Statistical power for cluster analysis

An Exploratory Analysis of Physical Examination Subtypes in Pediatric Athletes With Concussion

OBJECTIVE

Pediatric athletes with concussion present with a variety of impairments on clinical assessment and require individualized treatment. The Buffalo Concussion Physical Examination is a brief, pertinent clinical assessment for individuals with concussion. The purpose of this study was to identify physical examination subtypes in pediatric athletes with concussion within 2 weeks of injury that are relevant to diagnosis and treatment.

DESIGN

Secondary analysis of a published cohort study and clinician consensus.

SETTING

Three university-affiliated sports medicine centers.

PARTICIPANTS

Two hundred seventy children (14.9 ± 1.9 years).

INDEPENDENT VARIABLES

Orthostatic intolerance, horizontal and vertical saccades, smooth pursuits, vestibulo-ocular reflex, near-point convergence, complex tandem gait, neck range of motion, neck tenderness, and neck spasm.

MAIN OUTCOME MEASURES

Correlations between independent variables were calculated, and network graphs were made. k -means and hierarchical clustering were used to identify clusters of impairments. Optimal number of clusters was assessed. Results were reviewed by experienced clinicians and consensus was reached on proposed subtypes.

RESULTS

Physical examination clusters overlapped with each other, and no optimal number of clusters was identified. Clinician consensus suggested 3 possible subtypes: (1) visio-vestibular (horizontal and vertical saccades, smooth pursuits, and vestibulo-ocular reflex), (2) cervicogenic (neck range of motion and spasm), and (3) autonomic/balance (orthostatic intolerance and complex tandem gait).

CONCLUSIONS

Although we identified 3 physical examination subtypes, it seemed that physical examination findings alone are not enough to define subtypes that are both statistically supported and clinically relevant, likely because they do not include symptoms, assessment of mood or cognitive problems, or graded exertion testing.

Patterns of clinical and imaging presentations in patients with spontaneous intracranial hypotension due to spinal cerebrospinal fluid venous fistula: A single-center retrospective cross-sectional study

OBJECTIVE

To identify distinct clinical or imaging subtypes of spontaneous intracranial hypotension (SIH) due to spinal cerebrospinal fluid (CSF) venous fistula (CVF).

BACKGROUND

Spontaneous intracranial hypotension is classically understood to present clinically with an orthostatic headache and stereotyped brain magnetic resonance imaging (MRI) findings; however, most prior literature examining clinical and brain MRI features of SIH has focused on all types of spinal CSF leaks concurrently. This study aimed to evaluate whether data support the possibility of internally consistent subtypes based on brain imaging features and clinical symptoms analogous to those seen in primary headache syndromes.

METHODS

This retrospective cross-sectional single-institution study included 48 consecutive patients meeting the International Classification of Headache Disorders, 3rd edition criteria for SIH due to CVF. Clinical symptoms, pre-treatment brain MRI, and symptom duration were analyzed. Clinical and MRI data were analyzed to identify patterns and associations between symptoms and imaging findings.

RESULTS

A total of 20 males and 28 females were evaluated, with a mean (standard deviation) age of 61 (10) years. In all, 44/48 (92%) patients experienced headaches, though 18/48 (40%) did not endorse relief when flat, including six of the 48 (13%) with worsening symptoms when flat. In all, 19/48 (40%) patients reported at least one migraine symptom, and six of the 48 (13%) presented with at least one migraine symptom and had no relief when flat. Clinical symptoms clustered primarily into a "classic" presentation consisting of relief when flat, occipital head pain, comorbid neck pain, a pressure/throbbing headache quality, and an "atypical" presentation that was characterized by having several differences: less relief when flat (nine of 22 (41%) vs. 20/23 (87.0%), p = 0.002; odds ratio [OR] 0.110, 95% confidence interval [CI] 0.016-0.53), more frontal head pain (14/22 (64%) vs. one of 23 (4%), p < 0.001; OR 35.0, 95% CI 4.2-1681.0), less neck pain (two of 21 (4.5%) vs. nine of 13 (69.6%), p < 0.001; OR 0.023, 95% CI 0.0005-0.196), and more stabbing/sharp headache quality (nine of 22 (41%) vs. two of 23 (9%), p = 0.017; OR 7.0, 95% CI 1.18-75.9). Brain MRI findings clustered into three groups: those presenting with most imaging findings of SIH concurrently, those with brain sag but less pachymeningeal/venous engorgement, and those with pachymeningeal/venous engorgement but less brain sag.

CONCLUSION

This study highlights the clinical and imaging diversity among patients with SIH due to CVF, challenging the reliance on classic orthostatic headache alone for diagnosis. The findings suggest the existence of distinct SIH subtypes based on clinical and imaging presentations, underscoring the need for comprehensive evaluation in patients with suspected CVF. Future research should further elucidate the relationship between clinical symptoms and imaging findings, aiming to refine diagnostic criteria and enhance understanding of SIH's pathophysiology.

Cluster Analysis Identifies Clinical Phenotypes of Primary Hyperhidrosis

INTRODUCTION

Identifying subgroups of patients with primary hyperhidrosis (PHH) can improve the understanding of the disease pathophysiology. The study objective was to determine the naturally occurring subgroups of patients with PHH based on clinical characteristics.

METHODS

In this retrospective cohort study, data were collected from participants included in a clinical trial. The data were collected between January 2020 and June 2021 from outpatients with PHH attending a dermatologic department in Denmark. Overall, 84 patients with PHH were screened for inclusion in the clinical trial. Of these, 41 met the eligibility criteria. Four participants were excluded because of missing data. The main outcome was the identification of subgroups of patients with PHH using an unsupervised hierarchical cluster analysis.

RESULTS

Overall, 37 patients were included {28 (76.7%) females; median age at inclusion 28.0 (interquartile range [IQR] 24.0-38.3); median body mass index 24.9 (IQR 20.9-27.4); median age of onset 13.0 (IQR 9.5-18.5); and 26 (70.3%) had a familial disposition toward PHH}. Two clusters of 18 and 17 patients were identified. The first cluster had, when compared to the second, a younger age of onset (median age 11.0 [IQR 0-13.0] vs. 17.0 [IQR 15.0-21.0], p = 0.003) and higher sweat rates on gravimetry (median 175.0 [IQR 121.2-252.5] vs. 40.0 [IQR 20.0-60.0] milligrams of sweat/5 min, p < 0.001) and transepidermal water loss (median 93.7 [IQR 91.2-97.8] vs. 59.0 [IQR 44.4-73.2] g/m2/h, p < 0.001). No differences were observed for the other variables.

CONCLUSIONS

This study identifies 2 subgroups of patients with PHH. The patients with an onset of PHH during childhood had a substantially higher sweat and evaporation rate in adulthood than those with an onset during adolescence. These findings may imply a changed understanding of the pathophysiology of PHH, by indicating that an early disease onset can lead to a worse disease course.

Neurobehavioral outcomes of preterm infants: toward a holistic approach

Children born very preterm (VPT; <32 weeks gestation) are at high risk for adverse developmental outcomes, yet not all children fare poorly. Some children born VPT have few or no neurodevelopmental concerns, while others have significant impairment in one or more domains. Historically, research has taken a variable-centered approach, reporting rates of impairment in single domains or single assessments as if they are independent of one another. More recently, child-centered approaches have been applied to studying outcomes for preterm children. Child-centered analyses allow us to integrate across multiple measures and domains to more holistically describe groups of children who vary in terms of the severity and co-occurrence of neurodevelopmental and behavioral strengths and difficulties. In this review, we will summarize current research that has taken a "whole child" approach to describing neurodevelopmental outcomes following preterm birth while highlighting the implications of this approach for research and clinical practice. We end by describing unanswered questions and areas that are in need of future research. IMPACT: Most research on outcomes for children born very preterm has reported rates of impairment in single domains or on single instruments. Recent findings suggest that a child-centered approach can identify unique phenotypes composed of multiple measures and domains that may be of clinical interest. A better understanding of unique combinations of neurodevelopmental and behavioral strengths and weaknesses could improve post-NICU care by emphasizing a personalized approach to intervention and treatment.

Mechanisms of exercise intervention in type 2 diabetes: a bibliometric and visualization analysis based on CiteSpace

Objective

Type 2 diabetes (T2D) is a common chronic metabolic disease, and its prevalence is increasing globally. Exercise is crucial for T2D management, yet many aspects of its mechanisms remain unclear. This study employs CiteSpace to reveal research hotspots and frontier issues in exercise intervention for T2D.

Method

A literature review spanning from January 1, 2013 to December 31, 2022, was conducted using the Web of Science Core Collection (WoSCC), with keywords including "exercise," "type 2 diabetes," and "mechanisms." We analyzed network diagrams generated by CiteSpace, which depicted relationships among countries, authors, and keywords.

Results

This study includes 1,210 English papers from 555 journals, affiliated with 348 institutions across 80 countries/regions. Notably, the United States, China, and the United Kingdom account for nearly half of all publications. The University of Copenhagen leads in publication volume, followed by Harvard Medical School and the University of Colorado. Key authors include Kirwan, John P (Case Western Reserve University), Malin, Steven K (Rutgers University), and Pedersen, Bente Klarlund (University of Copenhagen). Based on co-occurrence analysis of keywords, it is evident that terms such as "disease," "glucagon-like peptide 1," and "cardiovascular risk factor" exhibit high intermediary centrality.

Conclusion

The analysis highlights ongoing investigations into molecular mechanisms, such as β-cell function enhancement, exerkines, and epigenetic mechanisms. Emerging areas include exercise response heterogeneity, circadian rhythm regulation, transcription factors, neurotrophic factors, and mitochondrial function. Future studies should prioritize understanding interactions between different exercise mechanisms and optimizing exercise prescriptions for T2D. Exercise prescriptions are crucial for effective interventions. Collaboration between countries and institutions is essential to understand the influences of different genetic backgrounds and environmental factors. Currently, a combination of aerobic and resistance training is considered the optimal form of exercise. However, considering time efficiency, high-intensity interval training (HIIT) has gained widespread attention and research due to its ability to achieve similar exercise effects in a shorter duration. Additionally, circadian rhythm regulation may affect the exercise outcomes of diabetic individuals at different times of the day, particularly concerning the specific types, doses, and intensities used for precision intervention in T2D.

