Association of device detected atrial and ventricular tachyarrhythmia with adverse events in patients with an implantable cardioverter-defibrillator.

INTRODUCTION: Heart failure patients with a history of atrial fibrillation (AF) and ventricular tachycardia/ventricular fibrillation (VT/VF) are known to have worse outcomes. However, there are limited data on the temporal relationship between development of these arrhythmias and the risk of subsequent congestive heart failure (CHF) exacerbation and death. METHODS: The study cohort comprised 5511 patients implanted with an implantable cardioverter-defibrillator (ICD) in landmark clinical trials (MADIT-II, MADIT-RISK, MADIT-CRT, MADIT-RIT, and RAID) who were in sinus rhythm at enrollment. Multivariate cox analysis was performed to evaluate the time-dependent association between development of in-trial device detected AF and VT/VF with subsequent CHF exacerbation and death. RESULTS: Multivariate analysis showed that AF occurrence and VT/VF occurrence were both associated with a similar magnitude of risk for subsequent CHF exacerbation (HR = 1.73 and 1.87 respectively, p < .001 for both). In contrast, only in-trial VT/VF was associated with a significant > two-fold increase in the risk of subsequent mortality (HR = 2.13, p < .001) whereas AF occurrence was not associated with a significant mortality increase after adjustment for in-trial VT/VF (HR = 1.36, p = .096). CONCLUSION: Our findings from a large cohort of ICD recipients enrolled in landmark clinical trials show that device detected AF and VT/VF can be used to identify patients with increased risk for CHF exacerbation and mortality. These findings suggest a need for early intervention in CHF patients who develop device-detected atrial and ventricular tachyarrhythmias.

Learning debiased graph representations from the OMOP common data model for synthetic data generation.

BACKGROUND: Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or intervention. We propose a highly available method which enables synthetic data generation from real patient records in a privacy preserving and compliant fashion, is interpretable and allows for expert intervention. METHODS: Our approach ties together two established tools in medical informatics, namely OMOP as a data standard for electronic health records and Synthea as a data synthetization method. For this study, data pipelines were built which extract data from OMOP, convert them into time series format, learn temporal rules by 2 statistical algorithms (Markov chain, TARM) and 3 algorithms of causal discovery (DYNOTEARS, J-PCMCI+, LiNGAM) and map the outputs into Synthea graphs. The graphs are evaluated quantitatively by their individual and relative complexity and qualitatively by medical experts. RESULTS: The algorithms were found to learn qualitatively and quantitatively different graph representations. Whereas the Markov chain results in extremely large graphs, TARM, DYNOTEARS, and J-PCMCI+ were found to reduce the data dimension during learning. The MultiGroupDirect LiNGAM algorithm was found to not be applicable to the problem statement at hand. CONCLUSION: Only TARM and DYNOTEARS are practical algorithms for real-world data in this use case. As causal discovery is a method to debias purely statistical relationships, the gradient-based causal discovery algorithm DYNOTEARS was found to be most suitable.

Identifying the Effect of Cognitive Motivation with the Method Based on Temporal Association Rule Mining Concept.

Being motivated has positive influences on task performance. However, motivation could result from various motives that affect different parts of the brain. Analyzing the motivation effect from all affected areas requires a high number of EEG electrodes, resulting in high cost, inflexibility, and burden to users. In various real-world applications, only the motivation effect is required for performance evaluation regardless of the motive. Analyzing the relationships between the motivation-affected brain areas associated with the task's performance could limit the required electrodes. This study introduced a method to identify the cognitive motivation effect with a reduced number of EEG electrodes. The temporal association rule mining (TARM) concept was used to analyze the relationships between attention and memorization brain areas under the effect of motivation from the cognitive motivation task. For accuracy improvement, the artificial bee colony (ABC) algorithm was applied with the central limit theorem (CLT) concept to optimize the TARM parameters. From the results, our method can identify the motivation effect with only FCz and P3 electrodes, with 74.5% classification accuracy on average with individual tests.

Frequency-Dependent Plasticity in the Temporal Association Cortex Originates from the Primary Auditory Cortex, and Is Modified by the Secondary Auditory Cortex and the Medial Geniculate Body.

