Search Results (624)

Background: RiBi is integral to cell proliferation, and its dysregulation is increasingly recognized as a hallmark of aggressive cancers. We sought to develop and validate a composite “PanRibo-515 score” reflecting RiBi activity across multiple tumor types, assess its prognostic significance, and explore its relationship with immune checkpoint therapy outcomes. Methods: We curated 515 RiBi–associated genes (PanRibo-515) and used a LASSO regression-based strategy on a training dataset (GSE202203) to select the prognostically most relevant subset of 68 genes (OncoRibo-68). Directionality (positive or negative impact on survival) was assigned based on the sign of the LASSO coefficients. We integrated a forward selection approach to identify a refined subset of genes for computing the OncoRibo-68 score. For validation, patients in The Cancer Genome Atlas (TCGA) were stratified into high or low OncoRibo-68 score groups for survival analyses. Additional validation for immunotherapy response was conducted using bioinformatic platforms used for immunotherapy response analysis. Results: A higher OncoRibo-68 score consistently correlated with poorer overall and progression-free survival across multiple cancers. Elevated OncoRibo-68 score was linked to an immunosuppressive tumor microenvironment, but interestingly to increased response to checkpoint inhibitors. Conclusions: Our findings highlight RiBi as an important determinant of tumor aggressiveness and identify the OncoRibo-68 score as a promising biomarker for risk stratification and therapy selection. Future research may evaluate whether targeting RiBi pathways could enhance treatment efficacy, particularly in combination with immunotherapy. Full article

Background/Objectives: While intravenous thrombolysis (IVT) is the standard treatment for acute ischemic stroke (AIS) within 4.5 h of symptom onset, many patients present beyond this time window. Recent trials suggest that IVT may be both effective and safe in selected patients treated after the standard time window. Methods: We searched MEDLINE, Scopus, and ClinicalTrials.gov for randomized-controlled clinical trials (RCTs) and individual patient-data meta-analyses (IPDMs) of RCTs comparing IVT plus best medical treatment (BMT) to BMT alone in AIS patients who were last-known-well more than 4.5 h earlier. The primary efficacy outcome was a 90-day excellent functional outcome [modified Rankin Scale (mRS)-scores of 0–1]. Secondary efficacy outcomes included good functional outcome (mRS-scores 0–2) and reduced disability (≥1-point reduction across all mRS-strata). The primary safety outcome was symptomatic intracranial hemorrhage (sICH); secondary safety outcomes were any ICH and 3-month all-cause mortality. Subgroup analyses were performed stratified by different thrombolytics, time-windows, imaging modalities, and affected circulation. Results: Nine studies were included, comprising 1660 patients in the IVT-group and 1626 patients in the control-group. IVT significantly improved excellent functional outcome (RR = 1.24; 95%CI:1.14–1.34; I² = 0%) and good functional outcome (RR = 1.18; 95%CI:1.05–1.33; I² = 70%). IVT was associated with increased odds of reduced disability (common OR = 1.3; 95%CI:1.15–1.46; I² = 0%) and increased risk of sICH (RR = 2.75; 95%CI:1.49–5.05; I² = 0%). The rates of any ICH and all-cause mortality were similar between the two groups. No significant subgroup differences were documented. Conclusions: IVT in the extended time window improved functional outcomes without increasing mortality, despite a higher rate of sICH. Full article

