EBM SEARCH-evidence-based medicine search
AI-powered EBM search, links, and summaries.

Finds, summarizes EBM literature, suggests keywords, search strategies, and URLs.
How can I find the latest guidelines on hypertension?
What's the best keyword strategy for searching on PubMed?
Can you help me find meta-analyses on diabetes management?
How can I generate a PubMed search URL for my research query?
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EBM SEARCH: a focused assistant for evidence-based medicine work
EBM SEARCH is a specialized helper built to speed up high-quality evidence retrieval and synthesis. Its design purpose is to turn clinical or research questions into actionable search strategies, surface the most credible sources (systematic reviews, meta-analyses, randomized trials, authoritative guidelines), and summarize findings clearly without giving medical advice. Core behaviors include: translating a free-text question into a structured PICO, proposing keywords plus MeSH terms and filters, generating shareable PubMed URLs (and, if you confirm, a full set of 10 PubMed Clinical Queries links), and explaining how to reproduce or adapt the search. It also outlines critical-appraisal points (risk of bias, effect sizes, diagnostic accuracy measures, and GRADE strength of evidence) so readers can judge study quality. Example scenario 1: a hospitalist asks whether low-dose colchicine reduces recurrent cardiovascular events after myocardial infarction; EBM SEARCH builds a PICO, proposes MeSH and keywords, crafts PubMed URLs for RCTs and meta-analyses, then summarizes major trials and their absolute risk reductions withEBM SEARCH overview NNT calculations. Example scenario 2: an ED team wonders if point-of-care ultrasound improves appendicitis diagnosis in children; EBM SEARCH provides search terms (including pediatric MeSH), suggests QUADAS-2 items to check in diagnostic studies, and shows how to filter for sensitivity/specificity papers. Example scenario 3: a quality-improvement lead needs to update a venous-thromboembolism prophylaxis protocol postpartum; EBM SEARCH identifies guideline bodies to check, proposes a surveillance strategy (alerts and periodic searches), and summarizes what changed since the last update, flagging certainty of evidence.
What EBM SEARCH does and how it is applied
Rapid evidence search and strategy building
Example
Query: Do GLP-1 receptor agonists compared with metformin monotherapy improve weight outcomes in adults with type 2 diabetes? EBM SEARCH converts this to PICO (Population adults with T2D, Intervention GLP-1 RA, Comparator metformin, Outcomes weight change and A1c, Study types RCTs and meta-analyses). It proposes synonyms and MeSH (e.g., Diabetes Mellitus, Type 2; Glucagon-Like Peptide 1; Metformin), shows Boolean logic without unnecessary quotes, adds filters (humans, adults, last 5 years for currency), and produces ready-to-click PubMed URLs for broad and focused sets. It also suggests how to extend to Cochrane Library or guideline repositories if desired.
Scenario
Time-pressured clinician needs a 5-minute quick search before a case conference; EBM SEARCH returns a small set of high-yield links, a brief synthesis of top studies, and notes on applicability to primary care versus specialty settings.
Critical appraisal and concise synthesis (non-advisory)
Example
For a new randomized trial on low-dose colchicine post-MI, EBM SEARCH explains design and setting, calculates or interprets absolute risk reduction, NNT, confidence intervals, and hazard ratios, comments on randomization, allocation concealment, and blinding (Cochrane RoB 2 domains), and compares results with prior meta-analyses. For diagnostic questions, it walks through sensitivity, specificity, likelihood ratios, pretest to posttest probability, and common pitfalls like spectrum bias and verification bias (using QUADAS-2). For observational harm or etiology questions, it flags confounding, selection bias, and tools such as Newcastle-Ottawa.
Scenario
Journal club preparation where residents must defend whether a statistically significant result is clinically meaningful; EBM SEARCH produces a one-page summary: structured abstract, forest-plot style interpretation in words, key limitations, applicability to the local population, and a bottom-line statement with GRADE certainty.
Reproducible linking and navigation (PubMed Clinical Queries, Similar Articles, and search documentation)
Example
After you provide keywords such as aspirin stroke, EBM SEARCH can ask whether you want the 10 PubMed Clinical Queries links (Therapy, Diagnosis, Prognosis, Etiology, Clinical prediction guides × Broad and Narrow scopes). If you confirm, it returns the 10 distinct URLs in the exact format so any team member can reopen the same filtered views later. It can also craft PubMed Similar Articles links starting from a key seed paper and provide variations of the search (e.g., pediatric vs adult filters, language limits) while explaining trade-offs in sensitivity versus specificity.
Scenario
A multidisciplinary guideline team needs a transparent, repeatable search record for audit and future updates; EBM SEARCH outputs the search logic, the generated URLs, notes on why filters were chosen, and a brief plan for quarterly surveillance so updates can be reproduced consistently.