Machine learning: a new era for cardiovascular pregnancy physiology and cardio-obstetrics research

The maternal cardiovascular system undergoes functional and structural adaptations during pregnancy and postpartum to support increased metabolic demands of offspring and placental growth, labor, and delivery, as well as recovery from childbirth. Thus, pregnancy imposes physiological stress upon the maternal cardiovascular system, and in the absence of an appropriate response it imparts potential risks for cardiovascular complications and adverse outcomes. The proportion of pregnancy-related maternal deaths from cardiovascular events has been steadily increasing, contributing to high rates of maternal mortality. Despite advances in cardiovascular physiology research, there is still no comprehensive understanding of maternal cardiovascular adaptations in healthy pregnancies. Furthermore, current approaches for the prognosis of cardiovascular complications during pregnancy are limited. Machine learning (ML) offers new and effective tools for investigating mechanisms involved in pregnancy-related cardiovascular complications as well as the development of potential therapies. The main goal of this review is to summarize existing research that uses ML to understand mechanisms of cardiovascular physiology during pregnancy and develop prediction models for clinical application in pregnant patients. We also provide an overview of ML platforms that can be used to comprehensively understand cardiovascular adaptations to pregnancy and discuss the interpretability of ML outcomes, the consequences of model bias, and the importance of ethical consideration in ML use.

Cluster analysis of prolonged grief, posttraumatic stress, and depression symptoms in bereaved asylum seekers and refugees

Background: Refugees and asylum seekers (ASRs) are frequently exposed to loss in addition to a variety of other stressors and often display high levels of various psychological symptoms.Objective: The study aimed to primarily determine clusters of prolonged grief disorder (PGD), posttraumatic stress disorder (PTSD), and depression symptoms in bereaved ASRs and secondly identify predictors of cluster membership. Sociodemographic  - and flight-related variables were investigated in exploratory analyses.Method: ASRs in Germany (N = 92) with interpersonal loss exposure, i.e. at least one missing or deceased relative or friend, were assessed with interview-based questionnaires for PGD, PTSD, and depressive symptoms. We used k-means cluster analysis to distinguish symptom profiles and logistic regression analyses to identify predictors of cluster membership.Results: We found a three-cluster-solution. The PGD-cluster (30%) was characterised predominantly by PGD symptoms, while the PGD/PTSD-cluster (32%) had high PGD and PTSD and moderate depressive symptoms. The resilient cluster (38%) showed low symptoms overall. insecure residence status predicted membership in the PGD and PGD/PTSD clusters relative to the resilient cluster, whilst higher attachment anxiety predicted membership in the PGD/PTSD cluster relative to the other clusters. Explorative analysis revealed duration of stay as a significant predictor.Conclusion: Findings can extend the current knowledge about different symptom profiles among bereaved ASRs in Europe. Insights to attachment  - and migration-related variables distinguishing between these profiles offer starting points for interventions.

Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs

Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51-80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions.

Exploring emotional distress symptom clusters in young adults with childhood traumatic brain injury

BACKGROUND

Depression, anxiety, and stress are persistent and co-occurring symptoms in survivors of childhood traumatic brain injury (TBI), and often impact on health-related quality of life (HRQoL). This paper explored emotional distress symptom clusters and associated factors in young adults with childhood TBI.

METHODS

We included 54 young adults who sustained mild (n = 14), moderate (n = 27), and severe (n = 13) childhood TBI, at 20 years post-injury. The Depression Anxiety Stress Scale was administered. Cluster group membership was identified using two-step clustering and hierarchical clustering methods, and associated factors were assessed with multiple regression models.

RESULTS

Two symptom cluster groups were identified, including a No Distress (n = 66%) and an Elevated Distress (n = 33%) group, with the latter showing significantly higher symptoms of depression, anxiety, and stress (all p < .001). Elevated Distress group membership was linked to tobacco use and poor sleep quality, while poor HRQoL was associated with younger age at injury and Elevated Distress group membership.

CONCLUSIONS

Using cluster methodology, we showed that one-third of young adults with childhood TBI had elevated emotional distress symptoms. This underscores the complex emotional profile of this subgroup and the need for assessment, analysis, and treatment methods that target a range of symptoms rather than relying on single-diagnostic protocols.

ABBREVIATIONS

ANOVA: Analysis of Variance; CT: Computed Tomography; DASS: Depression Anxiety Stress Scale; GCS: Glasgow Coma Scale; HREC: Human Research Ethics Committee; HRQoL: Health-Related Quality of Life; IBM: International Business Machines Corporation; MRI: Magnetic Resonance Imaging; PTA: Post-Traumatic Amnesia; QoL: Quality of Life; QOLIBRI: Quality of Life after Brain Injury Scale; REDCap: Research Electronic Data Capture; SES: Socioeconomic Status; SPSS: Statistical Package for the Social Sciences; TBI: Traumatic Brain Injury.

Clustering of Gastrointestinal Microorganisms in Human Stool Samples from Ghana

The study was conducted to identify cluster patterns of enteric microorganisms with potential etiological relevance for infectious gastroenteritis in stool samples of individuals from Ghana, which is a known high-endemicity setting for infectious gastroenteritis. These patterns were compared to previous observations with specimens from Colombian indigenous people in order to assess potentially stable clustering for temporally and spatially distinct populations from high-endemicity regions. By doing so, the study aimed to identify stable clusters as markers of microbial interaction with potential importance for etiological relevance assignment in cases of multiple enteric pathogen detections. Stool samples from 1569 Ghanaian individuals (875 from HIV patients, 30 from HIV-negative control adult patients, and 644 from children < 2 years of age) were assessed for enteric microorganisms by applying real-time PCR. As a result, nucleic acids of bacterial microorganisms were most frequently detected, followed by protozoa, microsporidia, and helminths. Interestingly, the cluster assessment confirmed interaction patterns known from the previous analysis with Colombian indigenous people, demonstrating a high likelihood of Blastocystis hominis for clustering with other microorganisms and a prominent, potentially mediating role of Dientamoeba fragilis for microbial interactions within the clusters. In conclusion, the assessment confirmed conserved clustering of enteric microorganisms with potential etiological relevance for human infectious gastroenteritis over geographically distinct high-endemicity settings. Furthermore, the composition of abundant microorganisms is more important than regional factors for the determination of the interplay of enteric microorganisms in the human gut. Thereby, some microbial pathogens and commensals seem more susceptible to a changing microbial composition in the human gut than others.

Sex-Moderated Divergence between Adult Child and Parental Dietary Behavior Patterns in Relation to Body Mass Condition-Evaluating the Mediating Role of Physical Activity: A Cross-Sectional Study

The main objective of this study was to explore the dietary behaviors of parents and their adult children, focusing on patterns, potential intrinsic and extrinsic predictors of body mass, and determinants of becoming overweight. Non-probability, cross-sectional sampling was used to select participants from a university student population. Young adults (19-21 years of age, n = 144) and their parents were examined. The data of those family pairs with complete sets of results were used. Dietary patterns and physical activity were assessed with questionnaires (QEB and IPAQ), and body height, weight measurements, and body mass indexes were calculated. A cophylogenetic approach with tanglegrams and heatmaps was used to study patterns, while predictors of body mass index were identified using multiple linear regression, stepwise logistic regression, and mediation analysis procedures. Cophenetic statistics confirmed significant incongruence between fathers and sons, confirmed by Baker's Gamma correlation (rBG = 0.23, p = 0.021), and mothers and daughters (rBG = 0.26, p = 0.030). The relationships between the dietary patterns of the fathers and daughters, as well as mothers and sons, were of medium strength (rBG = 0.33, p = 0.032, rBG = 0.43, p = 0.031; respectively). Most of the patterns were mixed. Fast food, fried meals, alcoholic drinks, energy drinks, and sweetened beverages were associated significantly with being overweight. Significant intrinsic predictors of excessive weight in young adults were sex (b = 2.31, p < 0.001), PA (b = -0.02, p < 0.001), and eating fermented milk and curd cheese (b = -0.55, p = 0.024), while extrinsic (parental) predictors included eating fast food and fried meals (b = -0.44, p = 0.049). Both physical activity and dietary behaviors independently determined the sons' overweight status (b = -1.25, p = 0.008; b = -0.04, p < 0.001; respectively); while only PA did in daughters (b = -0.04, p < 0.001). No mediating effects of physical activity were observed. Adult children and parental dietary patterns were divergent, reflecting the influence of multiple factors on a child's dietary habits. However, this divergence is moderated by sex. Reciprocal interactions between dietary intake-particularly positive dyads such as fruits and vegetables, fermented milk, and curd cheese-and physical activity significantly impacted children's body mass index (BMI). The study of dietary patterns in conjunction with physical activity (both as independent determinants), particularly in relation to the link between overweight/obese children and overweight/obese parents, presents a separate challenge.

Clustering of methamphetamine users based on personality characteristics and self-efficacy in the west of Iran

With the substantial increase in the use of stimulants, especially methamphetamine, in recent years, the present study aimed to cluster methamphetamine users based on personality traits and self-efficacy, and compare their mental health, sleep quality, and the risk of relapse in the identified clusters. This cross-sectional study was conducted through convenience sampling on 501 methamphetamine users in addiction treatment centers in Kermanshah, western Iran. The data were collected using the Schwarzer General Self-Efficacy Scale, Zuckerman-Kuhlman Personality Questionnaire, Goldberg and Hiller General Health Questionnaire (GHQ), Zuckerman-Kuhlman Personality Questionnaire, and Stimulant Relapse Risk Scale (SRRS). A total of 501 methamphetamine users were distinguished into three clusters with frequencies of 111 (22.2%), 298 (59.5%), and 92 (18.4%) members through hierarchical cluster analysis. The participants in the first cluster were characterized by low self-efficacy, high neuroticism, sensation seeking, and aggressiveness, along with low extroversion and activity, low positive health, high negative health, low sleep quality, and high risk of drug relapse. The participants in the second cluster reported moderate levels of self-efficacy, neuroticism, sensation seeking, activity, and aggressiveness, high extroversion, and moderate levels of mental health, sleep quality, and the risk of relapse. Moreover, the participants in the third cluster reported the highest level of self-efficacy, the lowest level of neuroticism, sensation seeking, and aggressiveness, moderate extroversion and high activity, low relapse risk, high sleep quality, as well as high positive and low negative health symptoms. The third cluster was significantly different from the other two clusters in terms of the mentioned factors. The findings of this study suggest that low self-efficacy and the presence of neuroticism, sensation seeking, and high aggressiveness contribute to reduced mental health and sleep quality, as well as an increased risk of relapse in methamphetamine users.

