Sinus tarsi approach versus extensile lateral approach for displaced intra-articular calcaneal fracture: a meta-analysis of current evidence base
Bibliographic record
Abstract
The extensile lateral approach (ELA) has been widely performed for displaced intra-articular calcaneal fractures (DIACFs), and wound complications remain a significant problem. As a minimal incision technique, the sinus tarsi approach (STA) was designed to overcome this disadvantage. There were already many reports about this approach but the conclusions were not completely consistent. Based on the current evidence, we performed this meta-analysis to compare the STA with ELA in the management of DIACF and expected to draw a certain and meaningful conclusion. All potentially relevant randomized controlled trials (RCTs) and cohort studies (CSs) were searched in the databases of PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrial.gov. The desirable outcomes including wound complications, excellent and good rate, secondary surgery rate and Böhler’s angle were extracted. RCT studies were assessed using the Risk of Bias Tool recommended by the Cochrane Collaboration, and cohort studies were evaluated using the Newcastle–Ottawa Scale. The data of RCTs and cohorts were pooled respectively using the fixed-effect model or random-effect model. Mean differences with 95% confidence intervals (CIs) were calculated for continuous data, and relative risks (RRs) with 95% CIs were calculated for dichotomous data. Statistical heterogeneity was assessed with the Q test and I 2 . Sensitivity analysis was developed to assess the reliability of pooled results. Seven studies including two RCTs and five CSs were eligible for the meta-analysis. No matter RCTs or CSs, the pooled data all showed that STA group had a lower incidence of wound complications than that in the ELA group and no significant difference was found in excellent and good rate and the recovery of Böhler’s angle between the two groups. The CSs also showed that the STA group had a lower incidence of secondary surgeries than that in the ELA group. Through a STA, we not only can reduce the problems in wound healing but also achieve nearly the same adequate restoration of DIACF along with the similar functional outcomes compared with through an ELA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.054 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".