Determination and characterization of patient subgroups based on pain trajectories in hand osteoarthritis

OBJECTIVES

To investigate pain, pain trajectories and their determinants in hand osteoarthritis (OA).

METHODS

Data from the HOSTAS (Hand OSTeoArthritis in Secondary care) consisting of consecutive hand OA patients were used. Australian Canadian Osteoarthritis Hand Index (AUSCAN) pain was measured yearly for four years. Patients with complete AUSCAN at ≥2 time points were eligible for longitudinal analysis. Associations between variables of interest and baseline AUSCAN pain were investigated with linear regression. Development of pain over time was modelled using latent class growth analysis (LCGA). Associations of LCGA classes with variables of interest were analysed using multinomial logistic regression adjusted for baseline pain.

RESULTS

A total of 484/538 patients [mean (s.d.) age 60.8 (8.5) years, 86% women, mean (s.d.) AUSCAN pain 9.3 (4.3)] were eligible for longitudinal analysis. Sex, marital and working status, education, disease duration and severity, anxiety and depression scores, lower health-related quality of life (HR-QoL), specific illness perceptions and coping styles were associated with baseline pain. LCGA yielded three classes, characterized by average pain levels at baseline; average pain remained stable over time within classes. Classes with more pain were positively associated with BMI, tender joint count, symptom duration, hand function scores and depression scores, negatively with physical HR-QoL, and education level.

CONCLUSION

Baseline pain was associated with patient and disease characteristics, and psychosocial factors. LCGA showed three pain trajectories in hand OA patients, with different baseline pain levels and stable pain over time. Classes were distinguished by BMI, education level, disease severity, depression and HR-QoL.

Body Mass Index Trajectory and Outcome Post Fontan Procedure

Background Patients with a single ventricle who experience early life growth failure suffer high morbidity and mortality in the perisurgical period. However, long-term implications of poor infant growth, as well as associations between body mass index (BMI) and outcome in adulthood, remain unclear. We aimed to model BMI trajectories of patients with a single ventricle undergoing a Fontan procedure to determine trajectory-based differences in baseline characteristics and long-term clinical outcomes. Methods and Results We performed a retrospective analysis of medical records from patients in the Australia and New Zealand Fontan Registry receiving treatment at the Royal Children's Hospital, The Children's Hospital at Westmead, Royal Melbourne Hospital, and Royal Prince Alfred Hospital from 1981 to 2018. BMI trajectories were modeled in 496 patients using latent class growth analysis from 0 to 6 months, 6 to 60 months, and 5 to 16 years. Trajectories were compared regarding long-term incidence of severe Fontan failure (defined as mortality, heart transplantation, Fontan takedown, or New York Heart Association class III/IV heart failure). Three trajectories were found for male and female subjects at each age group-lower, middle, higher. Subjects in the lower trajectory at 0 to 6 months were more likely to have an atriopulmonary Fontan and experienced increased mortality long term. No association was found between higher BMI trajectory, current BMI, and long-term outcome. Conclusions Poor growth in early life correlates with increased long-term severe Fontan failure. Delineation of distinct BMI trajectories can be used in larger and older cohorts to find optimal BMI targets for patient outcome.

Developmental trajectories of toddler sleep problems: can a person-centered approach help identify children at risk?

STUDY OBJECTIVES

Previous research examining toddler sleep problems has relied almost exclusively on variable-centered statistical approaches to analyze these data, which provide helpful information about the development of the average child. The current study examined whether person-centered trajectory analysis, a statistical technique that can identify subgroups of children who differ in their initial level and/or trajectory of sleep problems, has the potential to inform our understanding of toddler sleep problems and their development.

METHODS

Families (N = 185) were assessed at 12, 24, 30, and 36 months of child age. Latent class growth analysis was used to test for subgroups that differed in their 24-36 month sleep problems. Subgroups were compared on child 36-month externalizing, internalizing, and total problem behaviors, and on 12 month maternal mental health, inter-parental conflict, and maternal parenting behaviors.