Burden and positive aspects of caregiving: cluster profiles of dementia caregiving experiences

OBJECTIVES

Although caregiver burden is common in the context of dementia caregiving, the caregiving role is linked to beneficial outcomes too. Individuals reporting higher positive aspects of caregiving tend to exhibit lower burden relative to those reporting few. The goal of this retrospective review of outpatient memory clinic medical records was to demonstrate whether and how constructs of burden and positive aspects of caregiving coexist within individual caregivers, and to explore potential contributors to caregiver profiles created based upon these constructs.

METHOD

Cluster analyses were conducted on 1160 caregivers from an initial intake interview meeting criteria on primary measures of Positive Aspects of Caregiving and the Zarit Burden Interview and repeated with 225 caregivers meeting inclusion criteria on all measures. Samples were compared for similarity, and the smaller sample (n = 225) was deemed appropriately representative. Multinomial logistic regressions examined cluster predictors in sample with 225 caregivers.

RESULTS

Results suggested a three-cluster solution: a High Burden group, a High Positive Experiences group, and a Low-Moderate Experiences group showing low burden and moderate positive experiences. Greater behavioral problems predicted belonging to the High Burden cluster. Greater care recipient dependence predicted belonging to the High Positive Experiences cluster while greater independence predicted the Low-Moderate Experiences cluster.

CONCLUSION

Findings suggest that burden and positive aspects of caregiving do not simultaneously present in caregivers at high levels. Supportive caregiver interventions might be tailored to profiles demonstrated here. Future research should investigate other potential contributors to experiences of burden and positive aspects of caregiving.

Perceptual heterogeneity in developmental prosopagnosia is continuous, not categorical

Developmental prosopagnosia (DP) is associated with considerable perceptual heterogeneity, though the nature of this heterogeneity and whether there are discrete subgroups versus continuous deficits remains unclear. Bennetts et al. (2022) recently found that holistic versus featural processing deficits distinguished discrete DP subgroups, but their sample was relatively small (N = 37), and subgroups were defined using a single task. To characterize perceptual heterogeneity in DPs more comprehensively, we administered a broad face perception battery to a large sample of 109 DPs and 134 controls, including validated measures of face matching (Cambridge Face Perception Test - CFPT, Computerized Benton Facial Recognition Test, Same/Different Face Matching Task), holistic processing (Part-Whole Task), and feature processing (Georges Task and Part-Whole part trials). When examining face matching measures, DPs exhibited a similar distribution of performance as controls, though shifted towards impairment by an average of 1.4 SD. We next applied Bennetts (2022) hierarchical clustering approach and k-means clustering to the CFPT upright, inverted, and inversion index measures, similarly finding one group of DPs with poorer inverted face performance and another with a decreased face inversion effect (holistic processing). However, these subgroup differences failed to generalize to other measures of feature and holistic processing beyond the CFPT. We finally ran hierarchical and k-means cluster analyses on our larger battery of face matching, feature, and holistic processing measures. Results clearly showed subgroups with generally better versus worse performance across all measures, with the distinction between groups being somewhat arbitrary. Together, these findings support a continuous account of DP perceptual heterogeneity, with performance differing primarily across all aspects of face perception.

Persistent transcriptional changes in cardiac adaptive immune cells following myocardial infarction: New evidence from the re-analysis of publicly available single cell and nuclei RNA-sequencing data sets

INTRODUCTION

Chronic immunopathology contributes to the development of heart failure after a myocardial infarction. Both T and B cells of the adaptive immune system are present in the myocardium and have been suggested to be involved in post-MI immunopathology.

METHODS

We analyzed the B and T cell populations isolated from previously published single cell RNA-sequencing data sets (PMID: 32130914, PMID: 35948637, PMID: 32971526 and PMID: 35926050), of the mouse and human heart, using differential expression analysis, functional enrichment analysis, gene regulatory inferences, and integration with autoimmune and cardiovascular GWAS.

RESULTS

Already at baseline, mature effector B and T cells are present in the human and mouse heart, having increased activity in transcription factors maintaining tolerance (e.g. DEAF1, JDP2, SPI-B). Following MI, T cells upregulate pro-inflammatory transcript levels (e.g. Cd11, Gzmk, Prf1), while B cells upregulate activation markers (e.g. Il6, Il1rn, Ccl6) and collagen (e.g. Col5a2, Col4a1, Col1a2). Importantly, pro-inflammatory and fibrotic transcription factors (e.g. NFKB1, CREM, REL) remain active in T cells, while B cells maintain elevated activity in transcription factors related to immunoglobulin production (e.g. ERG, REL) in both mouse and human post-MI hearts. Notably, genes differentially expressed in post-MI T and B cells are associated with cardiovascular and autoimmune disease.

CONCLUSION

These findings highlight the varied and time-dependent dynamic roles of post-MI T and B cells. They appear ready-to-go and are activated immediately after MI, thus participate in the acute wound healing response. However, they subsequently remain in a state of pro-inflammatory activation contributing to persistent immunopathology.

Syndromic case definitions for lower respiratory tract infection (LRTI) are less sensitive in older age: an analysis of symptoms among hospitalised adults

BACKGROUND

Lower Respiratory Tract Infections (LRTI) pose a serious threat to older adults but may be underdiagnosed due to atypical presentations. Here we assess LRTI symptom profiles and syndromic (symptom-based) case ascertainment in older (≥ 65y) as compared to younger adults (< 65y).

METHODS

We included adults (≥ 18y) with confirmed LRTI admitted to two acute care Trusts in Bristol, UK from 1st August 2020- 31st July 2022. Logistic regression was used to assess whether age ≥ 65y reduced the probability of meeting syndromic LRTI case definitions, using patients' symptoms at admission. We also calculated relative symptom frequencies (log-odds ratios) and evaluated how symptoms were clustered across different age groups.

RESULTS

Of 17,620 clinically confirmed LRTI cases, 8,487 (48.1%) had symptoms meeting the case definition. Compared to those not meeting the definition these cases were younger, had less severe illness and were less likely to have received a SARS-CoV-2 vaccination or to have active SARS-CoV-2 infection. Prevalence of dementia/cognitive impairment and levels of comorbidity were lower in this group. After controlling for sex, dementia and comorbidities, age ≥ 65y significantly reduced the probability of meeting the case definition (aOR = 0.67, 95% CI:0.63-0.71). Cases aged ≥ 65y were less likely to present with fever and LRTI-specific symptoms (e.g., pleurisy, sputum) than younger cases, and those aged ≥ 85y were characterised by lack of cough but frequent confusion and falls.

CONCLUSIONS

LRTI symptom profiles changed considerably with age in this hospitalised cohort. Standard screening protocols may fail to detect older and frailer cases of LRTI based on their symptoms.

Observed and future shifts in climate zone of Borneo based on CMIP6 models

Climate change has significantly altered the characteristics of climate zones, posing considerable challenges to ecosystems and biodiversity, particularly in Borneo, known for its high species density per unit area. This study aimed to classify the region into homogeneous climate groups based on long-term average behavior. The most effective parameters from the high-resolution daily gridded Princeton climate datasets spanning 65 years (1950-2014) were utilized, including rainfall, relative humidity (RH), temperatures (Tavg, Tmin, Tmax, and diurnal temperature range (DTR)), along with elevation data at 0.25° resolution. The FCM clustering method outperformed K-Mean and two Ward's hierarchical methods (WardD and WardD2) in classifying Borneo's climate zones based on multi-criteria assessment, exhibiting the lowest average distance (2.172-2.180) and the highest compromise programming index (CPI)-based correlation ranking among cluster averages across all climate parameters. Borneo's climate zones were categorized into four: 'Wet and cold' (WC) and 'Wet' (W) representing wetter zones, and 'Wet and hot' (WH) and 'Dry and hot' (DH) representing hotter zones, each with clearly defined boundaries. For future projection, EC-Earth3-Veg ranked first for all climate parameters across 961 grid points, emerging as the top-performing model. The linear scaling (LS) bias-corrected EC-Earth3-Veg model, as shown in the Taylor diagram, closely replicated the observed datasets, facilitating future climate zone reclassification. Improved performance across parameters was evident based on MAE (35.8-94.6%), MSE (57.0-99.5%), NRMSE (42.7-92.1%), PBIAS (100-108%), MD (23.0-85.3%), KGE (21.1-78.1%), and VE (5.1-9.1%), with closer replication of empirical probability distribution function (PDF) curves during the validation period. In the future, Borneo's climate zones will shift notably, with WC elongating southward along the mountainous spine, W forming an enclave over the north-central mountains, WH shifting northward and shrinking inland, and DH expanding northward along the western coast. Under SSP5-8.5, WC is expected to expand by 39% and 11% for the mid- and far-future periods, respectively, while W is set to shrink by 46%. WH is projected to expand by 2% and 8% for the mid- and far-future periods, respectively. Conversely, DH is expected to expand by 43% for the far-future period but shrink by 42% for the mid-future period. This study fills a gap by redefining Borneo's climate zones based on an increased number of effective parameters and projecting future shifts, utilizing advanced clustering methods (FCM) under CMIP6 scenarios. Importantly, it contributes by ranking GCMs using RIMs and CPI across multiple climate parameters, addressing a previous gap in GCM assessment. The study's findings can facilitate cross-border collaboration by providing a shared understanding of climate dynamics and informing joint environmental management and disaster response efforts.

