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

AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Individual and dual trajectories of insomnia symptoms and body mass index before and after retirement and their associations with changes in subjective cognitive functioning.

BACKGROUND: We examined individual and dual trajectories of insomnia symptoms and body mass index (BMI) before and after retirement, and their associations with changes in subjective cognitive functioning after retirement. METHODS: We used the Helsinki Health Study's (n = 2360, 79% women, aged 40-60 at baseline, Finland) repeated surveys to identify the developmental patterns of insomnia symptoms and BMI (2000-2017) and changes in subjective cognitive functioning (2017-2022). We analysed the data using latent group-based dual trajectory modelling and logistic regression analysis. RESULTS: Three latent groups were identified for insomnia symptoms (stable low, decreasing and increasing symptoms) and BMI (stable healthy weight, stable overweight and stable obesity). Insomnia symptoms were associated with declining subjective cognitive functioning and largely explained the effects in the dual models. CONCLUSION: The association between dual trajectories of insomnia symptoms and BMI with subjective cognitive decline is dominated by insomnia symptoms.

Maternal diet quality trajectories from pregnancy to 3.5 years postpartum and associated maternal factors.

PURPOSE: This study examined maternal diet quality trajectories from pregnancy to 3.5 years postpartum and associated maternal factors. METHODS: Data of 473 Australian women from the Healthy Beginnings Trial were used. A food frequency questionnaire collected dietary intake in pregnancy and 1, 2 and 3.5 years postpartum. Diet quality scores were calculated using the 2013 Dietary Guideline Index (DGI-2013) and RESIDential Environments Guideline Index (RDGI). Group-based trajectory modelling identified diet quality trajectories from pregnancy to 3.5 years postpartum. Multivariable logistic regression investigated factors associated with maternal diet quality trajectories. RESULTS: Two stable trajectories of low or high diet quality were identified for the DGI-2013 and RDGI. Women who smoked had higher odds of following the low versus the high DGI-2013 (OR 1.77; 95%CI 1.15, 2.75) and RDGI (OR 1.80; 95%CI 1.17, 2.78) trajectories, respectively. Women who attended university had lower odds of following the low versus the high DGI-2013 (OR 0.41; 95%CI 0.22, 0.76) and RDGI (OR 0.38; 95%CI 0.21, 0.70) trajectories, respectively. Women who were married had lower odds of following the low versus the high DGI-2013 trajectory (OR 0.39; 95%CI 0.17, 0.89), and women who were unemployed had higher odds of following the low versus the high RDGI trajectory (OR 1.78; 95%CI 1.13, 2.78). Maternal age, country of birth, household composition and pre-pregnancy body mass index were not associated with diet quality trajectories. CONCLUSION: Maternal diet quality trajectories remained stable from pregnancy to 3.5 years postpartum. Women who smoked, completed high school or less, were not married or were unemployed tended to follow low, stable diet quality trajectories.

Prediction of damage trajectories in systemic sclerosis using group-based trajectory modelling.

OBJECTIVES: Damage accrual in SSc can be tracked using the Scleroderma Clinical Trials Consortium Damage Index (DI). Our goal was to develop a prediction model for damage accrual in SSc patients with early disease. METHODS: Using patients with <2 years disease duration from Canada and Australia as a derivation cohort, and from the Netherlands as a validation cohort, we used group-based trajectory modelling (GBTM) to determine 'good' and 'bad' latent damage trajectories. We developed a prediction model from this analysis and applied it to patients from derivation and validation cohorts. We plotted the actual DI trajectories of the patients predicted to be in 'good' or 'bad' groups. RESULTS: We found that the actual trajectories of damage accumulation for lcSSc and dcSSc were very different, so we studied each subset separately. GBTM found two distinct trajectories in lcSSc and three in dcSSc. We collapsed the two worse trajectories in the dcSSc into one group and developed a prediction model for inclusion in either 'good' or 'bad' trajectories. The performance of models using only baseline DI and sex was excellent with ROC AUC of 0.9313 for lcSSc and 0.9027 for dcSSc. Using this model, we determined whether patients would fall into 'good' or 'bad' trajectory groups and then plotted their actual trajectories which showed clear differences between the predicted 'good' and 'bad' cases in both derivation and validation cohorts. CONCLUSIONS: A simple model using only cutaneous subset, baseline DI and sex can predict damage accumulation in early SSc.