Background: Breast and hematological cancer treatments, especially with anthracyclines, have been shown to be associated with an increased risk of cardiotoxicity (CTX). An accurate prediction of cardiotoxicity risk and early detection of myocardial injury may allow for effective cardioprotection to be instituted and tailored to reverse cardiac dysfunction and prevent the discontinuation of essential cancer treatments. Objectives: The PRoactive Evaluation of Function to Evade Cardio Toxicity (PREFECT) study sought to evaluate the ability of fast-strain-encoded (F-SENC) cardiac magnetic resonance imaging (CMR) and 2D echocardiography (2D Echo) to stratify patients at risk of CTX prior to initiating cancer treatment, detect early signs of cardiac dysfunction, including subclinical CTX (sub-CTX) and CTX, and monitor for recovery (REC) during cardioprotective therapy. Methods: Fifty-nine patients with breast cancer or lymphoma were prospectively monitored for CTX with F-SENC CMR and 2D Echo over at least 1 year for evidence of cardiac dysfunction during anthracycline based chemotherapy. F-SENC CMR also monitored myocardial deformation in 37 left ventricular (LV) segments to obtain a MyoHealth risk score based on both longitudinal and circumferential strain. Sub-CTX and CTX were classified based on pre-specified cardiotoxicity definitions. Results: CTX was observed in 9/59 (15%) and sub-CTX in 24/59 (41%) patients undergoing chemotherapy. F-SENC CMR parameters at baseline predicted CTX with a lower LVEF (57 ± 5% vs. 61 ± 5% for all, p = 0.05), as well as a lower MyoHealth (70 ± 9 vs. 79 ± 11 for all, p = 0.004) and a worse global circumferential strain (GCS) (−18 ± 1 vs. −20 ± 1 for all, p < 0.001). Pre-chemotherapy MyoHealth had a higher accuracy in predicting the development of CTX compared to CMR LVEF and 2D Echo LVEF (AUC = 0.85, 0.69, and 0.57, respectively). The 2D Echo parameters on baseline imaging did not stratify CTX risk. F-SENC CMR obtained good or excellent images in 320/322 (99.4%) scans. During cancer treatment, MyoHealth had a high accuracy of detecting sub-CTX or CTX (AUC = 0.950), and the highest log likelihood ratio (indicating a higher probability of detecting CTX) followed by F-SENC GLS and F-SENC GCS. CMR LVEF and CMR LV stroke volume index (LVSVI) also significantly worsened in patients developing CTX during cancer treatment. Conclusions: F-SENC CMR provided a reliable and accurate assessment of myocardial function during anthracycline-based chemotherapy, and demonstrated accurate early detection of CTX. In addition, MyoHealth allows for the robust identification of patients at risk for CTX prior to treatment with higher accuracy than LVEF. Full article

Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more complex models incorporating biomarkers (e.g., NT-proBNP, sST2), imaging, and artificial intelligence techniques. In acute HF, models like EHMRG and STRATIFY aid early triage, while in chronic HF, tools like SHFM and BCN Bio-HF support long-term management decisions. Despite their utility, most models are limited by poor generalizability, reliance on static inputs, lack of integration into electronic health records, and underuse in clinical practice. Novel approaches involving machine learning, multi-omics profiling, and remote monitoring hold promise for dynamic and individualized risk assessment. However, these innovations face challenges regarding interpretability, validation, and ethical implementation. For prognostic models to transition from theoretical promise to practical impact, they must be continuously updated, externally validated, and seamlessly embedded into clinical workflows. This review emphasizes the potential of prognostic models to transform HF care but cautions against uncritical adoption without robust evidence and practical integration. In the evolving landscape of HF management, prognostic models represent a hopeful avenue, provided their limitations are acknowledged and addressed through interdisciplinary collaboration and patient-centered innovation. Full article

Background/Objectives: Androgen deprivation therapy (ADT) is widely used to manage prostate cancer (PC), but the emergence of treatment resistance remains a major clinical challenge. Although the GST family has been implicated in drug resistance, the specific role of GSTM5 remains poorly understood. This study investigates whether GSTM5, alone or in combination with clinical variables, can improve patient stratification based on the risk of early treatment resistance. Methods: In silico analyses were performed to examine GSTM5’s role in protein interactions, molecular pathways, and gene expression. The rs3768490 polymorphism was genotyped in 354 patients with PC, classified by ADT response. Descriptive analysis and logistic regression models were applied to evaluate associations between genotype, clinical variables, and ADT response. GSTM5 expression related to the rs3768490 genotype and ADT response was also analyzed in 129 prostate tissue samples. Results: The T/T genotype of rs3768490 was significantly associated with a lower likelihood of early ADT resistance in both individual (p = 0.0359, Odd Ratios (OR) = 0.18) and recessive models (p = 0.0491, OR = 0.21). High-risk classification according to D’Amico was strongly associated with early progression (p < 0.0004; OR > 5.4). Combining genotype and clinical risk improved predictive performance, highlighting their complementary value in stratifying patients by treatment response. Additionally, GSTM5 expression was slightly higher in T/T carriers, suggesting a potential protective role against ADT resistance. Conclusions: The T/T genotype of rs3768490 may protect against ADT resistance by modulating GSTM5 expression in PC. These preliminary findings highlight the potential of integrating genetic biomarkers into clinical models for personalized treatment strategies, although further studies are needed to validate these observations. Full article

