Evidence map›Paper›PMID 39040948›Full record

ArticleNorth American Spine Society journal2024

Lumbar disc herniation with radiculopathy: a comparison of NASS guidelines and ChatGPT.

Ankur Kayastha, Kirthika Lakshmanan, Michael J Valentine, Anh Nguyen, Kaushal Dholakia, Daniel Wang

Abstract read
In one paragraph

Article in North American Spine Society journal, 2024. 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

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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.

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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.

Ankur KayasthaKansas City University, Kansas City, MO, United States.
Kirthika LakshmananKansas City University, Kansas City, MO, United States.
Michael J ValentineKansas City University, Kansas City, MO, United States.
Anh NguyenKansas City University, Kansas City, MO, United States.
Kaushal DholakiaKansas City University, Kansas City, MO, United States.
Daniel WangMedStar Health, Baltimore, MD, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: ChatGPT is an advanced language AI able to generate responses to clinical questions regarding lumbar disc herniation with radiculopathy. Artificial intelligence (AI) tools are increasingly being considered to assist clinicians in decision-making. This study compared ChatGPT-3.5 and ChatGPT-4.0 responses to established NASS clinical guidelines and evaluated concordance. Methods: ChatGPT-3.5 and ChatGPT-4.0 were prompted with fifteen questions from The 2012 NASS Clinical Guidelines for the diagnosis and treatment of lumbar disc herniation with radiculopathy. Clinical questions organized into categories were directly entered as unmodified queries into ChatGPT. Language output was assessed by two independent authors on September 26, 2023 based on operationally-defined parameters of accuracy, over-conclusiveness, supplementary, and incompleteness. ChatGPT-3.5 and ChatGPT-4.0 performance was compared via chi-square analyses. Results: Among the fifteen responses produced by ChatGPT-3.5, 7 (47%) were accurate, 7 (47%) were over-conclusive, fifteen (100%) were supplementary, and 6 (40%) were incomplete. For ChatGPT-4.0, ten (67%) were accurate, 5 (33%) were over-conclusive, 10 (67%) were supplementary, and 6 (40%) were incomplete. There was a statistically significant difference in supplementary information (100% vs. 67%; p=.014) between ChatGPT-3.5 and ChatGPT-4.0. Accuracy (47% vs. 67%; p=.269), over-conclusiveness (47% vs. 33%; p=.456), and incompleteness (40% vs. 40%; p=1.000) did not show significant differences between ChatGPT-3.5 and ChatGPT-4.0. ChatGPT-3.5 and ChatGPT-4.0 both yielded 100% accuracy for definition and history and physical examination categories. Diagnostic testing yielded 0% accuracy for ChatGPT-3.5 and 100% accuracy for ChatGPT-4.0. Nonsurgical interventions had 50% accuracy for ChatGPT-3.5 and 63% accuracy for ChatGPT-4.0. Surgical interventions resulted in 0% accuracy for ChatGPT-3.5 and 33% accuracy for ChatGPT-4.0. Conclusions: ChatGPT-4.0 provided less supplementary information and overall higher accuracy in question categories than ChatGPT-3.5. ChatGPT showed reasonable concordance to NASS guidelines, but clinicians should caution use of ChatGPT in its current state as it fails to safeguard against misinformation.

Indexed as

Artificial intelligenceChatGPTClinical guidelinesLumbar disc herniationRadiculopathySciaticaSpine

Identifiers

PMID39040948
PMCPMC11261487

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LicenceCC BY-NC-ND
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Registered trials

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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.