Demographic Markers Research Articles

Unraveling the interplay of β-amyloid pathology and Parkinson's disease progression: Insights from autopsy-confirmed patients

BackgroundParkinson's disease (PD) is a prevalent neurodegenerative disorder that manifests with both motor and non-motor symptoms, with α-synuclein misfolding recognized as a key contributor. Cognitive decline in advanced PD stages prompts interest in amyloid deposition, a hallmark of Alzheimer's disease (AD), as a potential factor. This study explores the impact of β-amyloid (Aβ) pathology in PD patients on disease progression, aiming to elucidate the role of Aβ in PD development and progression. MethodsThis study included autopsy-confirmed PD patients with post-mortem analyses from the Parkinson's Progression Markers Initiative. Comprehensive clinical assessments, including demographic data, clinical features, CSF markers, and neuroimaging, were conducted. Statistical analyses assessed differences between groups based on the severity of AD neuropathological changes. ResultsAll 16 PD participants exhibited severe Lewy body pathology, with 75 % displaying AD neuropathological changes. At baseline, PD patients with severe or moderate AD neuropathological changes had a lower Aβ42 levels (p = 0.022) and Aβ42/tau ratio (p = 0.001). Longitudinal follow-up data indicated that individuals with severe or moderate AD neuropathological changes exhibited a more rapid decline in MOCA score and BJLOT score, along with a quicker increase in MDS-UPDRS Ⅲ score. ConclusionsThe study underscores the presence of severe Aβ pathology in PD, suggesting a role in accelerated disease progression. Cross-seeding between Aβ and α-synuclein may contribute to rapid clinical symptom progression. Further research is needed for a comprehensive understanding of neurodegenerative disease complexities and exploring potential therapeutic interventions targeting protein aggregation.

Assessment of measurable residual disease after induction chemotherapy in acute lymphoblastic leukemia patients in a tertiary care hospital

Background: Measurable residual disease (MRD) is a crucial prognostic factor in acute lymphoblastic leukemia (ALL), influencing treatment outcomes and long-term survival. This study investigates the prevalence of MRD post-induction chemotherapy and its association with clinical, demographic, and biochemical markers in ALL patients at a tertiary care hospital. Methods: This observational cross-sectional study was conducted at Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh, from August 2021 to July 2022. A total of 22 newly diagnosed ALL patients underwent induction chemotherapy and MRD evaluation using flow cytometry. Clinical signs, demographic data, and laboratory findings, including serum creatinine, uric acid, and BCR-ABL1 status, were recorded. Statistical analyses assessed the relationships between MRD status and various predictors. Results: Of the 22 patients, 7 (31.82%) remained MRD positive after induction chemotherapy. Anaemia was prevalent, affecting 20 participants (90.91%). MRD positive patients had higher serum creatinine (mean 1.23±0.31 mg/dl) and uric acid levels (mean 7.09±1.62 mg/dl) compared to MRD negative patients. None of the MRD positive patients tested positive for BCR-ABL1. Six of the 7 MRD positive patients were male (85.71%). Bone marrow analysis showed 5 MRD positive patients (71.43%) achieved complete remission. Risk stratification did not significantly correlate with MRD status. Conclusions: MRD is a critical prognostic tool in ALL management, correlating with higher biochemical markers of tumor burden and a distinct clinical profile. These findings support integrating MRD assessment with detailed clinical and laboratory evaluations to refine treatment strategies and improve patient outcomes in ALL.

Identification of type 1 diabetes risk phenotypes using an outcome-guided clustering analysis.

