Evidence map›Paper›PMID 40034607›Full record

ArticleOrthopaedic journal of sports medicine2025

Reason Profiles for not Returning to Preinjury Activity Level Following Anterior Cruciate Ligament Reconstruction- A Latent Class Analysis With Subgroup Comparison of Patient-Reported Outcome Measures.

Joseph D Lamplot, Erich J Petushek, Camryn B Petit, Shayla M Warren, Kim D Barber Foss, Alexis B Slutsky-Ganesh, Melanie Valencia, Charles D Kenyon, April L McPherson, John W Xerogeanes and 2 more

Abstract read
In one paragraph

Article in Orthopaedic journal of sports medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Biopsychosocial profiles following ACL reconstruction: A latent class analysis of barriers to return-to-activity.Physical therapy in sport : official journal of the Association of Chartered Physiotherapists in Sports Medicine · 2025
    Article
  2. Article
  3. Article
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

12 authors.

Joseph D LamplotEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
Erich J PetushekDepartment of Psychology and Human Factors, Michigan Technological University, Houghton, Michigan, USA.ORCID https://orcid.org/0000-0001-6837-5229
Camryn B PetitEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
Shayla M WarrenEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
Kim D Barber FossEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
Alexis B Slutsky-GaneshEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
Melanie ValenciaEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
Charles D KenyonEmory Sports Medicine Center, Atlanta, Georgia, USA.
April L McPhersonEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
John W XerogeanesEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.
Gregory D MyerEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.ORCID https://orcid.org/0000-0002-9983-8422
Jed A DiekfussEmory Sports Performance And Research Center, Flowery Branch, Georgia, USA.ORCID https://orcid.org/0000-0003-3835-363X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Given the high proportion of athletes who do not return to sports (RTS) after anterior cruciate ligament reconstruction (ACLR), strategies are needed to identify at-risk patients and optimize rehabilitation for successful RTS after ACLR. Purpose/Hypothesis: This study used latent class analysis (LCA) to characterize a unique clustering of reasons why athletes do not return to their preinjury activity level after ACLR. We hypothesized that patients with high pain scores and high levels of fear would be less likely to return to their preinjury activity level. Study Design: Cohort study; Level of evidence, 3. Methods: All patients at a single institution who underwent primary ACLR between 2005 and 2021 were contacted to complete a survey via REDCap. Patients' ability to RTS and their preinjury activity level, reasons for inability to return to the preinjury activity level, and patient-reported outcome scores were collected from 981 patients. LCA was performed to identify and compare patterns among patients' reasons for not returning to the preinjury activity level. Results: Of the 981 patients included, only 446 (45.5%) were fully able to return to their preinjury activity level. LCA categorized patients into 3 groups based on their reasons for not returning to preinjury activity levels: a high-function group (75.5%), which reported no barriers; a multisymptom group (16.1%), which cited pain, lack of strength, and instability; and a fear-limited group (8.4%), which reported fear as the sole reason. Among the high-function group, 86.2% reported RTS compared with <36.7% in the other classes. There was no difference in Knee injury and Osteoarthritis Outcome Score (KOOS) subscales-including Pain, Symptoms, or Activities of Daily Living-between the high-function and fear-limited groups; however, the multisymptom group presented with the lowest scores in all KOOS subscales ( Conclusion: Patients were differentiated into 3 distinct classes after primary ACLR. Furthermore, those with patient-reported characteristics of pain, lack of strength, instability, or fear were significantly less likely to return to their preinjury activity level or sport.

Indexed as

anterior cruciate ligamentkinesiophobiaknee ligamentslatent class analysispatient-reported outcome measurespsychological readinessreturn to sports

Identifiers

PMID40034607
PMCPMC11872736

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Registered trials

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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.