Background: Patients diagnosed with melanoma are at increased risk of developing multiple primary melanomas (MPMs). Identifying clinical and genetic factors associated with MPM is critical for implementing personalized surveillance strategies. This study aims to describe the clinical, histopathological, and genetic characteristics of patients with MPM managed in a tertiary hospital and to contextualize findings within the current literature. Methods: We conducted a retrospective review of patients diagnosed with two or more primary melanomas between 2010 and 2023 at a tertiary dermatology unit. Demographic data, personal and family cancer history, phototype, melanoma characteristics, genetic testing, staging, treatments, and outcomes were collected. These data were compared with findings from the recent literature. Results: Thirteen patients (ten males, three females; median age: 59 years) were found to have a total of 33 melanomas. Most patients had Fitzpatrick phototype II and no immunosuppression. The number of melanomas per patient ranged from two to five. Synchronous lesions were observed in two patients. Common locations included the trunk and extremities. Histologically, 57% were in situ melanomas, and subsequent melanomas were generally thinner than the index lesion. Two patients showed progression to advanced disease. One patient was positive for MC1R mutation; the rest were negative or inconclusive. Additional phenotypic and environmental risk factors were extracted from patient records and are summarized as follows: Ten patients (76.9%) had Fitzpatrick skin phototype II, and three (23.1%) had phototype III. Chronic occupational sun exposure was reported in four patients (30.8%), while five (38.5%) recalled having suffered multiple sunburns during childhood or adolescence. Eight patients (61.5%) presented with a total nevus count exceeding 50, and five (38.5%) exhibited clinically atypical nevi. None of the patients reported use of tanning beds. Conclusions: Our findings are consistent with the existing literature indicating that patients with MPM often present with thinner subsequent melanomas and require long-term dermatologic follow-up. The inclusion of genetic testing and phenotypic risk factors enables stratified surveillance and supports the application of personalized medicine in melanoma management. Full article

Background: In childhood acute lymphoblastic leukemia (ALL), in addition to classical chromosomal abnormalities, loss of heterozygosity (LOH), including copy-neutral LOH, is also observed. While LOH has been described in the literature, its clinical relevance in pediatric ALL remains unclear. The aim of this study is to identify and analyze patterns of LOH, assess their frequency, and evaluate their association with clinical characteristics and early treatment response during the induction phase of the ALL protocol. Methods: The study included 853 pediatric ALL patients, of whom 120 had B-ALL LOH+ and 58 had T-ALL LOH+. LOH was analyzed using CytoScan HD SNP microarrays. Patients were stratified using multiple correspondence analysis (MCA) and hierarchical clustering on principal components (HCPC), which identified three genetically and clinically distinct clusters. Results: In B-ALL, two clusters with extensive LOH—particularly involving chromosome 9—were associated with poor prognosis and suboptimal response to therapy. In contrast, Cluster 2, characterized by CDKN2A duplication and rare LOH, showed a favorable clinical course. In T-ALL, Cluster 1 had LOH in CDKN2A but favorable outcomes; Cluster 2 exhibited biallelic CDKN2A deletion and aggressive disease; Cluster 3 lacked CDKN2A alterations and showed a genetically stable profile. LOH was common on chromosomes not typically affected by trisomy and rare on those gained. Conclusions: Our study indicates that LOH profiling can positively influence patient stratification by identifying high-risk subgroups, inform prognosis by highlighting unfavorable genetic alterations, and help predict poor treatment response in specific clinical profiles. Full article

Background and Objectives: Cancer patients are particularly susceptible to infections caused by multidrug-resistant Gram-negative bacteria (MDR GNB) due to chemotherapy- or radiation therapy-induced immunosuppression. Colistin is often prescribed as a last-resort agent for MDR GNB infection, but its clinical benefit in oncology patients remains unclear. This study aims to evaluate the mortality risk associated with colistin versus non-colistin regimens in cancer patient with MDR GNB infections, stratified by resistance profiles, infection sites, and concomitant medication use. Materials and Methods: A retrospective cohort study was conducted in adult cancer patients with MDR GNB infections that are resistant to at least three antibiotic classes and identified from at least two anatomical sites at a tertiary care hospital in Korea. Propensity score-matched in a 1:3 ratio either to the colistin group or non-colistin group and multivariate Cox hazard regression analyses were used to evaluate mortality in cancer patients with MDR GNB infections, primarily Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Results: A total of 85 patients (29 patients in the colistin and 56 patients in the non-colistin group) were included in the analysis. Overall, colistin use did not show a statistically significant mortality benefit compared to non-colistin regimens (hazard ratio (HR) 0.93, 95% CI 0.47–1.87). However, the subgroup analysis revealed that colistin had a potential association with significantly lower mortality in pneumonia patients with aminoglycoside-resistant infections (HR 0.04, 95% CI 0.002–0.69). Concomitant use of antipsychotics and benzodiazepines in selected resistance profiles also correlated with improved outcomes. In contrast, a potential association was found between concomitant macrolide use and increased mortality in patients with fluoroquinolone- or penicillin-resistant profiles. Conclusions: Colistin may offer survival benefits in selected high-risk cancer patients with MDR GNB pneumonia. Treatment outcomes are influenced by resistance profiles, infection sites, and concomitant medications, indicating the significant importance of individualized antimicrobial therapy and antimicrobial stewardship in oncology patients. Full article