The brain areas that mediate the formation of auditory threat memory and perceptual decisions remain uncertain to date. Candidates include the primary (A1) and secondary (A2) auditory cortex, the medial division of the medial geniculate body (MGm), amygdala, and the temporal association cortex. We used chemogenetic and optogenetic manipulations with in vivo and in vitro patch-clamp recordings to assess the roles of these brain regions in threat memory learning in female mice. We found that conditioned sound (CS) frequency-dependent plasticity resulted in the formation of auditory threat memory in the temporal association cortex. This neural correlated auditory threat memory depended on CS frequency information from A1 glutamatergic subthreshold monosynaptic inputs, CS lateral inhibition from A2 glutamatergic disynaptic inputs, and non-frequency-specific facilitation from MGm glutamatergic monosynaptic inputs. These results indicate that the A2 and MGm work together in an inhibitory-facilitative role.SIGNIFICANCE STATEMENT: The ability to recognize specific sounds to avoid predators or seek prey is a useful survival tool. Improving this ability through experiential learning is an added advantage requiring neural plasticity. As an example, humans must learn to distinguish the sound of a car horn, and thus avoid oncoming traffic. Our research discovered that the temporal association cortex can encode this kind of auditory information through tonal receptive field plasticity. In addition, the results revealed the underlying synaptic mechanisms of this process. These results extended our understanding of how meaningful auditory information is processed in an animal's brain.

Temporal association between leg movements and respiratory events in patients with obstructive sleep apnea: description and differences between the AASM and WASM scoring criteria.

PURPOSE: To describe the temporal association between leg movements (LMs) and respiratory events in patients with obstructive sleep apnea (OSA), and to quantify the difference in scoring respiratory-related leg movement (RRLM) between the American Academy of Sleep Medicine (AASM) criterion and the criterion recommended by the World Association of Sleep Medicine (WASM). METHODS: Patients with OSA who presented with > 10 LMs of any type per hour of sleep were included in this study. For each participant, RRLMs were scored using both the AASM criterion and the recommended WASM criterion. The occurrence of LMs in relation to respiratory events and the difference in scoring RRLM between the AASM criterion and the criterion recommended by the WASM were quantified. RESULTS: In 32 patients enrolled, mean age was 48.1 ± 11.0 years and 78% were men. LMs were significantly more frequent after respiratory events, followed by before respiratory events, and were rare during respiratory events (P < 0.01). Compared with the AASM criterion, more LMs were classified as RRLMs based on the recommended WASM criterion (P = 0.01). CONCLUSION: LMs are more frequent after respiratory events than before and during respiratory events, and more LMs are scored as RRLMs based on the recommended WASM criterion than based on the AASM criterion.

Acquisition of temporal patterns from electronic health records: an application to multimorbid patients.

BACKGROUND: The exponential growth of digital healthcare data is fueling the development of Knowledge Discovery in Databases (KDD). Extracting temporal relationships between medical events is essential to reveal hidden patterns that can help physicians find optimal treatments, diagnose illnesses, detect drug adverse reactions, and more. This paper presents an approach for the extraction of patient evolution patterns from electronic health records written in Catalan and/or Spanish. METHODS: We propose a robust formulation for extracting Temporal Association Rules (TARs) that goes beyond simple rule extraction by considering the sequence of multiple visits. Our highly configurable algorithm leverages this formulation to extract Temporal Association Rules from sequences of medical instances. We can generate rules in the desired format, content, and temporal factors while accounting for different levels of abstraction of medical instances. To demonstrate the effectiveness of our methodology, we applied it to extract patient evolution patterns from clinical histories of multimorbid patients suffering from heart disease and stroke who visited Primary Care Centers (CAP) in Catalonia. Our main objective is to uncover complex rules with multiple temporal steps, that comprise a set of medical instances. RESULTS: As we are working with real-world, error-prone data, we propose a process of validation of the results by expert practitioners in primary care. Despite our limited dataset, the high percentage of patterns deemed correct and relevant by the experts is promising. The insights gained from these patterns can inform preventive measures and help detect risk factors, ultimately leading to better treatments and outcomes for patients. CONCLUSION: Our algorithm successfully extracted a set of meaningful and relevant temporal patterns, especially for the specific type of multimorbid patients considered. These patterns were evaluated by experts and demonstrated the ability to predict risk factors that are commonly associated with certain diseases. Moreover, the average time gap between the occurrence of medical events provided critical insight into the term of these risk factors. This information holds significant value in the context of primary healthcare and preventive medicine, highlighting the potential of our method to serve as a valuable medical tool.

