Evidence map›Paper›PMID 34787694›Full record

ArticleArchives of orthopaedic and trauma surgery2023

Can extant comorbidity indices identify patients who experience poor outcomes following total joint arthroplasty?

Kara M McConaghy, Melissa N Orr, Ahmed K Emara, SaTia T Sinclair, Alison K Klika, Nicolas S Piuzzi

Abstract read
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In one paragraph

Article in Archives of orthopaedic and trauma surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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  7. MRI use leading up to total knee arthroplasty: a retrospective cohort study.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2024
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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

6 authors at 2 institutions in 1 country.

Kara M McConaghyCase Western Reserve University School of Medicine, 9501 Euclid Avenue, Cleveland, OH, 44106, USA.
Melissa N OrrDepartment of Orthopaedic Surgery, Orthopaedic and Rheumatology Institute, Cleveland Clinic, 9500 Euclid Avenue, A41, Cleveland, OH, 44195, USA.
Ahmed K EmaraDepartment of Orthopaedic Surgery, Orthopaedic and Rheumatology Institute, Cleveland Clinic, 9500 Euclid Avenue, A41, Cleveland, OH, 44195, USA.
SaTia T SinclairDepartment of Orthopaedic Surgery, Orthopaedic and Rheumatology Institute, Cleveland Clinic, 9500 Euclid Avenue, A41, Cleveland, OH, 44195, USA.
Alison K KlikaDepartment of Orthopaedic Surgery, Orthopaedic and Rheumatology Institute, Cleveland Clinic, 9500 Euclid Avenue, A41, Cleveland, OH, 44195, USA.
Nicolas S PiuzziDepartment of Orthopaedic Surgery, Orthopaedic and Rheumatology Institute, Cleveland Clinic, 9500 Euclid Avenue, A41, Cleveland, OH, 44195, USA. piuzzin@ccf.org.ORCID http://orcid.org/0000-0003-3007-7538
Cleveland Clinic · USUniversity School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIt is uncertain if generic comorbidity indices commonly used in orthopedics accurately predict outcomes after total hip (THA) or knee arthroplasty (TKA). The purpose of this study was to determine the predictive ability of such comorbidity indices for: (1) 30-day mortality; (2) 30-day rate of major and minor complications; (3) discharge disposition; and (4) extended length of stay (LOS).

methodsThe American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was retrospectively reviewed for all patients who underwent elective THA (n = 202,488) or TKA (n = 230,823) from 2011 to 2019. The American Society of Anesthesiologists (ASA) physical status classification system score, modified Charlson Comorbidity Index (mCCI), Elixhauser Comorbidity Measure (ECM), and 5-Factor Modified Frailty Index (mFI-5) were calculated for each patient. Logistic regression models predicting 30-day mortality, discharge disposition, LOS greater than 1 day, and 30-day major and minor complications were fit for each index.

resultsThe ASA classification (C-statistic = 0.773 for THA and TKA) and mCCI (THA: c-statistic = 0.781; TKA: C-statistic = 0.771) were good models for predicting 30-day mortality. However, ASA and mCCI were not predictive of major and minor complications, discharge disposition, or LOS. The ECM and mFI-5 did not reliably predict any outcomes of interest.

conclusionASA and mCCI are good models for predicting 30-day mortality after THA and TKA. However, similar to ECM and mFI-5, these generic comorbidity risk-assessment tools do not adequately predict 30-day postoperative outcomes or in-hospital metrics. This highlights the need for an updated, data-driven approach for standardized comorbidity reporting and risk assessment in arthroplasty.

Indexed as

Arthroplasty, Replacement, HipArthroplasty, Replacement, KneeComorbidityHumansLength of StayPostoperative ComplicationsRetrospective StudiesRisk AssessmentRisk FactorsArthroplastyComorbiditiesHipKneeOutcomesValue-based care

Identifiers

PMID34787694
OpenAlexW3214622905

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.