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Optimizing the Yield of Abnormal Preoperative Chest Radiographs in Elective Non-cardiothoracic Surgery: Development of a Risk Prediction Score and External Validation

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Abstract

Background

Guideline recommendations for preoperative chest radiographs vary to the extent that individual patient benefit is unclear. We developed and validated a prediction score for abnormal preoperative chest radiographs in adult patients undergoing elective non-cardiothoracic surgery.

Methods

Our prospective observational study recruited 703 adult patients who underwent elective non-cardiothoracic surgery at Ramathibodi Hospital. We developed a risk prediction score for abnormal preoperative chest radiographs with external validation using data from 411 patients recruited from Thammasat University Hospital. The discriminative performance was assessed by receiver operating curve analysis. In addition, we assessed the contribution of abnormal chest radiographs to perioperative management.

Results

Abnormal preoperative chest radiographs were found in 19.5% of the 703 patients. Age, pulmonary disease, cardiac disease, and diabetes were significant factors. The model showed good performance with a C-statistics of 0.739 (95% CI, 0.691–0.786). We classified patients into four groups based on risk scores. The posttest probabilities in the intermediate-, intermediate-high-, and high-risk groups were 33.2%, 59.8%, and 75.7%, respectively. The model fitted well with the external validation data with a C statistic of 0.731 (95% CI, 0.674–0.789). One (0.4%) abnormal chest radiograph from the low-risk group and three (2.4%) abnormal chest radiographs from the intermediate-to-high-risk group had a major impact on perioperative management.

Conclusions

Four predictors including age, pulmonary disease, cardiac disease, and diabetes were associated with abnormal preoperative chest radiographs. Our risk score demonstrated good performance and may help identify patients at higher risk of chest abnormalities.

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Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department for Clinical Epidemiology and Biostatistics, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Ratchathewi, Bangkok, Thailand

    Alisa Seangleulur, Ammarin Thakkinstian & Chusak Okascharoen

  2. Department of Anesthesiology, Faculty of Medicine, Thammasat University, Khlong Luang, Pathum Thani, Thailand

    Alisa Seangleulur, Arpakorn Kunawudhi & Neranchala Soonthornkes

  3. Department for Anesthesiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Ratchathewi, Bangkok, Thailand

    Witchaya Supaopaspan

  4. Department of Radiology, Faculty of Medicine, Thammasat University, Khlong Luang, Pathum Thani, Thailand

    Amolchaya Kwankua

  5. Department for Radiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Ratchathewi, Bangkok, Thailand

    Warawut Sukkasem & Sith Phongkitkarun

  6. Department of Surgery, Faculty of Medicine, Thammasat University, Khlong Luang, Pathum Thani, Thailand

    Palin Limpavitayaporn

  7. Department for Surgery, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Ratchathewi, Bangkok, Thailand

    Pokket Sirisreetreerux

  8. Department of Internal Medicine, Faculty of Medicine, Thammasat University, Khlong Luang, Pathum Thani, Thailand

    Narongkorn Saiphoklang

  9. Center for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia

    John Attia

  10. Centre for Public Health, Institute of Clinical Science, Queen’s University Belfast, Belfast, Northern Ireland

    Gareth McKay

Authors
  1. Alisa Seangleulur
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  14. Chusak Okascharoen
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Corresponding author

Correspondence to Chusak Okascharoen.

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The authors declare that they have no conflict of interest.

Ethical approval

The study was approved by the Human Research Ethics Committee of the Faculty of Medicine Ramathibodi Hospital and Thammasat University No. 1.

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Seangleulur, A., Thakkinstian, A., Supaopaspan, W. et al. Optimizing the Yield of Abnormal Preoperative Chest Radiographs in Elective Non-cardiothoracic Surgery: Development of a Risk Prediction Score and External Validation. World J Surg 47, 2698–2707 (2023). https://doi.org/10.1007/s00268-023-07146-7

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