Although statistical models for predicting type 1 diabetes risk have been developed, approaches that reveal the heterogeneity of the at-risk population by identifying clinically meaningful clusters are lacking. We aimed to identify and characterise clusters of islet autoantibody-positive individuals who share similar characteristics and type 1 diabetes risk. We tested a novel outcome-guided clustering method in initially non-diabetic autoantibody-positive relatives of individuals with type 1 diabetes, using the TrialNet Pathway to Prevention study data (n=1123). The outcome of the analysis was the time to development of type 1 diabetes, and variables in the model included demographic characteristics, genetics, metabolic factors and islet autoantibodies. An independent dataset (the Diabetes Prevention Trial of Type 1 Diabetes Study) (n=706) was used for validation. The analysis revealed six clusters with varying type 1 diabetes risks, categorised into three groups based on the hierarchy of clusters. Group A comprised one cluster with high glucose levels (median for glucose mean AUC 9.48 mmol/l; IQR 9.16-10.02) and high risk (2-year diabetes-free survival probability 0.42; 95% CI 0.34, 0.51). Group B comprised one cluster with high IA-2A titres (median 287 DK units/ml; IQR 250-319) and elevated autoantibody titres (2-year diabetes-free survival probability 0.73; 95% CI 0.67, 0.80). Group C comprised four lower-risk clusters with lower autoantibody titres and glucose levels (with 2-year diabetes-free survival probability ranging from 0.84-0.99 in the four clusters). Within group C, the clusters exhibit variations in characteristics such as glucose levels, C-peptide levels and age. A decision rule for assigning individuals to clusters was developed. Use of the validation dataset confirmed that the clusters can identify individuals with similar characteristics. Demographic, metabolic, immunological and genetic markers may be used to identify clusters of distinctive characteristics and different risks of progression to type 1 diabetes among autoantibody-positive individuals with a family history of type 1 diabetes. The results also revealed the heterogeneity in the population and complex interactions between variables.

Novel measures of cognition and function for the AD spectrum in the Novel Measures for Alzheimer's Disease Prevention Trials (NoMAD) project: Psychometric properties, convergent validation, and contrasts with established measures.

This study derived composite scores for two novel cognitive measures, the No Practice Effect (NPE) battery and the Miami Computerized Functional Skills Assessment and Training system for use in early-stage Alzheimer's disease (AD) clinical trials. Their psychometric properties and associations with AD risk markers were compared to those of well-established measures. For 291 older adults with healthy cognition or early mild cognitive impairment, Exploratory factor analyses were used to identify the factor structure of the NPE. Factor and total scores were examined for their psychometric properties and associations with AD risk biomarkers. Composite scores from the novel cognitive and functional measures demonstrated better psychometric properties (distribution and test-retest reliability) and stronger associations with AD-related demographic, genetic, and brain risk markers than well-established measures, DISCUSSION: These novel measures have potential for use as primary cognitive and functional outcomes in early-stage AD clinical trials. Well-established cognitive tests may not accurately detect subtle cognitive changes. No Practice Effect (NPE) and Computerized Functional Skills Assessment and Training are novel measures designed to have improved psychometric properties. NPE had Executive Function, Cognitive Control/Speed, and Episodic Memory domains. Novel measures had better psychometric properties compared to established measures. Significant associations with Alzheimer's disease biomarkers were found with novel measures.

Diffusion tensor imaging analysis along the perivascular space in the UK biobank

BackgroundThe recently discovered glymphatic system may support the removal of neurotoxic proteins, mainly during sleep, that are associated with neurodegenerative diseases such as Alzheimer's and Parkinson's Disease. Diffusion tensor image analysis along the perivascular space (DTI-ALPS) has been suggested as a method to index the health of glymphatic system (with higher values indicating a more intact glymphatic system). Indeed, in small-scale studies the DTI-ALPS index has been shown to correlate with age, cognitive health, and sleep, and is higher in females than males. ObjectiveTo determine whether these relationships are stable we replicated previous findings associating the DTI-ALPS index with demographic, sleep-related, and cognitive markers in a large sample of participants from the UK Biobank. MethodsWe calculated the DTI-ALPS index in UK Biobank participants (n = 17723). Using Bayesian and Frequentist analysis approaches, we replicate previously reported relationships between the DTI-ALPS index. ResultsWe found the predicted associations between the DTI-ALPS index and age, longest uninterrupted sleep window (LUSWT) on a typical night, cognitive performance, and sex. However, these effects were substantially smaller than those found in previous studies. Parameter estimates from this study may be used as priors in subsequent studies using a Bayesian approach. These results suggest that the DTI-ALPS index is consistently, and therefore predictably, associated with demographics, LUWST, and cognition. ConclusionWe propose that the metric, calculated for the first time in a large-scale, population-based cohort, is a stable measure, but one for which stronger links to glymphatic system function are needed before it can be used to understand the relationships between glymphatic system function and health outcomes reported in the UK Biobank.

