: After reviewing fully published studies, 21 studies were included in this study based on the eligibility criteria. Our results showed that rs16944 and rs1143634 of IL-1β were significantly associated with the risk of PE. Regarding rs16944, the minor C allele significantly decreased the risk of PE (C vs. T: OR = 0.79, 95% CI = 0.69-0.90). In contrast, the minor T allele of rs1143634 significantly increased the risk of PE (T vs. C: OR = 1. 28, 95% CI = 1.04-1.58). There was no significant association between IL-6 rs1800795 (C vs. G: OR = 1.04, 95% CI = 0.93-1.16) polymorphism and PE risk., Conclusions: In conclusion, this meta-analysis suggests rs1143634 and rs16944 polymorphisms of IL-1β are related to the risk of PE.

Objectives: To evaluate the survival of twin-to-twin transfusion syndrome (TTTS) and concomitant twin anemia polycythemia sequence (TAPS) compared to TTTS without TAPS at the time of fetoscopic laser photocoagulation (FLP)., Methods: TTTS pregnancies undergoing FLP were divided to three groups including (i) traditional TAPS definition of middle cerebral artery (MCA) peak systolic velocity (PSV) < 1 multiple of the median (MoM) in recipient and > 1.5 MoM in the donor fetus, (ii) delta MCA-PSV > 0.5 MoM and (iii) delta MCA-PSV > 1.0 MoM., Results: A total of 353 monochorionic twins underwent FLP for TTTS. Based on the traditional definition, 335 (94.9 %) had TTTS only and 18 (5.1 %) had TTTS + TAPS. There were 245 (69.4 %) TTTS only and 108 (30.6 %) TTTS + TAPS considering delta MCA-PSV > 0.5 MoM and 339 (96 %) TTTS only and 14 (4 %) TTTS + TAPS considering delta MCA-PSV > 1.0 MoM. No significant differences in survival were noted at birth or 30-days after delivery between TTTS and TTTS with TAPS patients using the traditional definition, delta > 0.5 MoM or delta > 1.0 MoM., Conclusion: The rate of neonatal survival at birth or at 30-days of life following FLP for TTTS only and TTTS with TAPS were not different based on any of the clinically used TAPS definitions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Objective: This systematic review and meta-analysis aimed to compare the fetal survival rate and perinatal outcomes of triplet pregnancies after selective reduction to twin pregnancies vs singleton pregnancies., Data Sources: PubMed, Web of Science, Scopus, and Embase were systematically searched from the inception of the databases to January 16, 2022., Study Eligibility Criteria: Studies comparing the survival and perinatal outcomes between reduction to twin pregnancies and reduction to singleton pregnancies were included. The primary outcomes were fetal survival, defined as a live birth at >24 weeks of gestation. The secondary outcomes were gestational age at birth, preterm birth at <32 and <34 weeks of gestation, early pregnancy loss (<24 weeks of gestation), low birthweight, and rate of neonatal demise (up to 28 days after birth)., Methods: The random-effect model was used to pool the mean differences or odds ratios and the corresponding 95% confidence intervals. To provide a range of expected effects if a new study was conducted, 95% prediction intervals were calculated for outcomes presented in >3 studies., Results: Of note, 10 studies with 2543 triplet pregnancies undergoing fetal reduction, of which 2035 reduced to twin pregnancies and 508 reduced to singleton pregnancies, met the inclusion criteria. Reduction to twin pregnancies had a lower rate of fetal survival (odds ratio, 0.61; 95% confidence interval, 0.40-0.92; P=.02; 95% prediction interval, 0.36-1.03) and comparable rates of early pregnancy loss (odds ratio, 0.89; 95% confidence interval, 0.58-1.38; P=.61; 95% prediction interval, 0.54-1.48) and neonatal demise (odds ratio, 0.57; 95% confidence interval, 0.09-3.50; P=.55) than reduction to singleton pregnancies. Reduction to twin pregnancies had a significantly lower gestation age at birth (weeks) (mean difference, -2.20; 95% confidence interval, -2.80 to -1.61; P<.001; 95% prediction interval, -4.27 to -0.14) than reduction to singleton pregnancies. Furthermore, reduction to twin pregnancies was associated with lower birthweight and greater risk of preterm birth at <32 and <34 weeks of gestation., Conclusion: Triplet pregnancies reduced to twin pregnancies had a lower fetal survival rate of all remaining fetuses, lower gestational age at birth, higher risk of preterm birth, and lower birthweight than triplet pregnancies reduced to singleton pregnancies; reduction to twin pregnancies vs reduction to singleton pregnancies showed no substantial difference for the rates of early pregnancy loss and neonatal death., (Copyright © 2022 Elsevier Inc. All rights reserved.)