Profiles of Permanent Supportive Housing Residents Related to Their Housing Conditions, Service Use, and Associated Sociodemographic and Clinical Characteristics

As permanent supportive housing (PSH) is the main strategy promoted to reduce homelessness, understanding how PSH resident profiles may be differentiated is crucial to the optimization of PSH implementation - and a subject that hasn't been studied yet. This study identified PSH resident profiles based on their housing conditions and service use, associated with their sociodemographic and clinical characteristics. In 2020-2021, 308 PSH residents from Quebec (Canada) were interviewed, with K-means cluster analysis produced to identify profiles and subsequent analyses to compare profiles and PSH resident characteristics. Of the three profiles identified, Profiles 1 and 2 (70% of sample) showed moderate or poor housing, neighborhood, and health conditions, and moderate or high unmet care needs and service use. Besides their "moderate" conditions, Profile 1 residents (52%) reported being in PSH for more than two years and being less educated. With the "worst" conditions and high service use, Profile 2 (18%) included younger individuals, while Profile 3 (30%) showed the "best" conditions and integrated individuals with more protective determinants (e.g., few in foster care, homelessness at older age, more self-esteem), with a majority living in single-site PSH and reporting higher satisfaction with support and community-based services. Profiles 1 and 2 may be provided with more psychosocial, crisis, harm reduction, and empowerment interventions, and peer helper support. Profile 2 may benefit from more intensive and integrated care, and better housing conditions. Continuous PSH may be sustained for Profile 3, with regular monitoring of service satisfaction and met needs.

Sleep quality relates to language impairment in children with autism spectrum disorder without intellectual disability

OBJECTIVES

This study aimed to identify sleep quality profiles of children with autism spectrum disorder (ASD), to compare these profiles with those of typically developing (TD) children, and to verify whether there are differences between them in terms of language skills.

METHODS

We evaluated the sleep quality and language skills of 47 children with ASD without intellectual disability (ID) and 32 children with TD. Using a hierarchical cluster analysis, we identified two sleep quality ASD profiles (poor and good). We then performed a series of MANCOVAs and ANOVAs to compare the sleep quality and language skills of the two ASD clusters and the TD group.

RESULTS

A main group effect (TD, "poor" cluster, and "good" cluster) was found in the total sleep quality and all its dimensions. Significant differences were revealed between the "good" and "poor" clusters in the total structural language score (F1,46 = 10.75, p < 0.001) and three of its subscales (speech: F1,46 = 9.19, p < 0.001; syntax, F1,46 = 8.61, p = 0.001; coherence: F1,46 = 11.36, p < 0.001); the total pragmatic language score (F1,46 = 7.00, p = 0.001) and three of its subscales (inappropriate initiation: F1,46 = 8.02, p = 0.001; use of context: F1,46 = 8.07, p = 0.001; nonverbal communication: F1,46 = 7.35, p = 0.001); and the social relations score (F1,46 = 9.97, p = 0.003).

CONCLUSIONS

Sleep quality in children with ASD (especially a subgroup) is worse than in children with TD. There is an association between sleep quality and language skills, both at the pragmatic and structural levels.

Crown forms and gingival phenotypes: Insights from a diverse Asian population

Objective

This study aimed to classify the crowns of maxillary central incisors into distinct categories and to examine the associations between these crown forms and morphometric characteristics in an ethnically diverse Asian population. This is significant for the treatment planning and management of cases, especially for the anterior teeth, from the restorative and aesthetic points of view.

Method and Materials

Clinical measurements and photographic data were collected from 160 participants, comprising students, staff, and patients of the Faculty of Dentistry, Universiti Kebangsaan Malaysia. The crown length, crown width, contact surface, papilla height, papilla fill, keratinized mucosa width, and gingival tissue thickness were measured. Cluster analyses were performed to identify the different crown form categories and corresponding characteristics.

Results

The mean crown width measured 7.093 ± 0.637 mm, while the mean crown length was 10.209 ± 0.966 mm. Three crown-form clusters were identified: triangular (50 %), square/tapered (23.1 %), and square (26.9 %) shapes. The triangular cluster had a significantly higher mean papilla height (4.64 mm ± 0.818) and the highest incidence of incomplete papilla fill (17.5 %). The chi-squared test showed a significant difference in crown forms between the different ethnicities, χ2 (2, 160) = 0.033.

Conclusion

Within this diverse Asian population, the crown form demonstrates three clusters: triangular, square/tapered, and square, characterized by a notably small average crown width and crown length. Most participants predominantly exhibited triangular crown forms with reduced crown width, crown length, and crown width/ crown length ratio. Furthermore, noticeable variations in crown forms and their morphometric attributes were observed among the three ethnic groups: Malays, Chinese, and Indians.

Understanding Wellbeing Profiles According to White Matter Structural Connectivity Sub-types in Early Adolescents: The First Hundred Brains Cohort from the Longitudinal Adolescent Brain Study

Wellbeing is protective against the emergence of psychopathology. Neurobiological markers associated with mental wellbeing during adolescence are important to understand. Limited research has examined neural networks (white matter tracts) and mental wellbeing in early adolescence specifically. A cross-sectional diffusion tensor imaging analysis approach was conducted, from the Longitudinal Adolescent Brain study, First Hundred Brains cohort (N = 99; 46.5% female; Mage = 13.01, SD = 0.55). Participants completed self-report measures including wellbeing, quality-of-life, and psychological distress. Potential neurobiological profiles using fractional anisotropy, axial, and radial diffusivity were determined via a whole brain voxel-wise approach, and hierarchical cluster analysis of fractional anisotropy values, obtained from 21 major white matter tracts. Three cluster groups with significantly different neurobiological profiles were distinguished. No significant differences were found between the three cluster groups and measures of wellbeing, but two left lateralized significant associations between white matter tracts and wellbeing measures were found. These results provide preliminary evidence for potential neurobiological markers of mental health and wellbeing in early adolescence and should be tracked longitudinally to provide more detailed and robust findings.

DNA-PK and ATM drive phosphorylation signatures that antagonistically regulate cytokine responses to herpesvirus infection or DNA damage

The DNA-dependent protein kinase, DNA-PK, is an essential regulator of DNA damage repair. DNA-PK-driven phosphorylation events and the activated DNA damage response (DDR) pathways are also components of antiviral intrinsic and innate immune responses. Yet, it is not clear whether and how the DNA-PK response differs between these two forms of nucleic acid stress-DNA damage and DNA virus infection. Here, we define DNA-PK substrates and the signature cellular phosphoproteome response to DNA damage or infection with the nuclear-replicating DNA herpesvirus, HSV-1. We establish that DNA-PK negatively regulates the ataxia-telangiectasia-mutated (ATM) DDR kinase during viral infection. In turn, ATM blocks the binding of DNA-PK and the nuclear DNA sensor IFI16 to viral DNA, thereby inhibiting cytokine responses. However, following DNA damage, DNA-PK enhances ATM activity, which is required for IFN-β expression. These findings demonstrate that the DDR autoregulates cytokine expression through the opposing modulation of DDR kinases.

Bibliometric Analysis of Development Trends and Research Hotspots in the Study of Data Mining in Nursing Based on CiteSpace

Backgrounds

With the advent of the big data era, hospital information systems and mobile care systems, among others, generate massive amounts of medical data. Data mining, as a powerful information processing technology, can discover non-obvious information by processing large-scale data and analyzing them in multiple dimensions. How to find the effective information hidden in the database and apply it to nursing clinical practice has received more and more attention from nursing researchers.

Aim

To look over the articles on data mining in nursing, compiled research status, identified hotspots, highlighted research trends, and offer recommendations for how data mining technology might be used in the nursing area going forward.

Methods

Data mining in nursing publications published between 2002 and 2023 were taken from the Web of Science Core Collection. CiteSpace was utilized for reviewing the number of articles, countries/regions, institutions, journals, authors, and keywords.

Results

According to the findings, the pace of data mining in nursing progress is not encouraging. Nursing data mining research is dominated by the United States and China. However, no consistent core group of writers or organizations has emerged in the field of nursing data mining. Studies on data mining in nursing have been increasingly gradually conducted in the 21st century, but the overall number is not large. Institution of Columbia University, journal of Cin-computers Informatics Nursing, author Diana J Wilkie, Muhammad Kamran Lodhi, Yingwei Yao are most influential in nursing data mining research. Nursing data mining researchers are currently focusing on electronic health records, text mining, machine learning, and natural language processing. Future research themes in data mining in nursing most include nursing informatics and clinical care quality enhancement.

Conclusion

Research data shows that data mining gives more perspectives for the growth of the nursing discipline and encourages the discipline's development, but it also introduces a slew of new issues that need researchers to address.

Investigating the Influence of Heavy Metals and Environmental Factors on Metabolic Syndrome Risk Based on Nutrient Intake: Machine Learning Analysis of Data from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES)

This study delves into the complex interrelations among nutrient intake, environmental exposures (particularly to heavy metals), and metabolic syndrome. Utilizing data from the Korea National Health and Nutrition Examination Survey (KNHANES), machine learning techniques were applied to analyze associations in a cohort of 5719 participants, categorized into four distinct nutrient intake phenotypes. Our findings reveal that different nutrient intake patterns are associated with varying levels of heavy metal exposure and metabolic health outcomes. Key findings include significant variations in metal levels (Pb, Hg, Cd, Ni) across the clusters, with certain clusters showing heightened levels of specific metals. These variations were associated with distinct metabolic health profiles, including differences in obesity, diabetes prevalence, hypertension, and cholesterol levels. Notably, Cluster 3, characterized by high-energy and nutrient-rich diets, showed the highest levels of Pb and Hg exposure and had the most concerning metabolic health indicators. Moreover, the study highlights the significant impact of lifestyle habits, such as smoking and eating out, on nutrient intake phenotypes and associated health risks. Physical activity emerged as a critical factor, with its absence linked to imbalanced nutrient intake in certain clusters. In conclusion, our research underscores the intricate connections among diet, environmental factors, and metabolic health. The findings emphasize the need for tailored health interventions and policies that consider these complex interplays, potentially informing future strategies to combat metabolic syndrome and related health issues.

Clustering analysis of lipoprotein profiles to identify subtypes of hypertriglyceridemia in Miniature Schnauzers

BACKGROUND

Hypertriglyceridemia (HTG) is prevalent in Miniature Schnauzers, predisposing them to life-threatening diseases. Varied responses to management strategies suggest the possibility of multiple subtypes.

HYPOTHESIS/OBJECTIVE

To identify and characterize HTG subtypes in Miniature Schnauzers through cluster analysis of lipoprotein profiles. We hypothesize that multiple phenotypes of primary HTG exist in this breed.