Risk attitudes of tax practitioners and firm influence

PurposeThe purpose of this paper is to garner a deeper understanding of the site of influence of aspects of risk management for tax practitioners.Design/methodology/approachThe research design is twofold. Phase one consisted of a wide-scale international survey with 1,061 tax experts across 59 jurisdictions. In phase two, the authors followed up with 68 semi-structured interviews with tax practitioners working in 11 different countries.FindingsThe findings recognise the importance of the firm as a significant “site of influence” for tax practitioners in shaping their risk appetite in their tax work. The firm eclipses other influences of risk such as professional body oversight, public interest and demographic markers such as gender and career stage. The authors show that firm is significant, irrespective of size of firm.Practical implicationsThis work has practical implications as the findings highlight the importance of oversight of professional service firms by both the professional accountancy bodies and revenue authorities. The findings may have impact on the ethical training and guidance for trainee accountants in terms of an increased awareness on the employing firm as a site of influence for tax practitioners.Originality/valueThis research is important as it adds to the significant body of work on firm socialisation and highlights the important role that the firm holds in moderating (or exacerbating) the risk appetite of tax practitioners, which has significant implications in terms of pushing the boundaries of tax aggressive behaviours. The work aims to recognise the important role that tax practitioners can have in moderating aggressive tax practice, and, thus, reducing tax inequalities and shaping a better world of “Reduced Inequalities” (SDG10).

Association among retinal health, self-reported depressive symptoms, and demographic, lifestyle and health markers: the META-KLS cohort analysis

BackgroundRetinal health indices were suggested to be related to psychopathological symptoms, such as depressive symptoms. However, large-scale studies using optical coherence tomography (OCT) are missing to investigate the associations among them. MethodsIn the META-KLS cohort study, 1456 participants (mean age [standard deviation]= 54.6 [11.91] years; n= 680 [47.8%] women) completed the Patient Health Questionnaire (PHQ-9) to measure depressive symptoms and underwent OCT. Poor-quality OCTs and multivariate outliers were excluded, and principal component analysis was performed to obtain retinal health indices separately for macular (n= 930) and optic nerve head (ONH) thicknesses (n= 800). Linear regressions were run controlling for covariates. Exploratory interaction models were run with demographic, lifestyle and health markers. ResultsAlthough there were no direct significant associations between the retinal indices and depressive symptoms (macular: B= −0.05, 95% CI= [-0.15, 0.05], p= 0.32; ONH index: B= -0.02, 95% CI= [-0.11, 0.08], p= 0.71), their associations were moderated by demographic and health factors, e.g., C-reactive protein (CRP) (macular index: B= −0.03, 95% CI= [-0.05, −0.01], p= 0.002; ONH index: B= 0.05, 95% CI= [0.02, 0.08], p= 0.002). LimitationsStudy was cross-sectional and there were no functional assessments of vision. ConclusionsIn a large cohort, we observed associations between retinal indices and self-reported depressive symptoms depending on demographic and health factors, notably CRP. Following up, the study will investigate the prospective prediction of retinal health on depressive symptoms, especially in persons who may have chronic inflammation.

Factors Influencing the Consumption of Tobacco amongst the Khasi Indigenous People in Northeast India.

Tobacco use in any form is a major public health concern. It accounts for nearly 1.35 million deaths every year. Many chronic illnesses occur due to the consumption of tobacco, either smoke or smokeless form. The study aims to explore how smoking and smokeless tobacco consumption are distributed across a range of demographic and socioeconomic markers among Khasi indigenous people in Northeast India. It is a case-control study conducted in adults over 31 years of age. The study was carried out between June 2020 and August 2021. An Independent t-test was performed to determine the significant difference in age between smoking/smokeless tobacco users and non-tobacco users. Univariate and Multivariate analyses were conducted to determine the significant predictors affecting the use of smoking/smokeless tobacco in the respondents. A total of 505 respondents were included in the present study. There was a high statistically significant difference in the income level of tobacco and non-tobacco users (P value- 0.002). In Univariate analysis, it was found that the odds of consuming both forms of tobacco were significantly lower in the respondents aged between 51-60 (OR = 0.61, P value = 0.0453). The participants who studied till graduation and above had lower odds of both using forms of tobacco as compared to respondents who were illiterate/primary educated only (OR = 0.85, P value = 0.046). In conclusion, smoking and smokeless tobacco consumption are still widely prevalent in this region and strongly associated with age, gender, level of education, and place of residence. There is a need for further detailed analysis to identify risk factors that are strongly associated with the use of smoke and smokeless tobacco so that the community will be conscious about the hazardous effects of tobacco use in any form.

