Latent Class Trajectory Analysis Research Articles

Developmental trajectories of atopic dermatitis with multi-omics approaches in the infant gut: COCOA birth cohort.

An understanding of the phenotypes and endotypes of atopic dermatitis (AD) is essential for developing precision therapies. Recent studies have demonstrated evidence for the gut-skin axis in AD. To determine the natural course and clinical characteristics of AD phenotypes and investigate their mechanisms based on multi-omics analyses. Latent class trajectory analysis was used to AD phenotype in 2247 children who were followed until 9 years of age from the COhort for Childhood Origin of Asthma and allergic diseases (COCOA) birth cohort study. Multi-omics analyses (microbiome, metabolites, and gut epithelial cell transcriptome) using stool samples collected at 6 months of age were performed to elucidate the underlying mechanisms of AD phenotypes. Five AD phenotypes were classified as follows: never/infrequent, early-onset transient, intermediate-transient, late-onset, and early-onset persistent. Early-onset persistent and late-onset phenotypes showed increased risks of food allergy and wheezing treatment ever, with bronchial hyperresponsiveness only evident in the early-onset persistent phenotype. Multi-omics analyses revealed a significantly lower relative abundance of Ruminococcus gnavus and a decreased gut acetate level in the early-onset persistent phenotype, with potential associations to ACSS2, JAK-STAT signaling, and systemic Th2 inflammation. The early-onset transient phenotype was associated with AMPK and/or chemokine signaling regulation, whereas the late-onset phenotype was linked with IL-17 and barrier dysfunction. Multi-omics profiling in early life may offer insights into different mechanisms underlying AD phenotypes in children.

Abstract A001: Health expenditure trajectory and gastric cancer incidence in the National Health Insurance Senior Cohort: A nested case-control study

Abstract Background: Gastric cancer is the fourth most common cancer and highly prevalent in South Korea. Given its prolonged disease progression, understanding the impact of health expenditure patterns over time is crucial. This nested case-control study aimed to identify the association between health expenditure trajectory and incidence of gastric cancer. Methods: Data from the National Health Insurance Service Senior Cohort of South Korea were used. Individuals diagnosed with gastric cancer (N = 14,873) were matched to a non-diagnosed group (N = 44,619) in a 1:3 ratio using a nested case-control design. A latent class trajectory analysis was performed to identify the patterns of health expenditure among the matched participants. Furthermore, conditional logistic regression analysis was conducted to examine the relationship between healthcare expenditure trajectories and gastric cancer incidence. Results: Seven distinct health expenditure trajectories over a 5-year period were identified: consistently lowest (13.9%), rapidly increasing (6.4%), gradually increasing (14.1%), consistently second-highest (22.1%), middle-low (17.8%), gradually decreasing (12.8%), and consistently highest (12.9%). Compared to the Middle-low group, individuals in the rapidly increasing (OR = 2.07; 95% confidence interval [CI], 1.90–2.25), consistently lowest (OR = 1.43; 95% CI, 1.33–1.55), gradually increasing (OR = 1.23; 95% CI, 1.15–1.32), and consistently highest (OR = 1.08; 95% CI, 1.01–1.17) groups exhibited a higher risk of developing gastric cancer. Conclusion: Our findings emphasize the importance of monitoring health expenditures to prevent gastric cancer. The categorization of health expenditure by trajectories allowed the identification of specific risk groups that may be targeted by appropriate interventions. Citation Format: Minjee Lee, Ki-Bong Yoo, Woo-Ri Lee. Health expenditure trajectory and gastric cancer incidence in the National Health Insurance Senior Cohort: A nested case-control study [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A001.

Health expenditure trajectory and gastric cancer incidence in the National Health Insurance Senior Cohort: a nested case-control study

