The solitary pulmonary nodule on chest X-ray (CXR) is a common problem in pulmonary medicine. Its presence raises the question of lung cancer. As five-year survival after resection of a solitary bronchogenic carcinoma can be as high as 80%, prompt evaluation is crucial. This should begin with a cancer risk assessment based on clinical and radiographic factors. The risk and benefits of surgery should next be assessed, and together with the patient's preferences, a management plan can be decided upon. Surgery is recommended for patients at high risk of malignancy with a low surgical risk, while careful observation is adopted for patients at low risk of malignancy coupled with a high surgical risk. Further diagnostic tests may be warranted to aid in this decision process. Although CXR is not useful for lung cancer screening, low-dose computed tomography imaging is increasingly recommended for individuals at high risk for lung cancer.
Aged ; Diagnostic Imaging ; methods ; Humans ; Lung Diseases ; diagnosis ; Lung Neoplasms ; diagnosis ; Middle Aged ; Pulmonary Medicine ; methods ; Radiography ; methods ; Radiography, Thoracic ; methods ; Risk Assessment ; methods ; Risk Factors ; Solitary Pulmonary Nodule ; diagnosis

INTRODUCTION: Singapore's enhanced surveillance programme for COVID-19 identifies and isolates hospitalised patients with acute respiratory symptoms to prevent nosocomial spread. We developed risk prediction models to identify patients with low risk for COVID-19 from this cohort of hospitalised patients with acute respiratory symptoms. METHODS: This was a single-centre retrospective observational study. Patients admitted to our institution's respiratory surveillance wards from 10 February to 30 April 2020 contributed data for analysis. Prediction models for COVID-19 were derived from a training cohort using variables based on demographics, clinical symptoms, exposure risks and blood investigations fitted into logistic regression models. The derived prediction models were subsequently validated on a test cohort. RESULTS: Of the 1,228 patients analysed, 52 (4.2%) were diagnosed with COVID-19. Two prediction models were derived, the first based on age, presence of sore throat, dormitory residence, blood haemoglobin level (Hb), and total white blood cell counts (TW), and the second based on presence of headache, contact with infective patients, Hb and TW. Both models had good diagnostic performance with areas under the receiver operating characteristic curve of 0.934 and 0.866, respectively. Risk score cut-offs of 0.6 for Model 1 and 0.2 for Model 2 had 100% sensitivity, allowing identification of patients with low risk for COVID-19. Limiting COVID-19 screening to only elevated-risk patients reduced the number of isolation days for surveillance patients by up to 41.7% and COVID-19 swab testing by up to 41.0%. CONCLUSION Prediction models derived from our study were able to identify patients at low risk for COVID-19 and rationalise resource utilisation.
Humans ; COVID-19/epidemiology* ; SARS-CoV-2 ; Hospitalization ; Logistic Models ; Retrospective Studies ; Hemoglobins