Search Results (1,553)

Blood-based biomarkers offer a promising “biochemical imaging” approach for acute ischemic stroke (AIS) management, providing objective and accessible tools to complement conventional neuroimaging. This narrative review synthesizes recent advances in biomarkers derived from multiple neurovascular unit (NVU) compartments, including glial fibrillary acidic protein (GFAP), S100 calcium-binding protein B (S100B), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), neuron-specific enolase (NSE), neurofilament light chain (NfL), matrix metalloproteinase-9 (MMP-9), Claudin-5, Occludin, brain-derived neurotrophic factor (BDNF), interleukin-33 (IL-33), tumor necrosis factor-alpha (TNF-alpha), PARK7/DJ-1, glycogen phosphorylase BB (GP-BB), and circulating microRNAs. We focus on their stage-specific clinical utility across three scenarios: (1) ultra-early differentiation between ischemic stroke and intracerebral hemorrhage in prehospital and emergency settings; (2) dynamic prediction and monitoring of hemorrhagic transformation after reperfusion therapies; and (3) assessment of infarct burden, neurorepair potential, and long-term functional outcomes. Despite their promise, clinical translation remains hindered by assay platform heterogeneity, lack of standardized cut-off values, limited cost-effectiveness data, and insufficient prospective validation adjusted for key covariates such as age and renal function. We further discuss multi-marker panel construction, including strategies to address biomarker collinearity and overfitting. Future directions emphasize stage-specific panels, point-of-care testing devices, and artificial intelligence algorithms to advance precision medicine in stroke care. Full article

Walking is not merely locomotion but a window into the nervous system, integrating cortical, subcortical, cerebellar, spinal, and peripheral networks into a unified motor behavior. Across neurological diseases—including Parkinson’s disease, atypical parkinsonism, cerebellar ataxias, stroke, multiple sclerosis, neuropathies, neuromuscular disorders, and functional gait syndromes—gait disturbances are among the most disabling clinical features, contributing to falls, loss of independence, institutionalization, and premature mortality. Traditional bedside observation remains indispensable, but it lacks the sensitivity and reproducibility needed to capture subtle, episodic, or prodromal abnormalities. Over the past decade, advances in wearable sensors, marker-based and markerless motion capture, pressure-sensitive walkways, force plates, artificial intelligence, and machine learning have positioned digital mobility outcomes as promising, ecologically valid biomarkers of neurological function. These measures can support differential diagnosis, provide prognostic information on falls and survival, and serve as sensitive endpoints in therapeutic trials. They may also detect early abnormalities, such as increased stride-to-stride variability or prolonged double-support time, before overt clinical deterioration becomes evident. Clinical applications are increasingly evident across disorders, including distinguishing Parkinson’s disease from atypical parkinsonism, quantifying treatment response in normal-pressure hydrocephalus, tracking progression in ataxia and multiple sclerosis, predicting functional decline in motor neuron disease, and guiding rehabilitation after stroke. Integration with neuroimaging, electrophysiology, and molecular biomarkers is beginning to reveal the circuits underlying variability, instability, and freezing, positioning gait as a systems-level marker of neural integrity. Nevertheless, methodological heterogeneity, limited disease-specific validation, insufficient longitudinal data, and lack of consensus on clinically meaningful parameters continue to constrain translation. Cognitive, affective, and environmental influences also remain insufficiently represented in digital frameworks, while equity, accessibility, algorithmic bias, and privacy require careful ethical governance. Reconceptualizing gait as a “sixth vital sign” reframes mobility as a multidimensional biomarker of neural and systemic health. With harmonized protocols, robust validation, multimodal integration, and appropriate ethical frameworks, gait analysis could become a cornerstone of precision neurology. Full article

