Comorbidity Classes Research Articles

Twenty-year trends in excess costs of chronic obstructive pulmonary disease.

Several major risk factors for chronic obstructive pulmonary disease (COPD), such as population aging, smoking rates, and air pollution levels are rapidly changing, causing inevitable changes in the population burden of COPD. We determined the excess direct costs of COPD and their trend from 2001 to 2020. Using administrative health data from British Columbia, Canada, we created a retrospective matched cohort of physician-diagnosed COPD patients and non-COPD individuals. Excess direct medical costs (2020 $CAD) were estimated by analysing hospital records, outpatient services, medications, and community-care services. Comorbidity classes were assessed using the International Classification of Diseases codes. Excess COPD costs were estimated as the adjusted difference in direct medical costs between COPD and non-COPD cohorts. There were 208 554 and 404 703 individuals in the COPD and non-COPD cohorts, respectively (47.8% female; mean baseline age 69.1 and 68.2 years, respectively). Direct medical costs for COPD were $9224 per patient-year (/PY), compared to $3396/PY for non-COPD, giving rise to excess costs of $5828/PY (95% confidence interval [CI] 5759-5897). Excess costs increased by 48% over the study period. Excess costs due to comorbidities were $3588/PY (95% CI 3554-3622), with cardiovascular-related conditions alone exceeding the costs attributed to COPD ($1375/PY versus $904/PY). Despite multifaceted prevention and management initiatives, COPD-related economic burden is increasing, with the majority of costs due to comorbid conditions. Rising per-patient costs, combined with the flat or increasing prevalence of COPD in many jurisdictions, indicates a significant increase in COPD burden.

Typologies of Psychiatric Diagnoses Among Inpatients with Recent Suicide Attempts

Objective Psychiatric multimorbidity is a well-documented risk factor for suicide. However, diagnostic heterogeneity and patterns of comorbidity likely exists within the population of those who attempt suicide. Person-centered statistical approaches, such as latent class analysis (LCA), extract distinguishable groups differentiated by prevalence and comorbidity of psychiatric disorders. Method The present study used LCA to identify typologies of psychiatric heterogeneity in a sample of 213 inpatients (M age = 33.04 [SD = 12.67]; 57.3% female; 62.4% White; 23.9% Hispanic/Latino) with a history of suicide attempt who were recruited for a suicide prevention clinical trial. Class differences in suicide history characteristics; demographic characteristics; and cognitive-affective and behavioral risk factors, obtained from an initial evaluation involving the administration of a semi-structured diagnostic interview, suicide risk assessment, and battery of self-report measures, were explored. Results LCA identified three classes in the best-fitting solution: Depressive-High Comorbidity (n = 68), Depressive-Low Comorbidity (n = 86), and Bipolar (n = 59). The Depressive-Low Comorbidity class reported less severe suicidal ideation (p < .001), anxiety (p < .001), stress (p < .001), unlovability beliefs (p = .006), and impulsivity (p < .001). The Depressive-Low Comorbidity class also reported fewer actual attempts than the Bipolar class (p = .001) and fewer interrupted attempts than the Depressive-High Comorbidity class (p = .004). Conclusions The Depressive-High Comorbidity and Bipolar classes consistently endorsed higher levels of suicide risk factors. These findings may help to illuminate typologies of suicide attempters with unique clinical needs, which is an essential step toward personalized medicine.

Identification of latent classes in mood and anxiety disorders and their transitions over time: a follow-up study in the adult general population.

Mood and anxiety disorders are heterogeneous conditions with variable course. Knowledge on latent classes and transitions between these classes over time based on longitudinal disorder status information provides insight into clustering of meaningful groups with different disease prognosis. Data of all four waves of the Netherlands Mental Health Survey and Incidence Study-2 were used, a representative population-based study of adults (mean duration between two successive waves = 3 years; N at T0 = 6646; T1 = 5303; T2 = 4618; T3 = 4007; this results in a total number of data points: 20 574). Presence of eight mood and anxiety DSM-IV disorders was assessed with the Composite International Diagnostic Interview. Latent class analysis and latent Markov modelling were used. The best fitting model identified four classes: a healthy class (prevalence: 94.1%), depressed-worried class (3.6%; moderate-to-high proportions of mood disorders and generalized anxiety disorder (GAD)), fear class (1.8%; moderate-to-high proportions of panic and phobia disorders) and high comorbidity class (0.6%). In longitudinal analyses over a three-year period, the minority of those in the depressed-worried and high comorbidity class persisted in their class over time (36.5% and 38.4%, respectively), whereas the majority in the fear class did (67.3%). Suggestive of recovery is switching to the healthy class, this was 39.7% in the depressed-worried class, 12.5% in the fear class and 7.0% in the high comorbidity class. People with panic or phobia disorders have a considerably more persistent and chronic disease course than those with depressive disorders including GAD. Consequently, they could especially benefit from longer-term monitoring and disease management.

