Search Results (1,085)

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

We present a model that integrates the mapping of the phenology and climatic suitability for the spotted lanternfly (SLF), Lycorma delicatula (White, 1845) (Hemiptera: Fulgoridae), to provide guidance on when and where to conduct surveillance and management of this highly invasive pest. The model was designed for use in the Degree-Day, Establishment Risk, and Phenological Event Maps (DDRP) platform, which is an open-source decision support tool to help to detect, monitor, and manage invasive threats. We validated the model using presence records and phenological observations derived from monitoring studies and the iNaturalist database. The model performed well, with more than >99.9% of the presence records included in the potential distribution for North America, a large proportion of the iNaturalist observations correctly predicted, and a low error rate for dates of the first appearance of adults. Cold and heat stresses were insufficient to exclude the SLF from most areas of the conterminous United States (CONUS), but an inability for the pest to complete its life cycle in cold areas may hinder establishment. The appearance of adults occurred several months earlier in warmer regions of North America and Europe, which suggests that host plants in these areas may experience stronger feeding pressure. The near-real-time forecasts produced by the model are available at USPest.org and the USA National Phenology Network to support decision making for the CONUS. Forecasts of egg hatch and the appearance of adults are particularly relevant for surveillance to prevent new establishments and for managing existing populations. Full article

Food safety concerns related to pesticide residues in fruits and vegetables have increased globally, particularly in regions where monitoring programs are scarce or inconsistent. This study provides the first multi-year evaluation of pesticide contamination and associated dietary risks in Cape Verde, an African island nation increasingly reliant on imported produce. A total of 570 samples of fruits and vegetables—both locally produced and imported—were collected from major markets across the country between 2017 and 2020 and analyzed using validated multiresidue methods based on gas chromatography coupled to Ion Trap mass spectrometry (GC-IT-MS/MS), and both gas and liquid chromatography coupled to triple quadrupole tandem mass spectrometry (GC-QqQ-MS/MS and LC-QqQ-MS/MS). Residues were detected in 63.9% of fruits and 13.2% of vegetables, with imported fruits showing the highest contamination levels and diversity of compounds. Although only one sample exceeded the maximum residue limits (MRLs) set by the European Union, 80 different active substances were quantified—many of them not authorized under the current EU pesticide residue legislation. Dietary exposure was estimated using median residue levels and real consumption data from the national nutrition survey (ENCAVE 2019), enabling a refined risk assessment based on actual consumption patterns. The cumulative hazard index for the adult population was 0.416, below the toxicological threshold of concern. However, when adjusted for children aged 6–11 years—taking into account body weight and relative consumption—the cumulative index approached 1.0, suggesting a potential health risk for this vulnerable group. A limited number of compounds, including omethoate, oxamyl, imazalil, and dithiocarbamates, accounted for most of the risk. Many are banned or heavily restricted in the EU, highlighting regulatory asymmetries in global food trade. These findings underscore the urgent need for strengthened residue monitoring in Cape Verde, particularly for imported products, and support the adoption of risk-based food safety policies that consider population-specific vulnerabilities and mixture effects. The methodological framework used here can serve as a model for other low-resource countries seeking to integrate analytical data with dietary exposure in a One Health context. Full article

Introduction: Dental caries and molar–incisor hypomineralisation (MIH) are prevalent conditions affecting children’s oral health, with functional, aesthetic, and psychosocial implications. In Spain, previous studies have highlighted geographic and sociodemographic disparities in their distribution, particularly among rural and migrant populations. Objective: To characterise oral health status, in terms of caries and MIH, among 6–7-year-old children from the towns of Palos de la Frontera, Mazagón, and San Bartolomé. Methods: A cross-sectional study was conducted involving 229 children recruited from public primary schools. Sociodemographic, anthropometric, and behavioural data were collected through clinical examination and interview. Statistical analysis included univariate and multivariate logistic regression. The study protocol was approved by the Ethics Committee of Huelva. Results: The prevalence of caries (DMFT ≥ 1) was 53.3%, with mean DMFT and dft indices of 1.78 and 0.31, respectively. MIH affected 32.8% of the cohort, with a predominance in the first permanent molars (teeth 36 and 26). Multivariate analysis identified independent predictors of caries: African (OR = 7.47; 95% CI: 2.84–23.8) and European (OR = 4.56; 95% CI: 1.26–22.3) parental origin, poor oral hygiene (OR = 3.07; 95% CI: 1.60–6.03), and the presence of MIH (OR = 3.20; 95% CI: 1.64–6.42). The municipality of San Bartolomé was associated with a higher risk of MIH (OR = 2.90; 95% CI: 1.21–7.45). Conclusions: The high prevalence of caries and MIH in the Condado-Campiña district, exceeding national averages, reflects oral health inequities linked to social determinants (migrant origin, locality) and clinical factors (MIH, oral hygiene). Targeted preventive interventions are urgently needed in high-risk populations, including culturally tailored education and policies ensuring equitable access to dental care services. Full article