Background: Stroke remains a leading cause of mortality, disability, and health-system burden in Korea’s rapidly aging population. We aimed to describe national stroke incidence trends from 2011 to 2023, characterize ecological associations between stroke incidence and health-screening indicators, and generate model-based projections through 2028 to support health-system planning. Methods: This retrospective ecological longitudinal analysis used three publicly available aggregate national data sources: (1) NHIS annual aggregate statistics on crude and age-standardized stroke incidence, stroke case counts, first-onset vs. recurrent stroke, and case-fatality rates (2011–2023); (2) regional standardized health-awareness survey rates for stroke symptoms, myocardial infarction symptoms, blood pressure, and blood glucose (2017–2025); and (3) national cancer-screening outcome tallies for breast and cervical cancer (2010–2024). All analyses used pre-aggregated annual summary data; individual-level NHIS records were not used. Annual trends were modeled with ordinary least-squares linear regression (n = 13 annual observations). Pearson correlations were computed only for overlapping observation windows. Model-based projections are presented with 95% prediction intervals and are explicitly distinguished from observed NHIS values. This study is purely descriptive and ecological; no causal inference is made. Results: Crude stroke incidence increased from 199.2 to 221.1 per 100,000 (2011–2023; slope +2.32/year, R² = 0.83), whereas age-standardized incidence declined from 158.3 to 113.2 per 100,000 (slope −3.41/year, R² = 0.96), a pattern consistent with demographic aging as a contributing factor to growing absolute burden, though formal age-decomposition analysis would be required to confirm this inference. Total cases increased from 99,837 to 113,098; the 30-day case-fatality rate declined from 8.5% to 7.5%. Ecological correlations showed that blood glucose awareness was strongly negatively correlated with age-standardized incidence (r = −0.944, p = 0.001, n = 7), though these are ecological associations and must not be interpreted as individual-level causal relationships. Model-based projections estimate crude incidence near 230.7 (95%PI 219.2–242.2) and age-standardized incidence near 103.2 (95%PI 95.7–110.8) per 100,000 by 2026. Conclusions: Concurrent increase in crude burden and decline in age-standardized incidence reflects demographic aging as the primary driver of Korea’s stroke burden. Projections support integrated cardiovascular prevention, public health education, and age-sensitive service planning. All projections are short-horizon statistical extrapolations intended for policy scenario planning only and must not be interpreted as observed future NHIS outcomes. Full article

Understanding the impact of neighborhood-level factors on stroke prevalence is crucial for addressing existing disparities. However, there is a distinct lack of ecological studies at the census tract level that investigate the social determinants of health (SDOH) influencing stroke prevalence within the U.S. Health and Human Services Region 3 (HHS Region 3: Delaware, Maryland, Pennsylvania, Virginia, West Virginia, and the District of Columbia). This study adopted a multivariate modeling approach to investigate the association between the 13 indicators of the Health Opportunity Index (HOI) and stroke prevalence at the census tract level in HHS Region 3 using four HOI indicator profiles and to highlight the specific SDOHs that are most associated with stroke prevalence. The four HOI indicator profiles include: (a) neighborhood and built environment profile, (b) social and community context profile, (c) resource profile, and (d) economic profile. The methodological approach was quantitative, using secondary data. The sample size was 8021 census tracts. The HOI was estimated for each census tract in the study area. Ordinary least squares regression (OLS) analysis and spatial lag model (SLM) were run to examine whether the 13 indicators of the HOI (categorized into four profiles) reliably predict stroke prevalence and to determine the most appropriate model that best identifies the strongest predictors of stroke prevalence. The results show that affordability, education, spatial segregation, and income inequality indicators were the strongest predictors of stroke prevalence in HHS Region 3. This granular research identifies the neighborhood-level SDOH most strongly linked to stroke prevalence, which can be leveraged to guide the development of targeted public health programs, quality improvement initiatives, resource allocation, and policy creation to combat stroke-related morbidity and mortality across census tracts in HHS Region 3. For example, the built environment, encompassing factors like employment access, affordable housing, and walkability, profoundly influences stroke prevalence and provides urban planners with practical insights for developing healthier, more equitable communities, such as creating neighborhood parks to encourage physical activity, a key factor in stroke prevention. This study also provides neighborhood organizations with the evidence needed to pursue grant funding and raise awareness about the socio-structural influences on stroke outcomes in their respective neighborhoods. Lastly, the insights generated from our study can facilitate collaborative decision-making processes with communities in HHS Region 3 regarding the prioritization of neighborhood-level SDOH for targeted public health interventions. This prioritization should focus on addressing predictors of stroke prevalence that are congruent with the community’s established priorities, thereby maximizing cost savings. Full article

