Severe Stage Research Articles

Prognostic Modeling of Chronic Kidney Disease Progression: Bridging Mild and Severe Stages through a Machine Learning Approach

Background and Aim: Chronic Kidney Disease (CKD) is a condition where the kidneys gradually lose their ability to function properly over time. It is into stages based on the severity of kidney damage and the level of kidney function. The objective of our study is to employ machine learning models for the prediction of Chronic Kidney Disease (CKD) progression. Methods: Our study is centered on the prediction of CKD progression from mild (I, II, III) to advanced stages (IV, V, VI). We utilized logistic regression with a lasso-penalized approach and random forest model for our predictive analysis. We assessed the significance of features using the Gini index derived from the random forest model. The performance of our models was evaluated based on the Area Under Receiver Operating Characteristic (AU-ROC), AU-Precision-Recall (PR) curves, recall, precision and accuracy. Results: Our study showcases remarkable predictive performance of CKD progression from milder (I, II, III) to severe stages (IV, V, VI). Random forest model achieved an accuracy of 85%, a recall rate of 86%, a precision rate of 83%, an AU-ROC score of 92%, and an AU-PR score of 83%. The logistic regression model exhibited an accuracy of 84%, a recall rate of 84%, a precision rate of 85%, an AU-ROC score of 92%, and an AU-PR score of 81%. Regarding variable importance, our model identifies creatinine as the most critical feature, followed by eGFR. Conclusion: Our findings indicate that machine learning models hold promise in predicting CKD progression with substantial discriminative capabilities, as evidenced by high AUROC curves. This suggests their potential utility in real-world clinical settings for identifying patients at risk of transitioning from mild to severe stages of CKD.

Sample average treatment effect on the treated (SATT) analysis using counterfactual explanation identifies BMT and SARS-CoV-2 vaccination as protective risk factors associated with COVID-19 severity and survival in patients with multiple myeloma

Patients with multiple myeloma (MM), an age-dependent neoplasm of antibody-producing plasma cells, have compromised immune systems and might be at increased risk for severe COVID-19 outcomes. This study characterizes risk factors associated with clinical indicators of COVID-19 severity and all-cause mortality in myeloma patients utilizing NCATS’ National COVID Cohort Collaborative (N3C) database. The N3C consortium is a large, centralized data resource representing the largest multi-center cohort of COVID-19 cases and controls nationwide (>16 million total patients, and >6 million confirmed COVID-19+ cases to date). Our cohort included myeloma patients (both inpatients and outpatients) within the N3C consortium who have been diagnosed with COVID-19 based on positive PCR or antigen tests or ICD-10-CM diagnosis code. The outcomes of interest include all-cause mortality (including discharge to hospice) during the index encounter and clinical indicators of severity (i.e., hospitalization/emergency department/ED visit, use of mechanical ventilation, or extracorporeal membrane oxygenation (ECMO)). Finally, causal inference analysis was performed using the Coarsened Exact Matching (CEM) and Propensity Score Matching (PSM) methods. As of 05/16/2022, the N3C consortium included 1,061,748 cancer patients, out of which 26,064 were MM patients (8,588 were COVID-19 positive). The mean age at COVID-19 diagnosis was 65.89 years, 46.8% were females, and 20.2% were of black race. 4.47% of patients died within 30 days of COVID-19 hospitalization. Overall, the survival probability was 90.7% across the course of the study. Multivariate logistic regression analysis showed histories of pulmonary and renal disease, dexamethasone, proteasome inhibitor/PI, immunomodulatory/IMiD therapies, and severe Charlson Comorbidity Index/CCI were significantly associated with higher risks of severe COVID-19 outcomes. Protective associations were observed with blood-or-marrow transplant/BMT and COVID-19 vaccination. Further, multivariate Cox proportional hazard analysis showed that high and moderate CCI levels, International Staging System (ISS) moderate or severe stage, and PI therapy were associated with worse survival, while BMT and COVID-19 vaccination were associated with lower risk of death. Finally, matched sample average treatment effect on the treated (SATT) confirmed the causal effect of BMT and vaccination status as top protective factors associated with COVID-19 risk among US patients suffering from multiple myeloma. To the best of our knowledge, this is the largest nationwide study on myeloma patients with COVID-19.