Introduction: Respiratory Syncytial Virus (RSV) is the leading cause of lower respiratory tract infections in infants and children, as well as hospitalizations for respiratory infections in the pediatric population, representing a significant public health concern. Nirsevimab, a long-acting anti-RSV monoclonal antibody, has recently been approved by the European Medicines Agency (EMA). The aim of this study is to assess the utility of certain parameters, such as the Number Needed to Immunize (NNI), in supporting decision-makers regarding the introduction of nirsevimab as a universal prophylactic measure. Methods: A literature review was conducted to identify the definition and application of the NNI in the context of infectious disease prevention. The following online databases were consulted: Scopus, MEDLINE, Google Scholar, Web of Science, and Cochrane Library. The search was restricted to English-language texts published between 1 January 2000 and 30 January 2025. Results: The NNI represents the number of individuals who need to be immunized to prevent clinical outcomes such as medical visits and hospitalizations caused by infectious diseases. Six studies were identified that utilized this parameter to outline the benefits of immunization and describe the advantages of using monoclonal antibodies for RSV disease. Finelli and colleagues report that to prevent one RSV-related hospitalization, 37–85 infants aged 0–5 months and 107–280 infants aged 6–11 months would need to be immunized with long-acting anti-RSV antibodies. A recent study by Mallah et al. on the efficacy of nirsevimab estimates that the NNI required to prevent one RSV-related hospitalization is 25 infants. Studies by Francisco and O’Leary report NNI values of 82 and 128 infants, respectively, to prevent one RSV-related hospitalization with nirsevimab. Mallah et al. describe NNI as a metric useful to quantify the immunization effort needed to prevent a single RSV hospitalization. A recent Italian study reports that 35 infants need to be immunized to prevent one hospitalization due to RSV-LRTI and 3 infants need to be immunized to prevent one primary care visit due to RSV-LRTI. The studies indicate that the NNI for anti-RSV monoclonal antibodies is lower than the corresponding Number Needed to Vaccinate (NNV) for vaccines already included in national immunization programs. The main limitations of using this parameter include the absence of a shared threshold for interpreting results and the lack of consideration for the indirect effects of immunization on the population. Conclusions: The NNI is an easily understandable tool that can be used to convey the value of an immunization intervention to a variety of stakeholders, thereby supporting public health decision-making processes when considered in association with the uptake of the preventative strategy. At the current status, the estimated NNI of monoclonal antibodies against RSV results favourable and confirms the use in the first year of life for the prevention of RSV disease. Full article

Zoonotic opportunistic enteric protozoa represent a significant global health threat to immunocompromised populations, especially individuals with human immunodeficiency virus (HIV). Despite China’s severe HIV burden, molecular epidemiological data on enteric protozoa remain limited in this population. In this study, we investigated the occurrence and molecular characteristics of Cryptosporidium species, Giardia duodenalis, and Enterocytozoon bieneusi among 150 AIDS patients with severe immunodeficiency in Wuhan city, Hubei Province, China. The overall test-positive rate was 5.33% (8/150), comprising Cryptosporidium species (including C. hominis, C. parvum, and C. meleagridis) in 2.00% (3/150) and G. duodenalis (including assemblage A, B, and E) in 3.33% (5/150); E. bieneusi was not detected. Notably, this study reports the first identification of the C. parvum subtype IIcA5G3 in humans in China, certainly indicating possible cross-border transmission. Furthermore, the detection of C. meleagridis IIIbA22G1R1c provided additional molecular evidence for chicken-to-human transmission. The finding of G. duodenalis assemblage E highlights the underrecognized zoonotic spillover risks to immunocompromised populations. These findings emphasize the diversity of infectious reservoirs, and the need for enhanced national molecular surveillance of these neglected zoonotic enteric protozoa, alongside targeted interventions for vulnerable populations. Full article

