Personal independence payment (PIP) is a benefit that covers additional daily living costs people may incur from a long-term health condition or disability. Little is known about PIP receipt and associated factors among people who access mental health services, and trends over time. Individual-level data linking healthcare records with administrative records on benefits receipt have been non-existent in the UK.

To explore how PIP receipt varies over time, including PIP type, and its association with sociodemographic and diagnostic patient characteristics among people who access mental health services.

A data-set was established by linking electronic mental health records from the South London and Maudsley NHS Foundation Trust with administrative records from the Department for Work and Pensions.

Of 143 714 working-age patients, 37 120 (25.8%) had received PIP between 2013 and 2019, with PIP receipt steadily increasing over time. Two in three patients (63.2%) had received both the daily living and mobility component. PIP receipt increased with age. Those in more deprived areas were more likely to receive PIP. The likelihood of PIP receipt varied by ethnicity. Patients diagnosed with a severe mental illness had 1.48 odds (95% CI 1.42–1.53) of having received PIP, compared with those with a different psychiatric diagnosis.

One in four people who accessed mental health services had received PIP, with higher levels seen among those most likely in need, as indicated by a severe mental illness diagnosis. Future research using this data-set could explore the average duration of PIP receipt in people who access mental health services, and re-assessment patterns by psychiatric diagnosis.

Major Depressive Disorder (MDD) is a complex mental health condition characterized by a wide spectrum of symptoms. According to the Diagnostic Statistical Manual 5 (DSM-5) criteria, patients can present with up to 1,497 different symptom combinations, yet all receive the same MDD diagnosis. This diversity in symptom presentation poses a significant challenge to understanding the disorder in the wider population. Subtyping offers a way to unpick this phenotypic diversity and enable improved characterization of the disorder. According to reviews, MDD subtyping work to date has lacked consistency in results due to inadequate statistics, non-transparent reporting, or inappropriate sample choice. By addressing these limitations, the current study aims to extend past phenotypic subtyping studies in MDD.

(1) To investigate phenotypic subtypes at baseline in a sample of people with MDD;

(2) To determine if subtypes are consistent between baseline 6- and 12-month follow-ups; and

(3) To examine how participants move between subtypes over time.

This was a secondary analysis of a one-year longitudinal observational cohort study. We collected data from individuals with a history of recurrent MDD in the United Kingdom, the Netherlands and Spain (N=619). The presence or absence of symptoms was tracked at three-month intervals through the Inventory of Depressive Symptomatology: Self-Report (IDS-SR) assessment. We used latent class and three-step latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined participants’ transitions over time.

We identified a 4-class solution based on model fit and interpretability, including (Class 1) severe with appetite increase, (Class 2), severe with appetite decrease, (Class 3) moderate, and (Class 4) low severity. The classes mainly differed in terms of severity (the varying likelihood of symptom endorsement) and, for the two more severe classes, the type of neurovegetative symptoms reported (Figure 1). The four classes were stable over time (measurement invariant) and participants tended to remain in the same class over baseline and follow-up (Figure 2).

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Image 2:

We identified four stable subtypes of depression, with individuals most likely to remain in their same class over 1-year follow-up. This suggests a chronic nature of depression, with (for example) individuals in severe classes more likely to remain in the same class throughout follow-up. Despite the vast heterogeneous symptom combinations possible in MDD, our results emphasize differences across severity rather than symptom type. This raises questions about the meaningfulness of these subtypes beyond established measures of depression severity. Implications of these findings and recommendations for future research are made.

C. Oetzmann Grant / Research support from: C.O. is supported by the UK Medical Research Council (MR/N013700/1) and King’s College London member of the MRC Doctoral Training Partnership in Biomedical Sciences., N. Cummins: None Declared, F. Lamers: None Declared, F. Matcham: None Declared, K. White: None Declared, J. Haro: None Declared, S. Siddi: None Declared, S. Vairavan Employee of: S.V is an employee of Janssen Research & Development, LLC and hold company stocks/stock options., B. Penninx : None Declared, V. Narayan: None Declared, M. Hotopf Grant / Research support from: M.H. is the principal investigator of the RADAR-CNS programme, a precompetitive public–private partnership funded by the Innovative Medicines Initiative and the European Federation of Pharmaceutical Industries and Associations. The programme received support from Janssen, Biogen, MSD, UCB and Lundbeck., E. Carr: None Declared

Globally, mental disorders account for almost 20% of disease burden and there is growing evidence that mental disorders are associated with various social determinants. Tackling the United Nations Sustainable Development Goals (UN SDGs), which address known social determinants of mental disorders, may be an effective way to reduce the global burden of mental disorders.

