Cognitive decline is a major non-motor complication in early Parkinson's disease (PD), but predicting its progression remains challenging. Using data from 193 participants in the Early Parkinson's Disease Longitudinal Singapore (PALS) cohort, we evaluated whether repeated blood biomarker measurements (baseline, year 3, year 5)-neurofilament light chain (NfL) and total tau (t-tau)-could improve prediction of cognitive decline, defined as a one-point annual or sustained two-year drop in Montreal Cognitive Assessment scores. We applied three variable selection methods and five machine learning models across seven feature sets. Overall, 23% of participants experienced cognitive decline over five years. The XGBoost model trained on Random Forest-selected variables achieved the highest performance (AUC = 0.806), a substantial improvement over the baseline-only model (AUC = 0.560). Key predictors included diastolic blood pressure and summaries of t-tau and NfL. Time-varying biomarkers improved predictions over baseline data alone, supporting their integration with machine learning for early cognitive risk assessment in PD.

Clinical decision-making is a feedback system where risk estimates influence treatment, which in turn changes disease trajectories, and both shape clinicians' measurement practices. Static prediction often fails clinically: models trained on observational care logs conflate disease biology with clinician behavior, particularly under treatment confounder feedback and irregular or informative observation. This Review focuses on intervention-aware disease trajectory modeling in clinical AI–methods estimating patient-specific longitudinal disease evolution and assessing trajectory changes under alternative treatments. We organize the field around six linked components: three decision tasks (factual forecasting, counterfactual estimation, policy evaluation) and three data-generating mechanisms (disease evolution, treatment assignment, observation process) that determine identifiability. We present the first unified framework bridging forecasting, counterfactual trajectories, and policy evaluation across discrete/continuous time, explicitly addressing treatment assignment, time-varying confounding, and observation bias. We synthesize key method families (multistate/joint models, temporal point-process, deep sequence architectures, longitudinal causal inference), map them to relevant components, and align evaluation with claim strength via overlap diagnostics, uncertainty quantification, off-policy robustness, and target-trial validation. This synthesis advances benchmark prediction to decision-grade clinical evidence, enabling treatment-sensitive individualized futures, pre-deployment policy stress-testing, and safer closed-loop learning health systems that adapt/abstain when evidence is insufficient.

Background: Cerebral hypoperfusion and neuroinflammation contribute to mild cognitive impairment (MCI) through multiple mechanisms including oxidative stress and inflammation. This study examines distinct cognitive and biomarker profiles in a Southeast-Asian cohort to differentiate vascular and inflammatory-driven MCI. Methods: MCI participants from the Biomarkers and Cognition Study, Singapore, were classified into hypoperfusion-predominant(P+), neuroinflammation-predominant(I+), and control(P-) groups using k-means clustering based on MRI arterial spin labeling global gray matter perfusion and plasma Glial Fibrillary Acidic Protein(GFAP) profiles. Cognitive performance and plasma biomarkers were compared across the clusters. Mediation analysis assessed the interdependencies between hypoperfusion and neuroinflammation. Results: The P+ group showed significantly higher Neurofilament Light Chain(NfL) levels than the P- group(p=0.0395). The I+ group exhibited increased NfL(p=0.0001), elevated Oligomeric Amyloid-Beta(OAβ)(p = 0.0228), a reduced Amyloid-Beta 42/40(Aβ42/40) ratio(p = 0.0008), and lower global cognitive performance as assessed by Visual Cognitive Assessment Tool(VCAT) scores(p=0.0006) compared to P+. Compared to P-, the I+ group showed significantly higher NfL(p<0.0001), OAβ(p=0.0079), a lower Aβ42/40 ratio(p=0.0031), and lower VCAT scores(p=0.0011).Mediation analysis revealed that neuroinflammation mediated the relationship between perfusion and NfL elevation in P+ (ACME=0.00177, p<0.0001). In contrast, hypoperfusion mediated neuroinflammation’s effect on global cognitive scores(VCAT) in I+ (ACME=-.00085, p=0.00329). Conclusions: These findings identify distinctive biomarkers that differentiate neuroinflammation-predominant and hypoperfusion-predominant MCI. They reveal an interplay between hypoperfusion and neuroinflammation, highlighting their combined contributions to MCI pathology. These results emphasize the need for personalized therapeutic strategies addressing the dual pathologies of cerebrovascular and inflammatory dysfunctions, particularly in populations with geographic-specific variations in MCI pathology.