Predictors of mortality in hospitalized African American COVID-19 patients with cancer.

Coronavirus disease 2019 (COVID-19) manifest differently depending on patients' background and pre-existing conditions. It remains unclear how African Americans with cancer have been affected in comparison to those without. In this study, we aim to identify demographic, clinical, and laboratory markers associated with mortality in COVID-19 patients with cancer. We reviewed all COVID-19 hospitalized patients' records from Dec. 2019 to Oct. 2021 at Howard University Hospital. Patients having a history of, or active, cancer were reviewed. Clinical, treatment, lab test values, and pathological data were extracted. Univariable and multivariable analyses were conducted on the entire cohort as well as on cases and controls separately, using SPSS software. Out of 512 COVID-19 infected patients, 49 had cancer, either active or history of cancer (cases) and 463 COVID-19 were cancer-free (controls), allowing for comparison. African American race was predominant in both cases and controls, 83.7% and 66.7% respectively. Cancer patients were older than non-cancer patients (mean age: 70.6 vs. 56.3 years) and had an increased length of hospital stay (mean 13.9 vs. 9.4 days). Mortality is significantly higher among cancer patients (n=10, 20.4%, P=0.03) compared to non-cancer COVID-19 patients (n=41, 8.9%). Among cancer patients, breast cancer was more prevalent in females and prostate cancer in males (54% and 52%, respectively). A comparison of patients with active vs. previous cancer showed no significant difference in the clinical outcome, death vs. discharge (P=0.34). A higher reduction in albumin level in cancer cases, from the time of admission to day 5, was significantly associated with death during the hospital stay compared to those discharged (n=24, 49.0%, P<0.001). In controls, lymphopenia (n=436, 94.2%, P=0.05), aspartate aminotransferase (AST) (n=59, 12.7%, P=0.008) and albumin (n=40, 8.6%, P=0.02) have shown an association with increased mortality. Albumin level has an inverse relationship with clinical outcomes among all COVID-19 infected cancer patients. Reduction in albumin level during the hospital stay, particularly in COVID-19 cancer patients should be considered as a predictor of mortality. Further research with a large cohort size is needed to verify and identify other predictors of outcomes in COVID-19 patients with cancer.

Different aspects of failing to recover from proactive semantic interference predicts rate of progression from amnestic mild cognitive impairment to dementia.

This study investigated the role of proactive semantic interference (frPSI) in predicting the progression of amnestic Mild Cognitive Impairment (aMCI) to dementia, taking into account various cognitive and biological factors. The research involved 89 older adults with aMCI who underwent baseline assessments, including amyloid PET and MRI scans, and were followed longitudinally over a period ranging from 12 to 55 months (average 26.05 months). The findings revealed that more than 30% of the participants diagnosed with aMCI progressed to dementia during the observation period. Using Cox Proportional Hazards modeling and adjusting for demographic factors, global cognitive function, hippocampal volume, and amyloid positivity, two distinct aspects of frPSI were identified as significant predictors of a faster decline to dementia. These aspects were fewer correct responses on a frPSI trial and a higher number of semantic intrusion errors on the same trial, with 29.5% and 31.6 % increases in the likelihood of more rapid progression to dementia, respectively. These findings after adjustment for demographic and biological markers of Alzheimer's Disease, suggest that assessing frPSI may offer valuable insights into the risk of dementia progression in individuals with aMCI.