Medication non-adherence patterns and profiles for patients with incident myocardial infarction: Observations from a large multi-morbid US population.

BACKGROUND: Consistent adherence levels to multiple long-term medications for patients with cardiovascular conditions are typically advocated in the range of 50% or higher, although very likely to be much lower in some populations. We investigated this issue in a large cohort covering a broad age and geographical spectrum, with a wide range of socio-economic disability status. METHODS: The patients were drawn from three different health plans with a varied mix of socio-economic/disability levels. Adherence patterns were examined on a monthly basis for up to 12 months past the index date for myocardial infarction (MI) using longitudinal analyses of group-based trajectory modelling. Each of the non-adherent patterns was profiled from comorbid history, demographic and health plan factors using main effect logistic regression modelling. Four medication classes were examined for MI: betablockers, statin, ACE inhibitors and anti-platelets. RESULTS: The participant population for the MI/non-MI cohorts was 1,987,605 (MI cohort: mean age 62 years, 45.9% female; non-MI cohort: mean age 45 years, 55.3% females). Cohorts characterized by medication non-adherence dominated the majority of MI population with values ranging from 74% to 82%. There were four types of consistent non-adherence patterns as a function of time for each medication class: fast decline, slow decline, occasional users and early gap followed by increased adherence. The characteristics of non-adherence profiles eligible for improvement included patients with a prior history of hypertension, diabetes mellitus and stroke as co-morbidities, and Medicare plan. CONCLUSIONS: We found consistent patterns of intermediate non-adherence for each of four drug classes for MI cohorts in the order of 56% who are eligible for interventions aimed at improving cardiovascular medication adherence levels. These insights may help improve cardiovascular medication adherence using large medication non-adherence improvement programs.

Adherence levels and patterns for multiple cardiac medications prescribed to patients with incident atrial fibrillation events.

AIMS: Using advanced longitudinal analyses, this real-world investigation examined medication adherence levels and patterns for incident atrial fibrillation (AF) patients with significant cardiovascular and noncardiovascular multimorbid conditions for each of 5 medication classes (ß-blockers, calcium channel blockers/digoxin, antiarrhythmics, anticoagulants, antiplatelets). The population was derived from a large cohort covering a wide age spectrum/diversified US geographical areas/wide range of socioeconomic-disability status. METHODS: The patients were drawn from 3 different health plans. Adherence was defined in terms of the proportion of day covered (PDC), and its patterns were modelled in terms of group-based trajectory, with each pattern profiled in terms of comorbid history, demographic variables and health plan factors using multinomial regression modelling. RESULTS: The total population consisted of 1 978 168 patients, with the AF cohort being older (average age of 64.6 years relative to 44.7 years for the non-AF cohort) and having fewer females (47.8% relative to 55.4 for the non-AF cohort). The AF cohort had significant cardiovascular/noncardiovascular multimorbidities and was much sicker than the non-AF cohort. A 6-group based trajectory solution appears to be the most logical outcome for each medication class according to assessed criteria. For each medication class, it consisted of one consistent adherent group (PDC ≥ 0.84), one fast declining group (PDC ≤ 0.11) and 4 intermediate nonadherence groups (slow decline [0.30-0.74 PDC range], occasional users [0.24-0.55 PDC range] and early gap/increased adherence [0.62-0.75]). The most consistent adherent groups were much lower than 50% of the total population and equal to 12.5-27.0% of the population, with the fast declining nonadherent pattern in the 5.6-35.0% of the population and the intermediate nonadherence equal to ~61% of the population. CONCLUSION: Our findings confirm that medication adherence is of major concern among multimorbid patients, with adherence levels lower much than those reported in the literature. There are 3 patterns of intermediate nonadherence (slow decline, occasional users, early gap/increased adherence), which were found to be eligible for interventions aimed at improving their adherence levels for each medication class. This may help improve cardiovascular medication adherence using large medication nonadherence improvement programmes.

Evaluation and interpretation of latent class modelling strategies to characterise dietary trajectories across early life: a longitudinal study from the Southampton Women's Survey.