BackgroundGastric cancer is the fourth most common cancer and highly prevalent in South Korea. As one of the predictors of gastric cancer, we focused on health utilization patterns and expenditures, as the surrogate variables of health conditions. This nested case-control study aimed to identify the association between health expenditure trajectory and incidence of gastric cancer.MethodsData from the National Health Insurance Service Senior Cohort of South Korea were used. Individuals diagnosed with gastric cancer (N = 14,873) were matched to a non-diagnosed group (N = 44,619) in a 1:3 ratio using a nested case-control design. A latent class trajectory analysis was performed to identify the patterns of health expenditure among the matched participants. Furthermore, conditional logistic regression analysis was conducted to examine the relationship between healthcare expenditure trajectories and gastric cancer incidence.ResultsSeven distinct health expenditure trajectories for five years were identified; consistently lowest (13.8%), rapidly increasing (5.9%), gradually increasing (13.8%), consistently second-highest (21.4%), middle-low (18.8%), gradually decreasing (13.1%), and consistently highest (13.2%). Compared to the middle-low group, individuals in the rapidly increasing [odds ratio (OR) = 2.11, 95% confidence interval (CI); 1.94–2.30], consistently lowest (OR = 1.40, 95% CI; 1.30–1.51), and gradually increasing (OR = 1.26, 95% CI; 1.17–1.35) groups exhibited a higher risk of developing gastric cancer.ConclusionsOur findings suggest that health expenditure trajectories are predictors of gastric cancer. Potential risk groups can be identified by monitoring health expenditures.

Trajectories of serum HBsAg during treatment and association with HBsAg loss in children with HBeAg-positive chronic hepatitis B: a latent class trajectory analysis.

The change of serum hepatitis B surface antigen (HBsAg) during treatment are associated with HBsAg loss. However, little is known about the trajectory patterns of HBsAg in early treatment and their relationship with subsequent HBsAg loss. This study aimed to identify trajectories of HBsAg in children with HBeAg-positive chronic hepatitis B (CHB) and investigate the association between trajectory patterns and HBsAg loss. A retrospective study was conducted on 166 treatment-naive children with HBeAg-positive CHB. Latent class trajectory analysis was used to identify trajectory groups of serum HBsAg. Cox proportional hazard model was used to assess the association between HBsAg trajectory groups and HBsAg loss. The median follow-up time was 20.70 (12.54, 34.17) months, and HBsAg loss occurred in 70(42.17%) of all study participants. Using latent class trajectory analysis, HBeAg-positive CHB patients were classified into three trajectory groups: trajectory 1 (sustained stability, 24.70%), trajectory 2 (slow decline, 38.55%), and trajectory 3 (rapid decline, 36.75%), respectively. The median decline levels of HBsAg at the 3-month and 6-month follow-ups were the highest in trajectory 3 (1.08 and 3.28 log10 IU/ml), followed by trajectory 2 (0.27 and 1.26 log10 IU/ml), and no change in trajectory 1. The risk of achieving HBsAg loss was higher in both trajectory 2 (HR, 3.65 [95% CI, 1.70-7.83]) and trajectory 3 (HR, 7.27 [95% CI, 3.01-17.61]), respectively. Serum HBsAg levels during early treatment can be classified into distinct trajectory groups, which may serve as an additional predictive indicator for HBsAg loss in HBeAg-positive CHB children.

Longitudinal HbA1c patterns before the first treatment of diabetes in routine clinical practice: A latent class trajectory analysis

AimsTo examine the longitudinal heterogeneity of HbA1c preceding the initiation of diabetes treatment in clinical practice. MethodsIn this population-based study, we used HbA1c from routine laboratory and healthcare databases. Latent class trajectory analysis was used to classify individuals according to their longitudinal HbA1c patterns before first glucose-lowering drug prescription irrespective of type of diabetes. ResultsAmong 21,556 individuals initiating diabetes treatment during 2017–2018, 20,733 (96 %) had HbA1c measured (median 4 measurements [IQR 2–7]) in the 5 years preceding treatment initiation. Four classes with distinct HbA1c trajectories were identified, with varying steepness of increase in HbA1c. The largest class (74 % of the individuals) had mean HbA1c above the 48 mmol/mol threshold 9 months before treatment initiation. Mean HbA1c was 52 mmol/mol (95 % CI 52–52) at treatment initiation. In the remaining three classes, mean HbA1c exceeded 48 mmol/mol almost 1.5 years before treatment initiation and reached 79 mmol/mol (95 % CI 78–80), 105 mmol/mol (95 % CI 104–106), and 137 mmol/mol (95 % CI 135–140) before treatment initiation. ConclusionWe identified four distinct longitudinal HbA1c patterns before initiation of diabetes treatment in clinical practice. All had mean HbA1c levels exceeding the diagnostic threshold many months before treatment initiation, indicating therapeutic inertia.

