Lung cancer remains one of the leading causes of cancer-related deaths worldwide, emphasizing the need for improved diagnostic and treatment approaches. In recent years, the emergence of artificial intelligence (AI) has sparked considerable interest in its potential role in lung cancer. This review aims to provide an overview of the current state of AI applications in lung cancer screening, diagnosis, and treatment. AI algorithms like machine learning, deep learning, and radiomics have shown remarkable capabilities in the detection and characterization of lung nodules, thereby aiding in accurate lung cancer screening and diagnosis. These systems can analyze various imaging modalities, such as low-dose CT scans, PET-CT imaging, and even chest radiographs, accurately identifying suspicious nodules and facilitating timely intervention. AI models have exhibited promise in utilizing biomarkers and tumor markers as supplementary screening tools, effectively enhancing the specificity and accuracy of early detection. These models can accurately distinguish between benign and malignant lung nodules, assisting radiologists in making more accurate and informed diagnostic decisions. Additionally, AI algorithms hold the potential to integrate multiple imaging modalities and clinical data, providing a more comprehensive diagnostic assessment. By utilizing high-quality data, including patient demographics, clinical history, and genetic profiles, AI models can predict treatment responses and guide the selection of optimal therapies. Notably, these models have shown considerable success in predicting the likelihood of response and recurrence following targeted therapies and optimizing radiation therapy for lung cancer patients. Implementing these AI tools in clinical practice can aid in the early diagnosis and timely management of lung cancer and potentially improve outcomes, including the mortality and morbidity of the patients.

The pathophysiology of ST-elevated myocardial infarction (STEMI) extends beyond coronary artery occlusion to include microvascular and endothelial dysfunction, both of which critically influence outcomes. Endocan, a soluble dermatan sulfate proteoglycan secreted by endothelial cells, has emerged as a novel biomarker of endothelial activation and dysfunction. Recent studies suggest that elevated endocan levels may carry prognostic significance in patients with STEMI, particularly those undergoing percutaneous coronary intervention (PCI). A comprehensive search of PubMed, Cochrane Library, and Google Scholar was conducted to identify studies evaluating endocan as a prognostic biomarker in STEMI. Review articles, case reports, case series, and experimental studies were excluded. Seven clinical studies, comprising sample sizes ranging from 80 to 320 patients, met the inclusion criteria. Across these studies, endocan levels were analyzed in relation to established prognostic markers and clinical outcomes. Key findings demonstrated that higher endocan levels correlated with stress hyperglycemia (r = 0.21, p < 0.05), higher SYNTAX scores, and worse in-hospital outcomes. A cutoff value of 1.7 ng/mL predicted STEMI with 76.1% sensitivity and 73.6% specificity. Elevated endocan levels also showed positive correlations with the TIMI risk score, major adverse cardiovascular events (MACE), and were identified as independent predictors of incomplete ST-segment resolution (STR) (p = 0.044) and no-reflow phenomenon (NRP) (p < 0.001, OR = 2.39, 95% CI = 1.37–4.15). Collectively, the evidence indicates that endocan is strongly associated with endothelial dysfunction, MACE, NRP post-PCI, and impaired reperfusion. Moreover, traditional prognostic indices such as TIMI and SYNTAX scores appear to correlate with circulating endocan levels. However, variability in reported cutoff values across studies highlights the need for larger, multicenter trials with standardized endpoints to establish endocan’s diagnostic and prognostic utility in STEMI.

Background: Obstructive sleep apnea (OSA) is associated with an increased risk of major cardiac and cerebrovascular events (MACCE). However, data on the burden and predictors of MACCE in geriatric patients with OSA (G-OSA) remain limited. Methods: Using the National Inpatient Sample from 2018, we identified G-OSA admissions (age ≥ 65 years) and divided them into non-MACCE vs. MACCE (all-cause mortality, stroke, acute myocardial infarction, and cardiac arrest). We compared the demographics and comorbidities in both cohorts and extracted the odds ratio (multivariate analysis) of MACCE and associated in-hospital mortality. Results: Out of 1,141,120 geriatric obstructive sleep apnea G-OSA admissions, 9.9% (113,295) had MACCE. Males, Asians, or the Pacific Islander/Native American race, and patients from the lowest income quartile revealed a higher MACCE rate. Significant clinical predictors of MACCE in elderly OSA patients on multivariable regression analysis in decreasing odds were pulmonary circulation disease (OR 1.47, 95% CI 1.31–1.66), coagulopathy (OR 1.43, 95% CI 1.35–1.50), peripheral vascular disease (OR 1.34, 95% CI 1.28–1.40), prior sudden cardiac arrest (OR 1.34, 95% CI 1.11–1.62), prior myocardial infarction (OR 1.27, 95% CI 1.22–1.33), fluid and electrolyte imbalances (OR 1.25, 95% CI 1.20–1.29), male sex (OR 1.22, 95% CI-1.18–1.26), hyperlipidemia (OR 1.20, 95% CI 1.16–1.24), low household income (OR 1.19, CI 1.13–1.26), renal failure (OR 1.15, 95% CI 1.12–1.19), diabetes (OR 1.14, 95% CI 1.10–1.17), metastatic cancer (OR 1.14, 95% CI 1.03–1.25), and prior stroke or TIA (OR 1.12, 95% CI 1.07–1.17) (All p value < 0.05). Conclusions: This study emphasizes the significant association between obstructive sleep apnea (OSA) and major cardiac and cerebrovascular events (MACCE) in the geriatric population. Among the elderly OSA patients, a substantial 9.9% were found to have MACCE, with specific demographics like males, Asian or Pacific Islander/Native American individuals, and those from the lowest income quartile being particularly vulnerable. The study sheds light on several significant clinical predictors, with pulmonary circulation disease, coagulopathy, and peripheral vascular disease topping the list. The highlighted predictors provide valuable insights for clinicians, allowing for better risk stratification and targeted interventions in this vulnerable patient cohort. Further research is essential to validate these findings and inform how tailored therapeutic approaches for geriatric OSA patients can mitigate MACCE risk. Clinical Implications: Elderly individuals with a high risk for MACCE should undergo routine OSA screening using tools like the sensitive STOP-BANG Questionnaire. Implementing CPAP treatment can enhance cardiovascular outcomes in these patients.