Postoperative ileus is a prolonged impairment of gastrointestinal motility following surgical procedures. This often leads to increased morbidity, extended hospital stays, and high healthcare expenditures. In this review, we discuss the pathophysiology underlying postoperative ileus, its epidemiology, and perioperative management strategies. Patient characteristics, as well as expected perioperative course, could be used to stratify the risks of postoperative ileus. Preventive measures hinge upon a multimodal approach, minimally invasive surgical techniques, fluid management, early postoperative ambulation, and opioid-sparing analgesia strategies. Adjuvant interventions such as alvimopan, caffeine, and chewing gum have demonstrated efficacy in modulating the neurogenic and inflammatory components of postoperative ileus. Minimally invasive approaches, comprehensive perioperative management, and adjuvant therapies hold promise for prevention. Current management relies heavily on supportive care, underscoring the need for research into the underlying neurogenic and inflammatory mechanisms to guide the development of targeted treatments. Full article

Background/Objectives: Patients with stage IV gastric cancer who develop chronic intestinal failure require home parenteral nutrition (HPN). This study aimed to evaluate the prognostic relevance of nutritional and immune–inflammatory biomarkers and to construct an individualised survival prediction model using machine learning techniques. Methods: A secondary analysis was performed on a cohort of 410 patients with TNM stage IV gastric adenocarcinoma who initiated HPN between 2015 and 2023. Nutritional and inflammatory indices, including the Controlling Nutritional Status (CONUT) score and lymphocyte-to-monocyte ratio (LMR), were assessed. Independent prognostic factors were identified using Cox proportional hazards models. A Random Survival Forest (RSF) model was constructed to estimate survival probabilities and quantify variable importance. Results: Both the CONUT score and LMR were independently associated with overall survival. In multivariate analysis, higher CONUT scores were linked to increased mortality risk (HR = 1.656, 95% CI: 1.306–2.101, p < 0.001), whereas higher LMR values were protective (HR = 0.632, 95% CI: 0.514–0.777, p < 0.001). The RSF model demonstrated strong predictive accuracy (C-index: 0.985–0.986) and effectively stratified patients by survival risk. The CONUT score exerted the greatest prognostic influence, with the LMR providing additional discriminatory value. A gradual decline in survival probability was observed with an increasing CONUT score and a decreasing LMR. Conclusions: The application of machine learning to immune–nutritional data offers a robust tool for predicting survival in patients with advanced gastric cancer requiring HPN. This approach may enhance risk stratification, support individualised clinical decision-making regarding nutritional interventions, and inform treatment intensity adjustment. Full article

Background: Pleural empyema remains a serious clinical condition with high morbidity and mortality, especially in elderly patients. As life expectancy increases, a growing number of older individuals require surgical treatment. This retrospective single-center study investigated age-related differences in clinical presentation, perioperative features, and postoperative outcomes in patients undergoing surgery for pleural empyema. Methods: We conducted this retrospective study at Helios University Hospital Wuppertal, Witten Herdecke University in Germany, from December 2019 to May 2024. We stratified the patients into two age groups: <65 and ≥65 years. We compared baseline characteristics, American Society of Anesthesiologists (ASA) physical status classification, empyema stage, hospital stay, drainage duration, complication rates, and in-hospital mortality. Results: A total of 103 patients were included, of whom 43 (41.7%) were aged ≥ 65 years. Older patients had significantly higher ASA scores and presented with more advanced empyema stages. Hospital stay was significantly longer in this group. However, complication rates (60.0% vs. 44.9%; p = 0.25), drainage duration, ICU admissions (91.4% vs. 83.7%; p = 0.48), and in-hospital mortality (0% in both groups) did not differ significantly. Conclusions: Although older patients had higher perioperative risks, their surgical outcomes were similar to those of younger patients. Chronological age alone should not be a limiting factor for surgical treatment of pleural empyema. Surgical decisions should be based on clinical condition rather than chronological age. Full article