Associations of Dietary Diversity Trajectories with Frailty among Chinese Older Adults: A Latent Class Trajectory Analysis Based on a CLHLS Cohort.

High dietary diversity has been found to be associated with frailty. However, the trajectory of dietary diversity intake in relation to frailty is unclear. Using the latent class trajectory modeling approach, we identified distinctive dietary variety trajectory groups among 2017 participants based on the Chinese Longitudinal Healthy Longevity Survey acquired at four time points within a 10-year period. Frailty status was assessed using a frailty index comprising 37 health deficits. Dietary diversity was quantified using the dietary variety score (DVS), based on food category consumption frequency. Logistic regression analyses were employed to explore the association between DVS change trajectories and frailty. This study identified two distinct DVS trajectories: "Moderate-Slow decline-Slow growth", encompassing 810 (40.16%) individuals, and "Moderate-Slow growth-Accelerated decline", including 1207 (59.84%) individuals. After adjusting for covariates, the odds ratio for DVS in the "Moderate-Slow decline-Slow growth" group was 1.326 (95% confidence interval: 1.075-1.636) compared to the "Moderate-Slow growth-Accelerated decline" group. The "Moderate-Slow decline-Slow growth" trajectory continued to decrease and was maintained at a low level in the early stages of aging. Sustaining a high dietary diversity trajectory over time, particularly in the early stages of aging, could potentially decrease the risk of frailty among older Chinese adults.

Outpatient mean arterial pressure: A potentially modifiable risk for acute kidney injury and death among patients with cirrhosis.

Mean arterial blood pressure (MAP), which decreases as portal hypertension progresses, may be a modifiable risk factor among patients with cirrhosis. We included adults enrolled in the Functional Assessment in Liver Transplantation study. We completed latent class trajectory analyses to define MAP trajectories. We completed time-dependent Cox-regression analyses to test the association between outpatient MAP and 3 cirrhosis-related outcomes: (1) stage 2 acute kidney injury (AKI), defined as a ≥200% increase in serum creatinine from baseline; (2) a 5-point increase in the MELD-Na score, defined as the incidence of increase from initial MELD-Na; (3) waitlist mortality, defined as death on the waitlist. For each outcome, we defined MAP cut points by determining the maximally selected Log-rank statistic after univariable Cox-regression analyses. Among the 1786 patients included in this analysis, our latent class trajectory analyses identified 3 specific outpatient MAP trajectories: "stable-low," "stable-high," and "increasing-to-decreasing." However, >80% of patients were in a "stable-low" trajectory. We found in adjusted analyses that outpatient MAP was associated with each of our outcomes: Stage 2 AKI (adjusted hazard ratio 0.88 per 10mmHg increase in MAP [95% CI: 0.79-0.99]); 5-point increase in MELD-Na (adjusted hazard ratio: 0.91 [95% CI: 0.86-0.96]; waitlist mortality (adjusted hazard ratio: 0.89 [95% CI: 0.81-0.96]). For each outcome, we found that an outpatient MAP of 82mmHg was most associated with outcomes ( p <0.05 for all). Our study informs the association between outpatient MAP and cirrhosis-related outcomes. These findings, coupled with the identification of specific thresholds, lay the foundation for the trial of targeted outpatient MAP modulation in patients with cirrhosis.

Abstract P305: Room for Improved Secondary Prevention of Major Cardiovascular Events Among the Population With New Onset Diabetes: A Longitudinal Latent Class Trajectory Analysis

