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Record W4408752605 · doi:10.2196/65271

Assessing Postoperative Pain in Patients Who Underwent Total Knee Arthroplasty Using an Automated Self-Logging Patient-Reported Outcome Measure Collection Device: Retrospective Cohort Study

2025· article· en· W4408752605 on OpenAlexvenueno aff
Prabjit Ajrawat, Blaine Price, Daniel Gooch, Rudolf Serban, R Al-Habsi, Oliver Pearce

Bibliographic record

VenueJMIR Human Factors · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTotal knee arthroplastyRetrospective cohort studyPreprintArthroplastyPhysical therapySurgeryComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Background: Patient-reported outcome measures (PROMs) are tools for assessing symptoms and the quality of care. Despite their growing use, conventional data collection methods limit widespread PROM implementation. In orthopedics, pain is a frequent patient complaint and a common PROM, especially following total knee arthroplasty (TKA). Although TKA is generally successful, some patients still report postoperative pain, potentially due to tourniquet use. Using an improved PROM data-gathering technique may help to address tourniquet use during a TKA procedure and its impact on postoperative pain. The PainPad, an automated self-logging device, was developed to capture patient pain levels accurately. Objective: The aim of the study is to assess the feasibility and effectiveness of the PainPad device in quantifying in-hospital postoperative pain following TKA with or without tourniquet use. Methods: A retrospective study with 234 patients who underwent TKA from 2018 to 2021 at Milton Keynes University Hospital was conducted. Patients were categorized as receiving TKA with an intraoperative tourniquet (tourniquet group) or TKA without a tourniquet (nontourniquet group). Postoperative pain during the first 24 hours was self-reported every 2 hours using the PainPad device. From both groups, data on hospital length of stay, total tourniquet time, and the presence of postoperative deep vein thrombosis were also collected. Results: There were 115 TKAs with tourniquets (72/115, 62.6% female patients; mean age 69.26, SD 9.93 years) and 119 TKAs without tourniquets (91/119, 76.4% female patients; mean age 70.97, SD 9.01 years). When assessing 24-hour mean postoperative pain scores, the PainPad device data indicated no significant difference (P=.53; 95% CI -0.76 to 0.39) between the tourniquet (mean pain score 3.31, SD 2.34) and nontourniquet groups (mean pain score 3.12, SD 2.15). There was no correlation between tourniquet times and the pain scores retrieved from the PainPad device. A subgroup analysis comparing longer (>90 minutes) versus shorter (<90 minutes) tourniquet times showed no significant difference in terms of pain and length of stay. Conclusions: The PainPad device is a feasible and effective method for collecting and evaluating in-hospital postoperative pain following TKA, allowing for the quantification of individual pain levels. This study aligns with the current health care trend toward leveraging innovative technologies and personalized data to enhance patient-centered care.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.339
Teacher spread0.307 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2025
Admission routes1
Has abstractyes

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