Dementia is a neurodegenerative disorder characterized by progressive cognitive impairment that significantly affects daily living. Early detection of Alzheimer’s disease—the most common form of dementia—remains essential for prompt intervention and treatment, yet clinical diagnosis often requires extensive and resource-intensive procedures. This article explores the effectiveness of automated Natural Language Processing (NLP) methods for identifying Alzheimer’s indicators from audio transcriptions of the Cookie Theft picture description task in the PittCorpus dementia database. Five NLP approaches were compared: a classical Tf–Idf statistical representation and embeddings derived from large language models (GloVe, BERT, Gemma-2B, and Linq-Embed-Mistral), each integrated with a logistic regression classifier. Transcriptions were carefully preprocessed to preserve linguistically relevant features such as repetitions, self-corrections, and pauses. To compare the performance of the five approaches, a stratified 5-fold cross-validation was conducted; the best results were obtained with BERT embeddings (84.73% accuracy) closely followed by the simpler Tf–Idf approach (83.73% accuracy) and the state-of-the-art model Linq-Embed-Mistral (83.54% accuracy), while Gemma-2B and GloVe embeddings yielded slightly lower performances (80.91% and 78.11% accuracy, respectively). Contrary to initial expectations—that richer semantic and contextual embeddings would substantially outperform simpler frequency-based methods—the competitive accuracy of Tf–Idf suggests that the choice and frequency of the words used might be more important than semantic or contextual information in Alzheimer’s detection. This work represents an effort toward implementing user-friendly software capable of offering an initial indicator of Alzheimer’s risk, potentially reducing the need for an in-person clinical visit. Full article

Background/Objectives: Hypopharyngeal squamous cell carcinoma (HPSCC) carries a poor prognosis, and reliable, inexpensive biomarkers are needed to refine risk-stratified treatment. The Glasgow Prognostic Score (GPS), integrating C-reactive protein and albumin, reflects systemic inflammation and nutritional status, but its prognostic utility in curative radiotherapy for HPSCC remains unclear. Methods: We retrospectively reviewed 98 consecutive patients with pathologically confirmed HPSCC who received definitive tomotherapy (70 Gy in 35 fractions) from June 2015 to February 2024 at a single tertiary center. Pretreatment GPS was classified as 0–2. Overall survival (OS) and progression-free survival (PFS) were assessed by Cox proportional hazards models, which evaluated associations between GPS and other clinical parameters. Results: Median age was 68 years (range 41–89); 92% were male. GPS distribution was 0 in 74 patients (76%), 1 in 18 (18%), and 2 in 6 (6%). After a median follow-up of 36.2 months, 3-year OS and PFS for the whole cohort were 78.7% and 51.7%, respectively. Patients with GPS 0 showed significantly higher 3-year OS than those with GPS 1–2 (83.6% vs. 62.2%; p = 0.023). On multivariate analysis, elevated GPS (1–2) remained an independent predictor of worse OS (hazard ratio [HR] 2.62, 95% CI 1.03–6.70; p = 0.044) alongside poor performance status and advanced stage. Conclusions: Pretreatment GPS independently stratifies overall survival in HPSCC patients undergoing curative radiotherapy, complementing established clinical factors. Because CRP and albumin are routinely available, GPS may assist in identifying high-risk patients who could benefit from intensified multidisciplinary treatment. Prospective multicenter studies are warranted to validate these findings. Full article