Background: Following a stroke, body and brain temperatures are closely linked. Elevated temperature may reflect the severity of brain injury rather than infection. The significance of admission temperature remains unclear, and hypothermia treatment lacks proven efficacy and safety. Administering paracetamol (acetaminophen) above 36.5 °C is considered safe, though its clinical benefit is modest. This study aimed to examine how admission temperature, peak temperature in the first 24 h, and temperature fluctuations affect three-month functional outcomes. Methods: We conducted a retrospective study using data from a prospective stroke registry, including 5883 patients (4830 with ischemic stroke [IS] and 1053 with hemorrhagic stroke [HS]). Temperature at admission, maximum temperature within the first 24 h, and the temperature increase during the first day were assessed. Patients with a temperature ≥ 37.5 °C received 3 g of paracetamol per day until normothermia was achieved. Results: Baseline temperature was not associated with 3-month functional outcomes. In IS patients, an increasing temperature during the first 24 h was associated with a 10-fold higher risk of poor functional outcome (sensitivity 81%, specificity 64%); whereas in HS, the risk increased sevenfold (sensitivity 88%, specificity 53%). The most reliable predictor of therapeutic response was the temperature increase on the first day, with sensitivities of 89% and 83%, and specificities of 84% and 71%, for IS and HS, respectively. Conclusions: An increase in temperature during the first 24 h, rather than a single measurement, is the most reliable temperature-based biomarker for predicting poor functional outcomes and guiding the initiation of antihyperthermic treatment. Full article

Background: Prolonged cardiac monitoring increases atrial fibrillation (AF) detection after ischemic stroke or transient ischemic attack (TIA). The AS5F score was developed to identify patients at higher risk of post-stroke AF, but its performance in real-world populations remains incompletely characterized. We aimed to externally validate the AS5F score and to evaluate whether left atrial dilatation (LAD) improves risk prediction. Methods: We conducted a retrospective single-center study including 410 patients with ischemic stroke or TIA who underwent prolonged Holter monitoring between 2021 and 2025. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to assess discrimination. Model calibration was evaluated using the Hosmer–Lemeshow test. Results: AF was detected in 33 patients (8.0%). The AS5F score was significantly associated with AF detection (OR 1.07 per point; 95% CI 1.03–1.11; p < 0.001), showing modest discrimination (AUC 0.69). Age alone demonstrated similar performance (AUC 0.69). LAD was strongly associated with AF (OR 4.00; 95% CI 1.79–8.93; p = 0.001) but had lower discriminatory ability (AUC 0.61). In patients with available echocardiographic data (n = 369), a combined age + LAD model achieved an AUC of 0.73 with adequate calibration. The improvement compared with AS5F was not statistically significant. Conclusions: In this external real-world cohort, AS5F demonstrated moderate discrimination for post-stroke AF detection. A simplified model combining age and left atrial dilatation showed numerically higher performance and may represent a pragmatic strategy for risk stratification in clinical practice. Full article