Utilidad del estudio del complejo de células ganglionares de la mácula mediante tomografía de coherencia óptica en el diagnóstico de progresión del glaucoma

IntroductionThe aim of this work is to evaluate the usefulness of the study of the ganglion cell complex of the macula using optical coherence tomography (OCT) to estimate the progression of glaucoma according to its severity. Material and methodsThis is a retrospective cross-sectional study. It includes 205 eyes of 131 patients with glaucoma or ocular hypertension followed for a mean of 5.7years. The parameters and rates of three tests have been analyzed using the progression software of each instrument: visual field, OCT in the ganglion cell complex of the macula and in the nerve fiber layer of the optic nerve. The results of each test, the concordance between them and how they differ according to severity stage have been evaluated. ResultsVisual field classifies more cases of progression in moderate-advanced glaucoma, while in mild glaucoma its capacity is limited. Optic nerve fiber layer OCT classifies more cases of progression in mild glaucoma than in moderate-advanced glaucoma, as it is artifacted by the floor effect. OCT of the macular ganglion cell complex is the test that classifies more cases of progression and has the highest agreement with visual field, regardless of severity. ConclusionThe study of the macula ganglion cell complex using OCT could be a better biomarker of progression than the study of the optic nerve fiber layer, at any stage of glaucoma.

Reduced Lipopolysaccharide-Binding Protein (LBP) Levels Are Associated with Non-Alcoholic Fatty Liver Disease (NAFLD) and Adipose Inflammation in Human Obesity.

Lipopolysaccharide (LPS) and its binding protein LBP have emerged as potential contributors to the progression from overweight/obesity to overt metabolic diseases and NAFLD. While LPS is known to activate hepatocyte inflammation, thus contributing toward NAFLD development, the role of LBP is more intricate, and recent data have shown that experimental reduction in hepatic LBP promotes NAFLD progression. In this cross-sectional investigation, we evaluated circulating LBP in relation to obesity, NAFLD, visceral adipose tissue (VAT) inflammation, and type 2 diabetes (T2D). We recruited 186 individuals (M/F: 81/105; age: 47 ± 10.4 years; BMI: 35.5 ± 8.6 kg/m2); a subgroup (n = 81) underwent bariatric surgery with intra-operative VAT and liver biopsies. LBP levels were higher in obese individuals than non-obese individuals but were inversely correlated with the parameters of glucose metabolism. Reduced LBP predicted T2D independent of age, sex, and BMI (p < 0.001). LBP levels decreased across more severe stages of hepatosteatosis and lobular inflammation, and were inversely associated with VAT inflammation signatures. In conclusion, LBP levels are increased in obese individuals and are associated with a more favorable metabolic profile and lower NAFLD/NASH prevalence. A possible explanation for these findings is that hepatic LBP production may be triggered by chronic caloric excess and facilitate LPS degradation in the liver, thus protecting these individuals from the metabolic consequences of obesity.

ROS-Scavenging Lignin-Based Tolerogenic Nanoparticle Vaccine for Treatment of Multiple Sclerosis.

Multiple sclerosis (MS) is a demyelinating autoimmune disease, in which the immune system attacks myelin. Although systemic immunosuppressive agents have been used to treat MS, long-term treatment with these drugs causes undesirable side effects such as altered glucose metabolism, insomnia, and hypertension. Herein, we propose a tolerogenic therapeutic vaccine to treat MS based on lignin nanoparticles (LNP) with intrinsic reactive oxygen species (ROS)-scavenging capacity derived from their phenolic moieties. The LNP loaded with autoantigens of MS allowed for inducing tolerogenic DCs with low-level expression of costimulatory molecules while presenting antigenic peptides. Intravenous injection of an LNP-based tolerogenic vaccine into an experimental autoimmune encephalomyelitis (EAE) model led to durable antigen-specific immune tolerance via inducing regulatory T cells (Tregs). Autoreactive T helper type 1 cells, T helper type 17 cells, and inflammatory antigen presentation cells (APCs) were suppressed in the central nervous system (CNS), ameliorating ongoing MS in early and late disease states. Additionally, the incorporation of dexamethasone into an LNP-based tolerogenic nanovaccine could further improve the recovery of EAE mice in the severe chronic stage. As lignin is the most abundant biomass and waste byproduct in the pulping industry, a lignin-based tolerogenic vaccine could be a novel, cost-effective, high-value vaccine platform with potent therapeutic efficiency in treating autoimmune diseases.

Management of Severe Persistent Asthma Stage 4 Gina Associated with Multiple Pulmonary Complications

Abstract We present the case of a 42-year-old female patient, known with the diagnosis of severe persistent l asthma stage 3 Gina since 2012, for which she is on treatment with Formoterol/Budesonid (Symbicort) 160mcg/4.5 mcg 1 puff/12 h, inhaler, daily and Salbutamol (Ventolin) 100 mcg, 2 puffs as needed, maximum 6 puffs/24 h, inhaler, who is being treated for exacerbation of respiratory symptoms. It is important to mention the onset of asthma - at the age of 1 year, with rapidly progressive evolution towards the severe stage and association of multiple pulmonary complications. In order to determine the evolutionary stage of the disease and the therapeutic management, spirometry, DLCO examination and native thoraco-pulmonary CT was performed, the patient presenting an important atopic field: multiallergy-environmental factors and iodine. After the establishment of the therapeutic step and the degree of severity, a complex, multimodal treatment was initiated, with a relatively good evolution and prognosis, provided the patient's compliance.