There is increasing interest in modelling longitudinal dietary data and classifying individuals into subgroups (latent classes) who follow similar trajectories over time. These trajectories could identify population groups and time points amenable to dietary interventions. This paper aimed to provide a comparison and overview of two latent class methods: group-based trajectory modelling (GBTM) and growth mixture modelling (GMM). Data from 2963 mother-child dyads from the longitudinal Southampton Women's Survey were analysed. Continuous diet quality indices (DQI) were derived using principal component analysis from interviewer-administered FFQ collected in mothers pre-pregnancy, at 11- and 34-week gestation, and in offspring at 6 and 12 months and 3, 6-7 and 8-9 years. A forward modelling approach from 1 to 6 classes was used to identify the optimal number of DQI latent classes. Models were assessed using the Akaike and Bayesian information criteria, probability of class assignment, ratio of the odds of correct classification, group membership and entropy. Both methods suggested that five classes were optimal, with a strong correlation (Spearman's = 0·98) between class assignment for the two methods. The dietary trajectories were categorised as stable with horizontal lines and were defined as poor (GMM = 4 % and GBTM = 5 %), poor-medium (23 %, 23 %), medium (39 %, 39 %), medium-better (27 %, 28 %) and best (7 %, 6 %). Both GBTM and GMM are suitable for identifying dietary trajectories. GBTM is recommended as it is computationally less intensive, but results could be confirmed using GMM. The stability of the diet quality trajectories from pre-pregnancy underlines the importance of promotion of dietary improvements from preconception onwards.

Trajectories of dietary patterns from pregnancy to 12 years post-pregnancy and associated maternal characteristics: evidence from the Avon Longitudinal Study of Parents and Children.

PURPOSE: Dietary patterns (DPs) during pregnancy have been well researched. However, little is known about maternal diet after pregnancy. The aim of the study was to explore maternal DPs longitudinally, examine trajectories over 12 years after pregnancy and identify associated factors. METHODS: Of 14,541 pregnant women enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) complete dietary information was available for 5336 women. Principal components analysis (PCA) was used to derive DPs. DP scores at each time point were used to create DP trajectories using group-based trajectory modelling (GBTM). Multinomial logistic regression assessed the association with maternal factors. RESULTS: A total of six distinct DPs were identified over time with different numbers of DPs at each time point. The "healthy" and "processed" DPs persisted over the 12-year post-pregnancy. Three trajectories of "healthy" and "processed" DPs were identified from GBTM. Half the women were on the moderately healthy DP trajectory with 37% on the lower trajectory and 9% on the higher healthy DP trajectory. 59% of women were on the lower processed DP trajectory with 38% on the moderate trajectory and 3.3% on the higher processed DP trajectory. Low educational attainment, low social class and smoking in pregnancy were independently associated with being on a less favourable DP trajectory over the 12 years. CONCLUSION: Health professionals should provide support on smoking cessation along with healthy eating advice during ante-natal counselling. Continued support on eating healthily after pregnancy would be beneficial for mothers and families.

Trajectories of psychological distress during the COVID-19 pandemic among community-dwelling older adults in Quebec: A longitudinal study.

OBJECTIVE: The COVID-19 pandemic and its associated public health measures may increase the risk for psychological distress among vulnerable older adults. This longitudinal study aimed to identify predictors of psychological distress trajectories among community-dwelling older adults in Quebec, Canada. METHODS: The study spanned four time points across 13 months and three waves of the COVID-19 pandemic. The sample included 645 community-dwelling older adults ages 60 years and older in Quebec. Participants completed telephone-based interviews that included the Kessler 6-item Psychological Distress Scale (K6) to assess psychological distress at each time point as well as information on socioeconomic, medical, psychological and COVID-19 related factors. Group-based trajectory modelling was used to identify distinct trajectories of psychological distress across time. RESULTS: Three group-based trajectories of psychological distress were identified: the resilient (50.5%), reactive (34.9%), and elevated distress groups (14.6%). Individuals with mobility issues, insomnia symptoms, COVID-19 related acute stress, general health anxiety, increased loneliness symptoms, and those unable to use technology to see others were more likely to be in the reactive and elevated groups than the resilient group. Those with past mental health problems had uniquely increased odds of being in the reactive group compared to the resilient group. Individuals living in poverty and those who reported taking psychotropic medication had increased odds of being in the elevated distress group compared to the resilient group. CONCLUSION: These findings characterized distinct trajectories of psychological distress in older adults and identified risk factors for elevated distress levels.

Longitudinal lung function in urban firefighters: A group-based multi-trajectory modelling approach.