RESULTS

Results support a four-class solution, with "low, stable," "low, increasing," "high, increasing," and "high decreasing" classes. The classes whose sleep problems persisted or worsened over time had worse behavioral problems than those whose symptoms improved or remained stably low. Additionally, 12 month maternal depression and global symptom severity, intimate partner violence, and maternal harsh-intrusive parenting behaviors discriminated between the classes that had similar levels of 24 month sleep disturbance but who had diverging trajectories over time.

CONCLUSIONS

This statistical approach appears to have the potential to increase understanding of sleep problem trajectories in the early years of life. Maternal mental health, intimate partner violence, and parenting behaviors may be clinically useful markers of risk for the persistence or development of toddler sleep problems.

Longitudinal phenotyping of maternal antenatal depression in obese pregnant women supports multiple-hit hypothesis for fetal brain development, a secondary analysis of the UPBEAT study

BACKGROUND

Maternal antenatal depression is associated with offspring psychological disorders, but obesity is also widely implicated in maternal depression and neurodevelopment. In pregnant women with obesity we explored interrelationships between antenatal depressive symptom trajectories and multiple exposures implicated in fetal neurodevelopment which could explain these associations, as a prelude to exploring associations with infant mental health.

METHODS

The UK Pregnancies Better Eating and Activity Trial (UPBEAT) recruited multi-ethnic pregnant women with obesity (BMI >= 30kg/m²) between March 2009 and June 2014 from 8 UK sites and 1369 were included to model longitudinal antenatal depressive symptoms from Edinburgh Postnatal Depression Scale (EPDS) scores using Latent Class Growth Analysis. Classes were compared on maternal baseline demography, biomarkers of metabolism, inflammation and placental function, infection, diet and by pregnancy and birth outcomes. Odds ratios, mean differences and 95% Confidence Intervals were calculated using robust auxiliary modelling techniques.

FINDINGS

The chosen model produced four classes: "Not Depressed" (n=575 [42%], "reference"), "Mild" (n=523 [37·5%]), "Moderate" (n=219 [16%]) and "Severe" (n=62 [4·5%]) symptom trajectories. Socio-economic deprivation and ethnic diversity were greater in Severe and Moderate classes. Dietary glycaemic load and saturated fat intake were higher in Severe and Moderate classes (at 17 and 27 weeks). Higher Interleukin-6, glycoprotein acetyls (17 weeks), glucose (34 weeks) and lower placental growth factor (PlGF, 17 and 27 weeks) was found in the Severe class. PlGF was lower in the Moderate class (27 weeks). Infection was least likely in the Not Depressed class across gestation. Risks of preterm birth were associated with Severe depressive symptoms (aOR 3·05[1·11 to 8·36]).

INTERPRETATION

Comprehensive phenotyping exposes important fetal exposures implicated in adverse neurodevelopment, differing by depression class. This study expands substantially on causal models of suboptimal fetal neurodevelopment and offers potential new targets for intervention in obese pregnant women.

FUNDING

JNS was funded by a PhD studentship from the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. UPBEAT was supported by the European Union's 7th Framework Programme (FP7/2007-2013), project EarlyNutrition; grant agreement no. 289346 and the National Institute for Health Research (NIHR) (UK) Programme Grants for Applied Research Programme (RP-0407-10452), Medical Research Council UK Project Grant (MR/L002477/1). Support was also provided by the Chief Scientist Office Scotland, Guy's and St Thomas' Charity and Tommy's Charity (Registered charity no. 1060508). LP and SLW are funded by Tommy's Charity.

What methods are used to study the association between medication adherence trajectories, estimated with the group-based trajectory modeling (GBTM) method, and health-related outcomes?-a protocol for a systematic review

BACKGROUND

The group-based trajectory modeling (GBTM) method is increasingly used in pharmacoepidemiologic studies to describe medication adherence trajectories over time. However, assessing the associations between these medication adherence trajectories and health-related outcomes remains challenging. The purpose of this review is to identify and systematically review the methods used to assess the association between medication adherence trajectories, estimated from the GBTM method, and health-related outcomes.