Background: After a diagnosis of diabetes, specialist physicians may play a key role in the secondary prevention of major cardiovascular events (MACE). Yet, trajectories of visits to specialists are heterogenous and their efficacy in the prevention of MACE remains unexplored. Goal: To assess whether trajectories of visits to specialists are associated with MACE among new cases of diabetes. Methods: Using the Quebec Integrated Chronic Disease Surveillance System, we identified new cases of diabetes ≥20 years old during fiscal year 2013, who had no prior history of MACE (ischemic cardiopathy, stroke, myocardial infarction or cardiovascular death). Firstly, individual trajectories according to the presence/absence of ≥1 ambulatory visit to a specialist (cardiologist, internist, endocrinologist) were compiled over consecutive 3-month periods up to 2 years following diagnosis. Patients with no visit were compiled in a “primary care only” group, while others were classified in groups using latent class growth analysis. Patients who had a MACE during this period were excluded. Secondly, the risk of MACE occuring after the 2 years following diagnosis up to December 31 st 2019 was compared between groups using a marginal Cox proportional hazards regression model, adjusted with inverse probability weighting and providing adjusted hazard ratio (aHR) with 95% confidence intervals (CI). Results: Among the 24,782 patients included, 5 groups were identified ( Figure 1 ). A total of 2,837 MACE occurred. Compared with the “primary care only group”, those who consulted a specialist were at higher risk of MACE (Regular/frequent visits: aHR: 1.50 [95% CI: 1.26 to 1.66]; Late visits: aHR: 1.41 [1.13 to 1.73]; Regular/sparce visits: 1.38 [1.27 to 1.51]; Early visits: 1.36 [1.19 to 1.54]), while no difference was observed between these groups. Conclusions: Although confounding by indication cannot be totally ruled out, these results may suggest room for improvement in the secondary prevention of MACE after a diabetes diagnosis.

Patterns of comorbidities differentially affect long-term functional evolution and disease activity in patients with ‘difficult to treat’ rheumatoid arthritis

BackgroundCharacterisation of the long-term outcome of patients with ‘difficult to treat’ (D2T) rheumatoid arthritis and factors contributing to its evolution are unknown. Herein, we explored the heterogeneity and contributing factors...

Heterogeneity in glycaemic control in children and adolescents with type 1 diabetes: A latent class trajectory analysis of Danish nationwide data.

Suboptimal glycaemic control in children and adolescents with type 1 diabetes is prevalent and associated with increased risk of diabetes-related complications and mortality later in life. First, we aimed to identify distinct glycated haemoglobin (HbA1c) trajectories in children and adolescents (2-19 years) with type 1 diabetes. Second, we examined their associations with clinical and socio-demographic factors. Data were obtained from the Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids) comprising all Danish children and adolescents diagnosed with type 1 diabetes from 1996 to 2019. Subgroups of distinct mean trajectories of HbA1c were identified using data-driven latent class trajectory modelling. A total of 5889 children (47% female) had HbA1c measured a median of 6 times (interquartile range 3-8) and contributing to 36,504 measurements. We identified four mean HbA1c trajectories, referred to as 'Stable but elevated HbA1c' (83%), 'Increasing HbA1c' (5%), 'Late HbA1c peak' (7%), and 'Early HbA1c peak' (5%). Compared to the 'Stable but elevated HbA1c' group, the three other groups presented rapidly deteriorating glycaemic control during late childhood or adolescence, had higher HbA1c at study entry, and included fewer pump users, higher frequency of inadequate blood glucose monitoring, more severe hypoglycaemic events, lower proportions with Danish origin, and worse educational status of parents. The groups also represented significant differences by healthcare region. Children and adolescents with type 1 diabetes experience heterogenous trajectories with different timings and magnitudes of the deterioration of HbA1c levels, although the majority follow on average a stable, yet elevated HbA1c trajectory. The causes and long-term health implications of these heterogenous trajectories need to be addressed.

Predictors of preparedness for recovery following colorectal cancer surgery: a latent class trajectory analysis

Aim With an interest in providing knowledge for person-centred care, our overall goal is to contribute a greater understanding of diversity among patients in terms of their preparedness before and up to six months after colorectal cancer surgery. Our aim was to describe and provide a tentative explanation for differences in preparedness trajectory profiles. Material and methods The study was explorative and used prospective longitudinal data from a previously published intervention study evaluating person-centred information and communication. The project was conducted at three hospitals in Sweden. Patient-reported outcomes measures, including the Longitudinal Preparedness for Colorectal Cancer Surgery Questionnaire, were collected before surgery, at discharge, and four to six weeks, three months, and six months after surgery. Clinical data were retrospectively obtained from patients’ medical records. We used latent class growth models (LCGMs) to identify latent classes that distinguish subgroups of patients who represent different preparedness trajectory profiles. To determine the most plausible number of latent classes, we considered statistical information about model fit and clinical practice relevance. We used multivariable regression models to identify variables that explain the latent classes. Results The sample (N = 488) comprised people with a mean age of 68 years (SD = 11) of which 44% were women. Regarding diagnoses, 60% had colon cancer and 40% rectal cancer. The LCGMs identified six latent classes with different preparedness for surgery and recovery trajectories. The latent classes were predominantly explained by differences in age, sex, physical classification based on comorbidities, treatment hospital, global health status, distress, and sense of coherence (comprehensibility and meaningfulness). Conclusion Contrary to the received view that emphasizes standardized care practices, our results point to the need for adding person-centred and tailored approaches that consider individual differences in how patients are prepared before and during the recovery period related to colorectal cancer surgery.