RESEARCH QUESTION:What is the effect of fertility health screening (FHS) and fertility awareness tools (FAT) on parenthood intentions, as measured by the wife's intended age at first birth, compared with no intervention, 6 months after randomization? DESIGN:An effectiveness-implementation hybrid type I trial with a multicentre three-arm parallel group open-label randomized controlled trial. Married Singaporean couples with wives aged between 25 and 34 years were randomized to FHS, FAT or no intervention. The primary outcome was the wife's intended age at first birth. Secondary outcomes included fertility knowledge, attempts to conceive, pregnancy and pursuing further fertility screening, treatment, or both, 6 months after randomization. RESULTS:A total of 778 couples were randomized to the FHS (n = 226), FAT (n = 238) and control (n = 314) groups, respectively. Compared with the control group, no significant difference for either FHS or FAT was seen regarding the change in the wife's intended age at first birth at follow-up (0.07, 95% CI ‒0.17 to 0.32 and ‒0.01, 95% CI ‒0.25 to 0.23 years, respectively). Both interventions significantly increased fertility awareness, as measured by the mean increase in Cardiff Fertility Knowledge Score in wives (FHS, 0.38, 95% CI 0.03 to 0.73; FAT, 0.44, 95% CI 0.10 to 0.79 and husbands (FHS, 0.41, 95% CI 0.04 to 0.78; FAT 0.71, 95% CI 0.35 to 1.10). No significant differences were observed in all other secondary outcomes. CONCLUSION:Neither FHS nor FAT significantly modified parenthood intentions 6 months after randomization.

BACKGROUND AND OBJECTIVES:Seizures are a recognized comorbidity in dementia, with varying prevalence across Alzheimer disease (AD) and dementia with Lewy bodies (DLBs). Although previous studies have demonstrated an increased seizure risk in AD, the neuropathologic substrates underlying seizure susceptibility-particularly across dementia subtypes-remain incompletely understood. We aimed to identify distinct clinicopathologic correlates of clinically active seizures in AD and DLB using a large autopsy-confirmed cohort. METHODS:We conducted a retrospective cohort study using data from the National Alzheimer's Coordinating Center (2005-December 2022). Autopsy-confirmed AD and DLB cases were included. Individuals with a history of stroke or traumatic brain injury were excluded. The primary outcome was clinically active seizures, defined as seizures occurring within 3 years before or after the diagnosis of dementia. Neuropathologic exposures included Braak stage, cerebral amyloid angiopathy (CAA), frontotemporal lobar degeneration, and vascular pathologies. Multivariable logistic regression models were used to examine associations between pathologic features and seizure occurrence, adjusting for relevant demographic covariates. RESULTS:A total of 3,498 participants were included, comprising 3,040 with AD (mean age, 73.4 years; 48.5% female) and 458 with DLB (mean age, 75.1 years; 31.4% female). Active seizures were identified in 174 participants with AD (5.7%) and 13 with DLB (2.8%). In AD, Braak stage VI (vs V) was associated with higher odds of active seizures (adjusted odds ratio [OR], 1.81; 95% CI 1.20-2.82; p = 0.007), as was moderate to severe CAA (adjusted OR, 1.38; 95% CI 1.01-1.90; p = 0.045). In DLB, AD-related pathologic features were not associated with seizures. By contrast, vascular pathology was significantly associated with seizure occurrence, including microinfarcts (adjusted OR, 5.11; 95% CI 1.64-16.4; p = 0.005) and infarcts (adjusted OR, 4.11; 95% CI 1.27-12.9; p = 0.015). DISCUSSION:In this autopsy-confirmed cohort, seizure susceptibility was associated with advanced tau pathology and CAA in AD. In DLB, exploratory analyses suggested a possible association between vascular pathology and seizures; however, these findings should be interpreted cautiously. Overall, the results support potentially distinct pathologic contributions to seizure susceptibility across dementia subtypes. Limitations include the use of advanced-stage pathologic samples, which may limit generalizability to earlier disease stages.

[This corrects the article DOI: 10.3389/fnagi.2026.1883244.].