Background/Objectives: The accurate prediction of postprocedural mortality is critical for clinical decision-making; however, research on mortality risk models for patients undergoing mechanical thrombectomy remains limited. This study aimed to develop and validate machine learning models for predicting 90-day post-mechanical thrombectomy mortality. Methods: A retrospective-prospective cohort study involving 699 retrospective patients (January 2019–December 2022) and 274 prospective patients (January 2023–June 2024) from a single institution in Sichuan was conducted. The primary outcome was all-cause mortality within 90 days, ascertained via telephone follow-up. Predictors were identified using univariate analysis and LASSO regression. Eight predictive models were developed and evaluated using existing machine learning methods via 10-fold cross-validation. Model performance was assessed through discrimination, calibration, decision curve analysis, and interpretability via Shapley additive explanations. Results: The final dataset included 593 patients in the modeling set and 247 in the validation set. The 90-day mortality rates were 25.6% and 32.0%, respectively. Key predictors included age, hyperlipidemia, atrial fibrillation, pre-stroke statin use, antiplatelet/anticoagulant therapy within 48 h of onset, dysphagia, D-dimer levels, and activities of daily living scores. Logistic regression demonstrated superior performance in the modeling cohort (AUC = 0.87), whereas the multilayer perceptron model exhibited the greatest efficacy in the validation cohort (AUC = 0.77). Conclusions: Machine learning algorithms can accurately predict 90-day mortality among patients undergoing mechanical thrombectomy. The multilayer perceptron model demonstrated robust validation performance and offers a potential tool for personalized risk assessment and optimization of clinical decision-making. Full article

This paper proposes a data-driven framework for simulating turbocharger (TC) failure scenarios and modelling specific fuel oil consumption (SFOC) degradation in two-stroke low-speed marine diesel engines. A GaussianCopula model was fitted to the joint distribution of fifteen variables, using approximately eleven months of operational sensor data (n = 480 clean records, 4 h interval, January–December 2014) taken from a container ship. Three physically motivated failure scenarios were produced: turbine blade fouling, bearing wear and compressor surge. Predictive models trained on the real dataset achieved R² = 0.9998 for TC RPM and R² = 0.984 for fuel flow when using Gradient Boosting with 5-fold cross-validation. Feature importance analysis showed that the dominant determinants of TC speed were scavenging air intake pressure (35.3%) and engine power (MCR, 31.3%). Shaft power (45.5%) and TC RPM (19.3%) together explained most of the fuel consumption variance. Simulated failure scenarios produced SFOC increases of +6.6% (fouling), +9.6% (surge), and +13.3% (bearing wear) when compared to a normal operating baseline of 202 g/kWh, which is in line with published empirical data from MAN B&W engine performance curves. An IsolationForest anomaly detector trained only on normal operating samples flagged failure scenario records at a rate of 17.5–23.7%, which demonstrates that moderate-sensitivity early warning detection is feasible from routine sensor streams. The results show that TC condition monitoring could serve as a leading indicator of fuel-efficiency degradation. This has significant implications for condition-based maintenance planning and CII (Carbon Intensity Indicator) compliance. Full article

Objective: The objectives of this study were to characterise induction-phase regional cerebral oxygen saturation (rSO₂)–mean arterial pressure (MAP) dynamics during near-infrared spectroscopy (NIRS)-guided selective carotid endarterectomy (CEA) and to examine whether the Awake→Intubated pressure–oxygenation pattern may represent an early adjunctive physiological signal of subsequent cross-clamp-related ipsilateral cerebral desaturation. Methods: In this retrospective observational cohort study, 322 consecutive elective CEAs managed with an NIRS-guided selective shunting protocol between October 2019 and February 2025 were analysed, after excluding patients considered for routine pre-emptive shunting because of contralateral internal carotid artery occlusion or ≥70% stenosis. Standardised MAP and bilateral rSO₂ values were extracted at the Awake, Intubated, and Clamp stages, defined as 3 min after carotid cross-clamping. Awake→Intubated ipsilateral ΔrSO₂/ΔMAP was evaluated as a continuous, exploratory pressure–oxygenation index, with MAP–rSO₂ directional change classified as concordant or discordant. Clamp-related desaturation was defined as a ≥20% ipsilateral rSO₂ decrease from Awake to Clamp. Discrimination and adjusted associations were evaluated using receiver operating characteristic analysis and multivariable logistic regression, respectively. Results: Clamp-related ≥20% ipsilateral rSO₂ desaturation occurred in 43 patients (13.4%). The Awake→Intubated ipsilateral ΔrSO₂/ΔMAP ratio differed significantly between patients with and without ≥20% desaturation and showed significant discrimination on receiver operating characteristic analysis, with an area under the curve (AUC) of 0.799 (95% confidence interval [CI] 0.723–0.876; p < 0.001). Concordant pressure–oxygenation change was more frequent among patients with ≥20% desaturation (31/43, 72.1%), whereas discordant change predominated among those without desaturation (228/279, 81.7%; p < 0.001). In multivariable analysis, Awake→Intubated ipsilateral ΔrSO₂/ΔMAP remained associated with clamp-related ≥20% desaturation after adjustment (adjusted odds ratio [OR] 1.63, 95% CI 1.15–2.33; p = 0.006), along with symptomatic presentation and 50–69% contralateral stenosis. Postoperative stroke occurred in 4/322 patients (1.2%), and no 30-day mortality occurred. Conclusions: During NIRS-guided selective CEA, induction-phase rSO₂–MAP dynamics were associated with subsequent cross-clamp-related ipsilateral cerebral desaturation. As the outcome was a NIRS-defined desaturation rather than an independent clinical, neurological, or imaging endpoint, these findings indicate association with a surrogate marker rather than prediction of clinically relevant cerebral ischaemia. The Awake→Intubated ΔrSO₂/ΔMAP ratio and directional pressure–oxygenation pattern may represent early adjunctive physiological signals associated with clamp-related desaturation. These findings are hypothesis-generating and require prospective validation with systematic multimodal monitoring. Full article