Associations between long-term blood pressure trajectory and all-cause and CVD mortality among old people in China.

Optimal blood pressure (BP) management strategy among the elderly remains controversial, with insufficient consideration of long-term BP trajectory. This study aimed to identify BP trajectory patterns as well as terminal BP trajectory among the Chinese elderly and to explore the relationships between BP trajectories and all-cause mortality and cardiovascular disease (CVD) mortality. We included 11,181 participants older than 60 at baseline (mean age, 80.98 ± 10.71) with 42,871 routine BP measurements from the Chinese Longitudinal Healthy Longevity Survey. Latent class trajectory analysis and Cox proportional hazard model were conducted to identify trajectory patterns and their associations with mortality. Furthermore, we also applied mixed-effects model to identify terminal BP trajectories among the elderly. Compared with stable at normal high level trajectory, excess systolic BP (SBP) trajectory with decreasing trend was associated with a 34% (HR = 1.34, 95% CI: 1.23-1.45) higher risk of all-cause mortality. Considering the competing risk of non-CVD death, excess BP trajectory with decreasing trend had a more pronounced effect on CVD mortality, in which HR (95% CI) was 1.67 (1.17, 2.37). Similar results were also found in diastolic BP (DBP), pulse pressure (PP), and mean arterial pressure (MAP) trajectories. We further conducted a mixed-effects model and observed that SBP and PP trajectories first increased and began to decline slightly six years before death. In contrast, DBP and MAP showed continuous decline 15 years before death. Long-term BP trajectory was associated with all-cause mortality, especially CVD mortality. Keeping a stable BP over time may be an important way for CVD prevention among the elderly.

413-P: Intensive Insulin Therapy Delays the “Breakpoint” to Progressive Kidney Function Decline—New Findings and Implications of eGFR Trajectory Analysis in DCCT/EDIC Data

Patterns of kidney function decline vary among those with T1D. End-stage kidney disease (ESKD) develops after progressive kidney function decline that begins when kidney function is normal, regardless of albuminuria. We aimed to determine if these findings were observed in the DCCT/EDIC cohort, which enrolled 1,441 individuals and randomly assigned them to intensive insulin therapy (n=711) or conventional insulin therapy (n=730). Baseline mean eGFR and AER were 125 ml/min/1.73m2 and 12 mg/24 hours, respectively. During 27 years of follow-up 129 individuals reached reduced eGFR &amp;lt;60ml/min/1.73m2 or ESKD. For these individuals we applied latent class trajectory analysis minimizing sum of squares of linear spline models with varying knot placement to identify patterns of eGFR decline. We identified two patterns: i) slow decline without eGFR breakpoint (n=56) and ii) fast decline with clear breakpoint (n=73). Slow decliners reached reduced eGFR but rarely ESKD (2%), while many fast decliners progressed to ESKD (35%) within 5-15 years after the breakpoint. Fast decline was less frequent in intensive compared to conventional insulin therapy [26 (3.7%) vs 47 (6.4%), respectively, p=0.022] and had longer median time from enrollment to breakpoint (18 vs 13 years, respectively, p=0.0004). However, the slope of annual loss of eGFR after breakpoint did not differ. In conclusion, we identified a unique phenotype - the “breakpoint” to fast decline in eGFR - as the main predictor of ESKD in T1D. This breakpoint started while eGFR was normal, subsequent decline was linear, and the onset of the breakpoint was substantially delayed by intensive insulin therapy rather than the slope of decline itself. Research on biomarkers that predict the onset of the eGFR ‘breakpoint’ is needed. Disclosure K.Ihara: None. J.K.Skupien: None. E.Satake: None. B.A.Perkins: Advisory Panel; Dexcom, Inc., Insulet Corporation, Novo Nordisk, Sanofi, Vertex Pharmaceuticals Incorporated, Other Relationship; Abbott, Medtronic, Sanofi, Research Support; Novo Nordisk, Bank of Montreal (BMO). A.Krolewski: None.