We aimed to construct a prediction model based on computed tomography (CT) radiomics features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A total of 1110 patients were studied from a publicly available dataset with 4-class severity scoring performed by a radiologist (based on CT images and clinical features). The entire lungs were segmented and followed by resizing, bin discretization and radiomic features extraction. We utilized two feature selection algorithms, namely bagging random forest (BRF) and multivariate adaptive regression splines (MARS), each coupled to a classifier, namely multinomial logistic regression (MLR), to construct multiclass classification models. The dataset was divided into 50% (555 samples), 20% (223 samples), and 30% (332 samples) for training, validation, and untouched test datasets, respectively. Subsequently, nested cross-validation was performed on train/validation to select the features and tune the models. All predictive power indices were reported based on the testing set. The performance of multi-class models was assessed using precision, recall, F1-score, and accuracy based on the 4 × 4 confusion matrices. In addition, the areas under the receiver operating characteristic curves (AUCs) for multi-class classifications were calculated and compared for both models. Using BRF, 23 radiomic features were selected, 11 from first-order, 9 from GLCM, 1 GLRLM, 1 from GLDM, and 1 from shape. Ten features were selected using the MARS algorithm, namely 3 from first-order, 1 from GLDM, 1 from GLRLM, 1 from GLSZM, 1 from shape, and 3 from GLCM features. The mean absolute deviation, skewness, and variance from first-order and flatness from shape, and cluster prominence from GLCM features and Gray Level Non Uniformity Normalize from GLRLM were selected by both BRF and MARS algorithms. All selected features by BRF or MARS were significantly associated with four-class outcomes as assessed within MLR (All p values < 0.05). BRF + MLR and MARS + MLR resulted in pseudo-R 2 prediction performances of 0.305 and 0.253, respectively. Meanwhile, there was a significant difference between the feature selection models when using a likelihood ratio test (p value = 0.046). Based on confusion matrices for BRF + MLR and MARS + MLR algorithms, the precision was 0.856 and 0.728, the recall was 0.852 and 0.722, whereas the accuracy was 0.921 and 0.861, respectively. AUCs (95% CI) for multi-class classification were 0.846 (0.805-0.887) and 0.807 (0.752-0.861) for BRF + MLR and MARS + MLR algorithms, respectively. Our models based on the utilization of radiomic features, coupled with machine learning were able to accurately classify patients according to the severity of pneumonia, thus highlighting the potential of this emerging paradigm in the prognostication and management of COVID-19 patients., (© 2022. The Author(s).)

Background: Diet plays an important role in regulating inflammation, which is a hallmark of rheumatoid arthritis (RA). Our aim was to investigate the association between the Dietary Inflammatory Index (DII) scores and RA activity., Methods: This cross-sectional study was conducted on 184 patients with RA in rheumatology clinic in Kermanshah city, Iran, in 2020. RA was diagnosed according to the criteria of the 2010 American College of Rheumatology/ European League against Rheumatism. The overall inflammatory potential of the diet was extracted from a validated 168-item food frequency questioner (FFQ) using the DII. RA disease activity was assessed using Disease Activity Score 28 (DAS-28) scores. Logistic regression and one-way ANOVA/ ANCOVA were conducted., Results: Individuals in the highest DII quartile had the significantly higher odds of positive C-reactive protein than those in the lowest quartile of the DII scores (OR 4.5, 95% CI 1.16 - 17.41, P = 0.029). A statistically significant downward linear trend in fat-free mass and weight were observed with increasing the DII quartiles (P = 0.003, P = 0.019, respectively). Patients in the highest DII quartile had higher DAS-28 scores than those in the first quartile (Mean difference: 1.16, 95% CI 0.51 - 1.81, P < 0.001) and second quartile of the DII scores (Mean difference: 1.0, 95% CI 0.34 - 1.65, P < 0.001)., Conclusion: Our results indicated that reducing inflammation through diet might be one of the therapeutic strategies to control and reduce the disease activity in RA patients., (© 2022. The Author(s).)