METHODS

We will conduct a systematic review according to the recommendations of the Cochrane handbook for systematic reviews of interventions 6.2. Results will be reported following PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-analyses) recommendations. We will search in the following databases: PubMed, Embase, PsycINFO, Web of Science, CINAHL, and Cochrane Library. Two reviewers will independently select articles and extract data. Discrepancies at every step will be resolved through discussion, and consensus will be reached for all disagreed articles. A third reviewer will act as a referee if needed. We will produce tables to synthesize the modalities used to estimate medication adherence trajectories with GBTM. We will also synthesize the modalities used to assess the association between these medication adherence trajectories and health-related outcomes by identifying the types of health-related outcomes studied and how they are defined, the statistical models used, and how the medication adherence trajectories were used in these models, and the effect measure yield. We will also review the limitations and biases reported by the authors and their attempts to mitigate them. We will provide a narrative synthesis.

DISCUSSION

This review will provide a thorough exploration of the strategies and methods used in medication adherence research to estimate the associations between medication adherence trajectories, estimated with GBTM, and the different health-related outcomes. It will represent the first crucial steps toward optimizing these methods in adherence studies.

SYSTEMATIC REVIEW REGISTRATION

Prospero CRD42021213503 .

Trajectory of post-traumatic stress and depression among children and adolescents following single-incident trauma

OBJECTIVE

Post-traumatic stress disorder and depression have high comorbidity. Understanding their relationship is of clinical and theoretical importance. A comprehensive way to understand post-trauma psychopathology is through symptom trajectories. This study aims to look at the developmental courses of PTSD and depression symptoms and their interrelationship in the initial months post-trauma in children and adolescents.

METHODS

Two-hundred-and-seventeen children and adolescents aged between eight and 17 exposed to single-event trauma were included in the study. Post-traumatic stress symptoms (PTSS) and depression symptoms were measured at 2 weeks, 2 months and 9 months, with further psychological variables measured at the 2-week assessment. Group-based trajectory modelling (GBTM) was applied to estimate the latent developmental clusters of the two outcomes. Logistic regression was used to identify predictors associated with high symptom groups.

RESULTS

The GBTM yielded a three-group model for PTSS and a three-group model for depression. PTSS trajectories showed symptoms reduced to a non-clinical level by 9 months for all participants (if they were not already in the non-clinical range): participants were observed to be resilient (42.4%) or recovered within 2 months (35.6%), while 21.9% experienced high level PTSS but recovered by 9 months post-trauma. The depression symptom trajectories predicted a chronic non-recovery group (20.1%) and two mild symptom groups (45.9%, 34.0%). Further analysis showed high synchronicity between PTSS and depression groups. Peri-event panic, negative appraisals, rumination and thought suppression at 2 weeks predicted slow recovery from PTSS. Pre-trauma wellbeing, post-trauma anxiety and negative appraisals predicted chronic depression.

CONCLUSIONS

Post-trauma depression was more persistent than PTSS at 9 months in the sampled population. Cognitive appraisal was the shared risk factor to high symptom groups of both PTSS and depression.

Deleting "fear" from "fear extinction": Estimating the individual extinction rate via non-aversive conditioning

Individual differences in extinction learning have attracted ample attention of researchers and are under investigation as a marker for the onset of anxiety disorders and treatment response. Unfortunately, the common paradigm for obtaining the extinction rate, which entails aversive stimulus pairings, is subject to practical limitations. Therefore, the present study assessed whether the use of an aversive stimulus is actually needed to get a good estimate of the extinction rate. A total of 161 undergraduate students completed a conditioning task with both an aversive and a non-aversive stimulus. Using latent class growth analysis (LCGA), distinct trajectories, representing normal and stunted extinction learning, were identified for both these stimulus types. Participants' membership in these classes largely overlapped for aversive and non-aversive stimulus pairings and respective extinction indices were significantly correlated. Thereby, findings suggest that the use of a non-aversive stimulus could suffice for successfully capturing individual differences in extinction learning. However, future studies are needed to confirm that conditioning with a non-aversive stimulus may serve to predict clinically relevant outcomes.