Short-term relation between air pollutants and hospitalizations for respiratory diseases: analysis by temporal association rules.

This study investigates the relation between exposure to critical air pollution events with multipollutant (CO, PM10, PM2.5, NO2, O3, and SO2) and hospitalizations for respiratory diseases in the metropolitan area of São Paulo (RMSP) and in the countryside and coastline, from 2017 to 2021. Data mining analysis by temporal association rules searched for frequent patterns of respiratory diseases and multipollutants associated with time intervals. In the results, pollutants PM10, PM2.5, and O3 showed high concentration values in the three regions, SO2 on the coast, and NO2 in the RMSP. Seasonality was similar between pollutants and between cities and concentrations significantly higher in winter, except for O3, which was present in warm seasons. Hospitalizations were recurrent during the transition from summer to colder periods. In approximately 35% of the total days with hospitalization greater than the annual average, one or more pollutants had a high concentration. The rules showed that PM2.5, PM10, and O3 pollutants are strongly associated with increased hospitalizations in the RMSP (PM2.5 and PM10 with 38.5% support and 77% confidence) and in Campinas (PM2.5 with 66.1% support and 94% confidence) and the pollutant O3 with maximum support of 17.5%. On the coast, SO2 was related to high hospitalizations (43.85% support and 80% confidence). The pollutants CO and NO2 were not associated with the increase in hospitalizations. The ratio delay indicates the pollutants that were associated with hospitalizations, having concentration remained above the limit for three days, oscillating in smaller hospitalizations on the 1st day and again higher on the 2nd and 3rd days of delay, in a decreasing way. In conclusion, high pollutant exposure is significantly associated with daily hospitalization for respiratory problems. The cumulative effect of air pollutants increased hospitalization in the following days, in addition to identifying the pollutants and which pollutant combinations are most harmful to health in each region.

Age-specific difference in the association between prediabetes and subclinical atherosclerosis: an analysis of a chinese prospective cohort study.

BACKGROUND: Prediabetes is an important risk factor of cardiovascular disease (CVD) and is associated with subclinical atherosclerosis. However, the evidence of prediabetes as a cardiovascular risk factor is mainly derived from middle-aged adults. Recently, multiple studies supported that prediabetes in older adults would not lead to higher risk of CVD or mortality. We aimed to investigate the age-specific difference in the association between prediabetes and subclinical atherosclerosis in a Chinese prospective cohort study. METHODS: We included 4739 individuals aged ≥ 40 years and without diagnosed diabetes or CVD history, and divided them into middle-aged adults (age < 60) and older adults (age ≥ 60). Fasting plasma glucose (FPG), 2-h post-load plasma glucose (2 h-PPG) and glycated hemoglobin (HbA1c) were measured at baseline to identify prediabetes status. At follow-up visits, subclinical atherosclerosis status was assessed by branchial-ankle pulse wave velocity (baPWV) and carotid intima-media thickness (CIMT). Logistic regression analysis, restricted cubic splines and cross-lagged path analysis were used in statistical analysis. RESULTS: 1634 participants aged over 60 years, and 64.3% of them had prediabetes. 3105 participants aged 40-59 years, and 49.3% of them had prediabetes. We found that prediabetes was associated with increased risk of subclinical atherosclerosis in middle-aged adults, but the association attenuated substantially in older adults. Impaired glucose tolerance (IGT), compared to normal glucose tolerance, was associated with 39% lower risk of increased baPWV only in older adults. In accordance, the association between 2 h-PPG and risk of increased baPWV was "U-shaped" in older adults, while risk of elevated baPWV increased linearly with 2 h-PPG in middle-aged adults. In the cross-lagged analysis, increase in FPG and 2 h-PPG tended not to precede increase in baPWV in older adults, but appeared to increase simultaneously with baPWV in middle-aged ones. CONCLUSION: Our results indicated that prediabetes might be less related to subclinical atherosclerosis in older adults than in middle-aged adults and suggested that age was important to consider in the care of adults with prediabetes.