Stimulation of Cerebral Angiogenesis and Neurogenesis with Transcatheter Intracerebral Laser Photobiomodulation Therapy in Alzheimer’s Disease and Vascular Parkinsonism Aggravated by Dementia

AbstractBackgroundThe research is focused on the stimulation of cerebral angiogenesis and neurogenesis using Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) in patients with dementia in Alzheimer’s disease (AD) and patients with vascular parkinsonism (VP).MethodThe examination of 155 patients included assessment of CDR, The Tomography Dementia Rating scale (TDR), MMSE, cerebral CT, MRI, SG, rheoencephalography (REG) and cerebral MUGA.85 patients were selected, of whom:• 48 (30.97%) people suffering from AD, aged 34‐80 (mean age 67.5), men ‐ 17 (35.42%), women ‐ 31 (54.58%). According to dementia severity, patients were subdivided: preclinical stage (TDR‐0) ‐ 4, mild stage (TDR‐1) ‐ 16, moderately severe stage (TDR‐2) ‐ 21, severe stage (TDR‐3) ‐ 7 patients.• 37 (23.87%) people suffering from VP, aged 58‐80 (mean age 77), men 28 (75.68%), women ‐ 9 (24.32%). 19 (51.35%) had a mild dementia stage (CDR‐1).In hospital conditions, in a specialized cath lab, all patients underwent Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) (wavelength 632.8 nanometers).ResultAll 48 (100%) patients with AD underwent angiogenesis stimulation resulting in cerebral collateral capillary revascularization and closure of atreriovenous shunts.Simultaneously, patients showed a 10‐20% increase in cerebral temporal lobes volume, which indicates cerebral neurogenesis development and tissue regeneration. The process was accompanied by dementia level decrease and cognitive functions restoration. Consequently, patients were transferred to a milder TDR group. Depending on the initial dementia severity, the resulting positive effect was observed from 2 to 15 years.All 37 (100%) patients with VP underwent angiogenesis stimulation resulting in cerebral microcirculation improvement and cerebral involutive changes decrease, which indicates the neurogenesis development and tissue regeneration. The process was accompanied by decreased dementia and cognitive functions restoration. The resulting positive effect was observed over 10 years.ConclusionDespite the differences in AD and VP etiology, Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) is an effective treatment for dementia in these diseases. The method stimulates angiogenesis and improves blood supply to the brain, it stimulates neurogenesis and the restoration of normal tissue structures, which leads to improved mental and cognitive functions. The resulting effect persists for a long time.

CHANGES IN FRACTAL DIMENSION OF THIN AND THICK BLOOD VESSELS FROM RETINAL FUNDUS IMAGES FOR DIFFERENT STAGES IN DIABETIC RETINOPATHY

Retinal vasculature feature extraction plays a critical role in the diagnosis and treatment of systemic conditions, particularly in the cases of diabetic retinopathy (DR). This research introduces an algorithm that utilizes segmented blood vessels in retinal images to identify and differentiate five stages of DR, including mild, moderate, severe and proliferative. The algorithm effectively extracts retinal blood vessels by integrating morphological operators and matched filters, yielding a more precise output. The algorithm’s performance is evaluated using the database IDRiD, demonstrating precision and sensitivity scores comparable to those of a trained observer. A box-counting method was incorporated to measure the fractal dimension (FD) of DR-segmented vessel images at various stages to enhance the accuracy of DR staging. The FD analysis was applied to both thick and thin segments of the blood vessels, enabling the assessment of accuracy, sensitivity and specificity. The results indicate that the algorithm successfully identifies the different stages of DR with an accuracy of 93.65% for the mild stage, of 93.33% for the moderate and severe stages and of 92.71% for proliferative DR compared to the images without DR. The study reveals that the variation in FD between the thick and thin vessel components can be an effective biomarker for identifying the different stages of DR, contributing to a better understanding of disease progression. By combining morphological operators, matched filters and fractal dimension analysis, this research presents a promising approach for specialists involved in diagnosing and treating DR, eventually leading to improved patient care and consequences.

