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Objective <p>To evaluate ChatGPT-4o’s diagnostic accuracy for fever of unknown origin (FUO) compared to emergency physicians and assess its utility as an adjunctive diagnostic tool.</p> Methods <p>This retrospective analysis included 60 adult patients presenting to the emergency department (ED) with FUO (fever ≥ 38.3℃ for ≥ 3 weeks without diagnosis after initial evaluation). Only patients with a confirmed final discharge diagnosis were included; FUO cases remaining undiagnosed at discharge were excluded. ChatGPT-4o and emergency medicine (EM) physicians independently generated preliminary diagnoses and comprehensive diagnoses. Diagnostic accuracy was compared against final discharge diagnoses. EM physicians subsequently revised their diagnoses after reviewing ChatGPT-4o’s output. Statistical analysis employed Welch’s ANOVA.</p> Results <p>ChatGPT-4o significantly outperformed EM residents in both preliminary (70.0% vs. 46.11%; 95% CI, 57.6%-79.9% vs. 34.4%-59.3%, <i>P</i> = 0.008) and comprehensive diagnoses (75.0% vs. 55.0%, 95% CI, 62.9%-84.1% vs. 42.5%-66.9%, <i>P</i> = 0.002). While numerically higher than EM specialists in both preliminary (70.0% vs. 57.78%) and comprehensive diagnoses (75.0% vs. 68.89%), these differences did not demonstrate consistent statistical superiority. Incorporating ChatGPT-4o’s suggestions significantly improved accuracy for both EM residents (preliminary: 67.78% vs. 46.11%, 95% CI, 55.8%-78.6% vs. 34.4%-59.3%, <i>P</i> = 0.002; comprehensive: 78.33% vs. 55.0%, 95% CI, 66.8%-86.6% vs. 42.5%-66.9%, <i>P</i> = 0.01) and specialists (preliminary: 70.22% vs. 57.78%, <i>P</i> = 0.023), though the improvement in specialists’ comprehensive diagnoses remained non-significant (80.89% vs. 66.67%, <i>P</i> = 0.076). Stratified analysis showed that ChatGPT-4o significantly improved diagnostic accuracy across major etiologic categories, including infectious (76.0% vs. 59.4%, <i>P</i> = 0.003) and cancer-related causes (72.2% vs. 50.0%, <i>P</i> &lt; 0.001).</p> Conclusions <p>ChatGPT-4o demonstrates potential to augment FUO diagnosis, particularly aiding less experienced clinicians. While this study highlights AI’s complementary value, prospective trials are needed to validate its impact on clinical efficiency.</p>

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ChatGPT-4o assists emergency physicians in enhancing diagnostic accuracy for fever of unknown origin: retrospective analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月10日

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  • Hui Long,
  • Guoqing Huang,
  • Xinbo Yin,
  • Xiaojie Zheng,
  • Sijia Cao,
  • Nan Wang,
  • Xiangmin Li,
  • Xiaokai Wang

摘要

Objective

To evaluate ChatGPT-4o’s diagnostic accuracy for fever of unknown origin (FUO) compared to emergency physicians and assess its utility as an adjunctive diagnostic tool.

Methods

This retrospective analysis included 60 adult patients presenting to the emergency department (ED) with FUO (fever ≥ 38.3℃ for ≥ 3 weeks without diagnosis after initial evaluation). Only patients with a confirmed final discharge diagnosis were included; FUO cases remaining undiagnosed at discharge were excluded. ChatGPT-4o and emergency medicine (EM) physicians independently generated preliminary diagnoses and comprehensive diagnoses. Diagnostic accuracy was compared against final discharge diagnoses. EM physicians subsequently revised their diagnoses after reviewing ChatGPT-4o’s output. Statistical analysis employed Welch’s ANOVA.

Results

ChatGPT-4o significantly outperformed EM residents in both preliminary (70.0% vs. 46.11%; 95% CI, 57.6%-79.9% vs. 34.4%-59.3%, P = 0.008) and comprehensive diagnoses (75.0% vs. 55.0%, 95% CI, 62.9%-84.1% vs. 42.5%-66.9%, P = 0.002). While numerically higher than EM specialists in both preliminary (70.0% vs. 57.78%) and comprehensive diagnoses (75.0% vs. 68.89%), these differences did not demonstrate consistent statistical superiority. Incorporating ChatGPT-4o’s suggestions significantly improved accuracy for both EM residents (preliminary: 67.78% vs. 46.11%, 95% CI, 55.8%-78.6% vs. 34.4%-59.3%, P = 0.002; comprehensive: 78.33% vs. 55.0%, 95% CI, 66.8%-86.6% vs. 42.5%-66.9%, P = 0.01) and specialists (preliminary: 70.22% vs. 57.78%, P = 0.023), though the improvement in specialists’ comprehensive diagnoses remained non-significant (80.89% vs. 66.67%, P = 0.076). Stratified analysis showed that ChatGPT-4o significantly improved diagnostic accuracy across major etiologic categories, including infectious (76.0% vs. 59.4%, P = 0.003) and cancer-related causes (72.2% vs. 50.0%, P < 0.001).

Conclusions

ChatGPT-4o demonstrates potential to augment FUO diagnosis, particularly aiding less experienced clinicians. While this study highlights AI’s complementary value, prospective trials are needed to validate its impact on clinical efficiency.