Reliability of comorbidity indices as predictive indicators for frequent severe chronic obstructive pulmonary disease exacerbations.

Introduction: The relationship between comorbidities and chronic obstructive pulmonary disease (COPD) is two-sided. As the number of comorbidities increases, frequency of acute exacerbations of COPD (AECOPD) consequently increases. Comorbidity indices can be used to evaluate comorbidities while managing COPD patients. We aimed to compare comorbidity indices such as the Charlson comorbidity index (CCI), comorbidities in COPD index (COMCOLD) and COPD specific comorbidity test (COTE) regarding exacerbation frequency. Materials and Methods: Participants hospitalized for AECOPD were included in this bidirectional case-control study. Exacerbation severity, frequency, further exacerbations over a one-year follow-up period and CCI, COMCOLD, and COTE scores were recorded. High and low comorbidity groups were compared regarding AECOPD frequency, severity, and further exacerbations. Result: Ninety-two patients were enrolled. The frequency of AECOPD was significantly higher in high-comorbidity groups (p= 0.026 for CCI; 0.015 for COTE; 0.012 for COMCOLD) than that in low-comorbidity groups. Severe AECOPD was significantly higher in all high-comorbidity groups according to the indices. Median number of exacerbations during the one-year follow-up period was significantly higher in the high-comorbidity groups defined by CCI [0 (0-4) vs. 1 (0-4), p<0.001 and COMCOLD 0 (0-4) vs. 1 (0-3), p= 0.007]. Conclusions: Comorbidities are among the most important risk factors for AECOPD. Managing comorbidities begins with their identification, followed by appropriate interventions. Therefore, using at least one comorbidity index during assessment ensures that comorbidities are not overlooked during diagnostic and therapeutic processes. CCI, COTE, and COMCOLD comorbidity indices can be used in predicting COPD exacerbations.

Can the generalizability issue of artificial intelligence be overcome? Pneumothorax detection algorithm.

The generalizability of artificial intelligence (AI) models is a major issue in the field of AI applications. Therefore, we aimed to overcome the generalizability problem of an AI model developed for a particular center for pneumothorax detection using a small dataset for external validation. Chest radiographs of patients diagnosed with pneumothorax (n = 648) and those without pneumothorax (n = 650) who visited the Ankara University Faculty of Medicine (AUFM; center 1) were obtained. A deep learning-based pneumothorax detection algorithm (PDA-Alpha) was developed using the AUFM dataset. For implementation at the Health Sciences University (HSU; center 2), PDA-Beta was developed through external validation of PDA-Alpha using 50 radiographs with pneumothorax obtained from HSU. Both PDA algorithms were assessed using the HSU test dataset (n = 200) containing 50 pneumothorax and 150 non-pneumothorax radiographs. We compared the results generated by the algorithms with those of physicians to demonstrate the reliability of the results. The areas under the curve for PDA-Alpha and PDA-Beta were 0.993 (95% confidence interval (CI): 0.985-1.000) and 0.986 (95% CI: 0.962-1.000), respectively. Both algorithms successfully detected the presence of pneumothorax on 49/50 radiographs; however, PDA-Alpha had seven false-positive predictions, whereas PDA-Beta had one. The positive predictive value increased from 0.525 to 0.886 after external validation (p = 0.041). The physicians' sensitivity and specificity for detecting pneumothorax were 0.585 and 0.988, respectively. The performance scores of the algorithms were increased with a small dataset; however, further studies are required to determine the optimal amount of external validation data to fully address the generalizability issue.

Evaluation of lung cancer biomarkers profile for the decision of targeted therapy in EBUS-TBNA cytological samples.

BACKGROUND: Guidelines recommend performing biomarker tests for epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), BRAF and ROS proto-oncogene-1(ROS1) genes and protein expression of programmed death ligand-1(PD-L1) in patients with non-small lung cell carcinoma (NSCLC). Studies reported that endobronchial ultrasound-transbronchial needle aspiration (EBUS-TBNA) can provide sufficient material for cancer biomarker analyses, but there are still concerns about the subject. AIM: The purpose of the study was to assess the adequacy of EBUS-TBNA for testing lung cancer biomarkers. METHODS: We retrospectively reviewed patients with NSCLC whose EBUS-TBNA was analysed for EGFR, ALK, ROS-1, BRAF and PD-L1 expression between December 2011 and December 2020. RESULTS: A total of 394 patients were enrolled in the study. EGFR mutation and ALK fusion were the most common studied biomarkers. EBUS-TBNA adequacy rate for biomarker tests was found 99.0% for EGFR, 99.1 for ALK, 97.2% for ROS1, 100% for BRAF and 99.3% for PD-L1 testing. Multivariate analysis revealed the histological type, history of treatment for NSCL, size, or 18-fluorodeoxyglucose uptake of sampled lesion did not show any association with TBNA adequacy for biomarker testing. CONCLUSION: EBUS-TBNA can provide adequate material for biomarker testing for EGFR, ALK, ROS-1, BRAF and PD-L1 expression.

Is endobronchial ultrasound-transbronchial needle aspiration (EBUS-TBNA) reliable and safe procedure in geriatric patients?

BACKGROUND: Even though studies have indicated the usefulness and safety of endobronchial ultrasound-transbronchial needle aspiration (EBUS-TBNA), elderly patient data are limited due to the small sample sizes. AIM: We aimed to evaluate usage and safety of EBUS-TBNA in elderly population. METHODS: This single-center retrospective study was conducted with patients who underwent an EBUS-TBNA procedure between September 2011 and December 2019. The patients were categorized into two groups: those aged 65 years or older (elderly group) and those younger than 65 years (younger group). RESULTS: 2444 patient data, 1069 of which were in the elderly group, were analyzed. The cytological examination of EBUS-TBNA identified specimen adequacy in 96.8% of patients. One hundred and thirty patients (5.3%) experienced complications, with similar complication rates recorded in both the elderly and younger groups (5.4% vs 5.2%, p: 0.836). Logistic regression analyses revealed that age, and presence of hypertension, diabetes mellitus, coronary artery disease and malignancy are associated significantly with complication-related EBUS-TBNA. For the lymph nodes with a final diagnosis of malignancy, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of EBUS-TBNA revealed a diagnostic performance in excess of 90% except for metastasis and lymphoma. CONCLUSION: EBUS-TBNA can be considered a safe and effective technique in patients aged 65 years and over.

[Approach to chronic cough]. / Kronik öksürüge yaklasim.

Chronic cough, that 10-38% outpatients have, is an important cause of morbidity and mortality. This symptom can be seen 3-40% of adult patients and reduces quality of life. 95% patients that cough chronically have one of these three diseases: upper airway cough syndrome, gastroesophageal reflux or asthma. In this review these three diseases and rare causes of chronic cough will be discussed and diagnostic steps will be explained.