Thoracic Diseases

This observational study will compare how accurately anesthesiology residents and an artificial intelligence system (hChestXR) identify abnormalities on chest X-rays. Approximately 35 volunteer anesthesiology residents at Kayseri City Hospital will review the same set of 150 anonymized posteroanterior chest radiographs selected from the hospital imaging archive. The set will include normal images and images showing findings such as infiltration, atelectasis, and pleural effusion. Two radiologists will independently assess the images and resolve disagreements by consensus to establish the reference standard. Residents will not see the radiologists' assessments or the artificial intelligence results while interpreting the images. The study will measure diagnostic accuracy and other measures of diagnostic performance. No additional imaging, treatment, or change in patient care is planned.

Chest X-rays are widely used to detect thoracic and lung conditions, but reviewing high volumes of radiographs can lead to workload strain and variation between interpreters. Artificial intelligence (AI), particularly deep learning neural networks like DenseNet-121, has shown strong potential to assist clinicians with automated image interpretation. However, AI models trained on large international datasets, such as CheXpert, may perform differently across distinct patient populations due to variations in imaging technique, patient demographics, and disease presentation. The primary purpose of this study is to compare the diagnostic accuracy of a DenseNet-121 model trained or fine-tuned on local data against a DenseNet-121 model pretrained on the CheXpert dataset for identifying thoracic pathologies. Both models will evaluate de-identified frontal chest radiographs from adult patients. Model predictions will be compared against a reference standard established by expert radiologist consensus, with discordant findings resolved using chest computed tomography (CT). Findings will evaluate whether local model adaptation improves diagnostic precision and workflow efficiency in clinical settings.

This study aims to find out if an artificial intelligence (AI) system can help experienced radiologists write chest CT scan reports more quickly without lowering the quality of the report. Chest CT scans are common, and writing reports for them is a major part of a radiologist's job. In this trial, board-certified radiologists will interpret complex chest CT cases. For some cases, they will start with a complete draft report generated by the AI system, which they can review and edit as needed. For other cases, they will write the report from scratch without any AI help, following their usual routine. The main things we are measuring are: 1) how much time the AI draft saves, and 2) whether the final reports created with AI help are as good as or better than those written without it, as judged by other senior doctors who do not know which report came from which method. The hope is that this AI tool can make radiologists' work more efficient while maintaining high standards for patient care.

The goal of this observational study is to learn if an AI assistant tool can help doctors who read chest CT scans (called radiologists) write their reports faster and just as well or better. Chest CT scans are common pictures taken of the inside of the chest to help with diagnosis. The main questions the study aims to answer are: (1) Does using the AI tool save radiologists time when writing their reports? (2) Are the final reports written with the AI tool's help as good as or better than reports written without it? To answer these questions, researchers will compare two time periods at several hospitals. They will look at how long it took to write reports and how good the reports were, both from a time before the AI tool was available and from a time after it was in regular use. In this study, radiologists will use the AI tool as part of their normal daily work. The tool is built into the computer system they already use to look at scans. Researchers will then measure the time and quality of the reports produced during their regular shifts.

This study was conducted to determine the effects of a manual vibration technique applied to the chest wall on the duration of chest tube placement, secretion clearance, and hemodynamic parameters in patients with chest tubes.

The aim of this study is to determine if erector spinae injections with bolus infusions with local anesthetic decrease postsurgical pain and opioid consumption in patients undergoing pulmonary resection surgery.

Myocardial injury after noncardiac surgery (MINS) refers to postoperative elevation of cardiac troponin (cTn) levels caused by underlying ischemic mechanisms (i.e., coronary artery supply-demand imbalance or atherosclerotic thrombosis) without obvious non-ischemic causes (such as pulmonary embolism), with at least one cTn concentration exceeding the 99th percentile of the test reference upper limit, regardless of whether clinical symptoms and ECG changes are present. MINS, including myocardial infarction and ischemic myocardial injury, typically occurs within 30 days after surgery, most commonly within the first 2 postoperative days. It is an independent risk factor for 30-day postoperative mortality and is also closely associated with increased risk of mortality and vascular complications within 2 years . MINS is a common cardiovascular complication after thoracic surgery. Therefore, reducing the incidence of MINS in non-cardiac thoracic surgery to improve patient outcomes is a critical issue in anesthetic management for thoracic surgery. Ciprofol is a Class 1 innovative drug independently developed in China with global intellectual property rights. Currently, Ciprofol has completed Phase III clinical trials in China and the United States; its approved indications in China include sedation or anesthesia for various diagnostic procedures, general anesthesia for surgical operations, and sedation during intensive care unit (ICU) stays. Completed drug clinical trials and published clinical trial data of Ciprofol indicate that it can better maintain circulatory stability and ideal anesthetic depth during anesthesia induction and maintenance, making it a promising intravenous general anesthetic alternative to propofol. Maintaining hemodynamic stability is an important measure to reduce cardiovascular complications during the perioperative period. Given the good circulatory stability and sedative efficacy of Ciprofol, this study aims to investigate the impact of Ciprofol on MINS in non-cardiac thoracic surgery.

Globally, approximately 230 million adults undergo surgical procedures each year, with around 30% of patients maintaining smoking habits prior to surgery. Extensive clinical research has confirmed that tobacco exposure is a significant independent risk factor for perioperative complications. Epidemiological data indicate that long-term smokers experience a significantly higher all-cause mortality rate during hospitalization, approximately 20% greater than non-smokers, while the incidence of postoperative complications is 40% higher. Consequently, international guidelines universally recommend the establishment of standardized preoperative smoking cessation programs for surgical patients. Nicotine withdrawal, a typical clinical manifestation during smoking cessation, involves symptoms across multiple systems: neuropsychiatric symptoms such as mood depression, sleep disturbances, and irritability; autonomic dysfunction leading to postural dizziness and bradycardia; and metabolic dysregulation resulting in increased appetite and weight gain. Notably, these withdrawal symptoms exhibit a significant time-dependent pattern, typically peaking 24-72 hours after cessation. Multicenter studies have demonstrated that tobacco-dependent patients experience an average increase of IV Abstract 35-45% in opioid consumption within 24 hours postoperatively, with the duration of analgesic requirements extended by approximately 25%. However, some patients suffer from severe adverse reactions to opioids (e.g., nausea, vomiting, confusion), making the use of adjuvant medications for multimodal analgesia and optimized pain management particularly crucial. By the late 20th century, the analgesic properties of nicotine, a primary component of tobacco, were systematically studied and applied in clinical practice.

The purpose of the registry will be to support ongoing research in the etiology, early diagnosis, clinical management, and prognosis of lung cancer and other cancers and diseases of the thorax by developing a complete repository of specimens from patients with thoracic disease including but not limited to suspected lung cancer, mediastinal and pleural tumors, lung transplants and from patients at a very high risk of developing other thoracic cancers or other thoracic diseases.

This study is examining collecting data on steps walked (ambulation) per day by thoracic surgery patients over the age of 65 years-old before surgery. The name(s) of the study device involved in this study is: * Fitbit inspire