Cluster Headache Research Hub
A systematic database of peer-reviewed literature, clinical trials, case series and review articles relating to cluster headache pathophysiology, diagnosis, treatment and patient experience. Studies span 1947 to the present.
| Year | Title | Authors | Journal | Access | Grade |
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Enter a plain-language question or search term — for example "does melatonin help with cluster headache?"
or "verapamil dosing for prevention" — and the search engine will find the most relevant studies
in the database, score them for relevance, and automatically generate a synthesised answer with citations.
Community posts from r/clusterheads and r/ClusterHeadaches are also searched in parallel and included in
the synthesis where relevant, clearly labelled as patient-reported data.
Who I Am
My name is Craig. I'm a cluster headache patient — not a clinician, not a researcher, just someone who has lived with this condition and found that understanding it deeply is part of how I cope and how I fight back. This project grew out of obsessive note-taking, reading, and a desire to have something better than a scattered folder of PDFs.
A Patient-Led Passion Project
The CH Research Hub is a personal tool I built to organise and explore the peer-reviewed literature on cluster headache — over 3,000 references and counting. It pulls in new studies automatically, grades the evidence, extracts key findings using AI, and cross-references the lived experience shared by the community on Reddit. The goal isn't to replace medical care — it's to be an informed patient, to spot patterns, to ask better questions, and perhaps to contribute something useful to others who are searching for answers.
Complexity & Open-Mindedness
Cluster headache is not a simple disorder. Its pathophysiology spans the hypothalamus, the trigeminal system, circadian biology, neuroinflammation, vascular mechanisms, genetics, and more. No single theory fully explains it. I try to hold all of that complexity at once — to remain genuinely open-minded, to update my understanding as new evidence arrives, and to resist the pull toward any single neat narrative. If this project has a philosophy, it's that intellectual humility is a prerequisite for understanding something this intricate.
Synthesis reports now generated as professional Word (.docx) files with full Table of Contents,
running headers/footers, page numbers, and structured heading hierarchy — replacing the basic PDF
output. New generate_synthesis_docs.js script handles all Word generation from
synthesis markdown. Identified and scripted a fix for 499 papers (~12.6% of corpus) missing
domain assignments — assign_missing_domains.py uses Ollama LLM to assign up to 3
domains per paper based on title, abstract, and key finding. Key findings for refs 3911–3952
(42 papers) force-rewritten via redo_findings_3911plus.py. Convergence re-run
button removed from admin panel (synthesis always run in Cowork). Download buttons updated
to Word throughout.
Convergence Analysis and Intervention Report fully regenerated in Cowork with complete community + supplementary context: all 12 domain JSONs, community_synthesis.md (2,637 posts / 31,116 comments), supplementary_synthesis.json (15 sources), and ch_analysis.json integrated. Report now includes "What the Patient Community Adds" and "Working Pathogenesis Model" sections with per-component confidence grading. Intervention report gains dedicated Bob Wold/Batcheller D3 protocol section with full regimen details, explicit C* community grading, and 6 evidence-gap research priorities. PDFs regenerated. Admin panel description cleaned up.
New Synthesis tab: all 12 domain synthesis reports (Trigeminal, Hypothalamus, Circadian, etc.) with narrative summaries, key findings, mechanistic models, treatment implications, evidence gaps, and cross-domain links. Cross-domain convergence analysis and structured intervention report — viewable online and downloadable as formatted PDFs. Intervention report restructured into Pharmaceutical vs Natural & Patient-Led, each with Abortive, Bridging, and Preventative sub-categories, ranked by evidence strength. Admin panel gains a Domain Synthesis Re-run card for triggering re-analysis after new data ingestion.
Full admin panel rebuild: automated PubMed article fetching (tracks last-checked date), manual article addition by PMID / DOI / full entry with optional PDF attachment, auto PDF download via PMC and Unpaywall, upload-PDF-later workflow, inline streaming terminal output with close buttons, community data actions consolidated, model update tracker added. Unified CH model section (in progress). Brain favicon introduced.
AI Search tab introduced: semantic and keyword search over the full abstract corpus, parallel community post search, AI-generated evidence synthesis with citations. Runs locally via Ollama (qwen2.5:14b) with Claude API fallback. Model engine displayed prominently in the search header.
r/clusterheads and r/ClusterHeadaches posts ingested and stored locally. Community tab with filtering and search. Patient-reported treatments, triggers, and experiences cross-referenced against literature.
Core research library with 3,000+ references from the master XLSX database. Evidence grading (RCT, META, SR, OBS, CASE-R, CASE-S, REVIEW), domain tagging, key findings, abstract viewer, paper detail panels, author index, and supplementary resources tab.
| Type | Title | Authors | Year | Source / Journal | Category |
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About This Analysis
Cluster Headache Research Project · Evidence Synthesis Framework
This is an independent systematic evidence synthesis initiative built and maintained by a cluster headache patient. The project has assembled a corpus of peer-reviewed literature spanning 1947 to the present, supplemented by curated supplementary sources and a community corpus drawn from r/clusterheads and r/ClusterHeadaches.
The aim is to synthesise the current state of scientific understanding of cluster headache pathogenesis, triggers, and treatment options into an accessible, structured evidence base for patients, carers, and researchers. This project is not affiliated with any clinical institution, drug manufacturer, or research body.
Papers were identified through systematic PubMed searches using cluster headache-specific search strings and supplemented by manual curation. Each paper was graded using a modified evidence hierarchy:
Domain assignment reflects the primary mechanistic pathway each paper contributes to across 12 canonical domains. For each domain, a hierarchical multi-pass synthesis was performed using a large language model, processing papers in batches where domain size exceeded context budget. Cross-domain convergence analysis identifies findings supported by three or more independent domains or by Grade A/B evidence.
When users interact with the hypothesis via the Chat tab, those exchanges are logged and fed back into the synthesis model as additional context during the next re-synthesis run — ensuring the analysis can be challenged, refined, and updated as new evidence or perspectives emerge.
- Evidence grading is computer-assisted and may not fully capture all nuances of study quality or risk of bias.
- The community corpus (Grade C*) is not peer-reviewed; prevalence of mentions reflects online engagement patterns, not clinical efficacy.
- LLM-generated synthesis may contain errors, omissions, or hallucinations. All outputs should be verified against primary literature before clinical application.
- Correlation between community reports and clinical evidence does not imply causation or therapeutic endorsement.
- Psychedelic and controlled substance evidence is reported factually and does not constitute a legal or clinical endorsement given current regulatory frameworks.
- This project does not constitute medical advice. Treatment decisions should be made in consultation with a qualified medical professional.
Fetches title, authors, abstract and more from PubMed and fills the fields below. You can then attach your PDF and click Add Article.
Fields auto-fill after a lookup above. Or enter everything manually here if the article isn't in PubMed.
If a PDF wasn't downloaded automatically, drop it here to attach it to an existing record. The database Access status will be updated to Downloaded automatically.
Hidden papers remain in the database and XLSX but are removed from the library, search, and all front-end views. They can be restored at any time.
Re-runs synthesise_domains.py
against the current database. Use Incremental after adding new papers — it extracts claims
from only the new papers, merges them with prior claims, and re-synthesises each affected domain.
Requires Ollama to be running locally. Incremental runs finish in minutes; single domain takes 5–15 min;
full re-run takes 1–2 hours.