Co-occurring conditions during pregnancy and hospitalizations in the first year postpartum among persons with opioid use disorder

IntroductionPregnant persons with opioid use disorder (OUD) face a multitude of comorbid conditions that may increase the risk of adverse drug and health outcomes. This study characterizes typologies of comorbidities among pregnant persons with OUD and assesses the associations of these typologies with hospitalizations in the first year postpartum. MethodsA cohort of pregnant persons with OUD at delivery in 2018 were identified in a Pennsylvania statewide hospital dataset (n = 2055). Latent class analysis assessed 12 comorbid conditions including substance use disorders (SUDs), mental health conditions, and infections. Multivariable logistic regressions examined the association between comorbidity classes and hospitalizations (all-cause, OUD-specific, SUD-related, mental health-related) during early (0–42 days) and late (43–365 days) postpartum. ResultsA three-class model best fit the data. Classes included low comorbidities (56.9% of sample; low prevalence of co-occurring conditions), moderate polysubstance/depression (18.4%; some SUDs, all with depression), and high polysubstance/bipolar disorder (24.7%; highest probabilities of SUDs and bipolar disorder). Overall, 14% had at least one postpartum hospitalization. From 0 to 42 days postpartum, the moderate polysubstance/depression and high polysubstance/bipolar disorder classes had higher odds of all-cause and mental health-related hospitalization, compared to the low comorbidities class. From 43 to 365 days postpartum, the high polysubstance/bipolar disorder class had higher odds of all-cause hospitalizations, while both the high polysubstance/depression and moderate polysubstance/bipolar disorder classes had higher odds of SUD-related and mental health-related hospitalizations compared to the low comorbidities class. ConclusionsFindings highlight the need for long-term, multidisciplinary healthcare delivery interventions to address comorbidities and prevent adverse postpartum outcomes.

Urinary Incontinence Medications: Patient-Initiated Concerns in Primary Care.

Guideline-recommended medications for overactive bladder and urge urinary incontinence (OAB/UUI) are effective but have high costs and side effects. Little is known about patient concerns regarding these medications when prescribed by their primary care providers (PCPs). The aim of the study was to describe PCP-patient interactions when prescribing medications for OAB/UUI, specifically clinical concerns, cost and authorization issues, and mode of communication for these interactions. Using electronic health records, we identified a retrospective cohort of women aged 18-89 years who were prescribed a medication for OAB/UUI during a primary care office visit from 2017 to 2018. We examined the electronic health record from initial prescription through 15 subsequent months for documentation of prior authorization requests and patient concerns about cost, side effects, or ineffectiveness. The association of patient demographics, comorbidity, and medication class with these concerns was examined with logistic regression models. Overall, 46.2% of patients (n = 123) had 1 or more OAB/UUI medication concerns, and 52 reported outside an office visit. Only higher comorbidity was associated with reduced concern of any type. Although the overall percent age of patients reporting concerns was similar by medication type, the patterns of concern type varied. Compared with those taking short-acting antimuscarinics, patients taking long-acting antimuscarinics other than oxybutynin were less likely to have side effect concerns (adjusted odds ratio 0.35, 95% CI 0.16-0.78) and more likely to have cost concerns (adjusted odds ratio 5.10, 95% CI 1.53-17.03). Patient concerns regarding OAB/UUI medications were common in primary care practices and frequently reported outside of office visits. However, the patterns of concerns (cost vs side effects) varied between medication classes.

An investigation of neuropsychiatric symptoms, contextual factors, and antidepressant treatment as risk factors for dementia development in people with mild cognitive impairment.

