Supplementary file 1_Clinical characteristics, diagnosis, treatment, and prognosis of ritu
by Yi Huang·Updated 2mo ago
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Description
Yi Huang's supplementary data file contains a retrospective analysis of 39 reported cases of rituximab-induced serum sickness (RISS). The dataset was published on figshare in April 2026 and includes aggregated clinical characteristics, diagnostic markers, treatments, and prognoses extracted from 30 articles. It synthesizes case reports and series from databases including PubMed, EMBASE, Web of Science, WanFang Data, and CNKI.
Use Cases
Characterize the clinical presentation of RISS based on reported symptoms like arthralgia, fever, and rash.
Analyze treatment efficacy and recovery timelines based on reported corticosteroid use and median recovery time.
Assess risk factors for recurrence based on rechallenge data and recurrence rates.
Investigate diagnostic markers for RISS based on reported anti-rituximab antibody positivity and complement consumption.
Strengths
Aggregates data from 39 patients across 30 published articles, providing a consolidated view of a rare condition.
Includes specific clinical statistics: median age (33 years), female predominance (71.8%), and median symptom onset time (7 days).
Reports detailed outcome metrics: 82.1% complete recovery rate and median recovery time of 3.0 days.
Limitations
Row count is unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
Data is derived from published case reports, which may reflect publication bias.
Provenance
Source
figshare, author Yi Huang.
Collection Method
Retrospective analysis and data extraction from published case reports and series.
Time Range
Articles published up to November 2025.
Freshness
Last updated 2026-04-13 05:47:23; freshness should be verified.
Geography
Global, as sources include international (PubMed, EMBASE) and Chinese (WanFang, CNKI) databases.
File format is DOCX, which may require specific software for access; data is likely embedded in tables within the document.