Evidence map›Paper›PMID 42821076›Full record

ArticleInternational orthopaedics2026

Determining the learning curve for anterolateral supine total hip arthroplasty: a retrospective analysis of six hundred and forty consecutive cases performed by a single surgeon.

Shigeru Murasawa, Yuki Asanuma

Abstract read
PubMed Publisher
In one paragraph

Article in International orthopaedics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Shigeru MurasawaJoint Replacement Center, Reiwa Arakawa Hospital, Tokyo, Japan. s.murasawa@reiwa-arakawa.jp.
Yuki AsanumaDepartment of Orthopaedics, Musashino Red Cross Hospital, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo characterize the learning curve for single-surgeon performed anterolateral supine (ALS)-total hip arthroplasty (THA).

methodsWe analysed 640 consecutive primary ALS-THAs performed between April 2017 and August 2024, including procedures performed with supervised assistance during 2017-2019. Operative time (OT), blood loss (BL), and complication rate (CR) were evaluated. Temporal trends in OT and BL were assessed using cumulative sum (CUSUM) analysis, and a data-driven single change-point analysis was performed for CR using 100,000 Monte Carlo permutations. Firth's penalised logistic regression assessed the association between continuous case numbers and complications after adjustment for age, sex, and American Society of Anesthesiologists (ASA) physical status.

resultsOT and BL CUSUM curves peaked at cases 411 and 437, respectively. Mean OT decreased from 74.8 to 66.3 min and BL from 251.6 to 184.6 mL between 2022-2023 (both Holm-adjusted P < 0.001). Nine cases (1.4%) experienced 11 complication events. The estimated CR change point was case 281, with pre- and post-point CRs of 2.8% and 0.3%, respectively, but the permutation test was not significant (P = 0.1021). Increasing experience was associated with lower early complication odds after adjustment (odds ratio 0.64 per 100-case increase, 95% confidence interval 0.40-0.94; P = 0.023).

conclusionThe ALS-THA learning curve varied by outcome, with operative efficiency improving after approximately 400 procedures. Increasing experience was associated with lower odds of early complications, supporting outcome-specific rather than single-threshold assessment.

Indexed as

Anterolateral supine approachComplication rateLearning curveSupervisionTotal hip arthroplasty

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.