BACKGROUND AND OBJECTIVE: Urban firefighters are routinely exposed to both physical and chemical hazards that can negatively impact lung health, but it is unclear if firefighters experience accelerated decline in spirometry parameters due to chronic exposure and acute insults. This study aimed to describe sub-groups of firefighters with differing spirometry trajectories and examine the relationship between the identified trajectories and demographic, lifestyle and occupational characteristics. METHODS: Data from six waves of the Respiratory Function Measurement and Surveillance for South Australian Metropolitan Fire Service Study (2007-2019) were used to identify spirometry parameter z-score trajectories, using group-based multi-trajectory modelling (GBMTM). Analysis of variance and chi-square statistics were used to assess trajectory group differences in baseline self-reported demographic, lifestyle and occupational characteristics. RESULTS: In the 669 included firefighters, we identified five trajectories for the combination of Forced Expiratory Volume in the first second z-score (FEV1 z), Forced Vital Capacity z-score (FVCz) and the ratio of FEV1 and FVC z-score (FEV1 /FVCz). There were three stable trajectories of low, average and very high lung function and two declining trajectories of average and high lung function. Analysis of subgroup characteristics revealed no significant differences between expected and actual group proportions for the occupational characteristics of years of service and respiratory protection use. Significant differences were seen in respiratory health and body mass index. CONCLUSION: GBMTM defined distinct, plausible spirometry trajectory sub-groups. Firefighter longitudinal spirometry trajectory group membership was associated with BMI and respiratory disease or symptoms but not with self-reported smoking history or occupational factors.

Trajectories of housing affordability and mental health problems: a population-based cohort study.

PURPOSE: With housing costs increasing faster than incomes and a limited supply of social housing options, many households face unaffordable housing. Housing affordability problems may negatively impact mental health; however, longitudinal evidence is limited. This study investigates the association between trajectories of housing affordability problems and mental health. METHODS: We used data from 30,025 households from Understanding Society, a longitudinal household survey from the UK. Participants spending 30% or more of household income on housing were categorised as facing housing affordability problems. We estimated group-based trajectories of housing affordability problems from 9 waves of data (2009-2019). We used linear regression to calculate the association between the trajectories and mental health problems, as measured by General Health Questionnaire (GHQ) score in Wave 10 (2018-2020). RESULTS: We found six distinct trajectories of housing affordability problems. Those in the 'stable low' group had a consistently low probability of affordability problems, whilst those in 'high falling' group had a sustained high probability in the earlier waves of the study, subsequently decreasing over time. The adjusted analysis showed that trajectory group membership over the first nine waves of data predicted GHQ score in 2018-2020 (Wave 10). Compared to the 'stable low' group, those in the 'high falling' group had a GHQ score that was 1.06 (95% CI 0.53-1.58) points higher. CONCLUSION: This study provides evidence that sustained exposure to housing affordability problems is associated with long-term worse mental health, even in the absence of more recent problems.

A longitudinal area classification of migration in Great Britain: Testing the application of Group-Based Multi-Trajectory Modelling.

The migration of people affects the geographical distribution of the population and the demographic composition of areas over the short, medium and long terms. To recognise and respond to the corresponding needs and challenges, including consequences for service provision, social cohesion and population health, there is a continuing need to understand migration patterns of the past and present. Area classifications are a useful tool to simplify the inherently complex data on migration flows and characteristics. Yet, existing classifications often lack direct migration measures or focus solely on cross-sectional data. This study addresses these limitations by employing Group-Based Multi-Trajectory Modelling (GBMTM) to create a longitudinal, migration-specific classification of Great Britain's wards from 1981 to 2011, using six migration indicators. Using U.K. census data, we reveal six distinct migration clusters that highlight the rapid growth in studentifying neighbourhoods, the continuous influx of migrants into inner cities, and a noticeable North-South divide in terms of movers' tenure enforced by persisting income selectivity. Additionally, the geographical distribution of clusters shows a common pattern in urban areas irrespective of size or location. The longitudinal perspective of our GBMTM classification highlights trends and changes in migration patterns that are not well reflected in either the general purpose or the cross-sectional migration classification that we used as comparators. We conclude that the method presented and the classification generated offer a novel lens on migration and provide new opportunities to explore the effects of migration on a variety of outcomes and at various scales.

Different trajectories of depression, anxiety and anhedonia symptoms in the first 12 months of the COVID-19 pandemic in a UK longitudinal sample.