BACKGROUND AND AIMS:Malnutrition is a known complication in systemic sclerosis (SSc), yet longitudinal data using standardised diagnostic criteria in Asian populations are limited. We aimed to determine the prevalence and incidence of malnutrition, identify risk factors for its development and evaluate its association with mortality in the SSc cohort using the Global Leadership Initiative on Malnutrition (GLIM) criteria. METHODS:Patients aged 18 years and above, fulfilling the 2013 American College of Rheumatology/European Alliance of Associations for Rheumatology or 1980 ACR classification criteria for SSc who were consecutively recruited into the Singapore Systemic Sclerosis Cohort (SCORE) between January 2008 and December 2020 were eligible for inclusion. Patients were included if they had at least one baseline assessment and ≥6 months of follow-up. Patients with follow-up of less than 6 months were excluded. Malnutrition was defined using the GLIM criteria. Demographics, clinical, serological, treatment and mortality data were collected. Cox proportional hazards regression was used to assess predictors of incident malnutrition and factors associated with mortality. RESULTS:Among 341 patients with SSc, baseline malnutrition was 14.4%, with an incidence rate of 16.83 per 1000 person-years. No baseline clinical variables were significantly associated with the development of malnutrition. In contrast, increasing age [HR 1.04 (95% CI: 1.01-1.08), p = 0.005], disease duration [HR 0.99 (95% CI: 0.99-1.00), p = 0.001], and malnutrition [HR 2.76 (95% CI: 1.25-6.10), p = 0.012] were independently associated with increased mortality among patients with SSc. CONCLUSION:Despite a relatively low incidence, GLIM-defined malnutrition had a strong independent association with mortality in SSc. These findings are of prognostic value and support the integration of routine screening and standardized malnutrition diagnosis in SSc care in Asian populations.

Background/Objectives: Missing data in clinical observational studies, such as out-of-hospital cardiac arrest (OHCA) registries, can compromise statistical validity. Single imputation methods are simple alternatives to complete-case analysis (CCA) but do not account for imputation uncertainty. Multiple imputation (MI) is the standard for handling missing-at-random (MAR) data, yet its implementation remains challenging. This study evaluated the performance of MI in association analysis compared with CCA and single imputation methods. Methods: Using a simulation framework with real-world Singapore OHCA registry data (N = 13,274 complete cases), we artificially introduced 20%, 30%, and 40% missingness under MAR. MI was implemented using predictive mean matching (PMM), random forest (RF), and classification and regression trees (CART) algorithms, with 5-20 imputations. Performance was assessed based on bias and precision in a logistic regression model evaluating the association between alert issuance and bystander CPR. Results: CART outperformed PMM, providing more accurate β coefficients and stable CIs across missingness levels. Although K-Nearest Neighbours (KNN) produced similar point estimates, it underestimated imputation uncertainty. PMM showed larger bias, wider and less stable CIs, and in some settings performed similarly to CCA. MI methods produced wider CIs than single imputation, appropriately capturing imputation uncertainty. Increasing the number of imputations had minimal impact on point estimates but modestly narrowed CIs. Conclusions: MI performance depends strongly on the chosen algorithm. CART and RF methods offered the most robust and consistent results for OHCA data, whereas PMM may not be optimal and should be selected with caution. MI using tree-based methods (CART/RF) remains the preferred strategy for generating reliable conclusions in OHCA research.

BACKGROUND:Essential tremor (ET) is the most common movement disorder in the elderly. Despite a close relationship between ET onset and age, it remains unclear whether ET reflects accelerated brain ageing or disease-specific structural changes. This study investigated whether ET is associated with accelerated global brain ageing or altered regional ageing patterns. METHODS:We studied 38 ET patients and 37 matched controls using 3 T structural and diffusion MRI alongside clinical assessments. Brain age and brain age gap (BAG; the difference between chronological and brain age) were estimated by a deep learning model. We analyzed group differences in global brain morphometry, and regional correlations between brain age and volumetric data. Regions demonstrating differential ageing in ET were combined into a composite metric to characterize disease-specific effects. RESULTS:Spatial patterns of brain ageing differed between ET and controls despite no evidence of globally accelerated ageing. In controls, brain age was associated with enlarged ventricles and diffuse cortical thinning, consistent with prototypical ageing. In contrast, ET showed strong negative associations between brain age and volumes specifically in the cerebellar cortex, thalami, and cortical tremor network. A composite metric comprising these regions demonstrated a significant interaction with group and predicted brain age, with ET patients showing volume reduction. CONCLUSIONS:ET is characterized by a distinct, disease-specific pattern of brain ageing rather than accelerated global ageing. This suggests that ET al.ters the spatial distribution of age-related structural changes, preferentially affecting the tremor network, and may help explain ET clinical heterogeneity.