Temporal relationship between osteoarthritis and comorbidities: a combined case control and cohort study in the UK primary care setting.

OBJECTIVE: To determine the burden of comorbidities in OA and their temporal relationships in the UK. METHODS: The Clinical Practice Research Datalink (CPRD) GOLD was used to identify people with incident OA and age, gender and practice matched non-OA controls from UK primary care. Controls were assigned the same index date as matched cases (date of OA diagnosis). Associations between OA and 49 individual comorbidities and multimorbidities (two or more comorbidities excluding OA) both before and after OA diagnosis were estimated, adjusting for covariates, using odds ratios (aORs) and hazard ratios (aHRs), respectively. RESULTS: During 1997-2017, we identified 221 807 incident OA cases and 221 807 matched controls. Of 49 comorbidities examined, 38 were associated with OA both prior to and following the diagnosis of OA and 2 (dementia and systemic lupus erythematosus) were associated with OA only following the diagnosis of OA. People with OA had a higher risk of developing heart failure [aHR 1.63 (95% CI 1.56, 1.71)], dementia [aHR 1.62 (95% CI 1.56, 1.68)], liver diseases [aHR 1.51 (95% CI 1.37, 1.67)], irritable bowel syndrome [aHR 1.51 (95% CI 1.45, 1.58)], gastrointestinal bleeding [aHR 1.49 (95% CI 1.39, 1.59)], 10 musculoskeletal conditions and 25 other conditions following OA diagnosis. The aOR for multimorbidity prior to the index date was 1.71 (95% CI 1.69, 1.74), whereas the aHR for multimorbidity after the index date was 1.29 (95% CI 1.28, 1.30). CONCLUSIONS: People with OA are more likely to have other chronic conditions both before and after the OA diagnosis. Further study on shared aetiology and causality of these associations is needed.

Functional interaction of ventral hippocampal CA1 region and prelimbic cortex contributes to the encoding of contextual fear association of stimuli separated in time.

Although stimuli that are associated often overlap in time, previous events can also predict the occurrence of a later aversive stimulus and be associated with it to better guide future behavior. Associations of stimuli separated in time have been studied using discrete stimulus as the conditioned stimulus (CS) in trace conditioning or, more recently in our lab, using the context as the CS in contextual fear conditioning with temporal discontinuity (CFC-5s), a task that simultaneously includes the processing of time and space components. It is thought that fear memories are encoded by the strengthening of synaptic connections in a distributed neural network. However, it is unclear how this temporal factor, which may differentially require the maintenance of the stimulus over time, affects the interactivity between brain regions to form the association. Because the prelimbic cortex (PL) and the hippocampus have been individually engaged in trace conditioning, they may functionally interact to encode associations separated in time. This is anatomically supported by direct ipsilateral projections from the ventral hippocampal CA1 region (vCA1) to PL. The aim of the present study was to investigate the effect of the functional disconnection of vCA1 and PL on CFC-5s using pre-training asymmetric reversible inactivation with muscimol. For comparison, we also observed its effect on contextual fear conditioning (CFC). Results showed that the functional disconnection impaired the encoding of the CFC-5s, an association of stimuli separated in time, while did not affect the CFC, an association of stimuli overlapped in time. In addition, the preserved connection in one hemisphere was sufficient to support the encoding of CFC-5s. The time interval by itself did not increase freezing responses and both CFC and CFC tasks had similar generalization and higher freezing responses than unconditioned groups. These findings suggest that the time factor alters the requirement of the interactivity of the brain regions underlying fear conditioning and extend the relevance of hippocampal-prefrontal interactions in memory.

Risk of Parkinson's disease among patients with herpes zoster: a nationwide longitudinal study.

