Search Results (610)

Background: Operational cycle detection underpins a range of important tasks, such as predictive maintenance, energy consumption prediction, and energy management for mobile equipment in mining. Yet, no review has investigated the landscape of methods that segment mobile mining vehicle telemetry into discrete operating modes—a task termed operational cycle detection. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, Scoping Review extension (PRISMA-ScR) framework, we searched The Lens database on 27 June 2025, for records published between 2000 and 2025 that apply cycle detection to mobile mining vehicles. After de-duplication and two-stage screening, 20 empirical studies met all criteria (19 diesel, 1 electric-drive). Due to the sparse research involving battery electric vehicles (BEVs) in mining, three articles performing cycle detection on heavy-duty vehicles in a similar operational context to mining are synthesized. Results: Early diesel work used single-sensor thresholds, often achieving >90% site-specific accuracy, while recent studies increasingly employ neural networks using multivariate datasets. While the cycle detection research on mining BEVs, even supplemented with additional heavy-duty BEV studies, is sparse, similar approaches are favored. Conclusions: Persisting gaps in the literature include the absence of public mining datasets, inconsistent evaluation metrics, and limited real-time validation. Full article

Background/Objectives: Baricitinib, a selective Janus kinase (JAK) 1 and 2 inhibitor, has recently emerged as a therapeutic option for patients with severe alopecia areata (AA). The aim of this study was to identify clinical and biological predictors of early therapeutic response to baricitinib in patients with AA in real-world clinical practice. Methods: A retrospective cohort study was conducted including patients with AA initiating baricitinib between January 2022 and January 2025. Patients were stratified into early responders and non-early responders. Univariate and multivariate logistic regression analyses were performed to assess factors independently associated with early therapeutic response. Results: A total of 44 patients with AA treated with baricitinib were included, the majority being female (65.9%, 29/44), with a mean age of 37.3 years (SD 16.1). Early responders accounted for 34.1% (15/44) of the cohort. In multivariate analysis, early response to baricitinib was independently associated with a lower baseline Severity of Alopecia Tool (SALT) score, shorter disease duration, and elevated erythrocyte sedimentation rate (ESR) at baseline (p < 0.05). Receiver Operating Characteristic (ROC) curve analyses were performed to determine optimal thresholds for predicting early therapeutic response: ESR ≥ 9 mm/h, baseline SALT score ≤ 60%, and disease duration ≤ 7 years. Conclusions: Baseline stratification using easily obtainable clinical and laboratory parameters may help identify patients most likely to benefit from initiating treatment with baricitinib. Our findings support the existence of a therapeutic window of opportunity in AA, particularly in patients with lower disease burden, shorter disease duration, and elevated ESR values. Full article

Background/Objectives: Anaplastic thyroid cancer (ATC) is an aggressive thyroid cancer subtype with a poor prognosis. The Controlling Nutritional Status (CONUT) score, reflecting both immune and nutritional status, is a prognostic marker in several malignancies; however, its utility in ATC has not been established. We aimed to evaluate the predictive value of the pretreatment CONUT score in ATC and compare its prognostic utility with that of other nutritional indices, including the Prognostic Nutritional Index (PNI) and Geriatric Nutritional Risk Index (GNRI). Methods: We retrospectively reviewed clinical characteristics, laboratory parameters, and survival outcomes of 156 patients with ATC at our institution between January 2004 and May 2024. Based on survival analysis, patients were categorized into low- and high-risk groups based on each nutritional index (CONUT score, PNI, GNRI) using optimal cut-off values. One-year survival differences were evaluated using Kaplan–Meier curves and log-rank test. Independent predictors of 1-year mortality were identified using multivariable Cox proportional hazards regression. Results: Optimal thresholds were 3, 42, and 102 for the CONUT score, PNI, and GNRI, respectively. Patients with CONUT scores ≥ 3 exhibited significantly higher 1-year mortality, compared with those with scores < 3. Multivariable analysis revealed that CONUT score ≥ 3, PNI ≤ 42, and GNRI ≤ 102 were independently associated with increased 1-year mortality risk. Incorporation of CONUT score ≥ 3 into the baseline prediction model significantly enhanced its discriminatory performance. Conclusions: These findings underscore the prognostic value of pretreatment immuno-nutritional assessment and support the integration of the CONUT score into early risk stratification strategies for patients with ATC. Full article

