Seangleulur Alisa, Thakkinstian Ammarin, Supaopaspan Witchaya, Kwankua Amolchaya, Sukkasem Warawut, Kunawudhi Arpakorn, Soonthornkes Neranchala, Limpavitayaporn Palin, Sirisreetreerux Pokket, Saiphoklang Narongkorn, Attia John, McKay Gareth, Phongkitkarun Sith, Okascharoen Chusak
Department for Clinical Epidemiology and Biostatistics, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Ratchathewi, Bangkok, Thailand.
Department of Anesthesiology, Faculty of Medicine, Thammasat University, Khlong Luang, Pathum Thani, Thailand.
World J Surg. 2023 Nov;47(11):2698-2707. doi: 10.1007/s00268-023-07146-7. Epub 2023 Sep 6.
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.
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.
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.
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.
术前胸部X光片的指南建议差异很大，以至于个体患者的获益尚不清楚。我们开发并验证了一种针对接受择期非心胸外科手术的成年患者术前胸部X光片异常的预测评分。
我们的前瞻性观察性研究招募了703例在拉玛蒂博迪医院接受择期非心胸外科手术的成年患者。我们使用从法政大学医院招募的411例患者的数据，开发了一种术前胸部X光片异常的风险预测评分并进行了外部验证。通过受试者工作特征曲线分析评估鉴别性能。此外，我们评估了胸部X光片异常对围手术期管理的影响。
703例患者中，19.5%术前胸部X光片异常。年龄、肺部疾病、心脏疾病和糖尿病是显著因素。该模型表现良好，C统计量为0.739（95%CI，0.691 - 0.786）。我们根据风险评分将患者分为四组。中危、中高危和高危组的检验后概率分别为33.2%、59.8%和75.7%。该模型与外部验证数据拟合良好，C统计量为0.731（95%CI，0.674 - 0.789）。低危组有1例（0.4%）胸部X光片异常，中高危组有3例（2.4%）胸部X光片异常对围手术期管理有重大影响。
年龄、肺部疾病、心脏疾病和糖尿病这四个预测因素与术前胸部X光片异常相关。我们的风险评分表现良好，可能有助于识别胸部异常风险较高的患者。
