Syncope: A High-Yield Guide to Diagnosis, Mechanisms, and Clinical Management
A complete, high-yield revision integrating foundational understanding, clinical reasoning, and bedside application. 1 | What Exactly Is...
How Diagnostic Prediction Models and Clinical Prediction Rules (CPRs) Guide Clinical Decision-Making
Introduction In medicine, decisions are often made under uncertainty. Clinicians must interpret symptoms, signs, and tests to estimate...
The Edelman Equation – Core Formula and Interpretation
The Edelman equation mathematically models how plasma sodium concentration ([Na+]) depends not just on sodium and water balance but...
What Is Integrated Discrimination Improvement (IDI)? A Clear Guide with Example
🧪 What Is IDI? While Net Reclassification Improvement (NRI) focuses on category shifts , IDI measures how much the new model improves...
What Is Net Reclassification Improvement (NRI)? A Simple Guide with Examples
🧠 What Is NRI? The Net Reclassification Improvement (NRI) is a way to measure how much better a new diagnostic model or test is at...
Diagnostic Added-Value Research: How to Measure the Real Impact of a New Test
Introduction Traditional diagnostic accuracy research tells us whether a test can differentiate disease from non-disease. But in real...
How to Use QUADAS-2 to Assess Bias in Diagnostic Accuracy Studies
Introduction Diagnostic accuracy studies are essential for understanding whether a test can correctly distinguish between those with and...
STARD 2015: How to Report Diagnostic Accuracy Studies with Clarity and Rigor
Introduction Diagnostic tests form the cornerstone of clinical reasoning. But understanding whether a test is truly accurate requires...
Detecting Bias in Diagnostic Accuracy Studies: Types, Examples, and How to Avoid Them
Introduction In diagnostic research, bias can silently distort results and mislead conclusions—even in the absence of statistical errors....
How to Design Diagnostic Accuracy Studies: Object, Method, and Analysis Explained
Introduction Diagnostic tests serve as crucial decision points in clinical medicine. Whether confirming a suspected disease or ruling one...
Diagnostic Indices: Sensitivity, Specificity, Predictive Values, and Beyond
Introduction Every clinical diagnosis involves uncertainty. Diagnostic tests are tools that help us reduce that uncertainty by providing...
Phases and Types of Diagnostic Research: From Accuracy to Outcome Impact
Introduction Diagnostic research is not merely about test accuracy—it’s about how diagnostic tools operate across different clinical...
Clinical Diagnosis: Bayesian Reasoning, Thresholds, and Diagnostic Value
Introduction Clinical diagnosis sits at the very heart of medicine. It is the intellectual, evidence-informed process by which a...
Patient-Reported Outcomes (PROs) and Minimal Clinically Important Difference (MCID): Measuring What Truly Matters in Clinical Care
🎯 Why It Matters Imagine you’re treating a patient with chronic back pain. You prescribe a new therapy, and afterward their pain score...
Clinimetrics and the DEPTh Model: Choosing the Right Clinical Metrics for Research
📌 Why We Measure: The Role of Clinimetrics Clinical research isn’t just about collecting data—it’s about asking, “How do we know what...
Guide to Common Measures (Data type, Clinimetrics) in Clinical Research Using the DEPTh Model
🔍 Why Clinical Metrics Matter (Beyond “Significance”) Imagine you’re comparing two treatments in a heart failure unit. Or evaluating a...
Mastering Confounding in Causal (Explanatory) Research: Design, DAGs & Control Strategies
1. 🔍 What’s the Real Question Here? Before you even say “confounder,” ask this : Is this a causal (explanatory) question or a predictive...
Clarifying Adjustment in DAGs: Controlling Bias Paths Without Creating New Effects
เข้าใจการปรับตัวแปรใน DAG อย่างถูกต้อง: ควบคุมอคติ ไม่ใช่ลบตัวแปร 🧠 บริบทของความเข้าใจที่คุณมี การเข้าใจว่า: การปรับตัวแปรเหมือน...
DAGs vs. Causal Diagrams: What to Use for Clinical Causal Inference
🎯 TL;DR Summary Table Feature DAG (Directed Acyclic Graph) Causal Diagram (General) ✅ Arrows only Yes – all edges are directional...
Causal vs Non-Causal Paths in DAGs — How to Detect Bias and Adjust Causal Paths in Clinical Research Using DAGs
🎯 Objectives By the end, you’ll be able to: ✅ Distinguish causal from non-causal paths ✅ Diagnose if a path is open or closed ✅ Know...
Causal Inference with DAGs in Pediatric Clinical Research
🎯 Learning Objectives By the end of this guide, you’ll be able to: ✅ Classify variables into confounders, mediators, colliders, and...
How to Think Causally in Clinical Research — The Counterfactual + DAG Blueprint
“Causation isn’t just about what happened—it’s about what would have happened instead.” 🎯 The Clinical Dilemma Your patient, Mr. G, age...
Deep Dive: DDO vs. PICO (Aligned with DEPTh + Design Triad)
🧠 Think "DEPTh" First—Not Framework Before choosing DDO or PICO, classify the clinical challenge : Type Description Examples Diagnosis...
The Core of Clinical Research Design in 3 Moves: Object, Method, Analysis
1️⃣ Object Design: What’s the Clinical Problem? Use the DEPTh Model to define your study’s core question: DEPTh Type Clinical Aim...