To examine the evidence base for interventions that seek to improve mental health through targeting the social determinants of mental disorders.

We conducted a systematic review of reviews, using a five-domain conceptual framework which aligns with the UN SDGs (PROSPERO registration: CRD42022361534). PubMed, PsycInfo, and Scopus were searched from 01 January 2012 until 05 October 2022. Citation follow-up and expert consultation were used to identify additional studies. Systematic reviews including interventions seeking to change or improve a social determinant of mental disorders were eligible for inclusion. Study screening, selection, data extraction, and quality appraisal were conducted in accordance with PRISMA guidelines. The AMSTAR-2 was used to assess included reviews and results were narratively synthesised.

Over 20,000 records were screened, and 101 eligible reviews were included. Most reviews were of low, or critically low, quality. Reviews included interventions which targeted sociocultural (n = 31), economic (n = 24), environmental (n = 19), demographic (n = 15), and neighbourhood (n = 8) determinants of mental disorders. Interventions demonstrating the greatest promise for improved mental health from high and moderate quality reviews (n = 37) included: digital and brief advocacy interventions for female survivors of intimate partner violence; cash transfers for people in low-middle-income countries; improved work schedules, parenting programs, and job clubs in the work environment; psychosocial support programs for vulnerable individuals following environmental events; and social and emotional learning programs for school students. Few effective neighbourhood-level interventions were identified.

This review presents interventions with the strongest evidence base for the prevention of mental disorders and highlights synergies where addressing the UN SDGs can be beneficial for mental health. A range of issues across the literature were identified, including barriers to conducting randomised controlled trials and lack of follow-up limiting the ability to measure long-term mental health outcomes. Interdisciplinary and novel approaches to intervention design, implementation, and evaluation are required to improve the social circumstances and mental health experienced by individuals, communities, and populations.

None Declared

Police employees may experience high levels of stress due to the challenging nature of their work which can then lead to sickness absence. To date, there has been limited research on sickness absence in the police. This exploratory analysis investigated sickness absence in UK police employees.

Secondary data analyses were conducted using data from the Airwave Health Monitoring Study (2006–2015). Past year sickness absence was self-reported and categorised as none, low (1–5 days), moderate (6–19 days) and long-term sickness absence (LTSA, 20 or more days). Descriptive statistics and multinomial logistic regressions were used to examine sickness absence and exploratory associations with sociodemographic factors, occupational stressors, health risk behaviours, and mental health outcomes, controlling for rank, gender and age.

From a sample of 40,343 police staff and police officers, forty-six per cent had no sickness absence within the previous year, 33% had a low amount, 13% a moderate amount and 8% were on LTSA. The groups that were more likely to take sick leave were women, non-uniformed police staff, divorced or separated, smokers and those with three or more general practitioner consultations in the past year, poorer mental health, low job satisfaction and high job strain.

The study highlights the groups of police employees who may be more likely to take sick leave and is unique in its use of a large cohort of police employees. The findings emphasise the importance of considering possible modifiable factors that may contribute to sickness absence in UK police forces.

Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity.

Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions.

Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms.

Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly.

Cognitive symptoms are common during and following episodes of depression. Little is known about the persistence of self-reported and performance-based cognition with depression and functional outcomes.

This is a secondary analysis of a prospective naturalistic observational clinical cohort study of individuals with recurrent major depressive disorder (MDD; N = 623). Participants completed app-based self-reported and performance-based cognitive function assessments alongside validated measures of depression, functional disability, and self-esteem every 3 months. Participants were followed-up for a maximum of 2-years. Multilevel hierarchically nested modelling was employed to explore between- and within-participant variation over time to identify whether persistent cognitive difficulties are related to levels of depression and functional impairment during follow-up.

508 individuals (81.5%) provided data (mean age: 46.6, s.d.: 15.6; 76.2% female). Increasing persistence of self-reported cognitive difficulty was associated with higher levels of depression and functional impairment throughout the follow-up. In comparison to low persistence of objective cognitive difficulty (<25% of timepoints), those with high persistence (>75% of timepoints) reported significantly higher levels of depression (B = 5.17, s.e. = 2.21, p = 0.019) and functional impairment (B = 4.82, s.e. = 1.79, p = 0.002) over time. Examination of the individual cognitive modules shows that persistently impaired executive function is associated with worse functioning, and poor processing speed is particularly important for worsened depressive symptoms.