Tool wear significantly impacts the productivity and efficiency of sheet metal stamping operations, particularly in high-volume progressive die applications. This study presents an iterative calibration framework for Archard’s wear model, tailored to industrial stamping processes. The proposed methodology integrates finite element simulations with experimentally measured wear data obtained from production components, enabling data-driven calibration of the wear coefficient $K_{sim}$. The framework achieves high predictive accuracy, with deviations of 1.4–3.7% between simulated and optically measured wear depths and localization, after more than 15 million strokes. Rapid convergence is obtained within two to three calibration cycles, significantly reducing computational effort while maintaining physical fidelity. The simulation setup incorporates detailed modelling of contact pressure, sliding velocity, and stress distribution, validated using optical surface measurement systems and coordinate-based metrology. Beyond the specific industrial case, the framework demonstrates transferability to other sheet metal forming processes, such as bending, blanking, and coining, by leveraging physically based parameter adaptation across comparable pressure–velocity regimes. The approach enables predictive wear modeling in data-scarce environments and supports early-stage tool design workflows. Overall, the proposed methodology bridges the gap between empirical calibration and generalized simulation, contributing both methodological rigour and practical applicability to manufacturing science. Full article

Background/Objectives: The FIB-4 index is a laboratory test for predicting liver fibrosis. The aim of this study was to investigate the association between FIB-4 index and hematoma expansion in patients with intracerebral hemorrhage (ICH). Methods: A retrospective review was made of the records of 98 consecutive patients with ICH, separated into two groups according to the FIB-4 index: Group 1 (FIB-4 ≤ 2.67) and Group 2 (FIB-4 > 2.67). The demographic data, admission National Institutes of Health Stroke Scale (NIHSS) scores, hematoma volume on admission and follow-up cranial computed tomography (CT) within 72 h of admission, hematoma extension, mortality, and modified Rankin Scale (mRS) scores at discharge and the first follow-up visit were recorded. Results: Group 1 (FIB-4 ≤ 2.67) included 75 patients (28 (37.3%) females, 47 (62.7%) males) and Group 2 (FIB-4 > 2.67) included 23 patients (6 (26.1%) females, 17 (73.9%) males). The results of multivariable regression analysis to evaluate predictors of hematoma expansion showed an independent association of age and FIB-4 index > 2.67 with hematoma expansion. Increasing age was associated with a lower likelihood of hematoma expansion (OR 0.941, 95% CI 0.901–0.983, p = 0.012). A FIB-4 index > 2.67 indicated a markedly increased predisposition to hematoma expansion compared to a FIB-4 index ≤ 2.67 (OR 4.12, 95% CI 1.215–13.980, p = 0.032). Conclusions: The results of this study showed that an elevated FIB-4 index was associated with hematoma expansion. Large-scale prospective studies are needed to confirm this relationship and provide valuable insights for clinical practice. Full article

