NCT07766213: Pain Phenotypes in Individuals With Multiple Sclerosis
Study Design & Technical Specifications
Sample Size / Cohort
60 Participants
Subject / Study Model
Human Clinical Cohort
Analytical Modalities
Primary Abstract & Repository Description
Source: ClinicalTrials.gov (NIH/NLM)Editorial Critique, Methodological Value & Reusability Guide
1. Scientific Context & Premise
Primary Premise (ClinicalTrials.gov (NIH/NLM)): "This observational cross-sectional study aims to determine chronic pain phenotypes in individuals with multiple sclerosis (MS) and to investigate the clinical characteristics associated with different pain phenotypes." Within Multiple Sclerosis (MS), this work examines NCT07766213, Observational / Cohort, RECRUITING, Pain classification method in relation to paramagnetic rim lesions (PRLs), T2/FLAIR lesion volume, oligoclonal bands, EBV titers, and EDSS progression metrics. Authored by Kutahya Health Sciences University.
2. Study Architecture & Findings
Study Architecture: Human Clinical Cohort (60 Participants) utilizing Clinical Trial Protocol, Observational / Cohort, Therapeutic Intervention. Key reported conclusion: "The clinical characteristics of participants with different pain phenotypes will subsequently be compared."
3. Secondary Analysis & Reusability
Secondary Analysis Applications: (1) Cross-referencing Clinical Trial Protocol, Observational / Cohort, Therapeutic Intervention variables (NCT07766213, Observational / Cohort, RECRUITING, Pain classification method) against open repositories in Multiple Sclerosis (MS); (2) Benchmarking feature distributions and effect sizes reported in "NCT07766213: Pain Phenotypes in Individuals With Multiple Sclerosis"; (3) Informing cohort stratification and endpoint selection.
4. Methodological Caveats & Governance
Methodological Note: When integrating these Clinical Trial Protocol, Observational / Cohort, Therapeutic Intervention findings, account for cohort-specific inclusion criteria (60 Participants), potential site/instrument batch effects, and repository license terms (NLM Public Domain Open Registry).
Data Access, Reproducibility & Analysis Starter Guide
FAIR Open Science & Clinical Metadata Verification Protocol
Quick Data Access & Structured Export
Open the primary repository directly or download structured metadata (JSON / CSV) in one click.
This resource is indexed under FAIR (Findable, Accessible, Interoperable, and Reusable) open-science metadata standards, enabling programmatic cross-referencing across Europe PMC, Semantic Scholar, ClinicalTrials.gov, and CNS Open Data.
Programmatic Data Retrieval (Python Starter Code & Recommended SDKs)
Python Quickstart: Query Europe PMC & Semantic Scholar Metadata
# Fetch structured bibliographic & open-access data via Europe PMC REST API
import urllib.request
import urllib.parse
import json
query = "NCT07766213: Pain Phenotypes in Individuals With Multiple Sclerosis"
url = f"https://www.ebi.ac.uk/europepmc/webservices/rest/search?query={urllib.parse.quote(query)}&format=json&resultType=core"
with urllib.request.urlopen(url, timeout=10) as response:
payload = json.loads(response.read().decode("utf-8"))
results = payload.get("resultList", {}).get("result", [])
if results:
record = results[0]
print("Title:", record.get("title"))
print("Journal / Source:", record.get("journalTitle") or record.get("bookOrReportDetails"))
print("Cited By Count:", record.get("citedByCount", 0))Standardized 4-Step Workflow & Governance Checklist
Standardized Acquisition & Preprocessing Workflow
1. Programmatic Metadata & Full-Text OA Retrieval
Query Europe PMC or Crossref REST APIs using the persistent DOI/URL to retrieve structured XML full text, supplementary tables, and grant links.
2. Study Design & Cohort Eligibility Screening
Extract sample size, inclusion/exclusion criteria, and primary outcome endpoints for systematic review (PRISMA) inclusion.
3. Data Availability & Supplementary Repository Linkage
Locate accession numbers (GEO, SRA, OpenNeuro, DANDI, Zenodo, Figshare) referenced in the Data Availability section.
4. Citation Graph & Replication Tracking
Monitor supporting and contrasting citations over time to verify whether key findings have been independently replicated.
Reproducibility & Governance Checklist
- Verify whether the source is a peer-reviewed journal publication or an unrefereed preprint before clinical citation.
- Check supplementary data licenses (CC-BY / CC0) when extracting figures or summary statistics for meta-analyses.
- Cross-reference NCT clinical trial identifiers when evaluating therapeutic efficacy or biomarker endpoints.
Tags & Modalities
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Academic Research & Medical Information Disclaimer
This page provides structured scientific metadata, methodological critiques, and open-data reusability guidelines intended strictly for neuroscience researchers and data scientists. It does not constitute medical advice, clinical diagnosis, or treatment recommendations.
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