We replicated previous findings of greater persistence of cognitive difficulty with increasing severity of depression and further demonstrate that these cognitive difficulties are associated with pervasive functional disability. Difficulties with cognition may be an indicator and target for further treatment input.

Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an exciting opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks.

To describe the amount of data collected during a multimodal longitudinal RMT study, in an MDD population.

RADAR-MDD is a multi-centre, prospective observational cohort study. People with a history of MDD were provided with a wrist-worn wearable, and several apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks and cognitive assessments and followed-up for a maximum of 2 years.

A total of 623 individuals with a history of MDD were enrolled in the study with 80% completion rates for primary outcome assessments across all timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. Data availability across all RMT data types varied depending on the source of data and the participant-burden for each data type. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. 110 participants had > 50% data available across all data types, and thus able to contribute to multiparametric analyses.

RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible.

No significant relationships.

The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors.

Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change.

Prospective symptom analyses showed small decreases in depression (PHQ-9: −0.43 points) and anxiety [generalised anxiety disorder scale – 7 items (GAD)-7: −0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status.

We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.

Biobanks are a valuable resource for creating advancements in science through cutting-edge omics research. Twin research methods allow us to understand the degree to which genetics and environmental factors contribute to health outcomes.

The Sri Lankan Twin Registry biobank (SLTR-b) was established in 2015 as part of Colombo Twin and Singleton Follow-up Study. Venous blood and urine were collected from twins and comparative sample of singletons for clinical investigations and biobanking.

The SLTR-b currently houses 3369 DNA and serum samples. Biobank specimens are linked to longitudinal questionnaire data, clinical investigations, anthropometric measurements, and other data.

The SLTR-b aims to address gaps in health and genetics research. It will provide opportunities for academic collaborations, local and international, and capacity building of future research leaders in twin and omics research. This paper provides a cohort profile of the SLTR-b and its linked data, and an overview of the strategies used for biobanking.

Depression is a highly prevalent and heterogeneous disorder. This study aims to determine whether depression with atypical features shows different heritability and different degree of overlap with polygenic risk for psychiatric and immuno-metabolic traits than other depression subgroups.

Data included 30 069 European ancestry individuals from the UK Biobank who met criteria for lifetime major depression. Participants reporting both weight gain and hypersomnia were classified as ↑WS depression (N = 1854) and the others as non-↑WS depression (N = 28 215). Cases with non-↑WS depression were further classified as ↓WS depression (i.e. weight loss and insomnia; N = 10 142). Polygenic risk scores (PRS) for 22 traits were generated using genome-wide summary statistics (Bonferroni corrected p = 2.1 × 10−4). Single-nucleotide polymorphism (SNP)-based heritability of depression subgroups was estimated.

↑WS depression had a higher polygenic risk for BMI [OR = 1.20 (1.15–1.26), p = 2.37 × 10−14] and C-reactive protein [OR = 1.11 (1.06–1.17), p = 8.86 × 10−06] v. non-↑WS depression and ↓WS depression. Leptin PRS was close to the significance threshold (p = 2.99 × 10−04), but the effect disappeared when considering GWAS summary statistics of leptin adjusted for BMI. PRS for daily alcohol use was inversely associated with ↑WS depression [OR = 0.88 (0.83–0.93), p = 1.04 × 10−05] v. non-↑WS depression. SNP-based heritability was not significantly different between ↑WS depression and ↓WS depression (14.3% and 12.2%, respectively).

↑WS depression shows evidence of distinct genetic predisposition to immune-metabolic traits and alcohol consumption. These genetic signals suggest that biological targets including immune-cardio-metabolic pathways may be relevant to therapies in individuals with ↑WS depression.

Previous cross sectional studies have reported increased anxiety and depression in individuals with whiplash trauma. The common interpretation is that the whiplash trauma increases the risk of developing mental disorders. The aim of the present study is to test an hypothesis on the opposite direction of causality, namely that symptoms of anxiety and depression increase the risk reporting whiplash trauma in the future.

We used longitudinal data from two waves of a public health survey in Norway, conducted in 1984-86 and 1995-97, where 37 792 individuals participated in both waves (response rate at follow-up 68%). Mental health was screened for symptoms of anxiety and depression at baseline by self-report on 12 items (the Anxiety Depression Index-12). Self reported whiplash trauma was registered as a dichotomy at follow-up, and followed up with age at whiplash trauma in positive cases.

Whiplash trauma was reported by 956 individuals at follow-up, whereof 277 were reported to have occurred between baseline and follow-up. Symptoms of anxiety and depression increased the likelihood of self-report of whiplash trauma at follow-up (OR=1.24 per SD increase in mental symptom load, 95% confidence interval 1.10 – 1.40, p<.001), adjusted for age and gender. Whiplash was associated with increased disability pension award.