Understanding Predictors of Crohn’s Disease: Determinants of Altered Barrier Function in Pre-Disease Phase of Crohn’s Disease

Abstract The pathogenesis of Crohn’s disease (CD) remains unknown. The current working theory is that genetic susceptibility influences host–microbe interactions, resulting in chronic inflammation. Case–control studies fail to explain the triggers or pathogenesis of the disease, notably due to confounding factors in patients with established disease. Investigating the pre-disease phase of CD improves the capacity to assess these confounding factors and enables us to identify biomarkers associated with increased risk of CD. The Crohn’s Colitis Canada-Genes, Environment, Microbial (CCC-GEM) project is a prospective cohort of healthy first-degree relatives of patients with CD, allowing us to interrogate the pre-disease phase of CD. The CCC-GEM Project has led to the identification of several demographic, serological, and microbiome composition markers associated with an increased risk of disease in pre-clinical participants. Notably, altered intestinal barrier function, as measured by the fractional urinary excretion of lactulose mannitol ratio, is associated with a significantly increased risk of CD. We review the intrinsic and external factors that are associated with altered intestinal barrier integrity, including genetic risk, subclinical inflammation, serum proteomics, intestinal microbiome composition, and environmental components, such as diet and lifestyle. Providing insights into the factors and mechanisms of altered barrier function contributes to our understanding of the pathogenic mechanisms of CD. These advances may aid in developing strategies for preventing disease in high-risk individuals. Further research and personalized strategies are needed to optimize these mitigation strategies for individuals at-risk for CD.

Individualized and Biomarker-Based Prognosis of Longitudinal Cognitive Decline in Early Symptomatic Alzheimer's Disease.

Although individualized models using demographic, MRI, and biological markers have recently been applied in mild cognitive impairment (MCI), a similar study is lacking for patients with early Alzheimer's disease (AD) with biomarker evidence of abnormal amyloid in the brain. We aimed to develop prognostic models for individualized prediction of cognitive change in early AD. A total of 421 individuals with early AD (MCI or mild dementia due to AD) having biomarker evidence of abnormal amyloid in the brain were included in the current study. The primary cognitive outcome was the slope of change in Alzheimer's Disease Assessment Scale-cognitive subscale-13 (ADAS-Cog-13) over a period of up to 5 years. A model combining demographics, baseline cognition, neurodegenerative markers, and CSF AD biomarkers provided the best predictive performance, achieving an overfitting-corrected R2 of 0.59 (bootstrapping validation). A nomogram was created to enable clinicians or trialists to easily and visually estimate the individualized magnitude of cognitive change in the context of patient characteristics. Simulated clinical trials suggested that the inclusion of our nomogram into the enrichment strategy would lead to a substantial reduction of sample size in a trial of early AD. Our findings may be of great clinical relevance to identify individuals with early AD who are likely to experience fast cognitive deterioration in clinical practice and in clinical trials.

Retrospective analysis of elderly poisoning cases admitted to emergency departments: A two-center study

This study aims to analyze demographic, clinical, and biochemical markers of geriatric individuals admitted to emergency clinics due to poisoning to develop preventive public health projects for poisoning prevention. This study was a two-center study. Patients were categorized into accidental, suicide, and misuse groups, and the patient’s clinical and laboratory data were compared. The study included individuals aged 65 and over admitted to hospital emergencies between June 1, 2021, and June 1, 2023. The mean age of the patients admitted with poisoning was 71.7±6.3 years, and the median was 70 (65-90). 69.2% (n=27) of the patients were female, and 30.8% (n=12) were male. Common causes included misuse and suicidal poisoning, drug ingestion, corrosive substance exposure, and pesticide poisoning, Antidepressants and analgesic drugs were the most common agents. There was a statistically significant difference between the mean age rank scores of patients categorized into 3 groups: accidental, suicidal, and misuse (H(3):11.186, p=0.004). The risk of being elderly in accidental poisoning and abuse (non-suicide) patients was 1.203 times that of suicide patients. In other words, it was 20% higher (odds ratio=1.203, CI 95% [1.001-1.446], p=0.049). The mean rank score of troponin values differed significantly between the groups (p=0.027). The study highlights the high rate of poisoning among the elderly, especially women, and suggests preventive public health projects, increased public awareness, and strengthened health policies to improve their quality of life.

Epstein-Barr virus infection as potential indicator of the occurrence and clinical presentation of systemic lupus erythematosus.

