ReviewANZ journal of surgery2022
Implementing predictive tools in surgery: A narrative review in the context of orthopaedic surgery.
Review in ANZ journal of surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Artificial Intelligence in Surgery: A Systematic Review of Use and Validation.Journal of clinical medicine · 2024Review
- The ability of artificial intelligence tools to formulate orthopaedic clinical decisions in comparison to human clinicians: An analysis of ChatGPT 3.5, ChatGPT 4, and Bard.Journal of orthopaedics · 2024Article
- Machine learning algorithms to predict risk of postoperative pneumonia in elderly with hip fracture.Journal of orthopaedic surgery and research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Clinical predictive tools are a topic gaining interest. Many tools are developed each year to predict various outcomes in medicine and surgery. However, the proportion of predictive tools that are implemented in clinical practice is small in comparison to the total number of tools developed. This narrative review presents key principles to guide the translation of predictive tools from academic bodies of work into useful tools that complement clinical practice. Our review identified the following principles: (1) identifying a clinical gap, (2) selecting a target user or population, (3) optimizing predictive tool performance, (4) externally validating predictive tools, (5) marketing and disseminating the tool, (6) navigating the challenges of integrating a tool into existing healthcare systems, and (7) developing an ongoing monitoring and evaluation strategy. Although the review focuses on examples in orthopaedic surgery, the principles can be applied to other disciplines in medicine and surgery.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.