Evidence map›Paper›PMID 36162928›Full record

ArticleThe Journal of arthroplasty2022

Avoiding Systematic Bias in Orthopedics Research Through Informed Variable Selection: A Discussion of Confounders, Mediators, and Colliders.

Katrina L Devick, Isabella Zaniletti, Dirk R Larson, David G Lewallen, Daniel J Berry, Hilal Maradit Kremers

Abstract read
In one paragraph

Article in The Journal of arthroplasty, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Observational
  5. Review
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.

Katrina L DevickDepartment of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona.
Isabella ZanilettiDepartment of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona.
Dirk R LarsonDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota.
David G LewallenDepartment of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
Daniel J BerryDepartment of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
Hilal Maradit KremersDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.

Funding

Resource CoreP30AR076312 · NIAMS · MAYO CLINIC ROCHESTER · PI Daniel Berry · 2019 to 2026
$5.5M
RISK OF COGNITIVE IMPAIRMENT AND DEMENTIA IN TOTAL JOINT ARTHROPLASTYR01AG060920 · NIA · MAYO CLINIC ROCHESTER · PI MARADIT KREMERS, HILAL · 2019 to 2023
$3.6M
Precision Orthopedics: Multimodal Data Infrastructure for Personalized Surgical Decisions in Joint ArthroplastyR01AR073147 · NIAMS · MAYO CLINIC ROCHESTER · PI Hilal Maradit Kremers · 2018 to 2026
$3.5M
Cardiotoxicity in Total Joint ArthroplastyR01HL147155 · NHLBI · MAYO CLINIC ROCHESTER · PI MARADIT KREMERS, HILAL · 2019 to 2022
$2.8M
NHLBI NIH HHS R01 HL147155NIAMS NIH HHS P30 AR076312NIAMS NIH HHS R01 AR073147NIA NIH HHS R01 AG060920
6 · The paper itself

Abstract

There are 3 common variable types in orthopedic research-confounders, colliders, and mediators. All 3 types of variables are associated with both the exposure (eg, surgery type, implant type, body mass index) and outcome (eg, complications, revision surgery) but differ in their temporal ordering. To reduce systematic bias, the decision to include or exclude a variable in an analysis should be based on the variable's relationship with the exposure and outcome for each research question. In this article, we define 3 types of variables with case examples from orthopedic research. Please visit the followinghttps://youtu.be/V-grpgB1ShQfor videos that explain the highlights of the article in practical terms.

Indexed as

Orthopedic ProceduresOrthopedicsBiasHumansconfoundingdatabasesdirected acyclic graphmediation analysisselection biastotal joint arthroplasty

Identifiers

PMID36162928
PMCPMC9616679

What OpenQuestion holds

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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.