Emergency department (ED) revisits within 72 h is a standard quality measure for emergency care but most revisits are managed and discharged. However, a sub-group of revisits are due to clinical deterioration resulting in admissions to higher acuity care or even mortality. We aimed to identify these critical revisits and their associated risk factors. Identification of these factors would allow development of strategies to reduce incidence of post discharge deterioration. A retrospective cohort study was conducted on all patients who had a revisit within 72 h of discharge from the ED of a tertiary hospital in Singapore from 2008 to 2020. Deidentified data were extracted from the electronic health records (EHR). We identified critical revisits, defined as a revisit that resulted in death or admission to Intensive Care Unit or High Dependency. These patients were compared to patients who had a revisit that resulted in discharge or admission to general ward. The main outcome was the rate of critical revisit. We also determined the commonest index and critical revisit ED diagnosis as well as factors associated with critical revisits. Out of 1,057,533 discharges from the ED over the study period, 44,506 (4.2

Cognitive assessments are essential for the diagnosis of mild cognitive impairment (MCI) and dementia. However, existing tests are mostly developed in English-speaking cohorts. Hence, their application in multilingual populations will need translation which may affect their test psychometrics. VCAT is a language-neutral visual-based assessment that is developed to address this issue. While VCAT was validated in Southeast Asian countries, its performance in diverse language cohorts remains unclear. Here, we aim to compare the utility of VCAT with established screening tests, Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE), in distinguishing MCI and dementia from cognitively normal (CN) individuals in a multinational study. This study supported by the Alzheimer’s Association has recruited 670 participants (294 CN, 244 MCI, 132 Dementia) from Brazil, Canada, China, India, Korea and Singapore and recruitment is ongoing. We standardized the administration of MMSE, MoCA and VCAT across all study sites. Participants answered a questionnaire on their demographics and underwent cognitive assessments (MMSE, MoCA and VCAT) on the same day. The performance of VCAT in distinguishing MCI and dementia from CN were assessed within each sites using the area under the curve (AUC) analysis. The demographics, diagnosis and cognitive scores of the participants from each site were summarized in Table 1. The AUCs of VCAT in detecting MCI+Dementia vs CN were 0.979 for Brazil, 0.708 for Canada, 0.929 for China, 0.956 for Korea, 0.808 for India and 0.731 for Singapore. In comparison, the AUCs of MoCA in detecting MCI+Dementia vs CN were 0.771 for Brazil, 0.751 for Canada, 0.899 for China, 0.964 for Korea, 0.806 for India and 0.682 for Singapore, while the AUCs for MMSE in detecting MCI+Dementia vs CN were 0.896 for Brazil, 0.721 for Canada, 0.891 for China, 0.895 for Korea, 0.712 for India and 0.640 for Singapore. VCAT showed satisfactory discriminative validity in differentiating MCI+Dementia from CN participants within multinational, multilingual cohorts. VCAT was also comparable to the MoCA and MMSE. Further analysis in a larger cohort within our study will be performed to validate the utility of VCAT globally.

Introduction: Global work patterns are changing, with more individuals engaged in shift work and remaining in the workforce later in life. Shift work is linked to disrupted sleep, impaired cognition, and greater risk of metabolic and neurodegenerative disease; effects that are amplified by aging. However, the neural correlates of shift work remain poorly characterized, leaving a critical gap in understanding how occupational schedules may shape the aging brain. Objectives: We aimed to determine the relationship between shift work on brain structure in healthy adults, and how brain structure changes over time in older-aged shift workers. Methods: We analysed data from a population-based longitudinal cohort study. We included data for employed individuals with no serious medical conditions. Participants completed self-report questionnaires on health, sleep, cognition and employment, and brain MRI. We used linear regression to compare shift workers and non-shift workers on 153 structural brain parameters, controlling for age, sex, chronotype, intracranial volume, smoking history, MRI head motion, hypertensive status and socioeconomic status. Results: We included n = 14,198 individuals (aged median 47 [IQR=7] years) comprising non-shift workers (n = 12,076) and shift workers (n = 2122). In shift workers, we detected a symmetrical pattern of volume loss in the right thalamus (Cohen’s d=-0.10, adjusted p = 0.026) and left amygdala (Cohen’s d=-0.11, adjusted p = 0.010). In subjects who ceased shift work after the baseline, we observed a halting of shift work-related volume loss within 2.4 years. Secondary analyses revealed microstructural degradation in the corticospinal tract, cerebral peduncle and right sagittal stratum, and negative correlation of volume loss with cognitive performance. Conclusion: Shift workers have selective volume loss of the thalamus and amygdala, which is halted within 2.4 years of stopping shift work. Monitoring, counselling and interventional measures, including adjustment of work schedules, could minimise brain volume loss in shift workers.