Using Panel Data to Understand the Dynamics of Human Behavior in Response to Flooding

Insights into the dynamics of human behavior in response to flooding are urgently needed for the development of effective integrated flood risk management strategies, and for integrating human behavior in flood risk modeling. However, our understanding of the dynamics of risk perceptions, attitudes, individual recovery processes, as well as adaptive (i.e., risk reducing) intention and behavior are currently limited because of the predominant use of cross-sectional surveys in the flood risk domain. Here, we present the results from one of the first panel surveys in the flood risk domain covering a relatively long period of time (i.e., four years after a damaging event), three survey waves, and a wide range of topics relevant to the role of citizens in integrated flood risk management. The panel data, consisting of 227 individuals affected by the 2013 flood in Germany, were analyzed using repeated-measures ANOVA and latent class growth analysis (LCGA) to utilize the unique temporal dimension of the data set. Results show that attitudes, such as the respondents' perceived responsibility within flood risk management, remain fairly stable over time. Changes are observed partly for risk perceptions and mainly for individual recovery and intentions to undertake risk-reducing measures. LCGA reveal heterogeneous recovery and adaptation trajectories that need to be taken into account in policies supporting individual recovery and stimulating societal preparedness. More panel studies in the flood risk domain are needed to gain better insights into the dynamics of individual recovery, risk-reducing behavior, and associated risk and protective factors.

Are trajectories of neck-shoulder pain associated with sick leave and work ability in workers? A 1-year prospective study

OBJECTIVES

The study aimed to determine the extent to which latent trajectories of neck-shoulder pain (NSP) are associated with self-reported sick leave and work ability based on frequent repeated measures over 1 year in an occupational population.

METHODS

This longitudinal study included 748 Danish workers (blue-collar, n=620; white collar, n=128). A questionnaire was administered to collect data on personal and occupational factors at baseline. Text messages were used for repeated measurements of NSP intensity (scale 0-10) over 1 year (14 waves in total). Simultaneously, self-reported sick leave (days/month) due to pain was assessed at 4-week intervals, while work ability (scale 0-10) was assessed using a single item (work ability index) at 12-week intervals over the year. Trajectories of NSP, distinguished by latent class growth analysis, were used as predictors of sick leave and work ability in generalised estimation equations with multiple adjustments.

RESULTS

Sick leave increased and work ability decreased across all NSP trajectory classes (low, moderate, strong fluctuating and severe persistent pain intensity). In the adjusted model, the estimated number of days on sick leave was 1.5 days/month for severe persistent NSP compared with 0.1 days/month for low NSP (relative risk=13.8, 95% CI 6.7 to 28.5). Similarly, work ability decreased markedly for severe persistent NSP (OR=12.9, 95% CI 8.5 to 19.7; median 7.1) compared with low NSP (median 9.5).

CONCLUSION

Severe persistent NSP was associated with sick leave and poor work ability over 1 year among workers. Preventive strategies aiming at reducing severe persistent NSP among working populations are needed.

A TPB-Based Smoking Intervention among Chinese High School Students

OBJECTIVES

China is the world's largest tobacco consumer and its adolescent smoking rate is increasing. Smoking interventions among high school students are limited. The aim of this study was to deliver and evaluate a brief theory-based smoking intervention in China, with a focus on anti-smoking cognitions.

METHODS

The intervention was based on the constructs of an extended theory of planned behavior and life skills training. Using class-level randomization sampling, 106 tenth graders from two high schools in Kunming, China received a four-session intervention; 101 students were assigned as control group members. Surveys were conducted at three time-points (1 week before the intervention, 1 week post-intervention, and 6 months post-intervention). MANOVA and latent class analysis were used to test the intervention's effectiveness and personal change trajectories over time.

RESULTS

The intervention failed to change smoking behavior, intention or willingness, but improved anti-smoking attitudes and perceived control over smoking. Skills showed a general enhancement, consistent with participants' qualitative feedback. Trajectories of smoking behavior, intention, and willingness all assumed two distinct but constant latent classes independent of the intervention.

CONCLUSIONS

This study suggests that addressing attitudinal and control beliefs among adolescents and building on assertiveness via additional strategies in life skills such as appropriate refusal skills may be beneficial. The absence of a successful change in subjective norm should be a focus for future anti-smoking programs in China.

Developmental trajectories of paediatric headache - sex-specific analyses and predictors

BACKGROUND

Headache is the most common pain disorder in children and adolescents and is associated with diverse dysfunctions and psychological symptoms. Several studies evidenced sex-specific differences in headache frequency. Until now no study exists that examined sex-specific patterns of change in paediatric headache across time and included pain-related somatic and (socio-)psychological predictors.

