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research Addressing continuous data for participants excluded from trial analysis: a guide for systematic reviewers
The conclusion is that the risk of losing significance in meta-analysis results increases with smaller effects and more missing data, and using the median standard deviation for imputation is recommended.
research LB892 Assessing the risk of alopecia areata development in patients with seasonal and food allergies: a matched population-level analysis
Allergies, especially both seasonal and food, increase the risk of developing alopecia areata.
research 41261 Identification of Demographic and Clinical Features Associated with Multi-Biologic Failure in the CorEvitas Psoriasis Registry
Certain factors like being female, having high cholesterol, using Medicaid, and previous non-biologic treatments increase the risk of multiple biologic failures in psoriasis patients.
research RETRACTION: Causal Effects of Genetically Determined Metabolites on Androgenetic Alopecia: A Two‐Sample Mendelian Randomization Analysis
research Bidirectional association between alopecia areata and migraine: A nationwide population-based cohort study
People with alopecia areata are more likely to get migraines, and vice versa.
research Using a capture–recapture method to assess the frequency of adverse drug reactions in a French university hospital
The study found that combining different databases gives a better estimate of drug side effects in hospitals.
research AI04 A novel machine learning software application for prognosticating cutaneous malignant melanoma based on data from 78 351 patients from the Surveillance, Epidemiology, and End Results (SEER) database
The new AI software predicts melanoma outcomes more accurately than traditional methods.
research Comparison of Linear Regression, Decision Tree Regression, and Random Forest Regression Algorithms in Predicting Baldness Risk
Random Forest Regression is best for predicting baldness risk.
research LB1040 Machine learning-based predictive model with routine blood work identifies moderate-severe alopecia areata
Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.
research Association of single nucleotide polymorphisms in the RAB5B gene 3′UTR region with polycystic ovary syndrome in Chinese Han women
Certain genetic variations in the RAB5B gene are linked to a higher risk of polycystic ovary syndrome in Chinese Han women.
research RETRACTED: Genetic association between asthma and alopecia areata: A two‐sample Mendelian randomization study
Asthma may increase the risk of alopecia areata.
research Genomewide analysis of copy number variants in alopecia areata in a C entral E uropean cohort reveals association with MCHR 2
MCHR2 gene duplications may be linked to alopecia areata.
research A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
Adding obesity data to machine learning models improves heart disease prediction accuracy.
research Genetically determined metabolites in allergic conjunctivitis: A Mendelian randomization study
Eight blood metabolites are linked to causing allergic conjunctivitis, offering new ways to predict and treat it.
research Association of 1-Year Blood Pressure Variability With Long-term Mortality Among Adults With Coronary Artery Disease
Higher variability in systolic blood pressure increases long-term mortality risk in coronary artery disease patients.
research PD57-09 NATIONAL SURGICAL QUALITY IMPROVEMENT PROGRAM SURGICAL RISK CALCULATOR POORLY PREDICTS COMPLICATIONS IN PATIENTS UNDERGOING RADICAL CYSTECTOMY WITH URINARY DIVERSION: THE CASE FOR A PROCEDURE-SPECIFIC RISK CALCULATOR
Finasteride use is linked to a lower risk of bladder cancer, especially in Caucasians and Hispanics.
research Multi-Omics Mendelian Randomization Reveals Causal Oxidative Stress Genes in Androgenetic Alopecia.
research Comment on “Association Between Androgenic Alopecia and Schizophrenia: A Bidirectional Mendelian Randomization Study”
research An exploratory analysis of 5‐alpha reductase inhibitors and risk of opioid use disorder among male Medicare beneficiaries receiving prescription opioid medications
Using 5-alpha reductase inhibitors may lower the risk of opioid addiction in men taking opioids.
research Mixture effects of endocrine disrupting compounds in vitro
Weak endocrine disruptors in mixtures can have significant effects and should be considered in risk assessments.
research Efficacy of serum anti-mullerian hormone (AMH) levels for prediction of polycystic ovary syndrome (PCOS) and its association with clinical, biochemical and hormonal parameters
research LO-009 Responsiveness of the CLASI to alopecia and mucous membrane involvement: a retrospective study of prospectively collected data
Excluding alopecia and mucous membrane components from the CLASI-A score reduces its effectiveness in capturing important disease activity.
research 50835 Air Quality Index (AQI) and atopic dermatitis risk in Taiwan: A nationwide population-based cohort study
Poor air quality increases the risk of atopic dermatitis in Taiwan.
research The prevalence of polycystic ovary syndrome in a normal population according to the Rotterdam criteria versus revised criteria including anti-Mullerian hormone
Adding anti-Müllerian hormone to PCOS criteria lowers the number of women diagnosed.
research Differential association between cumulative dose of 5α-reductase inhibitors and mortality
Higher doses of 5α-reductase inhibitors may lower mortality risk, but low doses increase it.
research Relative efficacy of minoxidil and 5-alpha-reductase inhibitors in the treatment of male androgenetic alopecia: protocol for a network meta-analysis study
research The temptation of large numbers
Large databases in research can lead to misleading conclusions due to biases and chance findings; researchers should analyze data more rigorously.
research No Association between Patient Demographics and Adverse Effects of Low-Dose Oral Minoxidil in a Retrospective Cohort study of Nonscarring Alopecia Patients
research Machine Learning Approach for Predicting Systemic Lupus Erythematosus in Oman-based Cohort
The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.