Background: Functional lumbar segmental instability (FLSI) is a clinically significant subtype of nonspecific low back pain, characterized by impaired motor control during mid-range spinal motion. Despite its prevalence, diagnostic approaches remain fragmented, and no single clinical test reliably captures its complexity. This scoping review aims to synthesize current evidence on the reliability, validity, subclassification, and predictive value of manual tests used in the evaluation of FLSI, and to identify conceptual and methodological gaps in the literature. Methods: A structured search was conducted across five databases (PubMed, Scopus, Web of Science, CINAHL, Embase) between May and August 2025. Twenty-four empirical studies and eleven foundational conceptual sources were included. Data were charted into five thematic domains: conceptual frameworks, diagnostic accuracy, reliability, subclassification models, and predictive value. Methodological appraisal was performed using QUADAS and QAREL tools. Results: The Passive Lumbar Extension Test (PLET) demonstrated the most consistent reliability and clinical utility. The Prone Instability Test (PIT) and Posterior Shear Test (PST) showed variable performance depending on protocol standardization. Subclassification models distinguishing functional, structural, and combined instability achieved high inter-rater agreement. Screening tools for sub-threshold lumbar instability (STLI) showed preliminary feasibility. Predictive validity of manual tests for rehabilitation outcomes was inconsistent, suggesting the need for multivariate models. Conclusions: Manual tests can support the clinical evaluation of FLSI when interpreted within structured diagnostic frameworks. Subclassification models and composite test batteries enhance diagnostic precision, but standardization and longitudinal validation remain necessary. Future research should prioritize protocol harmonization, integration of sensor-based technologies, and stratified outcome studies to guide individualized rehabilitation planning. Full article

Background: Hypertrophic cardiomyopathy (HCM) is a heterogeneous myocardial disease in which conventional prognostic models, primarily focused on sudden cardiac death, often fail to identify patients at risk of clinically relevant events such as heart failure progression or rehospitalization. Cardiopulmonary exercise testing (CPET) quantifies functional capacity, while stress echocardiography (SE) provides mechanistic insights into exercise-induced hemodynamic changes. Their combined application (CPET–SE) may enhance risk stratification in patients with HCM. Methods: In this retrospective study, 388 patients with obstructive and non-obstructive HCM (mean age 48 ± 15 years, 63.1% male) underwent baseline CPET–SE between 2010 and 2022 and were followed for a median of 7.4 years [IQR 4.3–10.2]. Echocardiographic parameters were assessed at rest and peak exercise, and CPET indices included peak oxygen consumption (pVO₂), ventilatory efficiency, and anaerobic threshold. The primary outcome was a composite of heart failure hospitalization or progression to end-stage HCM. Results: Over a median follow-up of 7.4 years, 63 patients (16.2%) experienced an event of the primary outcome. Patients who developed a primary outcome had greater left atrial diameter (45.0 vs. 41.0 mm, p < 0.001) and indexed volume at rest (36.4 vs. 29.0 mL/m², p < 0.001), with further dilation during stress (p = 0.046); increased LV wall thickness (p = 0.001); higher average E/e′ at rest and during stress (p ≤ 0.004); and higher pulmonary artery systolic pressure at rest (p = 0.027) and during stress (p = 0.044). CPET findings included lower pVO₂ (16.0 vs. 19.5 mL/kg/min, p = 0.001), reduced % predicted pVO₂ (p = 0.006), earlier anaerobic threshold (p = 0.032), impaired ventilatory efficiency (p = 0.048), and chronotropic incompetence (p < 0.001) in patients who experienced a primary outcome. Multivariable analysis identified dyslipidemia (OR 2.58), higher E/e′ (OR 1.06), and lower pVO₂ (OR 0.92) as independently associated with the primary outcome. Conclusions: CPET–SE provided a comprehensive evaluation of patients with HCM, associating aerobic capacity to its hemodynamic determinants. Reduced pVO₂ showed the strongest association with adverse outcomes, while exercise-induced diastolic dysfunction and elevated pulmonary pressures identified a high-risk phenotype. Incorporating CPET–SE into longitudinal management of patients with HCM may enable earlier detection of physiological decompensation and guide personalized therapeutic strategies. Full article