While some people with mild cognitive impairment (MCI) progress to dementia, many others show no progression. The aim of this study was to identify factors associated with risk of dementia development in this population. A large naturalistic retrospective cohort study was assembled from mental healthcare records in a south London catchment. Patients were selected at first recorded diagnosis of MCI and subsequent dementia diagnosis was ascertained from case notes or death certificate, excluding those with dementia diagnoses and deaths within 6months of MCI diagnosis. A range of demographic and clinical characteristics were ascertained around MCI diagnosis and Cox proportional hazards models were used to investigate independent predictors of dementia, focussing on neuropsychiatric symptoms, contextual factors, and antidepressant treatment. Of 2250 patients with MCI, 236 (10.5%) developed dementia at least 6months after MCI diagnosis. Aside from older age, lower cognitive function, and activities of daily living impairment, impaired social relationships and recorded loneliness were associated with a higher risk of developing dementia. Patients of Black (compared to White) ethnicity were at a lower risk. For depression and antidepressant receipt, only tricyclic use compared to no antidepressant use was associated with an increased dementia risk. No evidence was found for co-morbid affective disorders or different antidepressant classes as risk factors for dementia development following MCI diagnosis, but loneliness and social impairment were independent predictors and would be worth evaluating as targets for interventions to delay progression.

Patterns of comorbid PTSD, depression, alcohol use disorder, and insomnia symptoms in firefighters: A latent profile analysis

BackgroundFirefighters are an at-risk population for multiple psychiatric conditions, including posttraumatic stress disorder (PTSD), depression, alcohol use disorders (AUDs), and insomnia. These disorders are likely to co-occur; however, patterns of comorbidity have scarcely been investigated in firefighters. We aimed to identify subgroups of comorbidity of PTSD, depression, AUDs, and insomnia in a nationwide population of firefighters in South Korea. MethodsA total of 54,054 firefighters responded to an online survey. Latent classes of comorbidity were categorized using latent profile analysis (LPA) based on the symptom scores of PTSD, depression, AUDs, and insomnia. Analysis of variance was performed to compare the characteristics of the identified classes, and multinomial logistic regression was conducted to examine whether anger reactions, resilience, and number of traumatic events predicted class membership. ResultsThe LPA identified four subgroups: minimal symptoms (n = 42,948, 79.5 %), predominant PTSD (n = 2858, 5.3 %), subthreshold symptoms and comorbidity (n = 7003, 13.0 %), and high symptoms and comorbidity (n = 1245, 2.3 %). Three comorbidity classes were defined based on severity and one class showed predominant PTSD symptoms. Number of traumatic exposures predicted predominant PTSD, while resilience and anger reactions predicted severity of comorbidities. LimitationsThe cross-sectional design and usage of self-reported questionnaires are limitations of this study. ConclusionsThe severity of PTSD, depression, AUDs and insomnia tend to correlate and co-occur in firefighters. Our findings highlight the need to assess comorbid symptoms in firefighters and need to reduce anger reactions and enhance resilience in those with multiple comorbidities.

Mental and Physical Health Comorbidities in Traumatic Brain Injury: A Non-TBI Controls Comparison

ObjectiveTo examine whether aging with a TBI was associated with a greater burden of health-related comorbidities compared with a non-TBI control cohort and examine the associations between comorbidity burden, emotional outcomes, and health-related quality of life (HRQoL) after TBI across ages. DesignCross-sectional. SettingResearch center or telephone. ParticipantsThe study included 559 participants (NTBI=291, NControls=268). Participants with TBI were recruited during inpatient rehabilitation and had sustained a moderate-severe TBI 1-33 years previously. Non-TBI controls were a convenience sample recruited through advertisements in the community. InterventionsNot applicable. Main Outcome MeasuresThe number of cardiovascular, general physical health, and mental health comorbidities was compared between cohorts and age strata using Poisson regression. The relationships between comorbidities, age, emotional outcomes (Generalized Anxiety Disorder Scale-7, Patient Health Questionnaire-9), and HRQoL (PROMIS Global Health Measure) were examined with linear regression. Distinct subgroups of comorbidities were identified using latent class analysis. Associations between comorbidity classes with demographic and outcome variables were evaluated using multinomial logistic and linear regressions, respectively. ResultsTBI participants had a significantly higher comorbidity burden than controls, primarily driven by elevated rates of mental health disorders (RR=2.71, 95% confidence interval [1.37, 5.35]). Cardiovascular and physical health comorbidities were not elevated in the TBI group compared with controls. Both cohorts had 3 similar comorbidity subgroups, suggesting consistent patterns of co-occurring health conditions regardless of TBI exposure. Physical and mental health comorbidities were associated with elevated depression and anxiety symptoms and diminished HRQoL after TBI compared with controls. ConclusionTBI was associated with greater mental, but not physical, health comorbidities in the decades after injury. However, physical and mental health comorbidities significantly affected emotional and HRQoL status after TBI, underscoring a greater need for long-term support for individuals with TBI coping with both physical and mental health comorbidities.