Background/Objectives: Lung cancer remains a major cause of cancer-related mortality, with regional differences in incidence and patient characteristics. This study aimed to verify and quantify a perceived dramatic increase in lung cancer cases at a Romanian center, identify distinct patient phenotypes using unsupervised machine learning, and characterize contributing factors, including demographic shifts, changes in the healthcare system, and geographic patterns. Methods: A comprehensive retrospective analysis of 4206 lung cancer patients admitted between 2013 and 2024 was conducted, with detailed molecular characterization of 398 patients from 2023 to 2024. Temporal trends were analyzed using statistical methods, while k-means clustering on 761 clinical features identified patient phenotypes. The geographic distribution, smoking patterns, respiratory comorbidities, and demographic factors were systematically characterized across the identified clusters. Results: We confirmed an 80.5% increase in lung cancer admissions between pre-pandemic (2013–2020) and post-pandemic (2022–2024) periods, exceeding the 51.1% increase in total hospital admissions and aligning with national Romanian trends. Five distinct patient clusters emerged: elderly never-smokers (28.9%) with the highest metastatic rates (44.3%), heavy-smoking males (27.4%), active smokers with comprehensive molecular testing (31.7%), young mixed-gender cohort (7.3%) with balanced demographics, and extreme heavy smokers (4.8%) concentrated in rural areas (52.6%) with severe comorbidity burden. Clusters demonstrated significant differences in age (p < 0.001), smoking intensity (p < 0.001), geographic distribution (p < 0.001), as well as molecular characteristics. COPD prevalence was exceptionally high (44.8–78.9%) across clusters, while COVID-19 history remained low (3.4–8.3%), suggesting a limited direct association between the pandemic and cancer. Conclusions: This study presents the first comprehensive machine learning-based stratification of lung cancer patients in Romania, confirming genuine epidemiological increases beyond healthcare system artifacts. The identification of five clinically meaningful phenotypes—particularly rural extreme smokers and age-stratified never-smokers—demonstrates the value of unsupervised clustering for regional healthcare planning. These findings establish frameworks for targeted screening programs, personalized treatment approaches, and resource allocation strategies tailored to specific high-risk populations while highlighting the potential of artificial intelligence in identifying actionable clinical patterns for the implementation of precision medicine. Full article

Objectives: Pneumothorax is a critical condition frequently encountered in emergency departments (EDs), with spontaneous pneumothorax (SP) and traumatic pneumothorax (TP) presenting distinct clinical challenges. This study aimed to evaluate the epidemiological characteristics, clinical outcomes, and treatment strategies for SP and TP across different age groups and provide insights for optimizing emergency management protocols. Methods: This retrospective cohort study analyzed 2797 cases of pneumothorax over five years (2018–2023) at a tertiary care center. Patients were stratified by age (18–39, 40–64, and >65 years) and pneumothorax type (SP vs. TP). Data on demographics, clinical presentation, treatment, hospital stay, recurrence, and complications were extracted from medical records. Comparative statistical analyses were also conducted. Results: The mean age of patients with SP was 32.5 ± 14.7 years, whereas patients with TP were older (37.8 ± 16.2 years, p < 0.001). Male predominance was observed in both groups: 2085 (87.0%) in the SP group and 368 (92.0%) in the TP group (p = 0.01). The right lung was more frequently affected in the SP (64.2%) and TP (56.0%) groups (p < 0.001). Age-related differences were evident in both groups of patients. In the SP group, younger patients (18–39 years) represented the majority of cases, whereas older patients (≥65 years) were more likely to present with SSP and required more invasive management (p < 0.01). In the TP group, younger patients often had pneumothorax due to high-energy trauma, whereas older individuals developed pneumothorax due to falls or iatrogenic causes (p < 0.01). SP predominantly affected younger patients, with a history of smoking and male predominance associated with younger age (p < 0.01). TP is more frequent in older patients, often because of falls or iatrogenic injuries. Management strategies varied by age group; younger patients were often managed conservatively, whereas older patients underwent more invasive procedures (p < 0.01). Surgical intervention was more common in younger patients in the TP group, whereas conservative management was more frequent in elderly patients (p < 0.01). The clinical outcomes differed significantly, with older patients having longer hospital stays and higher rates of persistent air leaks (p < 0.01). Recurrence was more common in younger patients with SP, whereas TP recurrence rates were lower across all age groups (p < 0.01). No significant differences were observed in re-expansion pulmonary edema, empyema, or mortality rates between the age groups, suggesting that age alone was not an independent predictor of these complications when adjusted for pneumothorax severity and management strategy (p = 0.22). Conclusions: Age, pneumothorax subtype, and underlying pulmonary comorbidities were identified as key predictors of clinical outcomes. Advanced age, secondary spontaneous pneumothorax, and COPD were independently associated with recurrence, prolonged hospitalization, and in-hospital mortality, respectively. These findings highlight the need for risk-adapted management strategies to improve triaging and treatment decisions for spontaneous and traumatic pneumothorax. Full article