Interleukin-6 (IL-6) is a central mediator of systemic inflammation and is markedly elevated in critical illnesses, including sepsis, acute respiratory distress syndrome, and hyperinflammatory syndromes. Patient responses to immunomodulatory therapies vary, highlighting the need to better understand IL-6 regulation and its clinical implications. We retrospectively analyzed consecutive patients admitted to a medical intensive care unit in a quaternary academic center with a comprehensive cancer program, extracting clinical and laboratory data, including inflammatory markers and plasma IL-6 levels. Plasma IL-6 concentrations were measured using an electrochemiluminescence immunoassay. Survival analyses, multivariable adaptive Lasso regression, Bayesian logistic regression, and latent class analysis were performed to define determinants of IL-6 regulation, mortality, and inflammatory phenotypes. IL-6 levels were substantially elevated in sepsis (median 1150 pg/mL) and neutropenia (median 7866 pg/mL), with extreme concentrations exceeding 20,000 pg/mL when both were present. Although IL-6 across its full range was not independently predictive of intensive care unit mortality, dichotomized thresholds (≥200 pg/mL) correlated with lower survival. Advanced modeling defined a hyperinflammatory phenotype characterized by IL-6 ≥ 100 pg/mL and predicted mortality >40%, showing mortality of 58%, alongside distinct latent subgroups with heterogeneous inflammatory activity and outcomes. These results emphasize the prominent role of sepsis and neutropenia in driving IL-6 elevations and reveal inflammatory phenotypes with potential for risk stratification and targeted anti-cytokine therapy in critical illness. Full article

Background: The hemoglobin-to-red-cell distribution width ratio has emerged as a novel prognostic marker in various clinical settings. However, its association with total bone mineral density in adolescents remains inadequately explored. Methods: This cross-sectional study was based on data from the 2011–2018 National Health and Nutrition Examination Survey, including adolescents aged 12–19 years with complete data on hemoglobin, red cell distribution width, and total bone mineral density. Weighted multivariable linear regression models and generalized additive models were used to evaluate the association between hemoglobin-to-red-cell distribution width and total bone mineral density. A two-piecewise linear regression model was applied to assess potential threshold effects, with log-likelihood ratio tests used to determine the significance of inflection points. Subgroup and interaction analyses were further conducted to examine whether age, sex, race, and milk product consumption modified this association. Results: A total of 3789 adolescents were included. Participants in the highest hemoglobin-to-red-blood-cell distribution width ratio quartile had significantly higher hemoglobin levels, lower red blood cell distribution width, greater total bone mineral density, higher total calcium and blood urea nitrogen levels, and lower body mass index, high-density lipoprotein cholesterol, and serum 25OHD levels compared to lower quartiles. The hemoglobin-to-red-blood-cell distribution width ratio was positively associated with total bone mineral density (fully adjusted β = 0.078, 95% CI: 0.053, 0.104, p < 0.0001). A two-piecewise linear regression model identified an inflection point at the hemoglobin-to-red-cell distribution width ratio = 1.055; the positive association became stronger above this threshold (β = 0.143 vs. β = 0.039 below the threshold, p = 0.003 for nonlinearity). Subgroup analysis revealed significant gender interactions (p < 0.0001). A higher HRR was significantly associated with greater total BMD in males (β = 0.130, 95% CI: 0.089–0.171, p < 0.0001), whereas no significant association was observed in females (β = −0.009, 95% CI: −0.043–0.025, p = 0.604). Positive associations were also observed among participants aged 12–15 years, non-Hispanic Whites, non-Hispanic Blacks, other Hispanics, Mexican Americans, and frequent milk consumers. Conclusions: Our results indicate that the hemoglobin-to-red-cell distribution width ratio shows a potential association with bone mineral density in male adolescents, which may offer supportive value for bone health assessment but requires further validation. Full article