Association between war-related traumatic events and blood pressure trajectory: a population-based study among the mid-aged and older Palestinian adults living in Gaza.

Little is known regarding health status in an environment characterized by instability and ongoing war risks. This study investigated hypertension disease burden and associations of war-related traumatic events with blood pressure (BP) trajectory over time amongst mid-aged and older Palestinian adults in Gaza Strip. From nine primary healthcare centers, medical records between 2013 and 2019 were collected for 1,000 mid-aged and older Palestinian adults living in Gaza. Multinomial logistic regression analysis examined associations between war-related traumatic events and BP trajectories derived using latent class trajectory analysis (LCTA). The prevalence of self-reported injury (of participants or their family members), death of a family member, and violence due to house bombing was 51.4%, 54.1%, and 66.5%, respectively. In total, 22.4% and 21.4% of participants had constant-very-high (CVH) systolic BP (SBP) (>160 mmHg) and diastolic BP (DBP) (>95 mmHg), and normal-stable SBP and DBP was found only 54.9% and 52.6%, respectively. Injury (participants or family members), death of a family member, and violence due to house bombing during wars were associated with CVH SBP with odds ratios [95 CI, OR = 1.79 (1.28-2.48), 1.90 (1.36-2.65), and 1.44 (1.01-2.05)], respectively. The corresponding figures were [95 CI, OR = 1.92 (1.36-2.71), 1.90 (1.35-2.68), and 1.62 (1.13-2.38)] for CVH DBP. Living in debt was positively associated with CVH SBP, [95 CI, OR = 2.49 (1.73-3.60)] and CVH DBP, [95 CI, OR = 2.37 (1.63-3.45)]. The disease burden related to war-related traumatic events is high and positively related to adverse BP trajectory among the mid-aged and older Palestinians living in Gaza. Intervention programs are needed to manage and prevent chronic diseases in this vulnerable population.

Trajectories of Drug Use and Depressive Symptoms among Latinx Youth and Sexual Minority Youth.

Drug use and depression co-occur and disproportionately affect Latinx sexual minority youth relative to their heterosexual Latinx peers. However, heterogeneity in co-occurring patterns of drug use and depressive symptoms is unknown. The objective of the current study was to identify patterns of drug use and depressive symptom trajectories and examine how these patterns varied between Latinx sexual minority youth and Latinx non-sexual minority youth. Latent class trajectory analysis identified distinct patterns of drug use and depressive symptom trajectories among 231 Latinx adolescents (Latinx sexual minority youth: n = 46, 21.4%; Latinx non-sexual minority youth: n = 169, 78.6%). After identifying class mean trajectories, we examined differences in mean trajectories across groups. A 3-class model was selected as the optimal class trajectory model for both groups, yet classes and trajectories differed. There were differences in initial levels of depression and drug use trajectories between both groups, as well as differences in patterns of drug use trajectories between both groups in two of the three classes. Given the variation in trajectory patterns, there is a need for practitioners to consider the unique needs of both groups to inform the development of preventive interventions for these two populations.

Exploration of model misspecification in latent class methods for longitudinal data: Correlation structure matters.

Modeling longitudinal trajectories and identifying latent classes of trajectories is of great interest in biomedical research, and software to identify latent classes of such is readily available for latent class trajectory analysis (LCTA), growth mixture modeling (GMM) and covariance pattern mixture models (CPMM). In biomedical applications, the level of within-person correlation is often non-negligible, which can impact the model choice and interpretation. LCTA does not incorporate this correlation. GMM does so through random effects, while CPMM specifies a model for within-class marginal covariance matrix. Previous work has investigated the impact of constraining covariance structures, both within and across classes, in GMMs-an approach often used to solve convergence problems. Using simulation, we focused specifically on how misspecification of the temporal correlation structure and strength, but correct variances, impacts class enumeration and parameter estimation under LCTA and CPMM. We found (1) even in the presence of weak correlation, LCTA often does not reproduce original classes, (2) CPMM performs well in class enumeration when the correct correlation structure is selected, and (3) regardless of misspecification of the correlation structure, both LCTA and CPMM give unbiased estimates of the class trajectory parameters when the within-individual correlation is weak and the number of classes is correctly specified. However, the bias increases markedly when the correlation is moderate for LCTA and when the incorrect correlation structure is used for CPMM. This work highlights the importance of correlation alone in obtaining appropriate model interpretations and provides insight into model choice.