ANIMALS

Twenty Miniature Schnauzers with normal serum triglyceride concentration (NTG), 25 with primary HTG, and 5 with secondary HTG.

METHODS

Cross-sectional study using archived samples. Lipoprotein profiles, generated using continuous lipoprotein density profiling, were clustered with hierarchical cluster analysis. Clinical data (age, sex, body condition score, and dietary fat content) was compared between clusters.

RESULTS

Six clusters were identified. Dogs with primary HTG were dispersed among 4 clusters. One cluster showed the highest intensities for triglyceride-rich lipoprotein (TRL) and low-density lipoprotein (LDL) fractions and also included 4 dogs with secondary HTG. Two clusters had moderately high TRL fraction intensities and low-to-intermediate LDL intensities. The fourth cluster had high LDL but variable TRL fraction intensities with equal numbers of NTG and mild HTG dogs. The final 2 clusters comprised only NTG dogs with low TRL intensities and low-to-intermediate LDL intensities. The clusters did not appear to be driven by differences in the clinical data.

CONCLUSIONS AND CLINICAL IMPORTANCE

The results of this study support a spectrum of lipoprotein phenotypes within Miniature Schnauzers that cannot be predicted by triglyceride concentration alone. Lipoprotein profiling might be useful to determine if subtypes have different origins, clinical consequences, and response to treatment.

Phenotypes and Lung Microbiota Signatures of Immunocompromised Patients with Pneumonia-Related Acute Respiratory Distress Syndrome

Objective

We aim to identify the clinical phenotypes of immunocompromised patients with pneumonia-related ARDS, to investigate the lung microbiota signatures and the outcomes of different phenotypes, and finally, to develop a machine learning classifier for a specified phenotype.

Methods

This prospective study included immunocompromised patients with pneumonia-related ARDS. We identified phenotypes using hierarchical clustering to analyze clinical variables and serum cytokine levels. We then compared outcomes and lung microbiota signatures between phenotypes. Based on lung microbiota markers, we developed a random forest classifier for a specified phenotype with worse outcomes.

Results

This study included 92 patients, who were divided into three phenotypes, namely "type α" (N = 33), "type β" (N = 12), and "type γ" (N = 47). Compared to type α or type β, patients with type γ had no obvious inflammatory presentation and had significantly lower IL-6 levels and more severe oxygenation failure. Type γ was also related to higher 30-day mortality and lower ventilator free days. The microbiota signatures of type γ were characterized by lower alpha diversity and distinct compositions than those of other patients. We developed a lung microbiota-derived random forest model to differentiate patients with type γ from other phenotypes.

Conclusion

Immunocompromised patients with pneumonia-related ARDS can be clustered into three clinical phenotypes, namely type α, type β, and type γ. Phenotypes were distinguished from each other with different outcomes and lung microbiota signatures. Type γ, which was characterized by insufficient inflammation response and worse outcomes, can be detected with a random forest model based on lung microbiota markers.

Mapping neurodevelopmental diversity in executive function

Executive function, an umbrella term used to describe the goal-directed regulation of thoughts, actions, and emotions, is an important dimension implicated in neurodiversity and established malleable predictor of multiple adult outcomes. Neurodevelopmental differences have been linked to both executive function strengths and weaknesses, but evidence for associations between specific profiles of executive function and specific neurodevelopmental conditions is mixed. In this exploratory study, we adopt an unsupervised machine learning approach (self-organising maps), combined with k-means clustering to identify data-driven profiles of executive function in a transdiagnostic sample of 566 neurodivergent children aged 8-18 years old. We include measures designed to capture two distinct aspects of executive function: performance-based tasks designed to tap the state-like efficiency of cognitive skills under optimal conditions, and behaviour ratings suited to capturing the trait-like application of cognitive control in everyday contexts. Three profiles of executive function were identified: one had consistent difficulties across both types of assessments, while the other two had inconsistent profiles of predominantly rating- or predominantly task-based difficulties. Girls and children without a formal diagnosis were more likely to have an inconsistent profile of primarily task-based difficulties. Children with these different profiles had differences in academic achievement and mental health outcomes and could further be differentiated from a comparison group of children on both shared and profile-unique patterns of neural white matter organisation. Importantly, children's executive function profiles were not directly related to diagnostic categories or to dimensions of neurodiversity associated with specific diagnoses (e.g., hyperactivity, inattention, social communication). These findings support the idea that the two types of executive function assessments provide non-redundant information related to children's neurodevelopmental differences and that they should not be used interchangeably. The findings advance our understanding of executive function profiles and their relationship to behavioural outcomes and neural variation in neurodivergent populations.

Neuroimaging and Biosample Collection in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data

BACKGROUND

The Toronto Adolescent and Youth (TAY) Cohort Study will characterize the neurobiological trajectories of psychosis spectrum symptoms, functioning, and suicidality (i.e., suicidal thoughts and behaviors) in youth seeking mental health care. Here, we present the neuroimaging and biosample component of the protocol. We also present feasibility and quality control metrics for the baseline sample collected thus far.

METHODS

The current study includes youths (ages 11-24 years) who were referred to child and youth mental health services within a large tertiary care center in Toronto, Ontario, Canada, with target recruitment of 1500 participants. Participants were offered the opportunity to provide any or all of the following: 1) 1-hour magnetic resonance imaging (MRI) scan (electroencephalography if ineligible for or declined MRI), 2) blood sample for genomic and proteomic data (or saliva if blood collection was declined or not feasible) and urine sample, and 3) heart rate recording to assess respiratory sinus arrhythmia.

RESULTS

Of the first 417 participants who consented to participate between May 4, 2021, and February 2, 2023, 412 agreed to participate in the imaging and biosample protocol. Of these, 334 completed imaging, 341 provided a biosample, 338 completed respiratory sinus arrhythmia, and 316 completed all 3. Following quality control, data usability was high (MRI: T1-weighted 99%, diffusion-weighted imaging 99%, arterial spin labeling 90%, resting-state functional MRI 95%, task functional MRI 90%; electroencephalography: 83%; respiratory sinus arrhythmia: 99%).

CONCLUSIONS

The high consent rates, good completion rates, and high data usability reported here demonstrate the feasibility of collecting and using brain imaging and biosamples in a large clinical cohort of youths seeking mental health care.

An Index for Evaluating Exercise Capacity Improvement After Cardiac Rehabilitation in Patients After Myocardial Infarction

OBJECTIVE

We investigated relationships among predictors of improvement in exercise capacity after cardiac rehabilitation programs in patients after acute myocardial infarction.

METHODS

We carried out a secondary analysis of data from 41 patients with a left ventricular ejection fraction ≥ 40% who underwent cardiac rehabilitation after the first myocardial infarction. Participants were assessed using a cardiopulmonary exercise test and stress echocardiography. A cluster analysis was performed, and the principal components were analyzed.

RESULTS

Two distinct clusters with significantly different ( P = .005) proportions of response to treatment (peak VO 2 ≥ 1 mL/kg/min) were identified among patients. The first principal component explained 28.6% of the variance. We proposed an index composed of the top 5 variables from the first component to represent the improvement in exercise capacity. The index was the average of scaled O 2 uptake and CO 2 output at peak exercise, minute ventilation at peak, load achieved at peak exercise, and exercise time. The optimal cutoff for the improvement index was 0.12, which outperformed the peak VO 2 ≥ 1 mL/kg/min criterion in recognizing the clusters, with a C-statistic of 91.7% and 72.3%, respectively.

CONCLUSION

The assessment of change in exercise capacity after cardiac rehabilitation could be improved using the composite index.

Behavioral, physiological, and genetic drivers of coping in a non-human primate

Animals experience stressful situations, from predation to social conflicts, but mostly deal with them successfully. This adaptive mechanism, coping, reduces the adverse effects of stressors, and its failure may result in reduced fitness. Substantial inter-individual variation in coping is observed, yet little is known about how behavioral, physiological and genetic drivers regulate coping holistically and contribute to such variations. We assessed behavioral coping styles (n=30), emotional arousal (n=12), and personalities (n=32) of long-tailed macaques (Macaca fascicularis) and also investigated the association of coping with a valine/methionine polymorphism encoded by a critical human stress regulatory gene, catechol-O-methyltransferase (COMT) (n=26). Personality and the human equivalent COMT Val/Met polymorphism were associated with "nonaggression-based" and "aggression-based" coping styles. Compared to nonaggression-based, aggression-based copers maintained higher average facial temperatures, indicating potentially lower emotional arousal, as measured using infrared thermography. These findings demonstrate a complex interplay of various proximate mechanisms governing coping in a non-human primate.

In silico analyses of the involvement of GPR55, CB1R and TRPV1: response to THC, contribution to temporal lobe epilepsy, structural modeling and updated evolution

Introduction

The endocannabinoid (eCB) system is named after the discovery that endogenous cannabinoids bind to the same receptors as the phytochemical compounds found in Cannabis. While endogenous cannabinoids include anandamide (AEA) and 2-arachidonoylglycerol (2-AG), exogenous phytocannabinoids include Δ-9 tetrahydrocannabinol (THC) and cannabidiol (CBD). These compounds finely tune neurotransmission following synapse activation, via retrograde signaling that activates cannabinoid receptor 1 (CB1R) and/or transient receptor potential cation channel subfamily V member 1 (TRPV1). Recently, the eCB system has been linked to several neurological diseases, such as neuro-ocular abnormalities, pain insensitivity, migraine, epilepsy, addiction and neurodevelopmental disorders. In the current study, we aim to: (i) highlight a potential link between the eCB system and neurological disorders, (ii) assess if THC exposure alters the expression of eCB-related genes, and (iii) identify evolutionary-conserved residues in CB1R or TRPV1 in light of their function.

Methods

To address this, we used several bioinformatic approaches, such as transcriptomic (Gene Expression Omnibus), protein-protein (STRING), phylogenic (BLASTP, MEGA) and structural (Phyre2, AutoDock, Vina, PyMol) analyzes.