Background: Heart failure with preserved ejection fraction (HFpEF) is a major cause of hospitalization and mortality in older adults. Sudden cardiac arrest (SCA) is a leading cause of death in this population, yet national trends in incidence, outcomes, and disparities remain poorly defined. Methods: We performed a retrospective cohort study using the National Inpatient Sample from 2016 to 2020. Hospitalizations for patients aged ≥65 years with HFpEF and in-hospital cardiac arrest (CA) were identified using ICD-10-CM codes. Demographics, comorbidities, hospital outcomes, and temporal trends were examined. The primary outcome was in-hospital mortality. Secondary outcomes included length of stay, hospital charges, and discharge disposition. Results: Among 7,738,108 HFpEF admissions, 93,440 (1.2%) involved CA. Incidence rose from 1.1% in 2016 to 1.5% in 2020 (36% relative increase). The median age was 81 years; 54% were female, 70% White, 19% Black, and 8% Hispanic. CA incidence increased across all groups, with the largest relative rises among Native American (1.0% to 1.9%), Black (1.7% to 2.3%), and Hispanic patients (1.4% to 2.0%). In-hospital mortality was high, increasing from 58.2% to 61.7% over the study period (p < 0.001). Mortality rose most steeply among Black and low-income patients. Comorbidity patterns shifted toward greater metabolic complexity, including higher rates of complicated diabetes, hypertension, hyperlipidemia, and obesity. Conclusions: Elderly patients hospitalized with HFpEF are experiencing rising rates of in-hospital CA and persistently high mortality, with marked racial and socioeconomic disparities. These findings highlight the need for better risk stratification, targeted metabolic and inflammatory therapies, and more equitable care delivery.

BACKGROUND Coronavirus disease 2019 (COVID-19) has been shown to increase the risk of stroke. However, the prevalence and risk of recurrent stroke in COVID-19 patients with prior stroke/transient ischemic attack (TIA), as well as its impact on mortality, are not established. AIM To evaluate the impact of COVID-19 on in-hospital mortality, length of stay, and healthcare costs in patients with recurrent strokes. METHODS We identified admissions of recurrent stroke (current acute ischemic stroke admissions with at least one prior TIA or stroke) in patients with and without COVID-19 using ICD-10-CM codes using the National Inpatient Sample (2020). We analyzed the impact of COVID-19 on mortality following recurrent stroke admissions by subgroups. RESULTS Of 97455 admissions with recurrent stroke, 2140 (2.2%) belonged to the COVID-19-positive group. The COVID-19-positive group had a higher prevalence of diabetes and chronic kidney disease vs the COVID-19 negative group (P < 0.001). Among the subgroups, patients aged > 65 years, patients aged 45–64 years, Asians, Hispanics, whites, and blacks in the COVID-19 positive group had higher rates of all-cause mortality than the COVID-19 negative group (P < 0.01). Higher odds of in-hospital mortality were seen in the group aged 45-64 (OR: 8.40, 95%CI: 4.18-16.91) vs the group aged > 65 (OR: 7.04, 95%CI: 5.24-9.44), males (OR: 7.82, 95%CI: 5.38-11.35) compared to females (OR: 6.15, 95%CI: 4.12-9.18), and in Hispanics (OR: 15.47, 95%CI: 7.61-31.44) and Asians/Pacific Islanders (OR: 14.93, 95%CI: 7.22-30.87) compared to blacks (OR: 5.73, 95%CI: 3.08-10.68), and whites (OR: 5.54, 95%CI: 3.79-8.09). CONCLUSION The study highlights the increased risk of all-cause in-hospital mortality in recurrent stroke patients with COVID-19, with a more pronounced increase in middle-aged patients, males, Hispanics, or Asians.

The Anatolian Journal of Cardiology - Peer-reviewed cardiology journal publishing original research, reviews, case reports. Impact Factor 1.5. The Anatolian Journal of Cardiology - Leading international cardiology journal with Impact Factor 1.5. Publishing original research, reviews, and case reports in cardiovascular medicine. Indexed in PubMed, Scopus, and Web of Science.