BACKGROUND: While studies from the start of the COVID-19 pandemic have described initial negative effects on mental health and exacerbating mental health inequalities, longer-term studies are only now emerging. METHOD: In total, 34 465 individuals in the UK completed online questionnaires and were re-contacted over the first 12 months of the pandemic. We used growth mixture modelling to identify trajectories of depression, anxiety and anhedonia symptoms using the 12-month data. We identified sociodemographic predictors of trajectory class membership using multinomial regression models. RESULTS: Most participants had consistently low symptoms of depression or anxiety over the year of assessments (60%, 69% respectively), and a minority had consistently high symptoms (10%, 15%). We also identified participants who appeared to show improvements in symptoms as the pandemic progressed, and others who showed the opposite pattern, marked symptom worsening, until the second national lockdown. Unexpectedly, most participants showed stable low positive affect, indicating anhedonia, throughout the 12-month period. From regression analyses, younger age, reporting a previous mental health diagnosis, non-binary, or self-defined gender, and an unemployed or a student status were significantly associated with membership of the stable high symptom groups for depression and anxiety. CONCLUSIONS: While most participants showed little change in their depression and anxiety symptoms across the first year of the pandemic, we highlight the divergent responses of subgroups of participants, who fared both better and worse around national lockdowns. We confirm that previously identified predictors of negative outcomes in the first months of the pandemic also predict negative outcomes over a 12-month period.

Associations between Body Mass Index Trajectories in the first two years of life and Allergic Rhinitis, Eczema and Food Allergy outcomes up to early adulthood.

BACKGROUND: Early life body mass index (BMI) trajectories influence the risk of asthma at 18 years of age. However, it is unclear if these are also associated with other allergic diseases. OBJECTIVES: We investigated the associations between BMI trajectories and subsequent allergic rhinitis, eczema and food sensitisation/allergies. METHODS: Parent-reported anthropometric data were collected 18 times in the first two years of life from a cohort of 620 participants in a high-risk cohort. Group-based trajectory modelling was applied to develop BMI trajectories. Associations between trajectories and allergic rhinitis, eczema and food sensitisation at 6, 12 and 18 years of age were assessed using logistic regression models. Potential effect modifications by parental allergic disease, sex and allocated infant formula were assessed. RESULTS: We identified five BMI trajectories: average, below average, persistently low, early low and catch up, and persistently high. None showed an association with allergic rhinitis. In participants with maternal allergic rhinitis, 'early-low and catch-up' (OR = 2.83;95%CI 1.34-5.96, Pint  = 0.05) and 'below average' trajectories (OR = 2.39; 1.18-7.23, Pint  = 0.02) were associated with allergic rhinitis at 18 years of age compared with the average trajectory. No associations were observed with eczema or food sensitisation. CONCLUSION: Infants with early-low and catch-up, or below average BMI growth, were at increased risk of allergic rhinitis at 18 years if they had a mother with allergic rhinitis. These results require replication, but suggest that interactions between poor intrauterine growth, failure to thrive and maternal allergies may influence the risk of allergic rhinitis.

Dietary trajectories through the life course: opportunities and challenges.

Studying the dynamic patterns of dietary changes or stability (otherwise known as dietary trajectories) across the life course can provide important information about when and in whom to intervene with nutritional interventions. This article reviews evidence from longitudinal studies that describe dietary trajectories through the different life stages, covering early life, adolescence to young adulthood and from mid to late adulthood. Current findings suggest that the establishment of diet patterns likely occurs before 3 years of age and allude to other potential 'windows of change' in the life course such as the period of 7­9 years of age and during the period of adolescence and early adulthood. Examining diets using various diet parameters appears to be valuable in elucidating different aspects of the diet that can be changed to potentially alter trajectories. In adults, examining long-term diet trends at a population level can reveal shifts in eating patterns as countries undergo epidemiological and nutrition transitions and elucidate the longer-term impact of adherence to particular diets on the development of chronic diseases. While challenges such as the availability of adequate diet data points, consistency in the dietary assessment tools used and the limitations of statistical methods for trajectory modelling remain, integrating diet data with other lifestyle behaviours, high-dimensional biomarkers and genetics data into pattern analyses and examining them from a longitudinal approach, open up potential opportunities to gain deeper insights into diet­disease relationships and support the development of more holistic lifestyle disease prevention recommendations stratified for population groups.

Prospective dietary polyunsaturated fatty acid intake is associated with trajectories of fatty liver disease: an 8 year follow-up study from adolescence to young adulthood.

