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Record W7129105185 · doi:10.1093/asjof/ojaf146

Response by Hadid et al to “Hemostatic Nets in Facelifts: A Systematic Review and Meta-Analysis of Postoperative Complications and Patient Outcomes” by Caimi et al

2025· article· en· W7129105185 on OpenAlex
Karam Hadid, Forrest Bohler, Kongkrit Chaiyasate

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAesthetic Surgery Journal Open Forum · 2025
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsComplicationMEDLINEDiabetes mellitusDisease

Abstract

fetched live from OpenAlex

We read with interest the recent article by Caimi et al, “Hemostatic Nets in Facelifts: A Systematic Review and Meta-Analysis of Postoperative Complications and Patient Outcomes.”1 While the topic is of clinical relevance, we identified several methodological concerns that we believe undermine the reliability of the authors’ conclusions. Most notably, 2 of the included studies by Auersvald et al (2012 and 2014) appear to draw from overlapping patient populations.2,3 Both originate from the same surgeon and institution, cover overlapping study periods, and, most strikingly, report control groups of identical size (n = 120), identical mean age to 2 decimal places (55.40 years), and identical age range (33-77 years) as seen in the paper's Table 1.1 The probability of these parameters being identical in 2 independent control cohorts is extremely low, strongly suggesting that the same patients were included in both publications. Inclusion of these likely duplicate patients appears to have had a significant influence on the reported meta-analytic results. For example, 57.4% (651/1135) of patients contributing to the pooled hematoma rate in Figure 2, and as many as 89.1% (651/731) of those in the transient postoperative changes analysis in Figure 4, are likely duplicates from overlapping patient cohorts. If confirmed that these cohorts are overlapping, we respectfully suggest that the authors reanalyze their data in a response letter with one of the studies removed to provide an accurate and unbiased synthesis. Further, the risk-of-bias assessment raises concerns. The authors applied the Newcastle-Ottawa Scale uniformly to all included studies, despite substantial variation in study design, including a randomized controlled trial, prospective-retrospective cohort studies, and an uncontrolled case series. The Newcastle-Ottawa Scale is not validated for randomized trials or case series, and its use in these contexts produces misleading quality scores and creates false equivalence between fundamentally different levels of evidence.4 Established, design-specific tools such as the Cochrane RoB 2 for randomized trials and JBI checklists for case series would have provided a more accurate and defensible evaluation of bias.5 Given these issues, particularly the apparent duplication of patient data, we urge caution in interpreting the reported findings. Addressing these concerns in future meta-analyses will be critical to ensuring that conclusions about the efficacy and safety of hemostatic nets are both robust and reproducible. The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article. The authors received no financial support for the research, authorship, and publication of this article.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablemedium
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.011
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.379
Teacher spread0.337 · 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