Health‐related quality of life in full spectrum of Alzheimer’s disease: a longitudinal analysis

AbstractBackgroundUnderstanding the health‐related quality of life (HR‐QoL) in subjective cognitive decline (SCD), mild cognitive impairment (MCI) and demented patients is essential from the health economic perspective for evaluating new disease‐modifying treatments and preventive interventions. This study aims to assess HR‐QoL and the factors associated with longitudinal change in HR‐QoL in the full spectrum of Alzheimer’s disease.MethodLongitudinal data from 918 SCD and 1,346 MCI patients from the MEMENTO cohort were included in the study. MCI was defined as performing one standard deviation (SD) worse than the age, sex and education‐level thresholds in one or more cognitive domains identified within six months of the study enrollment. SCD was defined as having isolated subjective cognitive complaints but without any objective cognitive deficit and aged 60 years or older. HR‐QoL was measured by EuroQol EQ‐5D‐3L patient‐reported version. Linear mixed‐effect models with disease stage as a time‐varying covariate were used to (1) assess the utility changes over time across the dementia spectrum and (2) compare the utility changes between amyloid positive and negative SCD and MCI patients.ResultAt baseline, mean utilities were 0.84 ± 0.16 and 0.81 ± 0.18 in SCD and MCI patients. Linear mixed effect models estimated that the utilities were ‐0.016 (SE 0.003), ‐0.07 (SE 0.009), ‐0.18 (SE 0.014) and ‐0.36 (SE 0.034) lower than SCD in patients with MCI, mild, moderate and severe dementia over the study period. Time is associated with a significant decrease in utility with ‐0.008 (SE 0.001) per year. Baseline age, BMI, female, diabetes, cardiovascular history, neuropsychiatric symptoms and inability to perform Instrumental activity of daily living (IADL) were negatively associated with utilities. Amyloid‐positive SCD patients showed a faster decline in utility than amyloid‐negative SCD patients (p &lt; 0.05). The decrease was not statistically significant in amyloid‐positive MCI patients compared to amyloid‐negative MCI.ConclusionHealth utilities decrease over time in all stages of dementia, and the decline is steeper in moderate and severe stages. Positive amyloid accelerates health utility decline in SCD but not MCI individuals. The ability to perform IADL is the major factor affecting HR‐QoL in all phases of dementia.

The decline of quantitative EEG goes along with neuropathology in Alzheimer’s Disease

AbstractBackgroundFew studies investigate the correlation between the quantitative EEG (QEEG) and the neuropathological picture. The purpose of this study is to explore how QEEG can recognize the type and extent of neuropathological changes.MethodThe EEG traces and brains belonging to 14 donors of the Abbiategrasso Brain Bank were analyzed. The subjects suffered from neurocognitive disorders due to AD, LBD or AD/vascular lesions (mixed dementia‐MD), with different stages of clinical and neuropathological severity. Clinical and neuropathological characterization was performed according to our protocol; biochemical measurements to determine the amount of proteinopathies are in runtime on frozen samples. QEEG analysis considered the relative power distribution (RPD) of the frequency bands (β, α, θ, δ) and the peak frequency (PF), i.e. the most represented frequency considering all the leads. The PF was measured every 2 seconds for 200‐400 samples, and then averaged. The Kruskall‐Wallis test was used for the comparison between groups.ResultThe clinical diagnosis included: 2 MCI, 4 AD, 6 MD, and 2 LBD. The neuropathological definite diagnosis demonstrated frequent co‐pathologies, and some discrepancies compared to the clinical diagnosis. The neuropathological characterization identified 2 cases with low AD pathology (corresponding to the 2 MCI), 8 cases with intermediate or high AD pathology (4 MD with concomitant cerebrovascular disease), and 4 cases with prevalent LBD pathology. Considering both clinical and neuropathological diagnoses, the comparison between groups revealed no significant differences in QEEG parameters. Nonetheless, a trend emerges towards a lower β‐RPD and a higher θ‐RPD in cases with prevalent LBD pathology. Grouping based on the severity of AD pathology (2 low, 4 intermediate, 4 high) demonstrated significant differences depending upon the neuropathological scoring with a progressive decrease of α‐RPD (p = 0.029) and PF (p = 0.019), and an increase of δ‐RPD (p = 0.020).ConclusionRPD and PF show low discriminatory capacity on etiology. Nonetheless, the presence of LBD seems to boost the EEG slowing. The PF slowing down parallels the increase of AD pathology, representing an indicator for the degenerative load. PF is a simple QEEG parameter, easily obtainable through standard digital EEG; it can be useful for monitoring neurodegenerative burden and disease evolution.

How much would England’s National Health Service have to invest to bring its capacity to deliver an Alzheimer’s treatment to G7 average capacity levels?