Do Patterns of Early Disease Severity Predict Grade 12 Academic Achievement in Youths With Childhood-Onset Chronic Rheumatic Diseases?

To test the association of early disease severity with grade 12 standards test performance in individuals with childhood-onset chronic rheumatic diseases (ChildCRDs), including juvenile arthritis and systemic autoimmune rheumatic diseases. We used linked provincial administrative data to identify patients with ChildCRDs born between 1979 and 1998 in Manitoba, Canada. Primary outcomes were Language and Arts Achievement Index (LAI) scores and Math Achievement Index (MAI) scores from grade 12 standards test results as well as enrollment data. The secondary outcome was enrollment in grade 12 by 17 years of age. Latent class trajectory analysis identified disease severity groups using physician visits following diagnosis. Multivariable linear regression tested the association of disease severity groups with LAI and MAI scores, and logistic regression tested the association of disease severity with age-appropriate enrollment, after adjusting for sociodemographic factors and psychiatric morbidities. The study cohort included 541 patients, 70.1% of whom were female. A 3-class trajectory model provided the best fit; it classified 9.7% of patients as having severe disease, 54.5% as having moderate disease, and 35.8% as having mild disease. After covariate adjustment, severe disease was associated with poorer LAI and MAI scores but not with age-appropriate enrollment. Among patients with ChildCRDs, those with severe disease performed more poorly on grade 12 standards tests, independent of sociodemographic and psychiatric risk factors. Clinicians should work with educators and policy makers to advocate for supports to improve educational outcomes of patients with ChildCRDs.

Variability in recovery following microdiscectomy and postoperative physiotherapy for lumbar radiculopathy: A latent class trajectory analysis

ObjectivesThe clinical course of lumbar radiculopathy following microdiscectomy and post-operative physiotherapy varies substantially. No prior studies assessed this variability by deriving outcome trajectories. The primary aims of this study were to evaluate the variability in long-term recovery after lumbar microdiscectomy followed by post-operative physiotherapy and to identify outcome trajectories. The secondary aim was to assess whether demographic, clinical characteristics and patient-reported outcome measures routinely collected at baseline could predict poor outcome trajectories. MethodsWe conducted a prospective cohort study with a 24-month follow-up. We included 479 patients with clinical signs and symptoms of lumbar radiculopathy confirmed by Magnetic Resonance Imaging findings, who underwent microdiscectomy and post-operative physiotherapy. Outcomes were leg pain and back pain measured with Visual Analogue Scales, and disability measured with the Roland-Morris Disability Questionnaire. Descriptive statistics were performed to present the average and the individual clinical course. A latent class trajectory analysis was conducted to identify leg pain, back pain, and disability outcome trajectories. The best number of clusters was determined using the Bayesian Information Criterion, Akaike’s information criteria, entropy, and overall interpretability. Prediction models for poor outcome trajectories were assessed using multivariable logistic regression analyses. ResultsSeveral outcome trajectories were identified. Most patients were assigned to the ‘large improvement’ trajectory (leg pain: 79.3%; back pain: 70.2%; disability: 59.5% of patients). Smaller proportions of patients were assigned to the ‘moderate improvement’ trajectory (leg pain: 7.9%; back pain: 10.6%; disability: 20.7% of patients), the ‘minimal improvement’ trajectory (leg pain: 4.9%, back pain: 6.7%, disability: 16.3% of patients) and the ‘relapse’ trajectory (leg pain: 7.9%; back pain: 12.5%; disability: 3.5%). Approximately one-third of patients (32.6%) belonged to one or more than one poor outcome trajectory. Patients with previous treatment (prior back surgery, injection therapy, and medication use) and those who had higher baseline pain and disability scores were more likely to belong to the poor outcome trajectories in comparison to the large improvement trajectories in back pain, leg pain and disability, and the moderate improvement trajectory in disability. The explained variance (Nagelkerke R2) of the prediction models ranged from 0.06 to 0.13 and the discriminative ability (Area Under the Curve) from 0.66 to 0.73. ConclusionThe clinical course of lumbar radiculopathy varied following microdiscectomy and post-operative physiotherapy, and several outcome trajectories could be identified. Although most patients were allocated to favorable trajectories, one in three patients was assigned to one or more poor outcome trajectories following microdiscectomy and post-operative physiotherapy for lumbar radiculopathy. Routinely gathered data were unable to predict the poor outcome trajectories accurately. Prior to surgery, clinicians should discuss the high variability and the distinctive subgroups that are present in the clinical course with their patients.

