Retrospective Bias
Research gap analysis derived from 5 medicine papers in our local library.
The gap
Most studies rely on retrospective data collection methods, which may introduce selection and recall biases. Future research should focus on prospective validation.
Consensus across the literature
The papers collectively establish the presence of bias in retrospective studies but leave open the specific mechanisms and impacts of these biases.
Research trend
Emerging — attention growing, methods still coalescing.
Supporting evidence — 5 representative gaps
- Case Report: Hypereosinophilic syndrome misdiagnosed as atopic dermatitis due to refractory pruritic rash masking peripheral neuropathy (2026) · doi
Structured neurological outcome measures were not prospectively applied, and pruritus severity was retrospectively quantified, which may introduce recall bias.
Keywords: structured neurological outcome measures prospectively applied pruritus severity retrospectively quantified introduce recall bias - A deep learning model based on multiphase DCE-MRI for preoperative prediction of Ki-67 expression in breast cancer (2026) · doi
The study was conducted retrospectively at a single institution. The use of historical data may introduce selection bias, and future efforts should involve prospective, multi-center validation.
Keywords: conducted retrospectively single institution historical introduce selection bias future efforts involve prospective multi center validation - AI-assisted 3D preoperative planning in primary total hip arthroplasty for secondary hip osteoarthritis: etiology-specific perioperative burden and early recovery in DDH versus post-septic sequelae (2026) · doi
The long inclusion period may introduce temporal bias, and no formal early-versus-late comparison was performed to quantify potential learning-curve effects.
Keywords: long inclusion period introduce temporal bias formal early versus late comparison performed quantify potential learning - Global insights into pediatric ischemic stroke: a bibliometric and visualization analysis (2026) · doi
The bibliometric analysis relied on software-based algorithms, which may introduce certain biases in clustering and visualization.
Keywords: bibliometric relied software based algorithms introduce certain biases clustering visualization - Comparative evaluation of bipolar versus monopolar energy platforms in G-POEM for gastroparesis: technical performance, learning curves, and clinical outcomes (2026) · doi
This was a retrospective, single-center study, which may limit the generalizability of findings and introduce potential selection bias.
Keywords: retrospective single center limit generalizability introduce potential selection bias
Explore this gap further
Search “Retrospective Bias” across open scholarly engines for the latest related literature.
Working on this gap? Publish with us.
Science AI Journal reviews manuscripts in under 15 minutes with 8 specialised AI reviewers calibrated on 23,000+ real peer reviews. Open access, CC BY 4.0.
Free tools for your next paper
Related gaps in Medicine
- Liability and legal frameworks for organizations using AI in clinical decision-making processes require development and clarification.Liability and legal frameworks for organizations using AI in clinical decision-making processes require development and clarification.
- Recent literature from 2025 to 2026 has firmly established AI as a core driver in the methodological evolution of precision oncology for HCC. By implementing VFMs to mitigate imaging domain shifts andRecent literature from 2025 to 2026 has firmly established AI as a core driver in the methodological evolution of precision oncology for HCC.…
- PURPOSE: The aim of this review was to critically appraise the literature on the use of antibiotics to treat peri-implantitis, with the ultimate goal of supporting evidence-based clinical recommendatiPURPOSE: The aim of this review was to critically appraise the literature on the use of antibiotics to treat peri-implantitis, with the ulti…
- External validation is required before the model can be applied in clinical settings.External validation is required before the model can be applied in clinical settings.