AbstractBackgroundThe arrival of disease‐modifying treatments for Alzheimer’s disease (AD) creates a substantial challenge for health systems because of the large patient pool and a complex diagnostic pathway, and in particular, for those countries that already have comparatively low capacity to provide timely, accurate AD diagnostic services. We estimate how much NHS England would have to invest over 10 years to bring its memory assessment services infrastructure up to the average capacity of the other G7 countries and project the resulting changes in wait times for a disease‐modifying Alzheimer’s treatment.MethodDesk research and expert interviews for capacity and cost data. Markov model to estimate the effect of investment on wait times because of limited capacity for specialist visits and confirmatory biomarker testing.ResultEngland has the lowest number of MRI and PET scanners and the second lowest number of AD specialists of the G7 countries (Table 1). Closing this gap would require an estimated investment of ∼GBP 5.5 billion over 10 years, of which 9% would go toward acquisition of 126 PET and 1,196 MRI scanners including building modification, maintenance and IT equipment cost, and 91% to support operative costs (salaries, CSF assays, tracers, and facility use). On an annual basis, this number amounts to GBP 99 per capita and 3.1% of the overall NHS budget. Wait times in the diagnostic process to determine treatment eligibility would go from an average 58 months to 10 months by year 10 of the investment (Figures 1 and 2)ConclusionAs a result of a long‐standing underinvestment in health system infrastructure, wait times to receive an AD treatment would be substantial in England. Targeted investments aimed at increasing the NHS’ capacity to the average of the remaining G7 countries would decrease those wait times significantly. While the required investment is sizeable, the cost of inaction is equally so, since the disease would progress to more severe and costly stages while patients are held up on wait lists.

Interpretable deep learning framework towards understanding molecular changes associated with neuropathology in human brains with Alzheimer’s disease

AbstractBackgroundPostmortem brain tissues have been used to characterize some of the molecular networks and drivers associated with Alzheimer’s disease (AD). In this study, we extend our previous work of a deep learning approach to characterize the molecular changes associated with the severity of AD‐related neuropathology and cognitive impairment, by applying the framework to different brain regions with larger sample sizes.MethodWe trained multi‐layer perceptron (MLP) models for classification of neuropathologically confirmed AD vs. healthy controls (HC) using the transcriptomic data of three brain regions (dorsolateral prefrontal cortex (DLPFC, Total N = 1092), posterior cingulate cortex (PCC, Total N = 647), and head of caudate nucleus (HCN, Total N = 717)) respectively from the ROSMAP study. We performed z‐score normalization for each gene expression and randomly split data in ratio 80:20 with matching class (AD and HC) distributions for training and testing. We embedded the expression profiles of all the subjects to the same Uniform Manifold Approximation and Projection (UMAP) space using the final layer of the trained models and obtained progressive trajectories that mirrored AD pathological severity and cognitive impairment of the whole cohort. Interpretable technique SHapley Additive exPlanations (SHAP) was explored to explain model predictions and obtain significant genes contributing to AD. Network analysis was then carried out to identify key gene modules presented in the models underlying AD progression of different brain regions.ResultThe MLP models differed for each dataset with the number of layers ranging between 3‐5 and achieved the best AUC of 0.891, 0.940 and 0.776 on DLPFC, PCC and HCN datasets respectively. The AD severity indexes (SI) calculated from the trajectory were highly correlated with neuropathology biomarkers (R ∼ 0.6, p &lt; 1e‐11) and global cognitive function (R ∼ 0.7, p &lt; 2.2e‐16). Significant genes identified by the SHAP explainer revealed common and specific transcriptomic signatures from different brain regions implicated in AD.ConclusionThis study illustrates the potentials of deep learning methods to multi‐omic data to characterize the molecular networks associated with increasingly severe clinical and neuropathological stages of neurodegenerative diseases like AD. This offers the opportunity to discover drug targets and/or biomarkers.

OP142 Progression Analysis Versus Traditional Methods To Quantify Slowing Of Disease Progression In Alzheimer’s Disease