Comorbidity clusters and in-hospital outcomes in patients admitted with acute myocardial infarction in the USA: A national population-based study.

The prevalence of multimorbidity in patients with acute myocardial infarction (AMI) is increasing. It is unclear whether comorbidities cluster into distinct phenogroups and whether are associated with clinical trajectories. Survey-weighted analysis of the United States Nationwide Inpatient Sample (NIS) for patients admitted with a primary diagnosis of AMI in 2018. In-hospital outcomes included mortality, stroke, bleeding, and coronary revascularisation. Latent class analysis of 21 chronic conditions was used to identify comorbidity classes. Multivariable logistic and linear regressions were fitted for associations between comorbidity classes and outcomes. Among 416,655 AMI admissions included in the analysis, mean (±SD) age was 67 (±13) years, 38% were females, and 76% White ethnicity. Overall, hypertension, coronary heart disease (CHD), dyslipidaemia, and diabetes were common comorbidities, but each of the identified five classes (C) included ≥1 predominant comorbidities defining distinct phenogroups: cancer/coagulopathy/liver disease class (C1); least burdened (C2); CHD/dyslipidaemia (largest/referent group, (C3)); pulmonary/valvular/peripheral vascular disease (C4); diabetes/kidney disease/heart failure class (C5). Odds ratio (95% confidence interval [CI]) for mortality ranged between 2.11 (1.89-2.37) in C2 to 5.57 (4.99-6.21) in C1. For major bleeding, OR for C1 was 4.48 (3.78; 5.31); for acute stroke, ORs ranged between 0.75 (0.60; 0.94) in C2 to 2.76 (2.27; 3.35) in C1; for coronary revascularization, ORs ranged between 0.34 (0.32; 0.36) in C1 to 1.41 (1.30; 1.53) in C4. We identified distinct comorbidity phenogroups that predicted in-hospital outcomes in patients admitted with AMI. Some conditions overlapped across classes, driven by the high comorbidity burden. Our findings demonstrate the predictive value and potential clinical utility of identifying patients with AMI with specific comorbidity clustering.

Multimorbidity Pattern and Risk for Mortality Among Patients With Dementia: A Nationwide Cohort Study Using Latent Class Analysis.

Individuals with dementia are at a substantially elevated risk for mortality; however, few studies have examined multimorbidity patterns and determined the inter-relationship between these comorbidities in predicting mortality risk. This is a prospective cohort study. Data from 6,556 patients who were diagnosed with dementia between 1997 and 2012 using the Taiwan National Health Insurance Research Database were analyzed. Latent class analysis was performed using 16 common chronic conditions to identify mortality risk among potentially different latent classes. Logistic regression was performed to determine the adjusted association of the determined latent classes with the 5-year mortality rate. With adjustment for age, a three-class model was identified, with 42.7% of participants classified as "low comorbidity class (cluster 1)", 44.2% as "cardiometabolic multimorbidity class (cluster 2)", and 13.1% as "FRINGED class (cluster 3, characterized by FRacture, Infection, NasoGastric feeding, and bleEDing over upper gastrointestinal tract)." The incidence of 5-year mortality was 17.6% in cluster 1, 26.7% in cluster 2, and 59.6% in cluster 3. Compared with cluster 1, the odds ratio for mortality was 9.828 (95% confidence interval [CI]=6.708-14.401; p<0.001) in cluster 2 and 1.582 (95% CI=1.281-1.953; p<0.001) in cluster 3. Among patients with dementia, the risk for 5-year mortality was highest in the subpopulation characterized by fracture, urinary and pulmonary infection, upper gastrointestinal bleeding, and nasogastric intubation, rather than cancer or cardiometabolic comorbidities. These findings may improve decision-making and advance care planning for patients with dementia.