Fully integrated MITC4 (mixed interpolation of tensorial components) shells remain costly for large-deformation sheet-metal forming benchmarks at production mesh sizes. This paper presents a GPU-resident explicit MITC4 shell solver, implemented as a single CUDA pipeline in which co-rotational kinematics, assumed natural strain transverse shear, through-thickness J2 elasto-plasticity, and rigid-surface penalty contact remain in device memory. The study is positioned as computational verification and benchmarking for the Nakajima hemispherical-dome forming benchmark. Canonical shell tests verify the element kernel through membrane and bending patches and a force-driven cantilever, with the cantilever deflection agreeing with the MacNeal–Harder reference within about 2%. On the 10K-element Nakajima benchmark, the present solver agrees with Abaqus/Explicit with a mean von Mises error of 2.95% over 94% of specimen elements and a maximum shell thickness error of 2.08%. In the clamped/binder transition band, section-mean von Mises agrees to +1.0%, whereas section-maximum stress is under-predicted by 10.9%. A 50K-element Abaqus check remains bounded at 80 mm stroke, with section-mean von Mises differences of +0.6% globally and +0.4% in the transition band. For throughput, a separate 500K-element deck over 1.0 × 10⁻³ s and 15,808 steps give per-step speed-ups of 43.7×, 17.7×, and 13.5× versus 1-, 8-, and 32-core LS-DYNA MPP. Full article

Objectives: In patients presenting to the emergency department with acute ischemic stroke (AIS), there is a growing need for practical and rapid biomarkers that can effectively predict prognosis and infarct volume, complementing neurological examination and imaging methods. Methods: This study retrospectively evaluates patients diagnosed with AIS at the emergency department of Bilecik Training and Research Hospital between 1 March 2022, and 30 September 2023. Patients who were transferred for reperfusion therapy were excluded, as thrombolysis and mechanical thrombectomy were not available at our institution during the study period. The systemic immune–inflammation index (SII) and the systemic inflammation response index (SIRI) scores were calculated based on patients’ laboratory values. Additionally, infarct volumes were independently assessed by two experienced radiologists and calculated by multiplying the hyperintense areas on diffusion-weighted magnetic resonance imaging by slice thickness. Results: Of the 349 patients diagnosed with AIS during this study period, 257 who met the inclusion criteria were analyzed. The median age was 76 years (IQR: 66–83), and 130 (51%) patients were female. Lacunar infarction was present in 109 patients (42.4%), while 148 (57.6%) had non-lacunar infarction. The all-cause mortality rates at 1 month, 1 year, and 2 years were 7.8%, 21.4%, and 29.6%, respectively. SII and SIRI scores were significantly higher in deceased patients compared to survivors across all time points for mortality. Conclusions: The findings of this study suggest that SII and SIRI values, derived from complete blood count parameters, may contribute to the early identification and management of high-risk AIS patients. Full article