The relationship between Systemic lupus erythematosus (SLE) and Epstein-Barr virus (EBV) infection has been suggested for decades, but the underlying mechanism of the EBV influence on SLE development remains to be elucidated. The goals of this research, which included 103 SLE patients and 99 controls, were to investigate the association of the parameters of EBV infection and SLE, to explore whether pooled demographic, clinical and EBV markers achieve a more significant effect on SLE development than each of them individually, and to evaluate EBV nuclear antigen 1 (EBNA1) and latent membrane protein 1 (LMP1) gene polymorphisms in isolates from SLE patients. Comprehensive results related to serological, molecular and sequence markers of EBV infection in SLE patients demonstrated even 24 times higher possibility of having SLE if there is the presence of anti-EBV-EA(D) (early antigen) IgG antibodies (OR=24.086 95%CI OR=2.86-216.07, p=0.004). There was the same distribution of glucocorticoids (p=0.130), antimalarials (p=0.213), and immunosuppressives (p=0.712) in anti-EBV-EA(D) IgG positive and negative SLE patients. Further, higher anti-EBV-EA(D) IgG antibodies titers were identified as independent factors associated with lymphopenia, hematological SLE manifestation (OR=1.041, 95%CI OR=1.01-1.08, p=0.025, while a higher titer of anti-CA (viral capsid antigen) IgG antibodies (OR=1.015, 95%CI OR=1.01-1.03, p=0.019) and positive RF (rheumatoid factors) (OR=4.871, 95%CI OR=1.52-15.61, p=0.008) were identified as independent factors associated with alopecia within SLE. Finally, novel data on EBV EBNA1 and LMP1 gene polymorphisms in lupus are reported. The results support further investigation targeting EBV as a prognostic marker and therapeutic goal for lupus.

Characterizing cerebral microhemorrhage associations in dementia subtypes in the UK Biobank

AbstractBackgroundCerebral microbleeds (CMBs) are associated with neurodegenerative diseases (Charidimou, 2011) and have been identified as an adverse amyloid‐related imaging abnormality event (ARIA‐H) related to amyloid clearing medications (Sperling, 2011). Identifying risk factors for CMBs can help refine inclusion criteria for clinical trials and mitigate the risk of ARIA‐H. CMBs are readily detected on T2*‐GRE MRI sequences, including susceptibility weighted imaging (SWI) – a modality used to detect magnetic field distortions caused by paramagnetic products like iron (Haacke, 2004, Liu, 2017). We explore CMB associations with demographic, disease, and imaging markers in a subset of participants with varying dementia subtypes and complaints in the UK Biobank (Miller, 2016).MethodA total of 75 participants who had clinically diagnosed or self‐reported dementia and SWI imaging were selected; 4 participants were excluded due to extreme motion. We used MARS criteria (Gregoire, 2009) to identify CMBs on SWI and validated our findings using other sequences to exclude CMB ‘mimics’ (Figure 1A). The number, classification, and position of CMBs were recorded. Logistic regressions modeling the outcome of at least one ‘definite’ or ‘total’ (‘definite’ + ‘possible’) CMB were performed and effect sizes were calculated across hippocampal volume, white matter hyperintensity load (WMH), and global WM diffusion MRI (dMRI) microstructural measures.ResultParticipants were predominantly male (65%) with a mean age of 69.8 (± 7.1) years. 9 participants had at least one ‘definite’ CMB and 8 more had at least one ‘possible’ CMB for a ‘total’ of 17 individuals with CMBs. Individuals with CMB(s) were significantly older than those without. CMBs were mostly ‘strictly lobar’ for both definite (78%) and total (71%) classifications (Table 1). The presence of CMBs were found across a spectrum of dementia diagnoses (Figure 1B). Microstructural dMRI measures including global WM FA, MD, and ISOVF were significantly associated with presence of total CMBs (q&lt;0.05) (Figure 2).ConclusionMeasures reflecting WM organization were sensitive to the pathophysiology of CMBs in those with dementia. Future work should investigate whether WM microstructure can predict the development of CMBs in those with dementia, particularly in individuals undergoing amyloid clearing treatments.