Background: Anthracycline-based chemotherapy is associated with a risk of cancer therapy-related cardiac dysfunction (CTRCD), particularly in patients with moderate to high cardiovascular risk. Left ventricular global longitudinal strain (GLS) is a sensitive marker for early myocardial dysfunction, but the prognostic value of baseline GLS in this population remains unclear. Objective: We aimed to evaluate whether baseline GLS can predict CTRCD in moderate- to high-risk cancer patients undergoing anthracycline chemotherapy. Methods: In this prospective, single-center observational study, 80 anthracycline-naive cancer patients classified as moderate or high risk were enrolled. Baseline GLS was assessed via speckle-tracking echocardiography, with a threshold of ≥−18% considered decreased. Patients were followed for 12 months, and the primary endpoint was the development of CTRCD per ESC 2022 Cardio-oncology guidelines. Results: Of the 77 patients completing follow-up, 27.3% had decreased baseline GLS. CTRCD occurred in 62.4% of patients, with higher incidence among those with decreased GLS (76.7%) compared to those with normal GLS. In multivariable analysis, GLS ≥−18% was the only significant independent predictor of CTRCD (RR 12.0, 95% CI 2.0–71.9; p = 0.0065). All-cause mortality was also significantly higher in patients with decreased baseline GLS (19.1% vs. 1.8%, p = 0.018). Conclusions: Decreased baseline global longitudinal strain is an independent predictor of cancer therapy-related cardiac dysfunction and all-cause mortality in moderate- to high-risk patients receiving anthracycline therapy. These findings support the inclusion of baseline GLS in pre-treatment cardiovascular risk assessment, particularly in patients with an LVEF above 54%, to more effectively identify those who may benefit from early cardioprotective interventions. Full article

Background: Cancer, type 2 diabetes mellitus (T2DM), and psychiatric comorbidities such as depression and anxiety frequently coexist, with shared mechanisms involving systemic inflammation and neuroinflammatory pathways. Understanding these interactions is critical for improving multidisciplinary oncological care. Methods: We conducted a monocentric cross-sectional study (n = 174). Beyond descriptive and univariate analyses, we fitted multivariable models: linear regressions (HADS-Anxiety/Depression) with robust HC3 errors and the predictors ECOG, T2DM, age, sex, and residence, and logistic regression for ECOG ≥ 3. We assessed collinearity and model fit, and performed sensitivity checks. Results: Psychiatric comorbidity was present in 58% of patients, while more than 80% of those with available HADS data (n = 136) exceeded the clinical threshold for anxiety or depression. No significant differences in ECOG status were observed between patients with and without T2DM (mean ECOG 2.5 in both groups). Higher ECOG remained positively associated with both HADS-Depression (adjusted β = 2.77, 95% CI −1.03–6.57, p = 0.149) and HADS-Anxiety (β = 1.62, 95% CI −2.76–6.00, p = 0.468), although not statistically significantly. T2DM showed no independent association with either outcome (Depression β = −2.91, p = 0.130; Anxiety β = −0.80, p = 0.595). In logistic regression, T2DM was not significantly associated with ECOG ≥ 3 (aOR = 3.58, 95% CI 0.23–56.66, p = 0.365). Conclusions: The psychiatric burden is high among Romanian cancer patients, irrespective of T2DM status, and strongly associated with functional decline. These findings support the relevance of a neuroinflammatory framework linking somatic comorbidities and psychological distress. Routine psychiatric screening, early intervention, and integration of psycho-oncology into multidisciplinary care are recommended. Future prospective studies should incorporate inflammatory biomarkers to better define underlying mechanisms. Full article