Background and Objectives: Congenital heart defects (CHD) affect around 1% of the population, making them the most common congenital disease worldwide. Thanks to advances in treatment, over 90% of affected children are able to reach adulthood, shifting focus to long-term outcomes such as disease-specific quality of life (DsQoL). To date, there has been no validated, standardized instrument for assessing DsQoL in young German CHD patients. This study introduces the Congenital Heart Disease Specific Inventory (CHDSI), the first freely available German-language instrument for measuring DsQoL in children and adolescents with CHD. Materials and Methods: The CHDSI was developed at the German Heart Center Munich in collaboration with affected children and adolescents and validated nationwide via the National Register for Congenital Heart Defects (NRCHD) with 1201 participants (46 kindergarten children, 530 children, 625 adolescents). Two age-specific versions (36/37 items) and a 31-item preschool version were created, alongside a 6-item short form (CHDSI-SF) for rapid screening. Reliability was assessed using Cronbach’s alpha and split-half methods; construct validity via confirmatory factor analysis (CFA) using DWLS; and score interpretation through standardized stanine scales. The small sample size of kindergarten children precluded a model test for this group. The standard values given for this subsample should therefore be interpreted with caution. Results: The CHDSI showed excellent internal consistency (Cronbach’s α = 0.856 to 0.900) and high split-half reliability (>0.95). CFA confirmed a robust six-factor structure with excellent model fit (CFI and TLI ≥ 0.991, RMSEA ≤ 0.05). Subscales showed strong discriminant validity, and significant differences were found by CHD severity and sex. Conclusions: The CHDSI is a psychometrically valid, age-appropriate, and freely available instrument for assessing DsQoL in children and adolescents with CHD. It provides valuable support for clinical decision-making and research. Further studies should explore international validation and cultural adaptation. Full article

Background: Genetic insights from diverse populations are key to advancing cancer detection, treatment, and prevention. Unlike other Latin American countries, Colombia lacks a centralized registry for germline and somatic mutations in breast and ovarian cancer. This study describes the country’s first national variant registry, and the occurrence of recurrent mutations and potential founder effects in Colombia. Methods: To address this gap, we implemented the first capturing protocol using the REDCap system. In a group of 213 breast and/or ovarian cancer patients harboring genetic mutations, we collected genetic, clinical, and demographic data from 13 regional centers across Colombia. Statistical analyses assessed variant distribution and patient demographics. Results: Among 229 identified variants (105 germline, 124 somatic), most were classified as pathogenic or likely pathogenic (72.4% germline, 87% somatic). BRCA1 and BRCA2 accounted for the majority of recurrent mutations. Germline recurrent variants (seen >3 times) were recorded for BRCA1 (77.7%; 21/27) and BRCA2 (22.3%; 6/27). Similarly, recurrent somatic variants were identified for BRCA1 (82.6%; 38/46) and BRCA2 (17.4%; 8/46). Notably, four recurrent variants were previously reported as founder mutations: BRCA1 c.1674del (14.3% germline and 23.7% somatic), BRCA1 c.3331_3334del (33.3% germline and 52.6% somatic), BRCA1 c.5123C>A (52.4% germline and 23.7% somatic), and BRCA2 c.2808_2811del (50% germline and 50% somatic). Most cases originated from the Andean region, highlighting regional disparities. Conclusions: This registry offers the first overview of genetic variants in Colombian breast and ovarian cancer patients. Recurrent and region-specific mutations highlight the need for population-focused data to guide targeted screening and personalized care strategies. Full article