Results

Using RNA sequencing datasets, we did not observe any dysregulation of eCB-related transcripts in major depressive disorders, bipolar disorder or schizophrenia in the anterior cingulate cortex, nucleus accumbens or dorsolateral striatum. Following in vivo THC exposure in adolescent mice, GPR55 was significantly upregulated in neurons from the ventral tegmental area, while other transcripts involved in the eCB system were not affected by THC exposure. Our results also suggest that THC likely induces neuroinflammation following in vitro application on mice microglia. Significant downregulation of TPRV1 occurred in the hippocampi of mice in which a model of temporal lobe epilepsy was induced, confirming previous observations. In addition, several transcriptomic dysregulations were observed in neurons of both epileptic mice and humans, which included transcripts involved in neuronal death. When scanning known interactions for transcripts involved in the eCB system (n = 12), we observed branching between the eCB system and neurophysiology, including proteins involved in the dopaminergic system. Our protein phylogenic analyzes revealed that CB1R forms a clade with CB2R, which is distinct from related paralogues such as sphingosine-1-phosphate, receptors, lysophosphatidic acid receptors and melanocortin receptors. As expected, several conserved residues were identified, which are crucial for CB1R receptor function. The anandamide-binding pocket seems to have appeared later in evolution. Similar results were observed for TRPV1, with conserved residues involved in receptor activation.

Conclusion

The current study found that GPR55 is upregulated in neurons following THC exposure, while TRPV1 is downregulated in temporal lobe epilepsy. Caution is advised when interpreting the present results, as we have employed secondary analyzes. Common ancestors for CB1R and TRPV1 diverged from jawless vertebrates during the late Ordovician, 450 million years ago. Conserved residues are identified, which mediate crucial receptor functions.

Identifying overcontrol and undercontrol personality types among young people using the five factor model, and the relationship with disordered eating behaviour, anxiety and depression

BACKGROUND

Overcontrol and undercontrol personality types have been associated with an increase in eating pathology, depression and anxiety. The aim of the research was to explore whether latent overcontrol and undercontrol personality types could be identified using cluster analysis of the facets of the five factor model (FFM). We further aimed to understand how these personality types were associated with eating pathology, depressed mood and anxiety.

METHODS

A total of 561 participants (394 women and 167 men), aged 16-30 years in Australia completed a survey designed to assess disordered eating, FFM personality traits, anxiety, depression and stress. A systematic four-step process using hierarchical, k-means, and random forest cluster analyses were used to identify a meaningful 3-cluster solution.

RESULTS

The results revealed a cluster solution that represented overcontrol, undercontrol and resilient personality types, and highlighted facets of the FFM that were associated with each type. Both overcontrol and undercontrol personality types were associated with increased clinical symptoms compared to the resilient types.

CONCLUSIONS

It was concluded that FFM facets may potentially be more meaningful than broad domains in identifying personality types, and that both overcontrol and undercontrol personality types are likely associated with increased clinical symptoms.

Neurocognitive risk phenotyping to predict mood symptoms in adolescence

Predicting mood disorders in adolescence is a challenge that motivates research to identify neurocognitive predictors of symptom expression and clinical profiles. This study used machine learning to test whether neurocognitive variables predicted future manic or anhedonic symptoms in two adolescent samples risk-enriched for lifetime mood disorders (Sample 1, n = 73, ages = 13-25, M [SD] = 19.22 [2.49] years, 68% lifetime mood disorder) or familial mood disorders (Sample 2, n = 154, ages = 13-21, M [SD] = 16.46 [1.95] years, 62% first-degree family history of mood disorder). Participants completed cognitive testing and functional magnetic resonance imaging at baseline, for behavioral and neural measures of reward processing and executive functioning. Next, participants completed a daily diary procedure for 8-16 weeks. Penalized mixed-effects models identified neurocognitive predictors of future mood symptoms and stress-reactive changes in mood symptoms. Results included the following. In both samples, adolescents showing ventral corticostriatal reward hyposensitivity and lower reward performance reported more severe stress-reactive anhedonia. Poorer executive functioning behavior was associated with heightened anhedonia overall in Sample 1, but lower stress-reactive anhedonia in both samples. In Sample 1, adolescents showing ventral corticostriatal reward hypersensitivity and poorer executive functioning reported more severe stress-reactive manic symptoms. Clustering analyses identified, and replicated, five neurocognitive subgroups. Adolescents characterized by neural or behavioral reward hyposensitivities together with average-to-poor executive functioning reported unipolar symptom profiles. Adolescents showing neural reward hypersensitivity together with poor behavioral executive functioning reported a bipolar symptom profile (Sample 1 only). Together, neurocognitive phenotypes may hold value for predicting symptom expression and profiles of mood pathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Exploring the Molecular Mechanism of HongTeng Decoction against Inflammation based on Network Analysis and Experiments Validation

BACKGROUND

HongTeng Decoction (HTD) is a traditional Chinese medicine that is widely used to treat bacterial infections and chronic inflammation. However, its pharmacological mechanism is not clear. Here, network pharmacology and experimental verification were applied to investigate the drug targets and potential mechanisms of HTD in inflammation treatment.

METHODS

The active ingredients of HTD were collected from the multi-source databases and clarified by Q Exactive Orbitrap analysis in the treatment of inflammation. Then, molecular docking technology was used to explore the binding ability of key active ingredients and targets in HTD. In vitro experiments, the inflammatory factors and MAPK signaling pathways are detected to verify the anti-inflammatory effect of HTD on the RAW264.7 cells. Finally, the anti-inflammatory effect of HTD was evaluated in LPS induced mice model.

RESULTS

A total of 236 active compounds and 492 targets of HTD were obtained through database screening, and 954 potential targets of inflammation were identified. Finally, 164 possible targets of HTD acting on inflammation were obtained. The PPI analysis and KEGG enrichment analyses showed that the targets of HTD in inflammation were mostly related to the MAPK signaling pathway, the IL-17 signaling pathway, and the TNF signaling pathway. By integrating the results of the network analysis, the core targets of HTD in inflammation mainly include MAPK3, TNF, MMP9, IL6, EGFR, and NFKBIA. The molecular docking results indicated solid binding activity between MAPK3-naringenin and MAPK3-paeonol. It has been shown that HTD could inhibit the levels of inflammatory factors, IL6 and TNF-α, as well as the splenic index in the LPS-stimulated mice. Moreover, HTD could regulate protein expression levels of p-JNK1/2, and p-ERK1/2, which reflects the inhibitory effect of HTD on the MAPKS signaling pathway.

CONCLUSION

Our study is expected to provide the pharmacological mechanisms by which HTD may be a promising anti-inflammatory drug for future clinical trials.

Self-regulation profiles in addictive behaviors among adolescents: A transdiagnostic approach

Dual-pathway models suggest that poor self-regulation (immature regulatory combined with strong reactive processes) is an important factor underlying addictive behaviors among adolescents. This study examined whether there are different self-regulation profiles among community adolescents, and how these profiles are related to the presence, severity and comorbidity of different addictive behaviors. A community sample of 341 adolescents (54.5% female; 13-17 years) was recruited. Participants self-reported on regulatory (inhibitory control) and reactive (reward and punishment sensitivity) processes, as well as on different addictive behaviors (binge eating, tobacco-, cannabis- and alcohol use, gaming, gambling and pathological buying). A model-based clustering analysis found evidence for three meaningful profiles: 'impulsive/under-controlled', 'anxious' and 'protective'. The 'impulsive/under-controlled' profile was characterized by the highest prevalence and severity of cannabis use and the most severe alcohol use. The 'impulsive/under-controlled' and 'protective' profiles demonstrated the highest prevalence and severity of tobacco use, whereas the 'impulsive/under-controlled' and 'anxious' profiles showed the highest binge eating scores. Adolescents who reported more than three types of addictive behaviors generally belonged to the 'impulsive/under-controlled' profile. The profiles did not differ for gaming, gambling and pathological buying. The 'impulsive/under-controlled' profile emerged as the most vulnerable profile in the context of addictive behaviors (especially for binge eating and substance use).

Antineutrophil cytoplasmic antibody-associated vasculitis classification by cluster analysis based on clinical phenotypes: a single-center retrospective cohort study

OBJECTIVE

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) refers to a group of small vessel inflammatory disorders. Overlapping clinical phenotypes of AAV subgroups continually provoke controversies over their diagnostic and classification criteria.

METHODS

Using the agglomerative hierarchical clustering method, we classified 210 Korean patients diagnosed with AAV into mutually exclusive clusters according to Birmingham Vasculitis Activity Score items, ANCA specificity, sex, and age. We analyzed the resulting clusters' outcomes to investigate the clinical significance of the classification. We proposed a distance-based algorithm of patient assignment and explored its clinically relevant modification.

RESULTS

In total, 116 patients (55%) had microscopic polyangiitis, 53 (25%) had granulomatosis with polyangiitis, and 42 (20%) had eosinophilic granulomatosis with polyangiitis. Our model grouped the patients into five clusters, namely, "limited proteinase 3 (PR3)-ANCA vasculitis," "generalized PR3-ANCA vasculitis," "ANCA-negative vasculitis," "renal-limited vasculitis," and "myeloperoxidase-ANCA vasculitis." Patients clustered under "generalized PR3-ANCA vasculitis" had a higher relapse rate (hazard ratio [HR] = 2.12, P = 0.067). The incidence of end-stage renal disease was higher in patients belonging to the "renal-limited vasculitis" cluster (HR=1.50, P=0.03), and those in the "ANCA-negative vasculitis" cluster experienced a relatively milder clinical course of AAV (mortality = 0).

CONCLUSION

Because the clusters were naturally derived from their distinguished phenotypes and have different clinical courses, our clustering method may be a more clinically relevant classification system for AAV, revealing its phenotypic diversity. We also proposed a simple and intuitive distance-based assignment algorithm, which can be easily modified according to specific clinical needs. Key Points • In this study with a single-center AAV cohort, we showed that AAV can be divided into five distinct subclasses with different disease courses based on the clinical and laboratory features of the patients. • Our study revealed ethnic differences in AAV manifestation and suggests that physicians may need to analyze their own AAV patients to assess the disease status of AAV patients. • We proposed a distance-based cluster membership assignment method that can be clinically modified to fit the specific purpose of grouping patients.

Cluster analysis as a clinical and research tool in Behçet's syndrome

PURPOSE OF REVIEW

The purpose of this review was to comprehensively summarize recent phenotype research findings in Behçet's syndrome.

