According to data from the World Health Organization (WHO), lung cancer is becoming a global epidemic. It is particularly high in the list of the leading causes of death not only in developed countries, but also worldwide; furthermore, it holds the leading place in terms of cancer-related mortality. Nevertheless, many breakthroughs have been made the last two decades regarding its management, with one of the most prominent being the implementation of artificial intelligence (AI) in various aspects of disease management. We included 473 papers in this thorough review, most of which have been published during the last 5–10 years, in order to describe these breakthroughs. In screening programs, AI is capable of not only detecting suspicious lung nodules in different imaging modalities—such as chest X-rays, computed tomography (CT), and positron emission tomography (PET) scans—but also discriminating between benign and malignant nodules as well, with success rates comparable to or even better than those of experienced radiologists. Furthermore, AI seems to be able to recognize biomarkers that appear in patients who may develop lung cancer, even years before this event. Moreover, it can also assist pathologists and cytologists in recognizing the type of lung tumor, as well as specific histologic or genetic markers that play a key role in treating the disease. Finally, in the treatment field, AI can guide in the development of personalized options for lung cancer patients, possibly improving their prognosis.

Candidemia is a significant cause of morbidity and mortality among critically ill patients. Early-onset candidemia is characterized by occurring within the first seven days after admission to the Intensive Care Unit and presents several important challenges regarding its management. Risk factors may vary among patients with early- and late-onset infection, while clinical manifestations are generally non-specific and covered by the underlying disease and co-morbidities. Diagnosis and appropriate therapy are frequently delayed, with a high risk of progression to invasive, deep-seated infections, leading to rapid clinical deterioration. Management strategies to optimize the approach for patients with early-onset candidemia include the use of both conventional and novel diagnostic techniques, the initiation of appropriate antifungal therapy, administration of an adequate dose, daily evaluation of clinical response, de-escalation treatment whenever possible, and early discontinuation. Incorporating an antifungal stewardship program in clinical practice is essential in order to achieve the best clinical outcomes. Based on a review and analysis of the available literature, this article provides a thorough update on the risk factors, clinical characteristics, diagnostic methods, and management of early-onset candidemia in adult critically ill patients.

Infections with multidrug-resistant (MDR) organisms remain a significant cause of morbidity and mortality among liver transplant recipients, despite advances in surgical techniques and immunosuppressive therapy. This prospective observational study aimed to evaluate the impact of targeted perioperative antibiotic prophylaxis against MDR Gram-negative bacteria on postoperative infections and mortality in liver transplant recipients. Seventy-nine adult patients who underwent liver transplantation and were admitted to the ICU for more than 24 h postoperatively were included. Demographics, disease severity scores, comorbidities, and lengths of ICU and hospital stay were recorded. Colonization with carbapenem-resistant Gram-negative bacteria was assessed via preoperative and postoperative cultures from the blood, urine, rectum, and tracheal secretions. Patients were divided into two groups: those with MDR colonization or infection who received targeted prophylaxis and controls who received standard prophylaxis. Infectious complications (30.4%) occurred significantly less frequently than non-infectious ones (62.0%, p = 0.005). The most common infections were bacteremia (22.7%), pneumonia (17.7%), and surgical site infections (2.5%), with most events occurring within 15 days post-transplant. MDR pathogens isolated included Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa. Although overall complication and mortality rates at 30 days and 3 months did not differ significantly between groups, the targeted prophylaxis group had fewer infectious complications (22.8% vs. 68.5%, p = 0.008), particularly bacteremia (p = 0.007). Infection-related mortality was also significantly reduced in this group (p = 0.039). These findings suggest that identification of MDR colonization and administration of targeted perioperative antibiotics may reduce septic complications in liver transplant patients. Further prospective studies are warranted to confirm benefits on outcomes and resource utilization.

Introduction: There are many aspects in the relationship between smoking and sleep that have not been investigated thoroughly yet, especially in regards to obstructive sleep apnea-hypopnea syndrome (OSAHS). Methods: In this cross-sectional study, 2359 participants, who have visited the sleep clinic of our hospital during a 13-year period and were former or current smokers, were included. Their smoking history, measured in packyears of smoking, and their nicotine dependence, measured with the Fagerström scale, were correlated with various epidemiological and sleep-related variables. Results: Patients with respiratory, cardiovascular and metabolic comorbidities were older, more obese and presented a significantly greater history in packyears of smoking. Packyears were positively correlated with the Epworth sleepiness scale (ESS) (r = 0.06, p = 0.007), with %REM sleep time (r = 0.19, p = 0.042), apnea-hypopnea index (AHI) (r = 0.10, p < 0.001), oxygen desaturation index (ODI) (r = 0.10, p < 0.001), mean and maximum apnea duration (r = 0.10, p < 0.001 and r = 0.11, p < 0.001, respectively), while they were negatively correlated with mean and minimum SaO₂ (r = −0.18, p < 0.001 and r = −0.13, p < 0.001, respectively). Furthermore, smoking history exhibited a significantly increasing trend with increasing OSA diagnosis and severity (p < 0.001). Patients with abnormal movements during sleep and those with restless sleep showed a significantly higher nicotine dependence, measured with the Fagerström scale, compared to those without abnormal movements or restless sleep (5.4 ± 2.8 vs. 4.7 ± 2.8, p = 0.002 and 5.1 ± 2.9 vs. 4.7 ± 2.7, p = 0.043). Conclusions: Smoking history in packyears probably affects OSAHS characteristics, while nicotine dependence seems to be related more with abnormal sleep behaviors.

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Background: Diabetes mellitus (DM) is an independent risk factor for severe SARS-CoV-2 infection and is linked to higher incidences of infections and adverse outcomes in patients with DM. This study examines the association between DM and multidrug-resistant Gram-negative bacteria (MDR-GNB) in critically ill, intubated COVID-19 patients in the intensive care unit (ICU) and evaluates mortality rates and clinical factors contributing to unfavorable outcomes. Methods: This retrospective observational study included intubated COVID-19 patients diagnosed with secondary infections due to MDR-GNB. Patients were treated for acute respiratory distress syndrome (ARDS) in a tertiary care university hospital ICU between October 2020 and February 2022. Collected data included demographics, comorbidities, medication, and laboratory parameters including blood tests and culture samples. Results: Among 416 COVID-19 patients, 112 (26.9%) had T2DM. Cultures from lower respiratory tract specimens revealed a significantly higher likelihood of isolating Acinetobacter baumannii in patients with DM (OR: 2.18, 95% CI: 1.40–3.40, p < 0.001), and DM is an independent predictor of isolation Acinetobacter baumannii in bronchial secretions of COVID-19 intubated patients (OR: 2.046, 95% CI: 1.256–3.333. p < 0.004). DM was not significantly associated with differences in length of stay (LOS) until discharge or death (HR: 0.76, 95% CI: 0.51–1.12, p = 0.16; HR: 0.91, 95% CI: 0.70–1.19, p = 0.50) or 28-day ICU mortality (OR: 1.12, 95% CI: 0.52–2.41, p = 0.77). Age was linked to an increased 28-day mortality risk in patients with DM (OR: 1.10, 95% CI: 1.02–1.18, p = 0.011). Conclusions: In critically ill intubated COVID-19 patients, DM emerged as a significant and independent predictor for the isolation of Acinetobacter baumannii from bronchial secretions, highlighting a key link between DM and specific multidrug-resistant pathogens, even though no broader association with MDR-GNB-related secondary infections was observed.