Complement dysfunction results in impaired ability in clearing apoptotic cell debris that may stimulate autoantibody production in systemic lupus erythematosus (SLE). Herein, we provided a comprehensive search to find and meta-analyze any complement gene polymorphisms associated with SLE. The ITGAM, C1q, and MBL gene polymorphisms were included in this meta-analysis to reveal the exact association with SLE risk. Electronic databases, including Scopus, PubMed, and Google Scholar, were searched to find studies investigating the ITGAM, C1q, and MBL gene polymorphisms and SLE risk in different populations. The pooled odds ratio (OR) and its corresponding 95% confidence interval (CI) were used to analyze the association between ITGAM, C1q, and MBL gene polymorphisms and susceptibility to SLE. According to inclusion criteria, a total of 24 studies, comprising 4 studies for C1QA rs292001, 5 studies for C1QA rs172378, 9 studies for ITGAM rs1143679, 8 studies for MBL rs1800450, 3 studies for MBL2 rs1800451, and 3 studies for MBL2 rs5030737, were included in the final meta-analysis. A significant positive association was found between rs1143679 and SLE risk, while rs1800451 significantly associated with decreased SLE susceptibility. In summary, ITGAM gene rs1143679 SNP and MBL gene rs1800451 SNP were positively and negatively associated with SLE risk, respectively., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Backgrounds: This study aims to estimate and compare the parameters of some univariate and bivariate count models to identify the factors affecting the number of mortality and the number of injured in road accidents., Methods: The accident data used in this study are related to Kermanshah province in march2020 to march2021. Accidents areas were divided into 125 areas based on density characteristics. In a one-year period, 3090 accidents happened on the suburban roads of Kermanshah province, which resulted in 398 deaths and 4805 injuries. Accident information, including longitude and latitude of accident location, type of accident (fatal and injury), number of deaths, number of injuries, accident type, the reason of the accident, and the kind of accident were all included as population-level variables in the regression models. We investigated four frequently used bivariate count regression models for accident data in the literature., Results: In bivariate analysis, except for the DNM model, there is a reasonable decrease in the AIC measures of the saturated model compared to the reduced model for the other three models. For the injury models, MSE is lowest, respectively for DIBP (137.87), BNB (289.46), BP (412.36) and DNM (3640.89) models. These results are also established for death models. But, in univariate analysis, only injury models almost present reasonable results., Conclusions: Our findings show that the IDBP model is better suitable for evaluating accident datasets than other models. Motorcycle accidents, pedestrian accidents, left turn deviance, and dangerous speeding were all significant variables in the IDBP death model, and these parameters were linked to accident mortality., (© 2022. The Author(s).)

Objective: We sought to perform a meta-analysis of the predictive value of antenatal ultrasonographic markers of bowel dilation, gastric dilation, polyhydramnios and abdominal circumference that predict complex gastroschisis and adverse perinatal outcomes DATA SOURCES: PubMed, Web of Science, Scopus and Embase were searched for relevant articles up to December 2020. Studies reporting prenatal ultrasonographic markers including intra-abdominal bowel dilation (IABD), extra-abdominal bowel dilation (EABD), bowel wall thickness, polyhydramnios, abdominal circumference <5th percentile, gastric dilation (GD) and bowel dilation not otherwise specified (BD-NOS) were included. The primary outcome was prediction of complex gastroschisis; secondary outcomes were length of hospital stay for newborn, time to full enteral feeding, postnatal mortality rate, incidence of necrotising enterocolitis and short bowel syndrome., Results: Thirty-six studies were included in this meta-analysis. We found significant associations between complex gastroschisis and IABD (OR=5.42; 95% CI 3.24 to 9.06), EABD (OR=2.27; 95% CI 1.40 to 3.66), BD-NOS (OR=6.27; 95% CI 1.97 to 19.97), GD (OR=1.88; 95% CI 1.22 to 2.92) and polyhydramnios (OR=6.93; 95% CI 3.39 to 14.18). Second trimester IABD and EABD have greater specificity for the prediction of complex gastroschisis than third trimester values with specificity of 95.6% (95% CI 58.1 to 99.7) and 94.6% (95% CI 86.7 to 97.9) for the second trimester IABD and EABD, respectively., Conclusion: Prenatal ultrasonographic markers, especially the second trimester IABD and EABD, can identify fetuses that develop complex gastroschisis. Furthermore, these specific ultrasonographic markers can identify those babies at the highest risk for severe complications of this congenital anomaly and hence selected for future antenatal interventions., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: We aimed to analyze the prognostic power of CT-based radiomics models using data of 14,339 COVID-19 patients., Methods: Whole lung segmentations were performed automatically using a deep learning-based model to extract 107 intensity and texture radiomics features. We used four feature selection algorithms and seven classifiers. We evaluated the models using ten different splitting and cross-validation strategies, including non-harmonized and ComBat-harmonized datasets. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were reported., Results: In the test dataset (4,301) consisting of CT and/or RT-PCR positive cases, AUC, sensitivity, and specificity of 0.83 ± 0.01 (CI95%: 0.81-0.85), 0.81, and 0.72, respectively, were obtained by ANOVA feature selector + Random Forest (RF) classifier. Similar results were achieved in RT-PCR-only positive test sets (3,644). In ComBat harmonized dataset, Relief feature selector + RF classifier resulted in the highest performance of AUC, reaching 0.83 ± 0.01 (CI95%: 0.81-0.85), with a sensitivity and specificity of 0.77 and 0.74, respectively. ComBat harmonization did not depict statistically significant improvement compared to a non-harmonized dataset. In leave-one-center-out, the combination of ANOVA feature selector and RF classifier resulted in the highest performance., Conclusion: Lung CT radiomics features can be used for robust prognostic modeling of COVID-19. The predictive power of the proposed CT radiomics model is more reliable when using a large multicentric heterogeneous dataset, and may be used prospectively in clinical setting to manage COVID-19 patients., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)