OBJECTIVE: Several studies suggested a potential role of viral infection in the pathophysiology of Parkinson's disease (PD). However, the association between herpes zoster and PD was not investigated well till now. METHODS: Using the Taiwan National Health Insurance Research Database, 13 083 patients aged ≥45 years with herpes zoster and 52 332 (1:4) age-/sex-matched controls were enrolled between 1998 and 2008 and followed to the end of 2011. Those who developed PD during the follow-up period were identified. RESULTS: The Cox regression analysis with adjustment of demographic characteristics, health system utilization, and comorbidities demonstrated that patients with herpes zoster had an increased risk (hazard ratio [HR]: 1.80, 95% confidence interval [CI]: 1.43-2.28) of developing PD in later life compared to the control group. Sensitivity tests after excluding the first year (HR: 1.50, 95% CI: 1.16-1.93) and first 2-year (HR: 1.44, 95% CI: 1.10-1.88) observation periods showed consistent results. CONCLUSIONS: Patients with herpes zoster were more likely to develop PD in later life compared to the controls. Additional studies are necessary for validating our results and to clarify the underlying pathophysiology between herpes zoster and PD.

Detecting virus-specific effects on post-infection temporal gene expression.

BACKGROUND: Different types of viruses have different envelope proteins, and may have their shared or distinctive host-virus interactions which result in various post-infection effects in humans and animals. These effects often do not appear at once but take time to unfold. To characterize the virus-specific effects, we applied a Multivariate Polynomial Time-dependent Genetic Association (MPTGA) method, previously proposed for detecting differences in temporal gene expression traits, to test for the differences in mouse lung transcriptome response to infection of different subtypes of influenza A viruses. RESULTS: We compared two methods: the Multivariate Polynomial Time-dependent Genetic Association (MPTGA) method, and the conventional modified t-test, to study the virus-specific effects on mouse lung gene expression. Both methods found H3N2 to be the most different virus among the three viruses tested, with the largest number of genes with H3N2-specific effects. However, the MPTGA method demonstrated much higher power of detection, and the detected genes with virus-specific effects showed better biological relevance. CONCLUSIONS: Transcriptome response to virus infection is dynamic. MPTGA which leverages temporal gene expression traits showed increased power in detecting biologically relevant virus-specific effects comparing with conventional t-test method.

Neural representations of time-linked memory.

Many cognitive processes, such as episodic memory and decision making, rely on the ability to form associations between two events that occur separately in time. The formation of such temporal associations depends on neural representations of three types of information: what has been presented (trace holding), what will follow (temporal expectation), and when the following event will occur (explicit timing). The present review seeks to link these representations with firing patterns of single neurons recorded while rodents and non-human primates associate stimuli, outcomes, and motor responses over time intervals. Across these studies, two distinct firing patterns were observed in the hippocampus, neocortex, and striatum: some neurons change firing rates during or shortly after the stimulus presentation and sustain the firing rate stably or sidlingly during the subsequent intervals (tonic firings). Other neurons transiently change firing rates during a specific moment within the time intervals (phasic firings), and as a group, they form a sequential firing pattern that covers the entire interval. Clever task designs used in some of these studies collectively provide evidence that both tonic and phasic firing responses represent trace holding, temporal expectation, and explicit timing. Subsequently, we applied machine-learning based classification approaches to the two firing patterns within the same dataset collected from rat medial prefrontal cortex during trace eyeblink conditioning. This quantitative analysis revealed that phasic-firing patterns showed greater selectivity for stimulus identity and temporal position than tonic-firing patterns. Our summary illuminates distributed neural representations of temporal association in the forebrain and generates several ideas for future investigations.

Incorporating repeating temporal association rules in Naïve Bayes classifiers for coronary heart disease diagnosis.