Our finding suggests that the increased level of psychopathology found in individuals with a history of whiplash trauma might partly be present already prior to the whiplash injury. This finding is contrary to the common conception of causality in the whiplash-mental health association.

Autism Spectrum Disorders (ASDs) affect 1% of children and are associated with lifelong psychosocial impairments. The majority of children with ASD will experience co-occurring psychiatric disorders. In the UK, antipsychotics remain unlicensed for use in ASDs, however 10% of children with ASD receive antipsychotic treatment; the co-occurring disorders being targeted by these medications remains unclear.

To examine rates of antipsychotic medication use and identify associated co-occurring disorders among children with ASD receiving psychiatric care.

The sample consisted of 2844 children aged 2 to 17 with a NHS clinician recorded ICD-10 diagnoses for ASD between 2008–2013. Clinical variables extracted from their anonymised electronic patient records included disorder severity, medication use, co-occurring ICD-10 diagnoses, family characteristics, demographics and antipsychotic use.

Of the 2844 children (79% male), the majority (57%) had co-occurring psychiatric diagnoses. 313 (11%) received antipsychotic medication. The proportion of children aged 13 to 17 years and 6 to 12 years prescribed antipsychotics was 19% and 7% respectively. After controlling for socio-demographic factors, disorder severity, specialist treatment, inpatient duration, risk of self harm, violence to others, self injurious behaviour, maltreatment history, parental mental illness, caregiver anxiety, and neighbourhood deprivation, multivariate regression analysis revealed only hyperactivity disorders (O.R 1.94, 95%C.I. 1.32–2.86), psychotic disorders (O.R 5.12 95% C.I. 2.6–10.1), mood disorders (O.R 2.02, 95%C.I. 1.04–3.92) and intellectual disability (O.R 2.89 95% C.I. 1.89–4.71) were associated with anti-psychotic use.

The prescription of antipsychotic medications in this UK ASD clinical sample is strongly associated with specific co-occurring psychiatric disorders and intellectual disability.

Higher all-cause mortality and shorter life expectancies for people with severe mental illness (SMI, including schizophrenia, schizoaffective disorder, and bipolar disorder) have been frequently reported. Cancer contributes a substantial proportion of mortality (20 to 30%) as the second or third leading cause of death among people with SMI. Outcomes of cancer incidence studies in SMI were considerably heterogeneous, varying by cancer types and mental disorders.

To compare the incidence of overall and each type of cancer between people with SMI in southeast London and general population in UK.

Using the anonymised linkage between a regional monopoly secondary mental health service provider covering four southeast London boroughs and a population-based cancer register, we carried out the comparisons of cancer incidences between people with SMI and general population by age- and gender-standardisation in 2011.

Among SMI subjects with cancer (N=105), the most common cancer types were lung and colorectal cancer followed by breast cancer for women and prostate cancer for men in this area. Standardised incidence ratios (SIRs) for all cancers in SMI were 1.19 (95% CI: 0.97-1.44) overall, 2.43 (95% CI: 1.98-2.94) in men (n=61), and 0.98 (95% CI: 0.71-1.31) in women (n=44). Based on relatively small case numbers, raised SIRs were found for lung cancer in men (SIR=7.57, 95% CI: 3.04-15.6) and women (SIR=7.61, 95% CI: 2.79-16.6), and in women for colorectal (SIR=7.85, 95%CI: 2.55-18.32) and breast cancer (SIR=7.86, 95% CI: 4.58-12.59).

Specific pattern of elevated risks of cancer incidence were found for people with SMI.

Compared to the general population, people with schizophrenia have a substantially higher risk of premature mortality which translates into a 10–15 year reduction in life expectancy. The aim of this investigation was to determine if symptoms (including aggression, hallucinations or delusions, and depression) or the environmental and functional status of people with schizophrenia contribute to the high mortality risk observed in this patient group.

We identified cases of schizophrenia, aged ≥15 years in a large secondary mental healthcare case register linked to national mortality tracing. We modelled the effect of specific symptoms, activities of daily living (ADLs), living conditions, occupational and recreational activities (Health of the Nation Outcome Scale [HoNOS] subscales) on all-cause mortality over a 4-year observation period (2007-10) using Cox regression.

