# Trends and associations of pulmonary nodule detection rates in China, 2019–2023: A multicenter cross-sectional study based on Real-World Data

**Authors:** Jingxin Li, Zhouhua Xie, Yiping Chen, Guiyun Jin, Hua Lin, Qing Xu, Zhong Meng, Lusheng Liang, Huiwei Chen, Sujuan Guo, Xiongwen Li, Hao Li, Maosheng Liu, Youdong Li, Yuanzhuang Liao, Moyu Ming, Shifang Zhou, Yang Wu, Xikui Huang, Wangsheng Deng, Yihan Hou, Jianfeng Zhang, Chaoqian Li, Fumihiro Yamaguchi, Fumihiro Yamaguchi, Fumihiro Yamaguchi

PMC · DOI: 10.1371/journal.pone.0343207 · PLOS One · 2026-02-20

## TL;DR

This study tracks how often lung nodules were detected in China from 2019 to 2023, showing increases during and after the pandemic, possibly linked to AI use and SARS-CoV-2 infections.

## Contribution

The study reveals how pandemic phases and AI adoption influenced trends in pulmonary nodule detection rates across different hospital types in China.

## Key findings

- Pulmonary nodule detection rates surged in 2020−2021 and 2023, with steeper increases in outpatients and males.
- University-affiliated/provincial hospitals showed the sharpest increases in detection rates compared to other hospital tiers.
- AI adoption was linked to rising detection rates, while CT-suspected lung tumors/cancer remained stable and unrelated to nodule trends.

## Abstract

The post-coronavirus disease 2019 (COVID-19) pulmonary sequelae have garnered public concern. We conducted a multicenter cross-sectional study in outpatient and health exam populations from 23 clinical centers (including university-affiliated/provincial general hospitals, municipal general hospitals, county hospitals, and specialized hospitals) in China (2019−2023), to assess temporal trends and potential influencing factors in the detection of CT-diagnosed pulmonary nodules, pleural effusion, pneumonia, and suspected lung tumors, cancer and viral pneumonia, clarifying pandemic impacts on lung health. Dynamic comparisons across key phases including initial outbreak, vaccine rollout, population-wide vaccination, and major adjustment of pandemic control policies, were performed. This study analyzed 1,616,750 clinical samples (1,102,605 outpatient, 514,145 health examination; 885,945 males, 730,805 females). Pulmonary nodule detection rose progressively, with surges in 2020−2021 and 2023, plateauing in 2021−2022. Outpatients and males showed steeper increases. University-affiliated/provincial hospitals had sharpest increases vs. municipal and county tiers. Specialized hospitals matched general hospital rates. AI boosted detection rates. CT-suspected lung tumors/cancer remained low and stable, unrelated to nodule trends. These results underscore 2019−2023 pulmonary nodule detection surges linked to SARS-CoV-2 infections and AI adoption. COVID-19 vaccination did not accelerate detection but may have slowed it short-term. Long-term studies on infection, vaccine impacts and pandemic-detected nodules’ outcomes are urgently needed.

## Linked entities

- **Diseases:** coronavirus disease 2019 (MONDO:0100096), pneumonia (MONDO:0005249), cancer (MONDO:0004992), viral pneumonia (MONDO:0006012)

## Full-text entities

- **Diseases:** cancer (MESH:D009369), -COVID-19 (MESH:D000086382), lung abnormalities (MESH:D008171), lung cancer (MESH:D008175), infected (MESH:D007239), lung injury (MESH:D055370), Pulmonary Nodule (MESH:D055613), anxiety (MESH:D001007), lung nodule (MESH:D003074), CT abnormalities (MESH:D000014), fibrosis (MESH:D005355), respiratory symptoms (MESH:D012818), atelectasis (MESH:D001261), Nodule (MESH:D016606), infectious disease (MESH:D003141), Long COVID (MESH:D000094024), pleural effusion (MESH:D010996), lymphadenopathy (MESH:D008206), opacities (MESH:D003318), pneumonia (MESH:D011014), pulmonary fibrosis (MESH:D011658)
- **Chemicals:** Fumihiro (-)
- **Species:** Homo sapiens (human, species) [taxon 9606], Severe acute respiratory syndrome coronavirus 2 (no rank) [taxon 2697049]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12923060/full.md

## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12923060/full.md

## References

31 references — full list in the complete paper: https://tomesphere.com/paper/PMC12923060/full.md

---
Source: https://tomesphere.com/paper/PMC12923060