METHOD

Latent Class Growth Analysis (LCGA) was used in order to identify different trajectory classes of headache across four annual time points in a population-based sample (n = 3 227; mean age 11.34 years; 51.2 % girls). In multinomial logistic regression analyses the influence of several predictors on the class membership was examined.

RESULTS

For girls, a four-class model was identified as the best fitting model. While the majority of girls reported no (30.5 %) or moderate headache frequencies (32.5 %) across time, one class with a high level of headache days (20.8 %) and a class with an increasing headache frequency across time (16.2 %) were identified. For boys a two class model with a 'no headache class' (48.6 %) and 'moderate headache class' (51.4 %) showed the best model fit. Regarding logistic regression analyses, migraine and parental headache proved to be stable predictors across sexes. Depression/anxiety was a significant predictor for all pain classes in girls. Life events, dysfunctional stress coping and school burden were also able to differentiate at least between some classes in both sexes.

CONCLUSIONS

The identified trajectories reflect sex-specific differences in paediatric headache, as seen in the number and type of classes extracted. The documented risk factors can deliver ideas for preventive actions and considerations for treatment programmes.

Exploring the clinical course of neck pain in physical therapy: a longitudinal study

OBJECTIVE

To investigate the short-term trajectory of recovery from mechanical neck pain, and predictors of trajectory.

DESIGN

Prospective, longitudinal cohort study with 5 repeated measurements over 4 weeks.

SETTING

Community-based physical therapy clinics.

PARTICIPANTS

Convenience sample of community-dwelling adults (N=50) with uncomplicated mechanical neck disorders of any duration.

INTERVENTIONS

Usual physical therapy care.

MAIN OUTCOME MEASURES

Neck Disability Index (NDI), numeric rating scale (NRS) of pain intensity.

RESULTS

A total of 50 consecutive subjects provided 5 data points over 4 weeks. Exploratory modeling using latent class growth analysis revealed a linear trend in improvement, at a mean of 1.5 NDI points and 0.5 NRS points per week. Within the NDI trajectory, 3 latent classes were identified, each with a unique trend: worsening (14.5%), rapid improvement (19.6%), and slow improvement (65.8%). Within the NRS trajectory, 2 unique trends were identified: stable (48.0%) and improving (52.0%). Predictors of trajectory class suggest that it may be possible to predict the trajectory. Results are described in view of the sample size.

CONCLUSIONS

The mean trajectory of improvement in neck pain adequately fits a linear model and suggests slow but stable improvement over the short term. However, up to 3 different trajectories have been identified that suggest neck pain, and recovery thereof, is not homogenous. This may hold value for the design of clinical trials.

Individual- and community-level correlates of cigarette-smoking trajectories from age 13 to 32 in a U.S. population-based sample

BACKGROUND

Characterizing smoking behavior is important for informing etiologic models and targeting prevention efforts. This study explored the effects of both individual- and community-level variables in predicting cigarette use vs. non-use and level of use among adolescents as they transition into adulthood.

METHODS

Data on 14,779 youths (53% female) were drawn from the National Longitudinal Study of Adolescent Health (Add Health); a nationally representative longitudinal cohort. A cohort sequential design allowed for examining trajectories of smoking typologies from age 13 to 32 years. Smoking trajectories were evaluated by using a zero-inflated Poisson (ZIP) latent growth analysis and latent class growth analysis modeling approach.

RESULTS

Significant relationships emerged between both individual- and community-level variables and smoking outcomes. Maternal and peer smoking predicted increases in smoking over development and were associated with a greater likelihood of belonging to any of the four identified smoking groups versus Non-Users. Conduct problems and depressive symptoms during adolescence were related to cigarette use versus non-use. State-level prevalence of adolescent smoking was related to greater cigarette use during adolescence.

CONCLUSIONS

Individual- and community-level variables that distinguish smoking patterns within the population aid in understanding cigarette use versus non-use and the quantity of cigarette use into adulthood. Our findings suggest that efforts to prevent cigarette use would benefit from attention to both parental and peer smoking and individual well-being. Future work is needed to better understand the role of variables in the context of multiple levels (individual and community-level) on smoking trajectories.