In this paper, we develop a Naïve Bayes classification model integrated with temporal association rules (TARs). A temporal pattern mining algorithm is used to detect TARs by identifying the most frequent temporal relationships among the derived basic temporal abstractions (TA). We develop and compare three classifiers that use as features the most frequent TARs as follows: (i) representing the most frequent TARs detected within the target class ('Disease = Present'), (ii) representing the most frequent TARs from both classes ('Disease = Present', 'Disease = Absent'), (iii) representing the most frequent TARs, after removing the ones that are low-risk predictors for the disease. These classifiers incorporate the horizontal support of TARs, which defines the number of times that a particular temporal pattern is found in some patient's record, as their features. All of the developed classifiers are applied for diagnosis of coronary heart disease (CHD) using a longitudinal dataset. We compare two ways of feature representation, using horizontal support or the mean duration of each TAR, on a single patient. The results obtained from this comparison show that the horizontal support representation outperforms the mean duration. The main effort of our research is to demonstrate that where long time periods are of significance in some medical domain, such as the CHD domain, the detection of the repeated occurrences of the most frequent TARs can yield better performances. We compared the classifier that uses the horizontal support representation and has the best performance with a Baseline Classifier which uses the binary representation of the most frequent TARs. The results obtained illustrate the comparatively high performance of the classifier representing the horizontal support, over the Baseline Classifier.

Post-traumatic Stress Disorder and Risk of Parkinson Disease: A Nationwide Longitudinal Study.

OBJECTIVE: Increasing evidence has suggested a relationship between post-traumatic stress disorder (PTSD) and neurodegenerative disorder, such as Alzheimer disease. The association between PTSD and Parkinson disease (PD), however, remains unclear. METHOD: Using the Taiwan National Health Insurance Research Database, 7,280 subjects (1,456 patients aged ≥45 years with PTSD and 5,824 age-/sex-matched individuals without PTSD) were enrolled between 2002 and 2009 and followed to the end of 2011. Subjects who developed PD during the follow-up period were identified. RESULTS: An increased risk of developing PD was found in patients with PTSD (Wald χ2 = 12.061, hazard ratio [HR]: 3.46, 95% confidence interval [CI]: 1.72-6.96) compared with individuals without PTSD, after adjusting for demographic data and medical and psychiatric comorbidities. The sensitivity tests after excluding the first year observation (Wald χ2 = 7.948, HR: 3.01, 95% CI: 1.40-6.46) and the first 3-year observation (Wald χ2 = 5.099, HR: 3.07, 95% CI: 1.16-8.15) were consistent. CONCLUSIONS: Patients with PTSD had an elevated risk of developing PD in later life. Further studies would be required to clarify the exact pathophysiology between PTSD and PD and to investigate whether the prompt intervention for PTSD may reduce this risk.

Bidirectional triggering association between migraine and restless legs syndrome: A diary study.

OBJECTIVE: Migraine is comorbid with restless legs syndrome (RLS). However, the temporal association between these two episodic disorders remains elusive. The current study investigated the temporal relationship between migraine and RLS attacks. METHODS: Migraine patients with RLS were recruited from a headache clinic. Patients with symptomatic RLS, RLS mimics, daily headaches, or daily RLS attacks were excluded. The patients recorded their headaches and RLS attacks for two weeks in a diary. The severity of each headache or RLS attack was rated on a four-point (0-3) Likert scale. Logit-normal, random-effects models were employed to estimate the odds ratios (ORs) for the temporal association between migraine and RLS attacks. RESULTS: Thirty migraine patients with RLS (28 F/2 M, mean age 35.5 ± 9.0 years) completed the study. On the basis of 420 daily diary records, migraine attacks were associated with subsequent RLS attacks occurring on the same and next nights (OR = 6.94, 95% confidence interval (CI) = 4.39-11.0 and OR = 3.00, CI = 1.92-4.68; both ITALIC! p < 0.001). RLS attacks were associated with subsequent migraine attacks only on Day 1 (OR = 1.97 (CI = 1.3-2.98; ITALIC! p = 0.01). Overall, the frequencies of migraine and RLS attacks in two weeks were correlated (Spearman's correlation = 0.56, ITALIC! p = 0.001). CONCLUSIONS: Our study results showed a bidirectional triggering association between migraine and RLS attacks. The association was stronger and lasted longer for migraine triggering subsequent RLS than that for vice versa.

Eye movements during mental time travel follow a diagonal line.