BACKGROUND AND AIM: Dietary fat intake has long been associated with fatty liver. Our study aimed to determine the effect of dietary fats on longitudinal fatty liver index (FLI) trajectories from adolescence to young adulthood. METHODS: Nine hundred eighty-five participants in the Raine Study, Perth, Western Australia, Australia, had cross-sectional assessments at ages 14, 17, 20 and 22 years, during which anthropometric measurements and blood tests were obtained. FLI trajectories were derived from the longitudinal FLI results. Dietary fat intake was measured with a semi-quantitative food frequency questionnaire at 14 years and log multinominal regression analyses were used to estimate relative risks. RESULTS: Three FLI trajectories were identified and labelled as stable-low (79.1%, N = 782), low-to-high (13.9%, N = 132), and stable-high (7%, N = 71). The low-to-high group associated with an increased intake of the long-chain polyunsaturated fatty acids EPA, DPA and DHA (RR 1.27, 95% CI 1.10-1.48) relative to the stable-low group. Compared to the stable-low group, omega-6 and the ratio of omega-6 to omega-3 in the stable-high group were associated with an increased relative risk of 1.34 (95% CI 1.02-1.76) and 1.10 (95% CI 1.03-1.16), respectively. CONCLUSION: For those at high risk of fatty liver in early adolescence, high omega-6 fatty acid intake and a high ratio of omega-6 to omega-3 fatty acids are associated with increased risk of fatty liver. There should be caution in assuming these associations are causal due to possible undetected and underestimated confounding factors.

Modelling patient trajectories using multimodal information.

BACKGROUND: Electronic Health Records (EHRs) aggregate diverse information at the patient level, holding a trajectory representative of the evolution of the patient health status throughout time. Although this information provides context and can be leveraged by physicians to monitor patient health and make more accurate prognoses/diagnoses, patient records can contain information from very long time spans, which combined with the rapid generation rate of medical data makes clinical decision making more complex. Patient trajectory modelling can assist by exploring existing information in a scalable manner, and can contribute in augmenting health care quality by fostering preventive medicine practices (e.g. earlier disease diagnosis). METHODS: We propose a solution to model patient trajectories that combines different types of information (e.g. clinical text, standard codes) and considers the temporal aspect of clinical data. This solution leverages two different architectures: one supporting flexible sets of input features, to convert patient admissions into dense representations; and a second exploring extracted admission representations in a recurrent-based architecture, where patient trajectories are processed in sub-sequences using a sliding window mechanism. RESULTS: The developed solution was evaluated on two different clinical outcomes, unexpected patient readmission and disease progression, using the publicly available Medical Information Mart for Intensive Care (MIMIC)-III clinical database. The results obtained demonstrate the potential of the first architecture to model readmission and diagnoses prediction using single patient admissions. While information from clinical text did not show the discriminative power observed in other existing works, this may be explained by the need to fine-tune the clinicalBERT model. Finally, we demonstrate the potential of the sequence-based architecture using a sliding window mechanism to represent the input data, attaining comparable performances to other existing solutions. CONCLUSION: Herein, we explored DL-based techniques to model patient trajectories and propose two flexible architectures that explore patient admissions on an individual and sequence basis. The combination of clinical text with other types of information led to positive results, which can be further improved by including a fine-tuned version of clinicalBERT in the architectures. The proposed solution can be publicly accessed at https://github.com/bioinformatics-ua/PatientTM.

Elevated social anxiety symptoms across childhood and adolescence predict adult mental disorders and cannabis use.

AIM: We assessed the heterogeneous development of self-reported social anxiety symptoms across childhood and adolescence (ages 10 to 18; N = 701) and examined whether these groups predicted clinically derived diagnoses of social anxiety disorder (SAD), generalized anxiety disorder (GAD), depressive episodes, panic disorder (PD), agoraphobia, obsessive compulsive disorder (OCD), and substance use in adulthood (ages 19 to 22). RESULTS: Three distinct social anxiety symptom trajectories were found: a high increasing group (15.5%), a moderate group (37.3%), and a low group (47.2%). The high increasing and moderate trajectory groups were differentiated from the low trajectory group on the adult mental disorders examined: SAD (high OR = 15.74; moderate OR = 11.72), GAD (high OR = 13.08; moderate OR = 8.98), depressive episode (high OR = 19.75), PD (high OR = 8.43; moderate OR = 5.90), agoraphobia (high OR = 16.39; moderate OR = 9.68), and OCD (high OR = 3.49; moderate OR = 2.98). The high and moderate groups were not differentiated on SAD, GAD, PD, or OCD but were differentiated on depressive episodes (OR = 3.24). Relative to the low and moderate trajectory groups, the high increasing social anxiety symptoms trajectory group also predicted cannabis use, but not alcohol use in adulthood. Gender, ethnicity, household income, and parental education were accounted for when predicting adult outcomes. CONCLUSION: These results highlight the importance of early treatment of symptoms of childhood social anxiety in the prevention of mental health problems in adulthood.