Who benefits most from EBM SEARCH
Clinicians and care teams (physicians, NPs, PAs, pharmacists, nurses)
They face time-critical questions and need fast, credible pointers to the best evidence. EBM SEARCH translates bedside questions into PICO, builds efficient searches with appropriate filters, highlights key outcomes and applicability, and summarizes without making patient-specific recommendations. Typical uses include pre-round huddles, case conferences, formulary or stewardship decisions, and protocol updates.
Information specialists, researchers, and trainees (medical librarians, residents, students)
They need reproducible strategies and didactic explanations. EBM SEARCH teaches query construction (keywords, MeSH, Boolean operators), provides PubMed Clinical Queries links on request to balance sensitivity and specificity, maps appraisal frameworks (RoB 2, QUADAS-2, GRADE), and documents the search so others can replicate it. Typical uses include systematic review scoping, journal club prep, M&M discussions, and methods sections for research protocols.
How to use EBM SEARCH (quick guide)
Start here
Visit aichatonline.org for a free trial without login, also no need for ChatGPT Plus.
Prep your clinical question
List PICO elements (Patient/Problem, Intervention, Comparison, Outcomes), any setting/age limits, and date ranges. Typical use cases: locating recent RCTs/systematic reviews, checking guideline updates, scoping a topic for journal club, or drafting search strings for manuscripts and grants.
Search & scope
Enter plain-language keywords (no quotes needed for PubMed). Ask for MeSH terms, synonyms, and filters (e.g., Humans, Adults, RCT, Systematic Reviews). If you want PubMed Clinical Queries, say so—EBM SEARCH will generate 10 category/scope links (Therapy, Diagnosis, Prognosis, Etiology, Clinical prediction guides × Broad/Narrow) after you confirm.
Review evidence quickly
Get structured digests (study design, population, outcomes, effect direction, limitations) and direct links (PubMed/PMC/guidelines). Use tips like adding field tags ([tiabEBM SEARCH guide], [mh], [majr]), limiting by year, and requesting “Find similar articles” links to expand high-yield clusters.
Refine, export, repeat
Iterate with new synonyms or subheadings, save/share the generated PubMed URLs, and copy the search strategy into your protocol or manuscript. EBM SEARCH summarizes research for information purposes only—always appraise full texts and consult clinicians or librarians for patient care.
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Five common questions about EBM SEARCH
What exactly is EBM SEARCH?
A specialized, AI-powered assistant for evidence-based medicine. It helps you frame PICO questions, craft high-sensitivity PubMed strategies, suggest MeSH/synonyms/filters, summarize key findings from recent studies and guidelines, and—upon request—produce 10 PubMed Clinical Queries links for rapid retrieval. It focuses on reputable sources (e.g., PubMed/PMC, guideline bodies) and provides links for verification. It does not provide medical advice.
How do I build a robust PubMed search with it?
State your topic and constraints. EBM SEARCH proposes a strategy that blends keywords with MeSH (exploded where appropriate), uses Boolean logic, and applies targeted filters. Example (therapy): (aspirin[mh] OR aspirin[tiab] OR acetylsalicylic[tiab]) AND (stroke[mh] OR ischemic stroke[tiab]) AND (randomized controlled trial[pt] OR randomized[tiab]) NOT animals[mh] NOT editorial[pt]. You can request field tags ([tiab], [mh], [majr]), date limits, and human/age filters.
Can you generate PubMed Clinical Queries links for my keywords?
Yes—after you explicitly confirm. EBM SEARCH outputs 10 distinct links covering Therapy, Diagnosis, Prognosis, Etiology, and Clinical prediction guides, each in Broad and Narrow scope. The URLs follow: https://pubmed.ncbi.nlm.nih.gov/clinical/?term={your_terms}&clinical_study_category={category}&clinical_study_scope={broad|narrow}. Accented characters are normalized to ensure the links work.
How are summaries created and what about paywalled content?
EBM SEARCH surfaces authoritative records (PubMed/PMC, guideline organizations) and composes concise, structured digests: study type, participants, interventions/exposures, outcomes, timing, notable effects, caveats (risk of bias, imprecision). For paywalled articles, you still get the PubMed record and, when available, open-access versions (PMC, preprints) for immediate reading.
Any tips to get optimal results?
Start with a precise PICO and outcome. Specify population traits (age, setting), ceiling on publication year, and study designs of interest (RCTs, cohort, SR/MA). Request MeSH expansion plus ‘Find similar articles’ links to snowball. Avoid unnecessary quotation marks in PubMed (let Automatic Term Mapping work), and use truncation (*) sparingly because it disables mapping.