Evaluation of longer- vs short-term use of patiromer on health care resource utilization in the patiromer longer-term use evaluation (VALUE) study.

Studies suggest that continuous long-term use of patiromer by patients with hyperkalemia is associated with less health care resource utilization compared with not using potassium binders. To retrospectively evaluate health care resource utilization and costs with longer-term adherent vs short-term use of patiromer. Time-restricted extracts from Optum's de-identified Clinformatics® Data Mart Database (CDM; January 2016-May 2019) and Symphony Health (SHA; January 2016-September 2018) deidentified databases were analyzed. Both include participants enrolled in commercial and privatized public insurance programs (SHA includes some government programs). Both integrate health care claims data from medical and pharmacy claims. Patients aged 18 years or older with hyperkalemia and an index patiromer prescription were selected. Patiromer use was identified as short-term (<2 months) and any fill quantity or adherent longer-term with claims for at least 2 consecutive months and fill quantities of at least 80% of the total days. Groups were matched on multiple categorical covariates to control for demographic variables, baseline characteristics, and markers of disease severity. Random sampling without replacement was performed 50 times to identify 50 sets of patients matched from the short-term cohort to the longer-term cohort. Health care costs/charges and encounters were compared for a 6-month post-index period using t-tests. Of the CDM patients, 1,267 (40.2%) vs 1,887 (59.8%) and of the SHA patients, 2,234 (35.1%) vs 4,132 (64.9%) experienced longer-term vs short-term patiromer use, respectively. Patient sampling selected 242 and 485 patient-matched pairs from CDM and SHA databases, respectively. At 6 months post-index in longer-term vs short-term patiromer groups (P < 0.0001 for all differences shown), respective mean medical and prescription costs/charges were $42,000 vs $54,311 (-$12,311) and $6,816 vs $4,786 (+$2,030), respectively, for CDM patients and $75,147 vs $84,414 (-$9,267) and $4,689 vs $3,736 (+$953) for SHA patients. In the CDM database, medical costs were lower for longer-term vs short-term cohorts for end-stage renal disease services charges ($10,342 vs $14,976 [-$4,634]), inpatient charges ($15,789 vs $21,473 [-$5,684]), and office visit charges ($10,152 vs $13,152 [-$3,000]). Patient out-of-pocket costs ($658 vs $420 [+$238]) and total prescription charges ($6,158 vs $4,366 [+$1,792]) were higher for the longer-term cohort of CDM patients, with similar findings in the SHA dataset. Adherent, longer-term use of patiromer is associated with significantly lower medical costs offsetting higher prescription costs, driven by the largest changes in inpatient and clinic services at CDM and SHA, respectively. This illustrates an economic value of longer-term adherence to patiromer.

Serum Protein-Based Profiles for the Diagnostic Model of Alzheimer's Disease.

Determining a non-invasive, serum-based diagnostic panel for early diagnosis of AD will play a significant role in the prevention and treatment of the disease. We performed standardized clinical assessments and neuroimaging measurements in 45 patients with AD and an equal number of sex - and age-matched controls. 48 target peptides of 14 identified target proteins were quantitatively analyzed by PRM. 8 protein markers were screened, including SAA4, PPBP, PF4, APOA4, F10, CPB2, C1S and IGHM. An diagnosis panel including 8 proteins and demographic characteristics markers respectively was found to be the robust with a AUC of 92.3%. Our study developed a new panel including protein and demographic characteristics that could be used to distinguish AD from control candidates.

Blend Sign and Haemorrhage Location and Volume Predict Late Recurrence and Mortality in Intracerebral Haemorrhage Patients.