Background: Uric acid (UA) is linked to gout, renal dysfunction, and cardiovascular disease. Prior studies often assume linear relationships, potentially oversimplifying physiological complexity. Methods: We analyzed data from 5200 healthy Taiwanese men. Demographic, biochemical, lifestyle, and inflammatory variables were assessed using Pearson correlation, multiple linear regression (MLR), and multivariate adaptive regression splines (MARS), an interpretable machine learning method for detecting nonlinear, threshold-based effects. Results: Pearson correlation showed broad linear associations, whereas MARS identified fewer but more physiologically meaningful predictors. Waist-to-hip ratio (WHR) had a strong threshold effect, influencing UA only below 0.969. Creatinine showed a nonlinear impact, becoming substantial above 0.97 mg/dL, suggesting a renal threshold within the “normal” range. Calcium and high-sensitivity C-reactive protein (hs-CRP) each displayed inflection points (9.5 mg/dL and 3.38 mg/L, respectively), indicating range-specific effects. Notably, betel nut exposure, nonsignificant in linear models, emerged in MARS as a predictor with a complex, non-binary association with UA metabolism. Predictive performance was comparable (RMSE: 1.6694 for MARS vs. 1.6666 for MLR), but MARS offered superior interpretability by highlighting localized nonlinear effects. Conclusions: MARS modeling revealed critical nonlinear, threshold-dependent associations between UA and WHR, creatinine, calcium, hs-CRP, and betel nut exposure, which were not captured by conventional methods. These findings underscore the value of interpretable machine learning in metabolic research and suggest precise thresholds for clinical risk stratification. Full article

Background/Objectives: Peritonsillar abscess (PTA) and cellulitis (PTC) often present with similar clinical features, making differentiation challenging despite imaging. This study evaluates the diagnostic performance of serum HMGB1 and kallistatin levels as potential independent biomarkers to distinguish PTA from PTC. Methods: In this single-center prospective cohort study, 97 patients aged 18 to 65 years who met the inclusion criteria and presented with peritonsillar infection (39 PTA; 58 PTC) between February and July 2025 were enrolled. Serum levels of HMGB1, kallistatin, and routine inflammatory markers were measured and compared. Univariate and multivariate logistic regression analyses identified independent predictors for distinguishing PTA from PTC. Receiver operating characteristic (ROC) curve analysis assessed the diagnostic accuracy of biomarkers. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit of individual biomarkers and their combinations across a range of threshold probabilities. Results: Compared to controls, patients with peritonsillar infection had significantly higher WBC, neutrophil, CRP, procalcitonin, and HMGB1 levels and significantly lower kallistatin levels (all p < 0.05). Within the infection group, PTA patients showed significantly higher CRP (p = 0.036) and HMGB1 (p = 0.003) levels and lower kallistatin (p < 0.001) levels compared to PTC patients. In univariate analysis, CRP, HMGB1, and kallistatin were significantly associated with PTA; however, in multivariate analysis, only elevated HMGB1 (OR: 1.21; 95% CI: 1.09–1.35; p < 0.001) and reduced kallistatin (OR: 0.395; 95% CI: 0.24–0.648; p < 0.001) remained independent predictors. ROC analysis showed that both HMGB1 and kallistatin demonstrated good discriminative ability in distinguishing PTA from PTC. DCA revealed that the three-biomarker combination (kallistatin + HMGB1 + CRP) achieved the highest mean net benefit (0.183) across all threshold probabilities, outperforming individual biomarkers (kallistatin: 0.131, HMGB1: 0.111, CRP: 0.099) and the two-biomarker model (0.176). The combined model maintained superior net benefit across threshold probabilities of 25–75%, indicating optimal clinical utility within this decision range. Conclusions: Serum HMGB1 and kallistatin may be effective adjunctive biomarkers for differentiating PTA from PTC. Full article