RECENT FINDINGS

Cluster analysis has recently been employed as a phenotype research tool in Behçet's syndrome. Studies reported different clustering patterns caused by biological variation and some degree of artificial heterogeneity. However, some clusters were more consistent than others: 1) oral ulcers, genital ulcers, and skin lesions 2) oral ulcers, genital ulcers, skin lesions, and arthritis 3) oral ulcers, genital ulcers, skin lesions, and uveitis 4) oral ulcers, genital ulcers, skin lesions, and gastrointestinal involvement. A number of loci suggestive of differential risk for individual disease manifestations were proposed. Peripheral blood gene expression profile and plasma proteome exhibited significant differences in patients with different organ involvements and were able to differentiate between disease phenotypes. However, these observations require further validation and functional studies.

SUMMARY

Clustering patterns in Behçet's syndrome is highly heterogeneous. Artificial heterogeneity might obscure the true biological variation of disease expression. Preliminary genetic, transcriptomic and proteomic data suggest that different pathogenetic mechanisms may operate in different phenotypes of Behçet's syndrome.

Effects of Cd treatment on morphology, chlorophyll content and antioxidant enzyme activity of Elymus nutans Griseb., a native plant in Qinghai-Tibet Plateau

Cd pollution is a global environmental problem. However, the response mechanism of the alpine plant Pelagia under Cd stress remains unclear. Therefore, in this study, a native plant(Elymus nutans Griseb.) of the Qinghai-Tibet Plateau was used as the material to quantify plant height, leaf number, length of leaf, crown width, root number, biomass, Dry weight malondialdehyde (MDA), free proline, superoxide dismutase (SOD), ascorbate enzyme (APX), catalase (CAT) and chlorophyll contents under different Cd concentrations. The results showed that the growth of Elymus nutans Griseb. was a phenomenon of "low concentration promotes growth, high concentration inhibited growth" under Cd treatment. It meant that 10 mg·L^-1 Cd promoted the growth of leaf number, plant height, crown width and tiller number, while 40 mg·L^-1 Cd inhibited the growth of root number and biomass of Elymus nutans Griseb. compare with the control. The MDA content, free proline content, SOD activity, APX activity and CAT activity of Elymus nutans Griseb. was increased with the increase of Cd treatment concentration to resist the oxidative damage caused by Cd to the body. At the same time, the accumulation of chlorophyll A, chlorophyll B and chlorophyll AB was decreased with the increase of Cd stress concentration. In addition, the carotenoid content did not change much between the control group and the treatment group, indicating that Cd treatment had little effect on it. The results could provide a reference for the mechanism of heavy metal resistance and the selection and improvement of Cd -resistant varieties of Elymus nutans Griseb.

Not All Injuries Are the Same: Different Patterns in Sports Injuries and Their Psychosocial Correlates

Sports injuries are ubiquitous and can have far-reaching consequences for athletes (e.g., health, performance). Previous studies have examined various psychosocial influencing factors (e.g., stress), but have mostly focused on only one or two injury characteristics (e.g., frequency), neglecting the broader injury pattern. Thus, the present study aimed to obtain a more differentiated picture of potentially different injury patterns and related profiles of psychosocial factors. We investigated a sample of 213 athletes from a cross-sectional online study. Current injury status, frequency, severity, chronicity, medical treatment, and rehabilitation measures were subjected to cluster analysis indicating a 3-cluster solution with predominantly chronically injured athletes (n = 54), athletes not seeking treatment (n = 62), and athletes utilizing medical treatment and rehabilitation (n = 97). Building on the Model of Stress and Athletic Injury, we subsequently conducted three multivariate analyses of variance (MANOVAs) to examine whether the obtained clusters differed in terms of personality factors (e.g., athletic identity), history of stressors (e.g., life events), and coping resources (e.g., self-compassion). We observed significant differences in all three categories of psychosocial variables implying different intervention possibilities for different injury patterns in the future.

Interpretable machine learning accurately reclassifies lobectomy surgical approaches by cost

BACKGROUND

The volume of robotic lung resection continues to increase despite its higher costs and unproven superiority to video-assisted thoracoscopic surgery. We evaluated whether machine learning can accurately identify factors influencing cost and reclassify high-cost operative approaches into lower-cost alternatives.

METHODS

The Florida Agency for Healthcare Administration and Centers for Medicare and Medicaid Services Hospital and Physician Compare datasets were queried for patients undergoing open, video-assisted thoracoscopic surgery and robotic lobectomy. K-means cluster analysis was used to identify robotic clusters based on total cost. Predictive models were built using artificial neural networks, Support Vector Machines, Classification and Regression Trees, and Gradient Boosted Machines algorithms. Models were applied to the high-volume robotic group to determine patients whose cost cluster changed if undergoing a video-assisted thoracoscopic surgery approach. A local interpretable model-agnostic explanation approach personalized cost per patient.

RESULTS

Of the 6,618 cases included in the analysis, we identified 4 cost clusters. Application of artificial neural networks to the robotic subgroup identified 1,642 (65%) cases with no re-assignment of cost cluster, 583 (23%) with reduced costs, and 300 (12%) with increased costs if they had undergone video-assisted thoracoscopic surgery approach. The 5 overall highest cost predictors were patient admission from the clinic, diagnosis of metastatic cancer, presence of cancer, urgent hospital admission, and dementia.

CONCLUSION

K-means cluster analysis and machine learning identify a patient population that may undergo video-assisted thoracoscopic surgery or robotic lobectomy without a significant difference in total cost. Local interpretable model-agnostic explanation identifies individual patient factors contributing to cost. Application of this modeling may reliably stratify high-cost patients into lower-cost approaches and provide a rationale for reducing expenditure.

Unsupervised clustering analysis of comprehensive health status and its influencing factors on women of childbearing age: a cross-sectional study from a province in central China

BACKGROUND

Most previous studies on women of childbearing age have focused on reproductive health and fertility intentions, and evidence regarding the comprehensive health status of women of childbearing age is limited. This study aimed to comprehensively examine the health status of women of childbearing age through a multi-method and multi-indicator evaluation, analyze the factors that influence their overall health, and provide sound recommendations for the improvement and promotion of healthy behaviors.

METHODS

Data on women of childbearing age living in Shanxi Province were collected between September 2021 and January 2022 through online and offline surveys. The k-means algorithm was used to assess health-related patterns in women, and multivariate nonconditional logistic regression was used to assess the influencing factors of women's overall health.

RESULTS

In total, 1,258 of 2,925 (43%) participants were classified as having a good health status in all five domains of the three health dimensions: quality of life, mental health, and illness. Multivariate logistic regression showed that education level, gynecological examination status, health status of family members, access to medical treatment, age, cooking preferences, diet, social support, hand washing habits, attitude toward breast cancer prevention, and awareness of reproductive health were significantly associated with different health patterns.

CONCLUSIONS

The comprehensive health status of women of childbearing age in Shanxi Province is generally good; however, a large proportion of women with deficiencies in some dimensions remains. Since lifestyle greatly impacts women's health, health education on lifestyle and health-related issues should be strengthened.

Subphenotypes in patients with acute respiratory distress syndrome treated with high-flow oxygen

BACKGROUND

Acute respiratory distress syndrome (ARDS) subphenotypes differ in outcomes and treatment responses. Subphenotypes in high-flow nasal oxygen (HFNO)-treated ARDS patients have not been investigated.

OBJECTIVES

To identify biological subphenotypes in HFNO-treated ARDS patients.

METHODS

Secondary analysis of a prospective multicenter observational study including ARDS patients supported with HFNO. Plasma inflammation markers (interleukin [IL]-6, IL-8, and IL-33 and soluble suppression of tumorigenicity-2 [sST2]) and lung epithelial (receptor for advanced glycation end products [RAGE] and surfactant protein D [SP-D]) and endothelial (angiopoietin-2 [Ang-2]) injury were measured. These biomarkers and bicarbonate were used in K-means cluster analysis to identify subphenotypes. Logistic regression was performed on biomarker combinations to predict clustering. We chose the model with the best AUROC and the lowest number of variables. This model was used to describe the HAIS (High-flow ARDS Inflammatory Subphenotype) score.

RESULTS

Among 41 HFNO patients, two subphenotypes were identified. Hyperinflammatory subphenotype (n = 17) showed higher biomarker levels than hypoinflammatory (n = 24). Despite similar baseline characteristics, the hyperinflammatory subphenotype had higher 60-day mortality (47 vs 8.3% p = 0.014) and longer ICU length of stay (22.0 days [18.0-30.0] vs 39.5 [25.5-60.0], p = 0.034). The HAIS score, based on IL-8 and sST2, accurately distinguished subphenotypes (AUROC 0.96 [95%CI: 0.90-1.00]). A HAIS score ≥ 7.45 was predictor of hyperinflammatory subphenotype.

CONCLUSION

ARDS patients treated with HFNO exhibit two biological subphenotypes that have similar clinical characteristics, but hyperinflammatory patients have worse outcomes. The HAIS score may identify patients with hyperinflammatory subphenotype and might be used for enrichment strategies in future clinical trials.

Trajectories of change among highly challenging patients in intensive long-term psychoanalytic psychotherapy

OBJECTIVES

This study aimed to identify and describe trajectories of change in distress among highly challenging patients who had received long and intensive psychoanalytic psychotherapy.

METHODS

The longitudinal version of the K-means algorithm was applied to the outcome measures data of 74 patients treated in four public mental health centers. The patients were measured five times at 6-month intervals for three outcome measures.

RESULTS

For the OQ45 and Symptom Checklist-90, one trajectory was marked by a lower initial distress level. In this trajectory, the improvement occurred in the first half of the measurements, with a plateau thereafter. A second trajectory was characterized by higher initial severity and an improvement, mainly in the second part of the measurements. For the Beck Depression Inventory, one trajectory was marked by lower initial distress. In this group, the improvement occurred throughout the entire period. The remaining patients were characterized by higher initial distress and a decreased level of distress in the last part of treatment. They began to improve only during the third year of therapy.

CONCLUSION

The response to treatment is not uniform in long-term treatment for highly challenging patients. A significant number of patients require a longer period of therapy to ignite improvement.