Aphasia is a complex neurological syndrome that includes a multitude of signs and symptoms that describe a patient’s inability to use language (understanding and producing spoken and/or written language) after it has already been acquired, which is caused by cerebral lesions situated in the dominant (left) cerebral hemisphere in right-handed people. Aphasia has a prevalence of 25–30% in acute ischemic stroke (especially in arterial infarcts). In patients who suffered cerebral venous and dural sinuses thrombosis (CVST), aphasia has been noticed in almost 20% of cases, its presence being considered a negative predictive factor. We report the case of a 22-year-old right-handed woman with obesity and active smoking (10 cigarettes/day), undergoing treatment with oral contraceptives who presented to the Emergency Department with an intense headache, resistant to usual analgesic treatment, accompanied by language disorders onset within 24 h. The neurological examination was normal, except for language assessment, which revealed the severe impairment of the repetition domain (she was unable to repeat simple words), and difficulty in naming objects with some hesitations and mild comprehension difficulties (especially in complex orders). She underwent neuroimaging examinations at admission. Native Head Computed Tomography revealed spontaneous hyperdensity (parenchymatous hematoma) in the left temporal lobe. Cranial magnetic resonance imaging (MRI) confirmed venous infarction in the left temporal area and a hypointense signal on MRI T2*SW (susceptibility-weighted) in the region of the left lateral sinus and left jugular vein bulb, which confirmed the thrombosis at this level. Associated cortical vein thrombosis was diagnosed on indirect radiological grounds, since hemorrhagic transformation obscured the direct visualization of the adjacent cortical veins. MR venography was not performed at that time, but instead at the 1-month follow-up, MR venography confirmed the chronic, partial thrombosis of the left lateral sinus and left jugular vein bulb. Laboratory data demonstrated an elevated D-dimer and the presence of homozygosity for MTHFR C677T and PAI-1 4G/4G. Anticoagulation in the form of low-molecular-weight heparin was immediately started, followed by chronic treatment with oral anticoagulant (apixaban) and folic acid. The headaches resolved within three days, and her neurological examination was almost normal: the repetition continued being altered for complex phrases. We did not observe any left lateral sinus thrombosis recurrence, or other extra-cerebral embolic events (deep vein thrombosis or pulmonary embolism) during the follow-up year. The immediate anticoagulation since the admission resulted in a favorable outcome. Taking into consideration our interest in monitoring patients with aphasia secondary to CVST, we also analyzed data from the literature regarding the incidence of conduction aphasia and other aphasic syndromes in this CVST. Due to the limited number of articles identified in the last 21 years (2005–2026) in the literature, we concluded that conduction aphasia is an extremely rare clinical presentation in this kind of pathology and further studies should be conducted in order to identify significant statistical data. Full article

Background/Objectives: Athletes are characterized by distinct haemodynamic adaptations of the cardiovascular system, including descending aorta haemodynamics, that could influence the diagnosis of coarctation of the aorta. This study aims to evaluate the normal range for the maximum velocity of blood flow in the descending aorta (Vmax-AoDesc) and the predictors of Vmax-AoDesc in apparently healthy athletes without coarctation of the aorta. Methods: We examined 559 asymptomatic healthy athletes with an age of at least 12 years and a tricuspid aortic valve (420 males, age: 29 ± 14 years). We performed evaluations of athletic history, measurements of brachial systolic and diastolic blood pressure, cardiac and aorta ultrasonography and cardiopulmonary exercise testing. Forty athletes were reassessed after a median follow-up of 3.0 (IQR: 2.1) years. Results: The median Vmax-AoDesc was 1.29 (IQR: 0.28) m/s, with a maximum of 2.00 m/s. The Vmax-AoDesc could be independently predicted by age (β = −0.392, p < 0.001), ratio of systole/diastole (β = 0.095, p = 0.023), brachial systolic blood pressure (β = 0.251, p < 0.001), left ventricular stroke volume (β = 0.256, p < 0.001), ascending aorta diameter (β = −0.230, p < 0.001), aortic arch diameter (β = −0.111, p = 0.044) and descending aorta diameter (β = −0.103, p = 0.017). Age accounted for the greatest variability of Vmax-AoDesc (5.8%). Vmax-AoDesc correlated positively with h/week of endurance exercise training (rho = 0.182, p < 0.001) and oxygen uptake at second ventilatory threshold (rho = 0.299, p = 0.001). Vmax-AoDesc did not change significantly during follow-up (p = 0.438). The median change in Vmax-AoDesc was −0.05 (IQR: 0.18) m/s. However, when Vmax-AoDesc was adjusted for all the above-mentioned independent predictors of Vmax-AoDesc apart from age and systolic blood pressure, there was a reduction in adjusted Vmax-AoDesc during follow-up (p = 0.007), indicating a reduction in Vmax-AoDesc with aging. Conclusions: The upper limit of the normal range for Vmax-AoDesc was 2.00 m/s in athletes without coarctation of the aorta. Young age was the most important predictor for the measurement of high Vmax-AoDesc. There was an upregulation of Vmax-AoDesc in athletes with a greater volume of endurance exercise training. Full article