Background and Objectives: Albuminuria is a key clinical marker for early detection of diabetic kidney disease (DKD) in individuals with type 2 diabetes mellitus (T2DM). The triglyceride-glucose (TyG) index, a simple surrogate of insulin resistance, has been increasingly investigated for its potential association with renal complications. This study aimed to evaluate the relationship between the TyG index and albuminuria in patients with T2DM and assess its clinical utility as an accessible metabolic marker reflecting early renal involvement. Materials and Methods: This retrospective cross-sectional study included 570 adult patients with confirmed T2DM who were followed at a tertiary internal medicine outpatient clinic between January and December 2024. Participants were classified as albuminuric or non-albuminuric based on spot urine albumin-to-creatinine ratio (ACR) values. Clinical and biochemical parameters were collected from medical records, and the TyG index was calculated as ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Logistic regression models were used to identify independent factors associated with albuminuria. ROC analysis was performed to evaluate the discriminatory accuracy of the TyG index. Results: The median TyG index was significantly higher in the albuminuric group compared to the non-albuminuric group (10.0 vs. 9.1; p < 0.001) and increased progressively with albuminuria severity (p < 0.001). In multivariate logistic regression analysis, elevated TyG index, hyperlipidemia, and reduced estimated glomerular filtration rate were independently associated with albuminuria. When evaluated as a continuous variable, the TyG index showed strong discriminatory ability (area under curve (AUC) = 0.949; 95% confidence interval (CI): 0.933–0.964). Using the optimal cut-off threshold of 9.6, the TyG index maintained high diagnostic performance (AUC = 0.870; 95% CI: 0.839–0.902; sensitivity 87.7%, specificity 86.3%). Subgroup analyses confirmed the robustness of this association across clinical and demographic variables. Conclusions: In this study, higher TyG index values were significantly associated with the presence and severity of albuminuria in individuals with T2DM. While causality cannot be inferred, the findings suggest that the TyG index may serve as a practical, cost-effective tool for identifying patients at increased risk for early diabetic kidney involvement. Prospective longitudinal studies are needed to confirm its predictive value and clinical applicability. Full article

Background: Pediatric heart failure (PHF) remains a major contributor to morbidity and mortality, yet standardized diagnostic and prognostic frameworks–particularly those leveraging left ventricular ejection fraction (LVEF)–are not well-established. This study evaluates clinical profiles, therapeutic interventions, and mortality outcomes across LVEF thresholds while identifying an optimal cutoff to refine risk stratification in PHF. Methods: This multicenter retrospective cohort study analyzed 1449 PHF patients (aged 1–18 years) across 30 tertiary centers (2013–2022). LVEF stratification employed conventional thresholds (50%, 55%) and an ROC-optimized cutoff (53%, derived via Youden index maximization). The primary outcome was in-hospital all-cause mortality. Multivariable logistic regression models, adjusted for clinical covariates, evaluated mortality predictors. The discriminative performance of LVEF thresholds was compared using area under the curve (AUC) analysis. Results: Distinct clinical profiles, etiologies, and treatments were observed across LVEF strata (50% vs. 55%; p < 0.05). A data-driven optimized LVEF threshold of 53% was identified for mortality prediction, demonstrating superior diagnostic accuracy with enhanced sensitivity and specificity across age groups. Multivariate analysis revealed LVEF ≥ 55% as protective (OR = 0.81, 95% CI: 0.68–0.96, p = 0.003), while ≥50% was non-significant (OR = 0.91, 95% CI: 0.74–1.12, p = 0.06). Elevated BNP (OR = 2.78, p < 0.001) and NT-proBNP (OR = 2.34, p < 0.001) strongly correlated with mortality risk. Age and sex showed no significant association with outcomes. Conclusion: In conclusion, an LVEF of 53% emerged as the optimal pediatric threshold for mortality prediction, outperforming conventional cutoffs of 50% and 55%. The integration of LVEF with biomarkers (BNP/NT-proBNP) provides a robust prognostic framework, underscoring the necessity for pediatric-specific LVEF criteria and multidimensional risk assessment in PHF management. Full article