Studies on risk factors for primary intracerebral haemorrhage (ICH) focus on short-term predictive values of distinct clinical parameters or computed tomography (CT) markers and disregard the others. We, therefore, studied independent predictive values of demographic, clinical, and CT markers regarding ICH expansion, late ICH recurrence, and late mortality. In a retrospective study of 288 patients with primary ICH, ICH localization (158 lobar, 81 deep, and 49 cerebellar), volume, blend sign, spot sign, finger-like projections, and subarachnoid haemorrhages were evaluated. ICH localization-specific differences for demographic (age, sex), clinical parameters (vascular risk factors, antiplatelet, and anticoagulation therapy), and CT markers were evaluated using logistic regression. We applied Cox proportional hazards modelling using these parameters to predict risk factors for ICH expansion, late ICH recurrence, and late mortality. The blend sign in lobar ICH relates to increased risk of ICH expansion (HR2.3), late ICH recurrence (HR2.3), and mortality (HR1.6). Age, conditions requiring antiplatelet medication, deep ICH localization, volume, and blend sign represented the most important independent factors impacting overall mortality. Blend sign at baseline ICH is a manifestation of underlying detrimental vascular processes that signal increased ICH expansion risk, although is also indicative of long-term risks for late recurrent ICH and late mortality.

Predicting mild cognitive impairment in older adults: A machine learning analysis of the Alzheimer's Disease Neuroimaging Initiative.

Mild cognitive impairment (MCI) in older adults is potentially devastating, but an accurate prediction model is still lacking. We hypothesized that neuropsychological tests and MRI-related markers could predict the onset of MCI early. We analyzed data from 306 older adults who were cognitive normal (CN) attending the Alzheimer's Disease Neuroimaging Initiative sequentially (474 pairs of visits) within 3 years. There were 231 pairs of MCI conversion (CN to MCI), and 242 pairs of CN maintenance (CN to CN). Variables on demographic, neuropsychological tests, genetic, and MRI-related markers were collected. Machine learning was used to construct MCI prediction models, comparing the area under the receiver operating characteristic curve (AUC) as the primary metric of performance. Important predictors were ranked for the optimal model. The baseline age of the study sample was 74.8 years old. The best-performing model (gradient boosting decision tree) with 13 variables predicted MCI with an AUC of 0.819, and the rank of variable importance showed that intracranial volume, hippocampal volume, and score from task 4 (word recognition) of the Alzheimer's Disease Assessment Scale were important predictors of MCI. With the help of machine learning, fewer neuropsychological tests and MRI-related markers are required to accurately predict MCI within 3 years, thereby facilitating targeted intervention. Geriatr Gerontol Int 2024; 24: 96-101.

Related factors of renal injury in primary Sjögren's syndrome

BackgroundPrimary Sjögren’s syndrome (pSS) is a common chronic systemic autoimmune disorder which primarily affects the exocrine glands. Patients may have extraglandular disease involving multiple organs, including the kidneys. This study aimed at investigating the clinical data and laboratory markers which were associated with renal function damage or renal involvement.MethodOne thousand two hundred eighty-eight adult pSS patients from the Department of Rheumatology and Clinical Immunology were enrolled in this retrospective cohort study. And there were 334 patients of them followed up for more than two years for analyzing demographic, clinical data and laboratory markers. Statistical analysis was performed by R software (Version 3.6.2).ResultNearly 95% of 1288 pSS patients were women, and the positive rates of anti-SSA (Sjögren's syndrome A) and anti-SSB were 63% and 27% respectively. 12% of the pSS patients presented renal involvement with eGFR < 60 mL/min/1.73 m2, and the mean age of hospital presentation, serum creatinine and urea were the highest (P < 0.001), and ANA (antinuclear antibody)-positive, anti-SSB-positive and anti-scl-70-positive were more prevalent in this group. Multivariate analyses showed that age, urea, chlorine and anti-SSA indicate a significant association with renal dysfunction. Potassium, sodium and Jo-1 were also confirmed to be related with decreased renal function. The receiver operating characteristic (ROC) analysis including the above factors showed a good performance on the evaluation of renal injury including eGFR < 60 mL/min/1.73 m2 and eGFR 60 -90 mL/min/1.73 m2 in pSS, with area under curve (AUC) values of 0.957 and 0.821, and high sensitivity (71.1% and 84.4%) and specificity (95.5% and 70.5%). After a more than two years follow-up of anti-SSA positive patients, 34.14% of them developed decreased renal function, and 13.58% of them experienced a progression of renal injury with a 23.64% decrease in eGFR.ConclusionAge, urea, chlorine, and anti-SSA were highly associated with renal injury in pSS. Early screening for autoantibodies would be meaningful for evaluation and prevention of renal injury in pSS.