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Record W3122128462 · doi:10.1186/s13643-021-01579-8

Role of preoperative intravenous iron therapy to correct anemia before major surgery: a systematic review and meta-analysis

2021· review· en· W3122128462 on OpenAlexafffund
Abdelsalam M. Elhenawy, Steven Meyer, Sean M. Bagshaw, Roderick MacArthur, Linda Carroll

Bibliographic record

VenueSystematic Reviews · 2021
Typereview
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsMedicineIntravenous ironRandomized controlled trialCochrane LibraryPerioperativeAdverse effectMeta-analysisAnemiaMEDLINEConfidence intervalBlood transfusionInternal medicineSurgeryIron deficiency

Abstract

fetched live from OpenAlex

BACKGROUND: Preoperative anemia is a common comorbidity that often necessitates allogeneic blood transfusion (ABT). As there is a risk associated with blood transfusions, preoperative intravenous iron (IV) has been proposed to increase the hemoglobin to reduce perioperative transfusion; however, randomized controlled trials (RCT) investigating this efficacy for IV iron are small, limited, and inconclusive. Consequently, a meta-analysis that pools these studies may provide new and clinically useful information. METHODS/DESIGN: Databases of MEDLINE, EMBASE, EBM Reviews; Cochrane-controlled trial registry; Scopus; registries of health technology assessment and clinical trials; Web of Science; ProQuest Dissertations and Theses; Clinicaltrials.gov; and Conference Proceedings Citation Index-Science (CPCI-S) were searched. Also, we screened all the retrieved reference lists. SELECTION CRITERIA: Titles and abstracts were screened for relevance (i.e., relevant, irrelevant, or potentially relevant). Then, we screened full texts of those citations identified as potentially applicable. RESULTS: Our search found 3195 citations and ten RCTs (1039 participants) that met our inclusion criteria. Preoperative IV iron supplementation significantly decreases ABT by 16% (risk ratio (RR): 0.84, 95% confidence interval [CI]: 0.71, 0.99, p = 0.04). In addition, preoperatively, hemoglobin levels increased after receiving IV iron (mean difference [MD] between the study groups: 7.15 g/L, 95% CI: 2.26, 12.04 g/L, p = 0.004) and at follow-up > 4 weeks postoperatively (MD: 6.46 g/L, 95% CI: 3.10, 9.81, p = 0.0002). Iron injection was not associated with increased incidence of non-serious or serious adverse effects across groups (RR: 1.13, 95% CI: 0.78, 1.65, p = 0.52) and (RR: 0.96, 95% CI: 0.44, 2.10, p = 0.92) respectively. CONCLUSIONS: With moderate certainty, due to the high risk of bias in some studies in one or two domains, we found intravenous iron supplementation is associated with a significant decrease in the blood transfusions rate, and modest hemoglobin concentrations rise when injected pre-surgery compared with placebo or oral iron supplementation. However, further full-scale randomized controlled trials with robust methodology are required. In particular, the safety, quality of life, and cost-effectiveness of different intravenous iron preparations require further evaluation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.028
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.079
GPT teacher head0.350
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations79
Published2021
Admission routes2
Has abstractyes

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