IntroductionNew statistical methodology, known as progression models for repeated measures (PMRM), can estimate the slowing of progression (percentage slowing or time delay) of Alzheimer’s disease from trial data on disease-modifying therapies. We compared the PMRM methodology with mixed models for repeated measures (MMRM) and Cox time-to-event analysis on simulated trial data with respect to their power and interpretability of estimates.MethodsTwo novel models were included: PMRM (estimating slowing of progression and allowing different rates across visits) and proportional-slowing PMRM. Clinical Dementia Rating (CDR) Sum of Boxes score and progression to dementia as assessed by CDR global score were the primary outcomes for MMRM/PMRM and the Cox model, respectively. Subject-level placebo arm trajectories were jointly simulated based on estimated CDR mean trajectories and joint temporal correlation structure of 538 amyloid-positive patients with mild cognitive impairment who met typical disease-modifying trial inclusion criteria from the Alzheimer’s Disease Neuroimaging Initiative study. Active arm trajectories were simulated to show an average 20 percent slowing of disease progression, compared with placebo, at each visit. We conducted 1,000 simulations across multiple scenarios, varying the number of patients per arm (200 to 700) and clinical trial duration (18 to 36 months).ResultsThe power of PMRM models was greater than that of MMRM, and much greater than that of the Cox model whose power never exceeded 45 percent. PMRM models accurately estimated the underlying treatment effect (median 20% slowed progression, which translated to a delay in progression of 5 and 7 months at trial durations of 24 and 36 months, respectively), unlike quantifications of the MMRM (median estimated 25% reduction in decline), and the Cox model (median estimated hazard ratio of 0.9).ConclusionsFor disease-modifying therapies, PMRM estimates may have a more intuitive clinical interpretation in terms of delayed progression than MMRM or Cox models and enable a description of the amount of time spent in less severe disease stages. Among all the methods studied, PMRM offered the best combination of interpretability and power.

P113: Psychosocial interventions for dementia grief- a systematic review

Objective:Dementia grief can be described as a caregiver’s anticipatory grief experience due to losses occurring before the care recipient’s physical death. Among other things, these losses can include loss of memory, intimacy, communication, relationship resolution, and family identity. Psychosocial interventions have been developed to address and reduce these pre-loss grief reactions. The objective of this systematic review was to synthesize the evidence on existing dementia grief interventions for caregivers of persons with dementia (PwD).Methods:Electronic databases Web of Science (SSCI), PsycArticles, Psychology and Behavioral Sciences Collection, PsycINFO, PSYNDEX Literature with PSYNDEX Tests and MEDLINE were searched from September 2016 to September 2021. The systematic review was carried out following PRISMA guidelines and it was registered to the PROSPERO database (CRD42021268998). All adult family or friend carers of older persons with dementia were included. All types and severity stages of dementia were included except studies about young onset dementia and dementia grief. Also, family carers could not be bereaved.Results:The 12 included studies contained multifaceted interventions with heterogenous formats. Eight studies had a quantitative, two a qualitative and two a mixed method design. Sample size ranged from two to 273 participants. Interventions included elements of psychoeducation, cognitive and emotional therapeutic strategies based on CBT, acceptance- based and mindfulness-based strategies. The interventions showed statistically significant small to moderate effects on dementia grief. In addition to the effects on dementia grief, the interventions also had a positive impact on mental health-related variables such as burden, depression, empowerment, and resilience.Conclusion:There has been an increase in dementia grief interventions suggesting that dementia grief has been acknowledged as a valid and important construct to describe the dementia caregiver experience. It remains unclear whether health care providers know about and implement elements of the grief interventions in every day clinical encounters with dementia caregivers. Thus, future research should determine the practicing health care providers’ knowledge about dementia grief and its available interventions. Furthermore, it should be examined whether the intervention effects are transferable to caregivers of patients with other terminal illnesses or degenerative disorders, or whether they must be modified.

Disseminated intravascular coagulation is strongly associated with severe acute kidney injury in patients with septic shock

BackgroundDisseminated intravascular coagulation (DIC) worsens the prognosis of septic shock and contributes to multiple organ failure. To date, no data linking DIC and acute kidney injury (AKI) occurrence, severity, and evolution in this setting are available. We aimed at analyzing the association between AKI occurrence, severity and evolution in patients with septic shock-induced DIC. In a prospective monocentric cohort study, consecutive patients, 18 years and older, admitted in the ICU of Strasbourg University Hospital in the setting of systemic hypotension requiring vasopressor related to an infection, without history of terminal chronic kidney disease were eligible. AKI was defined according to the KDIGO classification. DIC diagnosis was based on the International Society on Thrombosis and Haemostasis (ISTH) score. Evolution of AKI was evaluated through the composite endpoint of major adverse kidney events. Only patients with DIC that occurred before or at the time of AKI diagnosis were considered. Univariate and multivariate analysis were performed to determine factors associated with renal outcomes.Results350 patients were included, of whom 129 experienced DIC. Patients with DIC were more seriously ill (median SAPS II 64 vs. 56, p < 0.001), and had higher 28-day mortality (43.3% vs. 26.2%, p < 0.001). AKI was more frequent in patients with DIC (86.8% vs. 74.2%, p < 0.005), particularly for the more severe stage of AKI [KDIGO 3 in 58.1% of patients with DIC vs. 30.8% of patients without DIC, p < 0.001, AKI requiring renal replacement therapy (RRT) in 47.3% of patients with DIC vs. 21.3% of patients without DIC, p < 0.001]. After adjustment for confounding factors, DIC occurrence remained associated with the risk of having the more severe stage of AKI with an odds ratio (OR) of 2.74 [IC 95% (1.53–4.91), p < 0.001], and with the risk of requiring RRT during the ICU stay [OR 2.82 (1.53–5.2), p < 0.001].ConclusionDIC appears to be strongly associated with the risk of developing the more severe form of AKI (stage 3 of the KDIGO classification, RRT requirement), even after adjustment for severity and other relevant factors.