The SNCA gene, encoding alpha-synuclein, is implicated in the pathogenesis of Parkinson’s disease (PD), with several single-nucleotide polymorphisms (SNPs) linked to increased risk. This study systematically evaluated the association between common SNCA polymorphisms and PD through a meta-analysis of cohort and case–control studies published before 20 November 2023. Eligible studies were identified via comprehensive searches of PubMed, Scopus, and Web of Science, and pooled odds ratios with 95% confidence intervals were calculated under allelic, dominant, and recessive models. Heterogeneity and publication bias were assessed, and subgroup and sensitivity analyses were performed. Twenty-seven studies were included. SNP rs11931074 showed consistent associations with PD across all models, with low heterogeneity and no evidence of publication bias. rs356219 and rs356165 were also significantly associated with PD, although regional differences contributed to heterogeneity. In contrast, rs2583988 showed marginal significance in the allelic model, which was lost after sensitivity analyses. No associations were found under dominant or recessive models for this SNP. These findings confirm rs11931074 as a robust PD risk variant and support the roles of rs356219 and rs356165 while suggesting weaker evidence for rs2583988. Large, multi-ethnic studies are warranted to elucidate underlying mechanisms and support precision medicine in PD.

ABSTRACT Background: Statins are the most prevalent treatment for dyslipidaemia, but cognitive side effects are disputed. This study examines the impact of statins on cognition within a prospective study specifically designed to examine cognitive outcomes and underlying pathobiology. Objective: To evaluate the association between statin-use on cognitive impairment and voxel-wise and network-based grey matter atrophy. Design: Cross-sectional cognitive and neuroimaging data obtained from a prospective cohort study. Setting: Community-based, Southeast Asian cohort. Participants: Participants(n=1170) from the BIOCIS cohort were classified as Cognitively Normal(CN) or Mild Cognitive Impairment(MCI). Participants were categorized into normal cholesterol no statins(S-C-), normal cholesterol with statins(S+C-), and high cholesterol no statins(S-C+). Exposures: Neuropsychological test battery, Magnetic Resonance Imaging, Apolipoprotein E4 genotyping Main Outcome(s) and Measure(s): Montreal Cognitive Assessment (MoCA) and z-scores across episodic memory, executive function, processing speed, visuospatial, and language domains were employed to evaluate cognitive performance and voxel-based and functional network-based grey matter atrophy. Results: 1170 participants (age=61.6±10.3, 63% female), comprising 558 CN and 612 MCI, were included. Among CN, S+C- performed significantly worse than S-C- on MoCA (Cohen's đ=-0.386, p=0.014), episodic memory (đ=-0.374, p<0.001), executive function (đ=-0.367, p<0.001), processing speed (đ=-0.551, p<0.001), language (đ=-0.393, p=0.004). Similar poorer cognitive performance among statin users were observed when comparing S+C- and S-C+. Parallel trends were observed in MCI: MoCA (đ=-0.400, p=0.002), episodic memory (đ=-0.430, p<0.001), executive function (đ=-0.364, p<0.001), processing speed (đ=-0.354, p=0.004), visuospatial (đ=-0.342, p=0.003), language (đ=-0.507, p<0.001). There was a significant effect of longer statin-use duration associating poorer cognitive performance: episodic memory (β=-0.021, corrected-p=0.011), executive function (β=-0.019, corrected-p=0.005), visuospatial (β=-0.026, corrected-p=0.008), language (β=-0.022, corrected-p=0.008). Widespread grey matter atrophy was observed in S+C- compared to S-C- and S-C+ in CN and MCI participants even with stringent false discovery rate correction (corrected-p<0.05). Regional atrophy in default mode and executive control network regions was observed in MCI statin users (corrected-p<0.05). Conclusions: Statin use and duration was significantly associated with impairment across cognitive domains in CN and MCI participants. Impairment in cognitive function among statin users was correlated to voxel-based and network-based grey matter atrophy in brain regions crucial for cognition. Prospective longitudinal studies need to confirm the adverse cognitive effects of statins and facilitate appropriate clinical use. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study received funding support from the Strategic Academic Initiative grant (SP1CLNT900-NTU-A630-PJ-03INP001400A630) from the Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, National Medical Research Council, Singapore under its Clinician Scientist Award (MOH-CSAINV18nov-0007), Ministry of Education Start-up Grant, Ministry of Education Academic Research Fund Tier 1 (RT02/21) and Ministry of Education Science of Learning grant (MOESOL2022-0002). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All participants provided informed consent, and the study was approved by the institutional ethics board(IRB-2021-1036). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data that support the findings of this study are available from the corresponding author upon reasonable request.