Comorbidity profiles in older patients last seen by mental health prior to suicide attempt

Objectives Suicide in late life is a public health concern. Determining profiles of psychiatric/medical comorbidity in those who attempt while engaged in mental health services may assist with prevention. We identified comorbidity profiles and their association with utilization, means, and fatality in a national sample who attempted suicide. Methods Using latent class analysis, all patients aged ≥ 65 from the Department of Veterans Affairs (VA) healthcare services (2012–2018) last seen in mental health prior to suicide attempt were included. Diagnoses and attempt data were obtained from VA and Center for Medicare & Medicaid Services, VA Suicide Prevention Applications Network, and VA National Mortality Data Repository. Results 2,269 patients were clustered into three profiles, all with high probability of depression. Profiles included minimal comorbidity (50.4%), high medical comorbidity (28.6%), and high (psychiatric/medical) comorbidity (21.0%). Over half (61.7%) attempted suicide within one week of their visit. The class with highest comorbidity had lowest proportion of fatal attempts, while minimal comorbidity class had highest proportion. Conclusions Older patients last seen in mental health prior to suicide attempt were characterized by depression and varying additional comorbidity and attempt-related factors. Findings have implications for risk assessment and intervention in mental health settings, beyond depression.

The validity of transdiagnostic factors in predicting homotypic and heterotypic continuity of psychopathology symptoms over time.

Studies of the continuity of psychopathology symptoms mainly involved the traditional conceptualization that mental disorders are discrete entities. However, high comorbidity rates suggest a few transdiagnostic factors that underlie individual disorders. Therefore, the present study examined the validity of transdiagnostic factors in predicting homotypic and heterotypic continuity of comorbidity classes across two waves in a nationally representative sample. We conducted a latent transition analysis to investigate how transdiagnostic factors differentially affect the transition probabilities of comorbidity classes across time. Results found a notable predictive validity of transdiagnostic factors: (a) internalizing strongly predicted the stability of the internalizing class and transition from the externalizing class to internalizing class, and (b) externalizing predicted the transition from the internalizing class to externalizing class. The study also found a more dynamic prediction pattern leading to equifinality and multifinality of psychopathology symptoms. The findings suggest that transdiagnostic factors can provide information on how individuals' symptom manifestations change over time, highlighting the potential benefits of incorporating transdiagnostic factors into assessment, treatment, and prevention.

Multimorbidity in patients with monoclonal gammopathy of undetermined significance.

Monoclonal gammopathy of undetermined significance (MGUS), a precursor to multiple myeloma, is present in over 5% of adults aged 70 and older, a population with a high prevalence of multimorbidity. MGUS is often diagnosed incidentally when patients seek care for unrelated conditions. Our study sought to examine patterns of multimorbidity among MGUS patients, as overall health may impact patient care and the prioritization of MGUS surveillance. We examined patterns of comorbidities in 429 patients diagnosed with MGUS (2007-2015) and 1287 matched controls. Twenty-seven conditions were defined at diagnosis/index date using algorithms developed by the Centers for Medicare and Medicaid Chronic Conditions Warehouse. Patterns of common comorbidities were identified individually, in dyads and triads, and compared between MGUS cases and controls. We conducted a latent class analysis to identify comorbidity patterns among cases only. We also examined comorbidity patterns among a subset of 32 MGUS cases who progressed to cancer during the study period. The most common comorbidities among both MGUS cases and controls included hypertension and hyperlipidemia. Anemia (cases: 43%; controls: 16%) and chronic kidney disease (CKD; cases: 36%; controls: 18%), and dyads and triads containing those conditions, were more common among cases. Latent class analysis identified three classes of comorbidity among MGUS cases: hypertension-hyperlipidemia plus anemia and CKD (31%); low comorbidity burden (17%); and hypertension-hyperlipidemia alone (52%). The higher prevalence among cases of anemia and CKD, which may be involved in the pathogenesis of, or surveillance for, MGUS, warrants additional investigation.

Multimorbidity patterns and health care utilization among older adults with schizophrenia