CSF levels of the synaptic marker Cyclase‐associated protein CAP2 in Alzheimer disease across clinical stages

AbstractBackgroundSynaptic dysfunction represent a key event in cognitive decline in Alzheimer disease. There is evidence that Cyclase‐associated protein 2 (CAP2) is involved in synaptic plasticity in AD models but its role in clinical setting has never extensively assessed. Aim of this study was to evaluate CAP2 levels in cerebrospinal fluids of AD and other neurodegenerative diseases and their relationship with amyloid and tau related biomarkers.Methodone‐hundred ten AD patients (prodromal AD n = 70; mild to moderate AD n = 40), 20 Lewy Body Dementia (LBD), 20 frontotemporal dementia (FTD) and 40 healthy controls (HC) were investigated and clinically assessed following a standardized neurological and cognitive behavioral assessment. All subjects underwent CSF analyses for h‐tau, p‐tau and Aß42 (Lumipulse) while CAP2 levels were assessed by using standard ELISA. Between‐groups differences and correlations between CSF biomarkers were evaluated using non‐parametric comparisons and partial correlation analyses adjusted for the effect of age, sex and disease duration.ResultAD patients across severity stages showed higher CAP2 levels compared to controls and non‐AD patients (p = 0.001). CAP2 levels did not correlate with disease severity and were independent of APOE genotype. In AD patients, CAP2 levels showed a positive correlation with t‐tau and p‐tau (p&lt;0.001).ConclusionCSF levels of CAP2 were significantly increased in AD patients and correlated with t‐tau and p‐tau independently of amyloid pathology. Altogether, these findings support the hypothesis that AD is specifically associated with synaptic dysfunction since early stages and that amyloid‐related synaptic changes parallels tau‐related axonal degeneration.

Caregiver Enablement Training to Support Homecare: A Study from India

AbstractHomecare is the prevalent model of dementia care in India and ‘attendants,’ who are non‐trained lay workers are often employed in Indian households to assist with personal care, ADL and other support which the family may need. Providing training to these attendants can support continued dementia care at home. We present initial data from a caregiver enablement program (CEP) being provided in India.MethodsThe (CEP) consists of a minimum of 6‐8 individually tailored sessions beginning with a clinical evaluation. Using a collaborative approach, challenging areas of caregiving are identified and prioritized. Across the sessions, information about what may be contributing to these challenges and tips for providing care are provided by a dementia trained specialist. Attendants and family members are encouraged to use these approaches and feedback was discussed in an iterative manner to improve the caregiving process and address emerging issues.ResultsTen families availed the caregiver enablement program, out of those 2 patients were living with their 24 hours attendant and 8 patients were living with family and attendants. The caregiver enablement program was conducted online, offline and in hybrid mode, 5 of them were online sessions, 4 offline sessions and one hybrid session (session conducted at home and online). Patients had moderate to severe stage dementia (Hindi MMSE Mn = 13.3, SD = 5.7; Caregiver burden: Zarit burden interview Mn = 29.8 SD = 19.6).Key areas where enablement was required were basic understanding of dementia, acceptance of the illness by the family and that they need external support, how to manage challenging behaviours like toileting, bathing, dressing, incontinence, transferring and feeding, how to engage the patient in meaningful activities and the need for environment modifications to improve safety and managing challenging behaviours. Psycho educational skill building, multi component intervention was found to be effective in the present study to combat the concerns shared by the attendants/family members.ConclusionThis study demonstrates how up‐skilling lay workers through training on dementia and management of challenging behaviours can support home care. Supporting the informal care system with specialised training can be an effective way of providing dementia care in low resource settings.

