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GRADE guidelines 6. Rating the quality of evidence—imprecision
Abstract
GRADE suggests that examination of 95% confidence intervals (CIs) provides the optimal primary approach to decisions regarding imprecision. For practice guidelines, rating down the quality of evidence (i.e., confidence in estimates of effect) is required if clinical action would differ if the upper versus the lower boundary of the CI represented the truth. An exception to this rule occurs when an effect is large, and consideration of CIs alone suggests a robust effect, but the total sample size is not large and the number of events is small. Under these circumstances, one should consider rating down for imprecision. To inform this decision, one can calculate the number of patients required for an adequately powered individual trial (termed the "optimal information size" [OIS]). For continuous variables, we suggest a similar process, initially considering the upper and lower limits of the CI, and subsequently calculating an OIS. Systematic reviews require a somewhat different approach. If the 95% CI excludes a relative risk (RR) of 1.0, and the total number of events or patients exceeds the OIS criterion, precision is adequate. If the 95% CI includes appreciable benefit or harm (we suggest an RR of under 0.75 or over 1.25 as a rough guide) rating down for imprecision may be appropriate even if OIS criteria are met.
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“The ERTupdated Cochrane review identi fi ed serious imprecision for 1 outcome -hypoglycemia requiring third-party assistance -because of a few events, well below the required optimal information size (as a rule of thumb, a value of 300 events, assuming modest effect sizes and baseline risks), resulting in the inability to exclude the minimally important clinical difference.”
From KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease (2022) · cites this paper as [135]
In the citing paper
“The overall quality of evidence was graded using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach, considering study limitations, inconsistency, indirectness, imprecision and publication bias [40–44].”
In the citing paper
“On the other hand, if only a few (small) studies are included in an overall effect size, the precision of meta-analytic results may, nevertheless, be low (Guyatt et al., 2011).”
From Meta-analytic evidence on the efficacy of hypnosis for mental and somatic health issues: a 20-year perspective (2024) · cites this paper as Guyatt et al., 2011
In the citing paper
“Quality of evidence in included systematic reviews was assessed by outcome using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system criteria [17-27].”
From Effects of Home Telemonitoring Interventions on Patients With Chronic Heart Failure: An Overview of Systematic Reviews (2015) · cites this paper as [22]
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“To determine the quality of evidence, the GRADE approach was used [29–36].”
In the citing paper
“RCTs are first categorised as high-quality evidence in the GRADE system, while observational studies are classified as low-quality data supporting estimates of intervention effects.”
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Metadata
- Authors
- Guyatt, G. H., Oxman, A. D., Kunz, R., Brozek, J., Alonso-Coello, P., Rind, D., Devereaux, P. J., Montori, V. M., Freyschuss, B., Vist, G., Jaeschke, R., Williams, J. W., Murad, M. H., Sinclair, D., Falck-Ytter, Y., Meerpohl, J., Whittington, C., Thorlund, K., Andrews, J., & Schünemann, H. J.
- Affiliations
- McMaster University (CA)
- Nasjonalt Kunnskapssenter for Helsetjenesten (NO)
- University Hospital of Basel (CH)
- Harvard University (US)
- Karolinska University Hospital (SE)
- Duke Medical Center (US)
- Mayo Clinic (US)
- Liverpool School of Tropical Medicine (GB)
- Case Western Reserve University (US)
- University Medical Center Freiburg (DE)
- University College London (GB)
- Vanderbilt University (US)
- Corresponding author
- Guyatt, Gordon H.
- ORCID
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2011-12
- Volume
- 64
- Issue
- 12
- Pages
- 1283-1293
- ISSN
- 0895-4356 (ISSN-L)
- OpenAlex
- W2090132603
- Cited by
- 2,693
- References
- 31
- Citations by year
- 2026: 189 · 2025: 194 · 2024: 255 · 2023: 217 · 2022: 266 · 2021: 260 · 2020: 224 · 2019: 165 · 2018: 186 · 2017: 179 · 2016: 172 · 2015: 162 · 2014: 96 · 2013: 69 · 2012: 48
- FWCI
- 73.46
- Type
- journal article
- Language
- en
- Update notices
- erratum (2021-09-01)
- Open access
- closed
- Locations
- Journal of Clinical Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Social Sciences › Sociology and Political Science › Delphi Technique in Research
- Keywords
- GRADE, quality of evidence, imprecision, confidence intervals, sample size, number of events, relative risk, continuous outcomes, systematic reviews, clinical guidelines
- MeSH terms
- Humans, Risk, Meta-Analysis as Topic, Confidence Intervals, Randomized Controlled Trials as Topic, Practice Guidelines as Topic, Sample Size, Evidence-Based Medicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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