Cluster features in fibrosing interstitial lung disease and associations with prognosis

BACKGROUND

Clustering is helpful in identifying subtypes in complex fibrosing interstitial lung disease (F-ILD) and associating them with prognosis at an early stage of the disease to improve treatment management. We aimed to identify associations between clinical characteristics and outcomes in patients with F-ILD.

METHODS

Retrospectively, 575 out of 926 patients with F-ILD were eligible for analysis. Four clusters were identified based on baseline data using cluster analysis. The clinical characteristics and outcomes were compared among the groups.

RESULTS

Cluster 1 was characterized by a high prevalence of comorbidities and hypoxemia at rest, with the worst lung function at baseline; Cluster 2 by young female patients with less or no smoking history; Cluster 3 by male patients with highest smoking history, the most noticeable signs of velcro crackles and clubbing of fingers, and the severe lung involvement on chest image; Cluster 4 by male patients with a high percentage of occupational or environmental exposure. Clusters 1 (median overall survival [OS] = 7.0 years) and 3 (OS = 5.9 years) had shorter OS than Clusters 2 (OS = not reached, Cluster 1: p < 0.001, Cluster 3: p < 0.001) and 4 (OS = not reached, Cluster 1: p = 0.004, Cluster 3: p < 0.001). Clusters 1 and 3 had a higher cumulative incidence of acute exacerbation than Clusters 2 (Cluster 1: p < 0.001, Cluster 3: p = 0.014) and 4 (Cluster 1: p < 0.001, Cluster 3: p = 0.006). Stratification by using clusters also independently predicted acute exacerbation (p < 0.001) and overall survival (p < 0.001).

CONCLUSIONS

The high degree of disease heterogeneity of F-ILD can be underscored by four clusters based on clinical characteristics, which may be helpful in predicting the risk of fibrosis progression, acute exacerbation and overall survival.

Managing With Atrial Fibrillation: An Exploratory Model-Based Cluster Analysis of Clinical and Personal Patient Characteristics

Background

Examining characteristics of patients with atrial fibrillation (AF) has the potential to help in identifying groups of patients who might benefit from different management approaches.

Methods

Secondary analysis of online survey data was combined with clinic referral data abstraction from 196 patients with AF attending an AF specialty clinic. Cluster analyses were performed to identify distinct, homogeneous clusters of AF patients defined by 11 relevant variables: CHA2DS2-VASc score, age, AF symptoms, overall health, mental health, AF knowledge, perceived stress, household and recreation activity, overall AF quality of life, and AF symptom treatment satisfaction. Follow-up analyses examined differences between the cluster groups in additional clinical variables.

Results

Evidence emerged for both 2- and 4-cluster solutions. The 2-cluster solution involved a contrast between patients who were doing well on all variables (n = 129; 66%) vs those doing less well (n = 67; 34%). The 4-cluster solution provided a closer-up view of the data, showing that the group doing less well was split into 3 meaningfully different subgroups of patients who were managing in different ways. The final 4 clusters produced were as follows: (i) doing well; (ii) stressed and discontented; (iii) struggling and dissatisfied; and (iv) satisfied and complacent.

Conclusions

Patients with AF can be accurately classified into distinct, natural groupings that vary in clinically important ways. Among the patients who were not managing well with AF, we found 3 distinct subgroups of patients who may benefit from tailored approaches to AF management and support. The tailoring of treatment approaches to specific personal and/or behavioural patterns, alongside clinical patterns, holds potential to improve patient outcomes (eg, treatment satisfaction).

Decision and response monitoring during working memory are sequentially represented in the human insula

Emerging research supports a role of the insula in human cognition. Here, we used intracranial EEG to investigate the spatiotemporal dynamics in the insula during a verbal working memory (vWM) task. We found robust effects for theta, beta, and high frequency activity (HFA) during probe presentation requiring a decision. Theta band activity showed differential involvement across left and right insulae while sequential HFA modulations were observed along the anteroposterior axis. HFA in anterior insula tracked decision making and subsequent HFA was observed in posterior insula after the behavioral response. Our results provide electrophysiological evidence of engagement of different insula subregions in both decision-making and response monitoring during vWM and expand our knowledge of the role of the insula in complex human behavior.

Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care

OBJECTIVE

This study aimed to identify temporal risk factor patterns documented in home health care (HHC) clinical notes and examine their association with hospitalizations or emergency department (ED) visits.

MATERIALS AND METHODS

Data for 73 350 episodes of care from one large HHC organization were analyzed using dynamic time warping and hierarchical clustering analysis to identify the temporal patterns of risk factors documented in clinical notes. The Omaha System nursing terminology represented risk factors. First, clinical characteristics were compared between clusters. Next, multivariate logistic regression was used to examine the association between clusters and risk for hospitalizations or ED visits. Omaha System domains corresponding to risk factors were analyzed and described in each cluster.

RESULTS

Six temporal clusters emerged, showing different patterns in how risk factors were documented over time. Patients with a steep increase in documented risk factors over time had a 3 times higher likelihood of hospitalization or ED visit than patients with no documented risk factors. Most risk factors belonged to the physiological domain, and only a few were in the environmental domain.

DISCUSSION

An analysis of risk factor trajectories reflects a patient's evolving health status during a HHC episode. Using standardized nursing terminology, this study provided new insights into the complex temporal dynamics of HHC, which may lead to improved patient outcomes through better treatment and management plans.

CONCLUSION

Incorporating temporal patterns in documented risk factors and their clusters into early warning systems may activate interventions to prevent hospitalizations or ED visits in HHC.

Profiles of physician motivation towards using virtual care: differences in workplace need fulfillment

BACKGROUND

Physicians appear to vary in their motivation towards using virtual care, but to what extent is unclear. To better understand this variance, which is important for supporting physician wellbeing and therefore patient care, the authors used self-determination theory's (SDT) framework. According to SDT, different types of motivation exist, ranging from controlled to autonomous, that lend to differences in engagement, performance, and wellbeing. The authors aimed to determine: (a) if there were distinct groups of physicians based on their quality of motivation towards using virtual care, and if so, (b) how these groups varied in fulfillment of basic psychological needs (autonomy, competence, and relatedness) in the workplace.

METHODS

In March-August 2022, the authors collected quantitative, survey-based data from a cross-section of 156 family physicians in Alberta, Canada. The survey contained existing scales that measure types of motivation (autonomous vs. controlled) and basic psychological need satisfaction/frustration at work. Cluster analysis was used to explore profiles of physician motivation towards using virtual care, and analysis of variance was used to determine how each profile differed with respect to workplace need fulfillment.

RESULTS

With motivation towards using virtual care, three higher-order profiles of physician motivation were identified: autonomous (19% family physicians), controlled (16% of family physicians), and ambivalent (66% of family physicians). The three profiles differed significantly in terms of psychological need fulfillment at work.

CONCLUSIONS

This study identifies specific profiles that family physicians currently fall into when it comes to motivation towards using virtual care. In line with SDT, findings suggest that basic psychological needs are fundamental nutrients for physicians to internalize and endorse the value of using virtual care in their practices. Implications for physician wellbeing are discussed.

Explorative Clustering of the Nitrogen Balance Trajectory in Critically Ill Patients: A Preliminary post hoc Analysis of a Single-Center Prospective Observational Study

BACKGROUND

The nitrogen balance estimates a protein net difference. However, since it has a number of limitations, it is important to consider the trajectory of the nitrogen balance in the clinical course of critically ill patients.

OBJECTIVES

We herein exploratively classified the nitrogen balance trajectory using a machine learning method.

METHOD

This is a post hoc analysis of a single-center prospective study for the patients admitted to our Emergency and Critical Center ICU. The nitrogen balance was evaluated with 24-h urine collection from ICU days 1-10 with 9 points. K-means clustering was performed to classify the nitrogen balance trajectory. We also evaluated factors associated with uncovered clusters.

RESULTS

Seventy-six eligible patients were included in the present study. After clustering, the nitrogen balance trajectory was classified into 4 classes. Class 1 was trajected as a negative balance over 10 days (24 patients). Class 2 had a positive conversion on day 3 or 4 (8 patients). Class 3 had a positive conversion on day 8 or 9 (28 patients). Class 4 initially had a positive balance and then converted to a negative balance (16 patients). Sepsis complication and steroid use were associated with negative nitrogen balance trajectory. Class 2 was associated with lower length of hospital stay and femoral muscle volume loss, however, frequently had frailty and sarcopenia on admission. Active nutrition therapy intention was not correlated with positive trajectory.

CONCLUSIONS

The nitrogen balance trajectory in critically ill patients may be classified into 4 classes for clinical practice. Among patients emergently admitted to the ICU, the positive conversion of the nitrogen balance might be delayed over 10 days.

Pan-cancer analysis of NFE2L2 mutations identifies a subset of lung cancers with distinct genomic and improved immunotherapy outcomes

BACKGROUND

Mutations in the KEAP1-NFE2L2 signaling pathway were linked to increased tumorigenesis and aggressiveness. Interestingly, not all hotspot mutations on NFE2L2 were damaging; some even were activating. However, there was conflicting evidence about the association between NFE2L2 mutation and Nrf2-activating mutation and responsiveness to immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and other multiple cancers.

METHODS

The study with the largest sample size (n = 49,533) explored the landscape of NFE2L2 mutations and their impact response/resistance to ICIs using public cohorts. In addition, the in-house WXPH cohort was used to validate the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC.

RESULTS

In two pan-cancer cohorts, Nrf2-activating mutation was associated with higher TMB value compared to wild-type. We identified a significant association between Nrf2-activating mutation and shorter overall survival in pan-cancer patients and NSCLC patients but not in those undergoing ICIs treatment. Similar findings were obtained in cancer patients carrying the NFE2L2 mutation. Furthermore, in NSCLC and other cancer cohorts, patients with NFE2L2 mutation demonstrated more objective responses to ICIs than patients with wild type. Our in-house WXPH cohort further confirmed the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC. Lastly, decreased inflammatory signaling pathways and immune-depleted immunological microenvironments were enriched in Nrf2-activating mutation patients with NSCLC.

CONCLUSIONS

Our study found that patients with Nrf2-activating mutation had improved immunotherapy outcomes than patients with wild type in NSCLC and other tumor cohorts, implying that Nrf2-activating mutation defined a distinct subset of pan-cancers and might have implications as a biomarker for guiding ICI treatment, especially NSCLC.