Change points caused by extreme events in global economic markets have been widely studied in the literature. However, existing techniques to identify change points rely on subjective judgments and lack robust methodologies. The objective of this paper is to generalize a novel approach that leverages topological data analysis (TDA) to extract topological features from time series data using persistent homology. In this approach, we use Taken’s embedding and sliding window techniques to transform the initial time series data into a high-dimensional topological space. Then, in this topological space, persistent homology is used to extract topological features which can give important information related to change points. As a case study, we analyzed 26 stocks over the last 12 years by using this method and found that there were two financial market volatility indicators derived from our method, denoted as $L_1$ and $L_2$. They serve as effective indicators of long-term and short-term financial market fluctuations, respectively. Moreover, significant differences are observed across markets in different regions and sectors by using these indicators. By setting a significance threshold of 98 % for the two indicators, we found that the detected change points correspond exactly to four major financial extreme events in the past twelve years: the intensification of the European debt crisis in 2011, Brexit in 2016, the outbreak of the COVID-19 pandemic in 2020, and the energy crisis triggered by the Russia–Ukraine war in 2022. Furthermore, benchmark comparisons with established univariate and multivariate CPD methods confirm that the TDA-based indicators consistently achieve superior F1 scores across different tolerance windows, particularly in capturing widely recognized consensus events. Full article

Background: Vascular calcification has been highlighted as a prognostic factor for perioperative thrombosis but a protective factor for late restenosis in lower limb peripheral artery disease (LLPAD). The aim of this study was to investigate the association between calcification and twelve-month primary patency in patients with stenting of the common femoral artery (CFA) and its bifurcation for atheromatous stenosis. Materials/Methods: This single-center retrospective study analyzed consecutive limbs (n = 90) that underwent CFA stenting for symptomatic lesions between January 2018 and January 2023. Calcification was assessed using dedicated computed tomography angiography analysis software (EndoSize; Therenva), with blinded evaluation of volume (mm³) and density (Hounsfield Units) across three anatomically distinct zones: proximal CFA (Zone 1); distal CFA (Zone 2); and bifurcation segments (Zone 3). The primary endpoint was twelve-month primary patency, defined as a peak systolic velocity ratio (PSVR) < 2.4 on duplex ultrasound without target lesion revascularization. Secondary endpoints included predictors of restenosis using multivariable logistic regression. Results: Ninety cases of CFA stenting for LLPAD (lower limb peripheral artery disease) were analyzed. A total of 78.9% of CFA lesions were treated for claudication and 21.1% for critical limb-threatening ischemia (CLTI). Lesions were distributed as Azema types I (1%), II (43%), and III (56%). At twelve-month follow-up, primary patency (PSVR < 2.4) was achieved in 77.4% of limbs. Patent CFA stenting demonstrated significantly higher median calcification density in Zone 2 compared to those with restenosis (1122 [IQR: 903–1248] vs. 858 [788–987] HU; p = 0.006; q = 0.021 after false discovery rate correction). ROC curve analysis identified a density threshold of 800 HU with a 76% reduction in restenosis risk (OR 0.24; 95% CI: 0.08–0.72; p = 0.011). Bootstrap validation (1000 replications) confirmed threshold stability at 821 HU (95% CI: 656–990 HU). Conclusions: In this exploratory study, dense calcification (≥800 HU) in the distal CFA appears to be protective against twelve-month restenosis following stenting. These findings suggest that calcification density may serve as a valuable predictor for patient selection and procedural planning in CFA interventions. Full article