IntroductionOlder adults with schizophrenia often have multiple chronic conditions, or multimorbidity, yet most prior research has focused on single medical conditions.ObjectivesTo characterize multimorbidity patterns and utilization among older adults with schizophrenia to understand how multimorbidity affects this population and their clinical service needs.MethodsThis retrospective cohort study included veterans aged 50 years and older with schizophrenia and followed their comorbid diagnoses and utilization (outpatient, inpatient, and emergency) from 2012 to 2019. Comorbid diagnoses included myocardial infarction, congestive heart failure, stroke, chronic obstructive pulmonary disease (COPD), cancer, dementia, traumatic brain injury, hepatitis C, osteoarthritis, renal disease, chronic pain, sleep disorder, depression, dysthymia, posttraumatic stress disorder (PTSD), general anxiety disorder, alcohol use disorder, other substance use disorder, and tobacco use disorder. Latent class analysis was used to identify latent profiles of psychiatric and medical comorbidity. Chi-square and F-tests were used to assess differences in demographics, comorbidities, and utilization across the latent classes.ResultsThe cohort included 82,495 adults with schizophrenia. Three distinct multimorbidity classes were identified: Minimal Comorbidity (67.0% of the cohort), High Comorbidity (17.6%) and Substance Use Disorders and Related Conditions (SUDRC) (15.4%). The Minimal Comorbidity class had &lt;10% prevalence of all comorbid diagnoses. The High Comorbidity class had &gt;20% prevalence of congestive heart failure, COPD, dementia, renal disease, sleep disorder, and depression. The SUDRC class had &gt;70% prevalence of alcohol and drug use disorders and &gt;20% prevalence of COPD, hepatitis C, depression, and PTSD. Although the High Comorbidity class had the highest rates of chronic medical conditions, the SUDRC class had the highest rates of emergency and inpatient medical care and emergency, inpatient, and outpatient mental health care utilization. Comparing across classes, all p-values were &lt;.001 for utilization.ConclusionsOlder adults with schizophrenia are a heterogeneous group with distinct multimorbidity classes and different patterns of utilization. Those with high prevalence of substance use disorders had the highest rates of emergency and inpatient medical and overall mental health care utilization. Tailoring integrated care services to target specific clinical needs could improve outcomes for this population.Disclosure of InterestNone Declared

Psychiatric comorbidity profiles among suicidal attempters: A cohort study

IntroductionMore than 700,000 people die by suicide in 2019 globally (World Health Organitation 2021). Mental health problems constitute a risk factor for suicidal behavior and death by suicide (Hoertel et al. Mol Psychiatry 2015; 20 718–726). Different mental disorders have been related to different forms of suicidal ideation and behavior (Conejero et al. Curr Psychiatry Rep 2018; 20, 33) (Quevedo et al. Compr Psychiatry 2020; 102 152194). However, little is known on comorbidity profiles among suicide attempters.ObjectivesThe aim of our work was to identify the psychiatric comorbidity profiles of individuals who were admitted a hospital emergency department due to a suicide attempt. Moreover, it intended to know their clinical characteristics according to comorbidity profile.MethodsA sample of 683 attempters (71.30% female; M age= 40.85, SD= 15.48) from the SURVIVE study was used. Patients were assessed within the 15 days after emergency department admission. Sociodemographic (i.e., sex, age, marital status and employment status) and clinical data were collected. The International Neuropsychiatric Interview (MINI) was used to assess DSM-V Axis 1 mental health diagnoses and the Columbia Suicide Rating Scale (C-SSRS) to assess suicidal ideation and behavior. The Acquired Capacity for Suicide-Fear of Death Scale (ACSS-FAD), the Patient Health Questionnaire (PHQ-9) to assess the frequency of depressive symptoms during the past 2 weeks, and the General Anxiety Disorder-7 (GAD-7) scale to assess symptoms of worry and anxiety were also conducted. For the identification of comorbidity profiles, latent class analysis framework was followed considering diagnosis to each individual disorder as clustering variables. On the other hand, binary logistic regression was used to study the relationship between comorbidity profile membership and clinical factors.ResultsTwo classes were found (Class I= mild symptomatology class, mainly featured by emotional disorder endorsement; and Class II= high comorbidity class, featured by a wide amount of endorsed diagnoses) (see figure 1). Individuals from the High comorbidity class were more likely to be female (OR= 0.98, p&lt;.05), younger in age (OR= 0.52, p&lt; .01), with more depressive symptoms (OR=1.09, p&lt;.001) and have greater impulsivity (OR= 1.01, p&lt;.05).Image:ConclusionsWe found two profiles of people with suicidal behavior based on the presence of mental disorders. Each of the suicidal subtypes had different associated risk factors. They also had a different profile of suicidal behavior.Disclosure of InterestNone Declared

Influence of comorbidity on mortality in patients with epilepsy and psychogenic nonepileptic seizures.

