ReviewInternational orthopaedics2026
Improving the design of observational studies in orthopaedics: a practical guide to target trial emulation.
Review in International orthopaedics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo explain how target trial emulation can help orthopaedic researchers design observational studies that are more clinically interpretable and less vulnerable to avoidable design bias.
methodsWe provide a methodological overview of target trial emulation for orthopaedic research, using the comparison of postoperative outcomes after total hip arthroplasty versus bipolar hemiarthroplasty for hip fracture as an illustrative example. The review focused on translating a causal question into a target trial protocol, how conventional observational designs can introduce bias, and how routinely collected data can be used to emulate a target trial when key design conditions are met.
resultsTarget trial emulation begins by specifying the clinical question, hypothetical trial, and assumptions required for causal interpretation. This explicit specification is particularly relevant to orthopaedic observational research, wherein treatment decisions are often influenced by prognosis, functional status, surgeon judgment, and institutional context. Conventional observational analyses may be difficult to interpret when the eligibility criteria include patients for whom one treatment is not realistic, treatment labels combine important procedural variations, treatment assignment and follow-up are not aligned at time zero, or post-baseline information is used to modify follow-up or exclude patients. This framework can emphasise these problems before analysis, although it cannot overcome residual confounding, poor measurement, informative loss to follow-up, or other data limitations.
conclusionsTarget trial emulation can guide observational studies' design around treatment decisions encountered in routine practice. Its application may help orthopaedic researchers produce studies that are more transparent, clinically interpretable, and better aligned with decision-making in practice.
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