H. pylori infects over half of the global population and is associated with various gastric and extra-gastric diseases. Other species, such as zoonotic non-Helicobacter pylori Helicobacters (NHPHs), have shown similar associations with gastritis and MALT lymphoma and H. pylori-negative cases with gastric disease have been identified, including gastric MALT lymphoma, chronic gastritis, and gastroduodenal ulcers. Accurate identification of these species is of great relevance but remains challenging using conventional diagnostic methods. This cross-sectional study aimed to determine the prevalence of H. pylori and NHPH infections, comparing standard histological protocols with molecular techniques. Between December 2024 and February 2025, 54 adult patients undergoing upper gastrointestinal endoscopy (UGE) with gastric biopsy in three hospitals in Algarve, Portugal were recruited. Endoscopic assessment was performed, and gastric biopsies were collected for histological and molecular analysis. DNA was extracted from antral biopsies and analyzed by conventional PCR to detect H. pylori and NHPH. H. pylori diagnostic techniques were compared, descriptive plus statistical analysis was performed, and p-values < 0.05 were considered to be statistically significant. Fifty-four patients were included in the study, with 51.9% of them presenting symptoms. Endoscopic gastritis was observed in 66.7% of patients, while histological gastritis was present in 88.9%, with statistically significant differences between the two diagnostic techniques (p = 0.004). Helicobacter spp. were identified in 44.4% (24/54) of the patients. H. pylori was detected in 42.6% of the patients by Modified Giemsa stain and in 33.3% by PCR. H. bizzozeronii was found in 35.9% of the patients, with 22.2% showing mixed infections. This study reveals a significant prevalence of Helicobacter spp. in patients from the Algarve region, with both H. pylori and zoonotic H. bizzozeronii detected. This is the first report of H. bizzozeronii DNA detection in gastric biopsies via PCR from patients undergoing UGE in Portugal, highlighting the need to consider NHPH in clinical diagnosis. It is important to include molecular methods in routine diagnostics and the need for broader studies to assess regional and national trends in Helicobacter infections besides H. pylori. Full article

Brachial plexus root avulsion [BPRA] and concomitant spinal cord injury [SCI] represent devastating injuries that come with limited hope for recovery owing to the adult spinal cord’s loss of intrinsic ability to spontaneously regenerate. BPRA/SCI is an enormous public health issue the world over, and its catastrophic impact goes beyond the patient, the family, businesses, and national health budgets, draining billions of dollars annually. The rising population and economic growth have seen the incidence of SCI surging. Genomic, transcriptomic, and proteomic studies have yielded loads of information on the various molecular events that precede, regulate, and support both regenerative and degenerative pathways post-SCI. Metabolomics, on the other hand, comes in as the search for a cure and the objective monitoring of SCI severity and prognosis remains on the horizon. Despite the large number of review articles on metabolomics and its application fields such as in cancer and diabetes research, there is no comprehensive review on metabolite profiling to study disease mechanisms, biomarkers, or neuroprotection in SCI. First, we present a short review on BPRA/SCI. Second, we discuss potential benefits of metabolomics as applied in BPRA/SCI cases. Next, a look at the analytical techniques that are used in metabolomics. Next, we present an overview of the studies that have used metabolomics to reveal SCI metabolic fingerprints and point out areas of further investigation. Finally, we discuss future research directions. Full article

This study aimed to predict the potential habitats of Luciola unmunsana using a species distribution model (SDM). Luciola unmunsana is an endemic species that lives only in South Korea, and because its females do not have genus wings and are less fluid, it is difficult to collect, so research related to its distribution and restoration is relatively understudied. Therefore, this study predicted the potential habitats of Luciola unmunsana across South Korea using the single model Maximum Entropy (MaxEnt) and a multi-model ensemble model to prepare basic data necessary for a conservation and habitat restoration plan for the species. A total of 39 points of occurrence were built based on public data and prior research from the Jeonbuk Green Environment Support Center (JGESC), the Global Biodiversity Information Facility (GBIF), and the National Institute of Biological Resources (NIBR). Among the input variables, climate variables were based on the shared socioeconomic pathway (SSP) scenario-based ecological climate index, while nonclimate variables were based on topography, land cover maps, and the Enhanced Vegetation Index (EVI). The main findings of this study are summarized below. First, in predicting Luciola unmunsana potential habitats, the EVI, water network analysis, land cover, and annual precipitation (Bio12) were identified as good predictors in both models. Accordingly, areas with high vegetation activity in their forests, adjacent to water resources, and stable humidity were predicted as potential habitats. Second, by overlaying the predicted potential habitats and highly significant variables, we found that areas with high vegetation vigor within their forests, proximity to water systems, and relatively high annual precipitation, which can maintain stable humidity, are potential habitats for Luciola unmunsana. Third, literature surveys used to predict potential habitat sites, including Geumsan-gun, Chungcheongnam-do, Yeongam-gun, Jeollabuk-do, Mudeungsan Mountain, Gwangju-si, Korea, and Gijang-gun, Busan-si, Korea, confirmed the occurrence of Luciola unmunsana. This study is significant in that it is the first to develop a regional SDM for Luciola unmunsana, whose population is declining due to urbanization. In addition, by applying various environmental variables that reflect ecological characteristics, it contributes to more accurate predictions of the potential habitats of this species. The predicted results can be used as basic data for the future conservation of Luciola unmunsana and the establishment of habitat restoration strategies. Full article