We identified 4270 schizophrenia cases (170 deaths) in the observation period. After controlling for a broad range of covariates, mortality was not significantly associated with hallucinations and delusions or overactive-aggressive behaviour, but was associated with subclinical depression (adjusted HR 1.5; 95% CI 1.1-2.2) and ADL impairment (adjusted HR 1.8; 95% CI 1.2-2.9).

Severity of symptoms, such as delusions and hallucinations, was less important in predicting mortality than subclinical depression and difficulties carrying out activities of daily living. The overall picture appears to be one where the highest all-cause mortality risk is in service users who are least visible to clinical teams.

Unemployment is a risk factor for later development of mental health problems, but characterisation of this in real world clinical data is limited. This study aimed to investigate the association between employment status and time-to-first-contact with mental health services using survey data linked to electronic health records(EHR).

SELCoH (n = 1698, 2008–2010) was a representative population survey of South East London, with a 71.9% household participation rate. Anonymised survey data for participants was linked with EHR, generating survival data for time-to-first-contact. Cox regression was used to assess associations between unemployment and time to first contact with mental health services.

The rate in the unemployed was 22.84 contacts per 1000 person-years, and in those not unemployed, it was 10 contacts per 1000 person-years. The crude (age-adjusted) hazard ratio (HR) for unemployment was 3.09 (95% CI: 1.66–5.75). The HR for contact for unemployment, after adjusting for age, gender, ethnicity and education, was 2.8 (95% CI: 1.44–5.47). On addition of symptoms of common mental disorder, post-traumatic stress, psychosis and suicide attempts, to the model, unemployed participants remained at elevated risk (HR:2.65, 95% CI: 1.33–5.27). Finally, illicit drugs and alcohol had minimal influence on estimates, giving a fully-adjusted estimate for the association between unemployment and rate of contact of 2.6 (95% CI: 1.31–5.14).

Unemployment was associated with a greater than two-fold increase in risk of accessing mental health care for the first time within the observation time, after adjustment for sociodemographic confounders, psychopathology, and substance use. Explanations for this association could include unobserved confounding, health behaviours associated with unemployment or effects of unemployment on stress processing.

The authors have not supplied their declaration of competing interest.

Only a minority of trauma-exposed individuals go on to develop post traumatic stress disorder (PTSD). Previous studies in high-income countries suggest that maladaptive family functioning adversities (MFFA) in childhood may partially ex-plain individual variation in vulnerability to PTSD following trauma. We test in a lower middle income setting (Sri Lanka) whether: (1) MFFA moderates the association between exposure to trauma and later (a) PTSD (b) other psychiatric diagnoses; (2) any moderation by MFFA is explained by experiences of interpersonal violence, cumulative trauma exposure or other psychopathology.

We conducted a population study of 3995 twins and 2019 singletons residing in Colombo, Sri Lanka. Participants completed the composite international diagnostic interview, including nine traumatic exposures and a questionnaire on MFFA.

In total, 23.4% of participants reported exposure to MFFA. We found that (1) MFFA moderates the association between trauma exposure and both (a) PTSD and (b) non-PTSD diagnosis. (2) This was not explained by interpersonal violence, cumulative trauma exposure or other psychopathology.

In our sample MFFA moderates the association between trauma and PTSD, and the association between trauma and non-PTSD psychopathology.

There is little information describing the trajectories of depression and anxiety symptomatology in the context of coronary heart disease (CHD), and their comparison according to sociodemographic and disability measures, cardiac risk factors, and health care costs.

Using a primary care cohort of 803 patients with a diagnosis of CHD, a latent class growth curve model was developed to study the distinct trajectories of depression and anxiety symptoms (using the hospital anxiety and depression scale) over a 3-year period comprised of 7 distinct follow-up points. Multinomial regression analysis was then conducted to study the association between latent classes, baseline risk factors, and total health care costs across time.

The 5-class model yielded the best combination of statistical best-fit analysis and clinical correlation. These classes were as follows: “stable asymptomatic” (n = 558), “worsening” (n = 64), “improving” (n = 15), “chronic high” (n = 55), and “fluctuating symptomatology” (n = 111). The comparison group was the “stable asymptomatic” class. The symptomatic classes were younger and had higher proportion of women, and were also associated with non-white ethnicity, being a current smoker, and having chest pain. Other measures of disease severity, such as a history of myocardial infarction and comorbidities, were not associated with class membership. The highest mean total health care costs across the 3 years were the “chronic high” and “worsening” class, with the lowest being the “improving” and “stable low” classes. The total societal costs for patients in the “chronic high” and “worsening” class were significantly higher, as compared to the “stable low” class.

The authors have not supplied their declaration of competing interest.