This study aims to determine the contribution of comorbidities to excess psychogenic nonepileptic seizures (PNES) mortality. A retrospective cohort study was conducted of tertiary epilepsy outpatients from St. Vincent's Hospital Melbourne, Australia with an 8:1 comparison cohort, matched by age, sex, and socioeconomic status (SES) to national administrative databases between 2007 and 2017. Privacy-preserving data linkage was undertaken with the national prescription, National Death Index, and National Coronial Information System. Forty-five comorbid disease classes were derived by applying the Australian validated RxRisk-V to all dispensed prescriptions. We fitted Cox proportional hazard models controlling for age, sex, SES, comorbidity, disease duration, and number of concomitant antiseizure medications, as a marker of disease severity. We also performed a parallel forward-selection change in estimate strategy to explore which specific comorbidities contributed to the largest changes in the hazard ratio. A total of 13 488 participants were followed for a median 3.2 years (interquartile range=2.4-4.0 years), including 1628 tertiary epilepsy outpatients, 1384 patients with epilepsy, 176 with PNES, and 59 with both. Eighty-two percent of epileptic seizures and 92% of typical PNES events were captured in an epilepsy monitoring unit. The age-/sex-/SES-adjusted hazard ratio was elevated for epilepsy (4.74, 95% confidence interval [CI] = 3.36-6.68) and PNES (3.46, 95% CI=1.38-8.68) and remained elevated for epilepsy (3.21, 95% CI=2.22-4.63) but not PNES (2.15, 95% CI = .77-6.04) after comorbidity adjustment. PNES had more pre-existing comorbidities (p= .0007), with a three times greater median weighted Rx-RiskV score. Psychotic illness, opioid analgesia, malignancies, and nonopioid analgesia had the greatest influence on PNES comorbid risk. Higher comorbidity appears to explain the excess PNES mortality and may represent either a wider underrecognized somatoform disorder or a psychological response to physical illness. Better understanding and management of the bidirectional relationship of these wider somatic treatments in PNES could potentially reduce the risk of death.

Association of dementia comorbidities with caregivers’ physical, psychological, social, and financial burden

BackgroundInformal caregivers of older adults with dementia may experience substantial burdens during their caregiving process, especially when caring for older adults with other comorbid conditions. This study evaluated whether and how comorbidity burden for persons with dementia (PWD) was associated with caregivers’ physical, psychological, social, and financial burden as well as caregiving gain.MethodsData were from 1,065 community-dwelling older adults living with dementia and their primary caregivers in the National Health and Aging Trends Study and the National Study of Caregiving. PWD’s comorbidity burden was measured by the count of chronic conditions and the pattern of comorbidity identified by the latent class analysis (LCA). We considered four domains of caregiving burden—physical, psychological, social, and financial burden. We used linear regressions to identify the unadjusted and adjusted associations between PWD’s comorbidity burden and caregiving burden and gain.ResultsOf 1,065 PWD, 13.5% had 0–1 and 24.9% had 5 or more number of comorbid chronic conditions, respectively. After multivariable adjustment, an additional chronic condition is associated with an 0.11- and 0.36-point increase in caregivers’ physical and psychological burden, respectively. Caregivers of PWD with 5 or more chronic conditions had a 0.64- and 2.22-point higher score of physical and psychological burden, respectively, than those caring for PWD with 0 or 1 comorbid condition. LCA divided PWD into two classes, a high comorbidity class (69.0%) and a low comorbidity class (31.0%). Caregivers of PWD in the high comorbidity burden class had a 0.46-point higher score of physical caregiving burden than those in the low comorbidity burden class. No significant association was found between care recipients’ comorbidity burden and their caregivers’ social and financial burden or caregiving gain.ConclusionsThe comorbidity burden of PWD was associated with their caregivers’ physical and psychological caregiving burden. Relevant interventions to manage the comorbid conditions of people living with dementia and support their caregivers are crucial to improving their physical health and psychological wellbeing.

Two-year change in latent classes of comorbidity among high-risk Veterans in primary care: a brief report

BackgroundSegmentation models such as latent class analysis are an increasingly popular approach to inform group-tailored interventions for high-risk complex patients. Multiple studies have identified clinically meaningful high-risk segments, but few have evaluated change in groupings over time.ObjectivesTo describe population-level and individual change over time in latent comorbidity groups among Veterans at high-risk of hospitalization in the Veterans Health Administration (VA).Research designUsing a repeated cross-sectional design, we conducted a latent class analysis of chronic condition diagnoses. We compared latent class composition, patient high-risk status, and patient class assignment in 2018 to 2020.SubjectsTwo cohorts of eligible patients were selected: those active in VA primary care and in the top decile of predicted one-year hospitalization risk in 2018 (n = 951,771) or 2020 (n = 978,771).MeasuresMedical record data were observed from January 2016–December 2020. Latent classes were modeled using indicators for 26 chronic health conditions measured with a 2-year lookback period from study entry.ResultsFive groups were identified in both years, labeled based on high prevalence conditions: Cardiometabolic (23% in 2018), Mental Health (18%), Substance Use Disorders (16%), Low Diagnosis (25%), and High Complexity (10%). The remaining 8% of 2018 patients were not assigned to a group due to low predicted probability. Condition prevalence overall and within groups was stable between years. However, among the 563,725 patients identified as high risk in both years, 40.8% (n = 230,185) had a different group assignment in 2018 versus 2020.ConclusionsIn a repeated latent class analysis of nearly 1 million Veterans at high-risk for hospitalization, population-level groups were stable over two years, but individuals often moved between groups. Interventions tailored to latent groups need to account for change in patient status and group assignment over time.