ABSTRACTAimWe aimed to investigate the prevalence and factors associated with C‐reactive protein (CRP) and procalcitonin (PCT) discordance in febrile infants with serious bacterial infections (SBIs).MethodsWe performed a retrospective review of febrile infants ≤ 90 days old presenting to the emergency department between December 2018 and June 2023. We compared conservative and pragmatic thresholds for PCT (< 0.5 ng/mL and < 1.7 ng/mL) and CRP (< 10 mg/L and < 20 mg/L). Discordance was defined as normal CRP with abnormal PCT and vice versa. Performance was presented using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).ResultsAmong 3459 infants, 426 infants (12.3%) had SBIs, among whom 355 (83.3%) had both CRP and PCT performed. Overall, a conservative CRP threshold had the highest sensitivity (74.1%, 95% CI 69.2%–78.6%) and NPV (95.6%, 95% CI 94.6%–96.4%). Among those with SBIs, 148/355 (41.7%) had a normal PCT (< 1.7 ng/mL) and an abnormal CRP (≥ 20 mg/L), while 16/355 (4.5%) had a normal CRP (< 20 mg/L) and an abnormal PCT (≥ 1.7 ng/mL). An increased discordance, specifically abnormal CRP with normal PCT, was found in males, infants 29–90 days old, and those with urinary tract infections.ConclusionSBI clinical decision rules should consider CRP‐PCT discordance in specific patient populations.

Alpha-synuclein gene promoter (SNCA Rep1) polymorphism has been linked to Parkinson's Disease (PD) susceptibility and motor symptom severity, but less is known about its longitudinal relationship with non-motor symptom severity. To address this gap, this is the first longitudinal study over 4 years investigating the relationship between Rep1 allele length and non-motor function amongst 208 early PD patients grouped into long (n = 111) vs. short (n = 97) Rep1 allele carriers. Long Rep1 carriers demonstrated faster decline in global cognition (p = 0.023) and increasing apathy (p = 0.027), with greater decline in attention and memory domains (p = 0.001), highlighting the utility of Rep1 polymorphism in stratifying patients at risk of non-motor symptom decline.

Background:Traditional lumbar punctures (LPs) often fail, leading to diagnostic delays and increased risks. Ultrasound guidance provides improved success rates but faces adoption barriers due to neuraxial-ultrasound training and implementation challenges. The Ultrasound-Guided Spinal Landmark Identification With Needle Navigation System and Position and Angular Marking System (uSINE-PAMS) were designed to address these issues: uSINE is a machine-learning software for neuraxial-ultrasound guidance; PAMS is a hardware that translates ultrasound data for accurate needle insertion. Recent Findings:A pilot study with 10 patients showed that uSINE-PAMS-guided LP achieved an 80% first-pass success rate with no complication; the median patient age was 43 years, and the median body mass index was 24.5 kg/m2. The uSINE-PAMS system showed feasibility. Implications for Practice:This pilot study showed that uSINE-PAMS-guided LP is feasible with a promising first-pass success rate at 80%. An ongoing phase 2 study (NCT05824546) of uSINE-PAMS may alter future standard of practice for LPs. Trial Registration Information:This pilot study is registered under ClinicalTrials.gov (ID: NCT05824546).