Three-year trajectories in functional limitations and cognitive decline among Dutch 75+ year olds, using nine-month intervals.

BACKGROUND: Using longitudinal panel data, we aimed to identify three-year trajectories in cognitive and physical functioning among Dutch older adults, and the characteristics associated with these trajectories. METHODS: We used Group-based Trajectory Modelling with mortality jointly estimated to identify trajectories, using a scale composed of 6 Activities of Daily Living (ADL) as a measure of physical functioning, and the short mini mental status examination (sMMSE) or the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) as a measure of cognitive functioning. Data came from 574 Dutch adults aged 75+, collected in five nine-month measurement waves (2015-2018) for the Longitudinal Aging Study Amsterdam. RESULTS: For physical functioning five trajectories were identified: 'high', 'moderate', 'steeply declining', 'gradually declining', and 'continuously low'; and for cognitive functioning: 'high', 'moderate', 'declining', and 'low'. Living in an institution, and being lower educated increased the probability of the two continuously low functioning trajectories, whereas old age and multimorbidity increased the probability of low physical functioning, but multimorbidity decreased the probability of low cognitive functioning. Associations for steeply declining physical functioning were absent. Being older and having multimorbidity increased the probability of gradually declining physical functioning and declining cognitive functioning. A higher prevalence of lung- and heart disease, cancer, and rheumatic disease was found in the gradually declining physical functioning group; and a higher prevalence of diabetes, cerebrovascular accidents, and cancer was found in the declining cognitive functioning group. High and moderate physical functioning and high cognitive functioning were characterized by being younger, community-dwelling, and higher educated. Having multimorbidity negatively predicted high and moderate physical functioning, but was not associated with high and moderate cognitive functioning. CONCLUSIONS: This study identified trajectories comparable to studies that used longer time intervals, showing the consistent presence of heterogeneity in both physical and cognitive trajectories. Co-modelling mortality resulted in bigger group sizes for the more adverse trajectories. The favourable trajectories, containing most of the participants, were mostly characterized by absence of disease. The prevalence of chronic diseases differed between the declining trajectories, suggesting that certain diseases tend to induce cognitive decline rather than physical decline, and vice versa.

A multi-trajectory analysis of commonly co-occurring mental health issues across childhood and adolescence.

Developmental trajectories of mental health issues can often be usefully summarised in a small number of clinically meaningful subtypes. Given the high levels of heterotypic and homotypic comorbidity in child and adolescent mental health symptoms, we explored whether it was possible to identify clinically meaningful developmental subtypes of multiple commonly co-occurring mental health issues. We evaluated the combined developmental trajectories of the most common and commonly co-occurring child and adolescent mental health issues: attention-deficit/hyperactivity disorder (ADHD), internalising, and externalising symptoms in a normative sample of youth with data (n = 1620) at ages 7, 8, 9, 10, 11, 12, 13 and 15 using group-based multi-trajectory modelling. Multinomial logistic regression was used to evaluate predictors of group membership. Our optimal model included six trajectory groups, labelled 'unaffected', 'normative maturing', 'internalising', 'multimorbid late onset', 'multimorbid remitting', and 'multimorbid with remitting externalising'. Examining covariates of group membership suggested that males and bully victims tend to have complex mental health profiles; academic achievement and smoking during pregnancy have general associations with mental health irrespective of symptom developmental trajectories or combination; and maternal post-natal depression is primarily related to symptoms that are already in evidence by the beginning of the school years. Results suggest that developmental trajectories of commonly co-occurring mental health issues can be usefully summarised in terms of a small number of developmental subtypes. These subtypes more often than not involve multiple co-occurring mental health issues. Their association with mental health covariates depends on the combination and developmental timing of symptoms in ways that suggest they can be clinically informative.