Recent research showed that past events are associated with the back and left side, whereas future events are associated with the front and right side of space. These spatial-temporal associations have an impact on our sensorimotor system: thinking about one's past and future leads to subtle body sways in the sagittal dimension of space (Miles, Nind, & Macrae, 2010). In this study we investigated whether mental time travel leads to sensorimotor correlates in the horizontal dimension of space. Participants were asked to mentally displace themselves into the past or future while measuring their spontaneous eye movements on a blank screen. Eye gaze was directed more rightward and upward when thinking about the future than when thinking about the past. Our results provide further insight into the spatial nature of temporal thoughts, and show that not only body, but also eye movements follow a (diagonal) "time line" during mental time travel.

Age-specific difference in the temporal relationships between updated cardiovascular health construct and arterial stiffness in middle-aged and older adults.

Previous studies have found that the association between modifiable risk factors and arterial stiffness varied with age. We aimed to explore the age-specific difference in the relationship between new cardiovascular health (CVH) score and arterial stiffness and further detected the age-specific temporal relationships in a prospective cohort study. During a median 4.3 years follow-up, 3757 participants were recruited in this study. A modified AHA "Life's Essential 8" construct (mLE8 with lacking information on diet habits) was used to evaluate CVH. Branchial-ankle pulse wave velocity (baPWV) was measured to assess arterial stiffness. Data were analyzed with logistic regression models, restricted cubic splines (RCS), and cross-lagged path analysis (age < 60 vs. age ≥ 60). In age-stratified analysis, moderate (OR = 2.21, 95% CI 1.11-4.43) and low (OR = 3.37, 95% CI 1.63-7.00) CVH were related with a higher incidence of elevated baPWV compared to high CVH in middle-aged adults, while this association was not detected in older adults. RCS curve showed a steeper linear association between CVH score and elevated baPWV in middle-aged adults than older individuals. In the cross-lagged path analysis, the decline in CVH score preceded the increment in arterial stiffness in middle-aged adults, but they appeared to alter simultaneously in older adults. Our study detected an age-specific difference in the relationship between mLE8 CVH score and elevated baPWV and showed that low CVH preceded alterations of baPWV in middle-aged adults, suggesting the importance of improvement in CVH during the early stage of the lifespan.

Temporal Association Rule Mining: Race-Based Patterns of Treatment-Adverse Events in Breast Cancer Patients Using SEER-Medicare Dataset.

PURPOSE: Disparities in the screening, treatment, and survival of African American (AA) patients with breast cancer extend to adverse events experienced with systemic therapy. However, data are limited and difficult to obtain. We addressed this challenge by applying temporal association rule (TAR) mining using the SEER-Medicare dataset for differences in the association of specific adverse events (AEs) and treatments (TRs) for breast cancer between AA and White women. We considered two categories of cancer care providers and settings: practitioners providing care in the outpatient units of hospitals and institutions and private practitioners providing care in their offices. PATIENTS AN METHODS: We considered women enrolled in the Medicare fee-for-service option at age 65 who qualified by age and not disability, who were diagnosed with breast cancer with attributed patient factors of age and race, marital status, comorbidities, prior malignancies, prior therapy, disease factors of stage, grade, and ER/PR and Her2 status and laterality. We included 141 HCPCS drug J codes for chemotherapy, biotherapy, and hormone therapy drugs, which we consolidated into 46 mechanistic categories and generated AE data. We consolidated AEs from ICD9 codes into 18 categories associated with breast cancer therapy. We applied TAR mining to determine associations between the 46 TR and 18 AE categories in the context of the patient categories outlined. We applied the spark.mllib implementation of the FPGrowth algorithm, a parallel version called PFP. We considered differences of at least one unit of lift as significant between groups. The model's results demonstrated a high overlap between the model's identified TR-AEs associated set and the actual set. RESULTS: Our results demonstrate that specific TR/AE associations are highly dependent on race, stage, and venue of care administration. CONCLUSIONS: Our data demonstrate the usefulness of this approach in identifying differences in the associations between TRs and AEs in different populations and serve as a reference for predicting the likelihood of AEs in different patient populations treated for breast cancer. Our novel approach using unsupervised learning enables the discovery of association rules while paying special attention to temporal information, resulting in greater predictive and descriptive power as a patient's health and life status change over time.