Water scarcity, exacerbated by climate change, population growth, and competing sectoral demands, poses a major threat to agricultural sustainability, particularly in irrigated regions such as the Nile Delta in Egypt. Addressing this challenge requires innovative approaches to evaluate irrigation performance despite the limitations in ground data availability. Traditional assessment methods are often costly, labor-intensive, and reliant on field data, limiting their scalability, especially in data-scarce regions. This paper addresses this gap by presenting a comprehensive and scalable framework that employs publicly accessible satellite data to map crop types and subsequently assess irrigation performance without the need for ground truthing. The framework consists of two parts: First, crop mapping, which was conducted seasonally between 2015 and 2020 for the four primary crops in the Nile Delta (rice, maize, wheat, and clover). The WaPOR v2 Land Cover Classification layer was used as a substitute for ground truth data to label the Landsat-8 images for training the random forest algorithm. The crop maps generated at 30 m resolution had moderate to high accuracy, with overall accuracy ranging from 0.77 to 0.80 in summer and 0.87–0.95 in winter. The estimated crop areas aligned well with national agricultural statistics. Second, based on the mapped crops, three irrigation performance indicators—adequacy, reliability, and equity—were calculated and compared with their established standards. The results reveal a good level of equity, with values consistently below 10%, and a relatively reliable water supply, as indicated by the reliability indicator (0.02–0.08). Average summer adequacy ranged from 0.4 to 0.63, indicating insufficient supply, whereas winter values (1.3 to 1.7) reflected a surplus. A noticeable improvement gradient was observed for all indicators toward the north of the delta, while areas located in the delta’s new lands consistently displayed unfavorable conditions in all indicators. This approach facilitates the identification of regions where agricultural performance falls short of its potential, thereby offering valuable insights into where and how irrigation systems can be strategically improved to enhance overall performance sustainably. Full article

Current structural barriers experienced by First Nations in Canada shape access and engagement for testing and treatment of hepatitis C virus (HCV) infections. This non-systematic informative review considers transdisciplinary perspectives, regional data, and published literature connecting context to the disproportionate HCV burden experienced by First Nations populations in the prairie provinces of Canada, and offers examples of participatory and community-led initiatives working toward the elimination of HCV as a public health threat. First Nations in Canada are disproportionately impacted by chronic HCV infection, with a reported rate of newly diagnosed HCV cases in First Nations communities five times the respective rate in the general Canadian population in 2022. This review explores the reasons underlying the disproportionate burden of HCV infection. Significant over-representation of First Nations in the Canadian Prairies is seen in the major risk categories for HCV acquisition, and the impact of these risk factors is aggravated by barriers to accessing healthcare services and medication coverage. These barriers stem from the legacy of colonialism, discrimination, disenfranchisement, and are exacerbated by stigmatization, victimization, and racism in the justice and healthcare systems. Other contributory factors that impede access to care include inadequate healthcare clinic staffing and infrastructure in First Nations communities, and significant geographical distances between First Nations reserves and laboratories, pharmacies, and treating/prescribing healthcare providers. Recent recognition of historical harms and early steps towards nation-to-nation reconciliation, along with support for culturally connected, holistic, and First Nations-led wellness programs, instill hope that elimination strategies to eradicate HCV infection in First Nations populations will be successful in Canada. Full article

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. 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