Systemic Sclerosis (SSc) Diagnosis & Management: 2013 ACR/EULAR Score, FIBROSIS Checklist, and Treat-the-Phenotype Approach
1. Confirming the Diagnosis Step How you do it Exam pearls 1 A. Clinical suspicion Look for skin thickening , Raynaud phenomenon, puffy...
Rheumatoid Arthritis OSCE & Ward Guide: Diagnosis, DAMP-SAFE Workup, T2T ≤ 6 Management (ACR/EULAR 2023)
1. Making the Diagnosis Step-wise approach, you can reproduce on the wards or in a viva: What you do Why it matters “Exam-ready” tips 1....
Viral Hepatitis A B C D E: One-Page Guide to Diagnosis, Treatment, and Mnemonics (CDC & WHO 2024)
A Hepatitis A (HAV) Investigate Serum anti-HAV IgM → acute infection. Treatment Purely supportive ; almost always self-limited....
Viral Hepatitis B & C — Super-Pocket Investigation + Treatment Guide (2025)
1 Hepatitis B (HBV) Investigate Screen: HBsAg, anti-HBs, total anti-HBc ± IgM anti-HBc (if acute suspected) If HBsAg + : HBeAg, HBV DNA...
Hepatitis B and C Treatment Guide: When to Treat, What to Use, and Monitoring Essentials (WHO 2024, AASLD 2024)
Below is a stage-by-stage “when to treat & how to treat” roadmap for both hepatitis B (HBV) and hepatitis C (HCV). I highlight triggers...
Positive (+) and Negative (–) Viral Hepatitis B and Viral Hepatitis C Profiles: Practical Interpretation with WHO & CDC 2024–25 Updates (Viral Hepatitis Profiles)
Below is a self-contained, exam-ready deep dive on reading positive (+) and negative (–) viral-hepatitis profiles. I keep the...
Rate-Based Measures in Clinical Research: Cumulative Incidence vs Incidence Rate
Introduction In clinical research, the concept of rate underpins our ability to quantify the frequency of events, particularly in...
Simplifying Clinical Prediction Models: Correlation, Complexity & Fit in Stata (R², R square, and Predictor Parameters)
✨ Abstract In the design of clinical prediction models—especially those involving continuous predictors—understanding the interplay...
Choosing the Right Generalized Linear Models (GLMs) in Stata: A DEPTh-Based Guide
Outcome Type (Y) GLM Family Link Function Common X Type Effect Estimate Assumption About Normality in Y Continuous gaussian identity...
How to Quit Coffee: Clinical and Behavioral Strategies for Caffeine Withdrawal Management
Caffeine, primarily consumed as coffee, is the most widely used psychoactive substance in the world . While it offers transient...
How to Choose Statistical Test in Clinical Research: T-test, Mann-Whitney U / Ranksum, ANOVA, Kruskal-Wallis, Paired t-test, Wilcoxon Signed-Rank, Chi-square, Fisher’s Exact, Log-rank, Cox regression
Step 1 Identify the Dependent Variable Y Y (Outcome) Example Data Type Typical Scale / Notes Blood-loss volume (mL), Hb level (g/dL)...
Parametric vs. Non-Parametric Tests in Clinical Research: When, Why, and How
📘 Parametric vs Non-Parametric: What's Realer ? In clinical epidemiology and biostatistics, selecting the appropriate statistical test...
Too Simple to Notice, Too Important to Ignore: Why Methods Projects Matter—and How to Build One That Shines
🧠 The Hidden Weak Links That Power Science Ask yourself: “What’s something we all do in clinical research—but never truly question?”...
What Is Regression in Clinical Epidemiology? A Simple Guide to Risk Difference and Risk Ratio
🧪 What is Regression in Simple Terms? Regression is a statistical method used to understand and quantify the relationship between one...
Risk Regression Models in Clinical Epidemiology: Estimating Risk Difference and Risk Ratio
Introduction When analyzing binary outcomes in clinical epidemiology—such as the presence or absence of a disease—choosing the...
Understanding Risk in Clinical Epidemiology: Incidence, Prevalence, and Comparative Measures
Introduction In clinical epidemiology, the concept of risk serves as a foundational pillar for evaluating disease frequency, identifying...
Likelihood Ratios: พื้นฐานความน่าจะเป็นในเชิงเงื่อนไข (Conditional Probability)
🔶 LR⁺ (Likelihood Ratio for a Positive Test) 📌 Definition The ratio of the probability of a positive test in someone with the disease...
Calculating Mean and SD of Change from Baseline Using Correlation
🎯 Purpose In clinical trials and observational studies, it's often necessary to compare change scores (e.g., improvement in blood...
Calculating Pooled Mean and SD from Subgroup Data: Meta-Analysis Guide
🎯 Purpose In clinical research and meta-analysis, it's common to have results from subgroups (e.g., age strata, treatment arms,...
Estimating Mean and SD Using Wan’s Method for Meta-Analysis
🎯 Purpose In meta-analyses, especially of clinical studies, researchers often encounter studies reporting medians, ranges, and quartiles...
RevMan-style meta-analysis workflows: Calculating Standard Deviations for Meta-Analysis from Confidence Intervals, SE, p-values, and t-values
Meta-analysis often requires mean and standard deviation (SD) , but studies frequently report incomplete data . This guide teaches how to...