Analysis and treatment workflow of modified seven-step approach for acute respiratory and circulatory disorders

Acute respiratory and circulatory disorders are the most common critical syndromes, the essence of which is damage to the organs/systems of the heart and lungs. These comprise the essential manifestation of disease and injury progression to the severe stage. Its development involves the following components: individual specificity, primary disease strike, dysregulation of the host's response, and systemic disorders. Admission for acute respiratory and circulatory disorders is a clinical challenge. Based on a previously proposed flow, a critical care ultrasound-based stepwise approach (PIEPEAR) as a standard procedure to manage patients with acute cardiorespiratory compromise and practical experience in recent years, a modified seven-step analysis and treatment process has been developed to help guide clinicians with rational thinking and standardized treatment when faced with acute respiratory and circulatory disorders. The process consists of seven steps: problem-based clinical analysis, intentional information acquisition, evaluation of core disorder based on critical care ultrasound, pathophysiology and host response phenotype identification, etiology diagnosis, act treatment through pathophysiology-host response and etiology, and re-check. The modified seven-step approach is guided by a "modular analysis" style of thinking and visual monitoring. This approach can strengthen the identification of clinical problems and facilitate a three-in-one analysis. It focuses on pathophysiological disorders, body reactions, and primary causes to more accurately understand the condition's key points, and make treatment more straight forward, to finally achieve the aim of "comprehensive cognition and refined treatment".

Prevalence and Severity Distribution of Alzheimer’s Disease in the United States from the Health and Retirement Study

AbstractBackgroundThere is limited data regarding Alzheimer’s disease (AD) prevalence by severity across the AD continuum. This study aimed to estimate prevalence of mild cognitive impairment (MCI) and mild, moderate, and severe AD in a representative sample of the United States (US) population.MethodData from the Health and Retirement Study (HRS), a bi‐annual national survey of older adults in the US, were analyzed (2014‐2018), applying cluster sampling weights. AD ascertainment from HRS was based on patient report of a clinical diagnosis (physician diagnosis‐based), or the test score of Modified Telephone Interview of Cognitive Status (TICS‐m) (cognitive performance‐based). Patients with MCI were identified with the cognitive performance‐based method only. MCI and AD severity stages were ascertained using a crosswalk between the scores of TICS‐m and the mini‐mental state examination (MMSE).ResultThe diagnosis‐based method identified 1.2%, 1.2%, 1.3% patients with AD in 2014, 2016 and 2018, respectively (2.2% pooled). The mean (SD) age was 79.4 (10.3) years, with 61% women and 22% had passed college education (combined across surveys). The cognitive performance‐based method identified 23%, 23%, 21% patients with MCI in 2014, 2016 and 2018, respectively (24% pooled), and 27%, 22%, 17% patients with AD in 2014, 2016 and 2018, respectively (30% pooled). For patients with MCI, the mean age was 67.3 (10.1) years, with 51% women and 36% passed college education; for patients with AD, the mean age was 72.8 (11.1) years, with 53% women and 28% had passed college education. Severity distributions are shown in Figure 1. Unweighted results were similar.ConclusionThe cognitive performance‐based method identified a substantially higher prevalence of AD than the diagnosis‐based method and enabled identification of MCI prevalence using HRS data. The prevalence of MCI was consistently higher than AD dementia severity categories over the years (2014, 2016, and 2018). The discordance in AD prevalence estimation between cognitive performance‐based and diagnosis‐based methods underscores a need for better understanding of clinical practice patterns in AD diagnosis, use of clinical assessment tools, and severity classification in the US.

No gender-specific differences in comorbidities in patients with chronic obstructive pulmonary disease due to alpha-1 antitrypsin deficiency

BackgroundA deficiency in alpha-1 antitrypsin (A1AD) leads to increased activity of proteolytic enzymes. The consequence is a damage of airways and alveoli and, ultimately, the development of emphysema and chronic obstructive pulmonary disease (COPD).PurposeGender-specific differences in terms of comorbidities are still unclear due to the rarity of this genetic autosomal recessive disease.Patients and methodsThis retrospective observational study was conducted from January 1, 2005, to November 30, 2022, in the Department of Pneumology, HELIOS University-Clinic Wuppertal, University of Witten/Herdecke, Germany.ResultsEleven patients with COPD due to A1AD could be included into the study (6 males, 54.5%; 95% CI 23.4–83.3%) with a mean age of 53.9 ± 11.6 years. The male study participants were of normal weight body mass index 24.17 ± 4.67, while the females were obese 31.2 ± 4.87 (p = 0.054). More women were smokers (60%, p = 0.567). Furthermore, all of the women had panlobular emphysema (100%, p = 0.455). All subjects suffered from COPD, with most male subjects in severe advanced stages (50%, p = 0.545). No case of liver involvement was observed in this study.ConclusionThe findings of this study showed no statistically relevant gender-specific differences in comorbidities of patients with COPD due to A1AD.