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the claim

A quantifiable number of paper abstracts are read when preparing a clinical systematic review

the verdict
SUPPORTED
the evidence backs this
Recorded sources
6 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that a quantifiable number of paper abstracts are read when preparing a clinical systematic review?

Yes. Multiple clinical systematic reviews report quantifiable numbers of paper abstracts and records screened during their literature review processes.

Verdict: SUPPORTED · 6 sources for, 0 against · Last checked

The analysis

The claim states that a quantifiable number of paper abstracts are read when preparing a clinical systematic review. All selected papers demonstrate this by explicitly stating the exact number of records or abstracts screened in various clinical systematic reviews (e.g., 1,381 and 3,146 in one study; 82,346 in one study; 1,873 in one study; 505 in one study; and 15,307 in one study). There is no contradictory evidence in the provided literature.

Evidence for · 6
Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews
2024
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Matsui, K., Utsumi, T., Aoki, Y., Maruki, T., Takeshima, M., & Takaesu, Y. (2024). Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews. doi.org. https://doi.org/10.2196/52758

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More for · 5
Challenges for Data Quality in the Clinical Data Life Cycle: Systematic Review
2024
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An, D., Lim, M., & Lee, S. (2024). Challenges for Data Quality in the Clinical Data Life Cycle: Systematic Review. doi.org. https://doi.org/10.2196/60709

Override rate of drug-drug interaction alerts in clinical decision support systems: A brief systematic review and meta-analysis
2024
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Felisberto, M., Lima, G. D. S., Celuppi, I. C., Fantonelli, M. d. S., Zanotto, W. L., Oliveira, J. M. D. d., Mohr, E. T. B., Santos, R. A. d., Scandolara, D., Cunha, C. L., Hammes, J. F., Rosa, J. D. d., Demarchi, I. G., Wazlawick, R., & Dalmarco, E. (2024). Override rate of drug-drug interaction alerts in clinical decision support systems: A brief systematic review and meta-analysis. doi.org. https://doi.org/10.1177/14604582241263242

Cardiopulmonary resuscitation coaching for resuscitation teams: A systematic review
2025
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Lauridsen, K. G., Bürgstein, E., Nabecker, S., Lin, Y., Donoghue, A., Duff, J. P., & Cheng, A. (2025). Cardiopulmonary resuscitation coaching for resuscitation teams: A systematic review. doi.org. https://doi.org/10.1016/j.resplu.2025.100868

The impact of midwife workload on delivery of care, and mother and baby outcomes in maternity settings in OECD countries: A systematic review
2025
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Mattock, R., Bojke, C., Wright, J., & Stacey, T. (2025). The impact of midwife workload on delivery of care, and mother and baby outcomes in maternity settings in OECD countries: A systematic review. doi.org. https://doi.org/10.1371/journal.pone.0329117

Capability of chatbots powered by large language models to support the screening process of scoping reviews: a feasibility study.
2026
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K, N., M, S., S, S., & F, F. (2026). Capability of chatbots powered by large language models to support the screening process of scoping reviews: a feasibility study.. doi.org. https://doi.org/10.1093/jamiaopen/ooaf098

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Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 8504 Aug 2026
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