Identification of glucose and insulin patterns during A 5-H glucose tolerance test and association with cardiometabolic risk factors.

Insulin resistance is key in the pathogenesis of the metabolic syndrome and cardiovascular disease. We aimed to identify glucose and insulin patterns after a 5-h oral glucose tolerance test (OGTT) in individuals without diabetes and to explore cardiometabolic risk factors, beta-cell function, and insulin sensitivity in each pattern. We analyzed the 5-h OGTT in a tertiary healthcare center. We identified classes using latent class trajectory analysis and evaluated their association with cardiometabolic risk factors, beta-cell function, and insulin sensitivity surrogates by multinomial logistic regression analysis. We included 1088 5-h OGTT performed between 2013 and 2020 and identified four classes. Class one was associated with normal insulin sensitivity and secretion. Class two showed hyperglycemia, dysinsulinism, and a high-risk cardiometabolic profile (obesity, hypertriglyceridemia, and low high-density lipoprotein [HDL] cholesterol). Class three included older individuals, a higher proportion of males, and a greater prevalence of hypertension, hyperglycemia, hyperinsulinemia, and postprandial hypoglycemia. Finally, class four showed hyperglycemia, dysinsulinism, and hyperinsulinemia; this class had the worst cardiometabolic profile (a high proportion of males, greater age, hypertension, obesity, hypertriglyceridemia, and low HDL cholesterol, p < 0.001 vs. other classes). The latent class analysis approach allows the identification of groups with an adverse cardiometabolic risk factor, and who might benefit from frequent follow-ups and timely multidisciplinary interventions.

Long-term waist circumference trajectories and body mass index with all-cause mortality in older Chinese adults: a prospective nationwide cohort study

BackgroundsAbdominal obesity has been linked to risk of mortality, but whether and how trajectory of waist circumstance (WC) underpins this association remains unclear. The study aimed to identify long-term WC change trajectories and examine their association and joint effect with body mass index (BMI) on mortality among Chinese older adults.MethodsThis present study included participants 60 years of age or older from China Health and Nutrition Survey (CHNS) from 1991 to 2015. The duration of follow-up was defined as period from the first to latest visit date attended with information on mortality, end of follow-up, or loss to follow-up (censoring). Latent class trajectory analysis (LCTA) was used to assess the changes of WC trajectories overtime. Cox proportional hazard models were used to assess hazard ratios (HRs) and corresponding 95% confidence internal (CIs) for mortality.ResultsA total of 2601 participants with 8700 visits were included, and 562 mortality (21.6%) occurred during a median follow-up of 8.7 years. Using a group-based modeling approach, four distinct trajectories of WC change among Chinese older adults were identified as loss (13.5%), stable (46.8%), moderate gain (31.2%) and substantial gain (8.5%). With WC stable group as reference, the multivariable adjusted HRs for mortality were 1.34(95%CI:1.01-1.78) in loss group, 1.13(0.91-1.41) in moderate gain and 1.54(1.12-2.12) in substantial gain group. Compared with participants with normal BMI at baseline and maintained WC stable, the risk of mortality generally increased for all WC change group in initial overweight/obesity individuals, and the highest risk were observed for WC loss and stable pattern (HR:2.43, 95%CI: 1.41–4.19; HR:1.67 (1.07–2.60)).ConclusionsIn older Chinese, both long-term WC loss and substantial gain conferred excess risk for mortality. The baseline BMI might modify the effect as overweight individuals had a greater risk imposed by WC loss than those in normal weight. Maintaining stable WC and normal weight might be necessary to reduce the risk of mortality.