Between-hospital variation in time to glioblastoma surgery: a report from the Quality Registry Neuro Surgery in the Netherlands.

Patients with glioblastoma are often scheduled for urgent elective surgery. Currently, the impact of the waiting period until glioblastoma surgery is undetermined. In this national quality registry study, the authors determined the wait times until surgery for patients with glioblastoma, the risk factors associated with wait times, and the risk-standardized variation in time to surgery between Dutch hospitals. The associations between time to surgery and patient outcomes were also explored. Data from all 4589 patients who underwent first-time glioblastoma surgery between 2014 and 2019 in the Netherlands were collected by 13 hospitals in the Quality Registry Neuro Surgery. Time to surgery comprised 1) the time from first MR scan to surgery (MTS), and 2) the time from first neurosurgical consultation to surgery (CTS). Long MTS was defined as more than 21 days and long CTS as more than 14 days. Potential risk factors were analyzed in multivariable logistic regression models. The standardized rate of long time to surgery was analyzed using funnel plots. Patient outcomes including Karnofsky Performance Scale (KPS) score change, complications, and survival were analyzed by multivariable logistic regression and proportional hazards models. The median overall MTS and CTS were 18 and 9 days, respectively. Overall, 2576 patients (56%) had an MTS within 3 weeks and 3069 (67%) had a CTS within 2 weeks. Long MTS was significantly associated with older age, higher preoperative KPS score, higher American Society of Anesthesiologists comorbidity class, season, lower hospital case volume, university affiliation, and resection. Long CTS was significantly associated with higher baseline KPS score, university affiliation, resection, more recent year of treatment, and season. In funnel plots, considerable practice variation was observed between hospitals in patients with long times to surgery. Fewer patients with KPS score improvement were observed after a long time until resection. Long CTS was associated with longer survival. Complications and KPS score decline were not associated with time to surgery. Considerable between-hospital variation among Dutch hospitals was observed in the time to glioblastoma surgery. A long time to resection impeded KPS score improvement, and therefore, patients who may improve should be identified for more urgent resection. Longer survival was observed in patients selected for longer time until surgery after neurosurgical consultation (CTS).

Is local excision an appropriate treatment modality in patients presenting with early-stage (cT1 N0 M0) rectal adenocarcinoma?

BackgroundPrior studies evaluating the safety and efficacy of local excision relative to surgical resection in early-stage rectal adenocarcinoma have primarily included low rectal cancers treated with abdominoperineal resection as control comparison cohorts. The role of local excision in early-stage rectal adenocarcinoma is incompletely defined. MethodsWe queried the National Cancer Database to identify patients with cT1 N0 M0 rectal adenocarcinoma between 2004 and 2019. Patients undergoing abdominoperineal resection were excluded. Multivariable regression was used to identify factors associated with use of local excision instead of low anterior resection. Patients undergoing local excision were propensity score matched for age, sex, demographic characteristics, Charlson-Deyo comorbidity class score, and tumor grade and size to those undergoing low anterior resection. Short-term clinical outcomes and 5-year overall survival for matched cohorts were compared by standard methods. ResultsA total of 5,693 patients met inclusion criteria; 1,973 patients underwent local excision and 3,720 low anterior resection. Age (adjusted odds ratio 1.26; 95% confidence interval, 1.17–1.37), tumor histology (poorly differentiated histology: adjusted odds ratio 0.66; 95% confidence interval, 0.51–0.86), and size (>4 cm: adjusted odds ratio 0.20; 95% confidence interval, 0.16–0.25) were associated with choice of intervention. On comparison of matched cohorts, patients undergoing LE demonstrated shorter hospital stay (2.4 ±9.8 vs 5.6 ±8.1 days; P < .001) and lower readmission rate (4% vs 7%; P = .002) but higher margin-positive resection rates (8% vs 2%; P < .001). Overall survival profiles for patients undergoing local excision were comparable with those for low anterior resection. ConclusionIn patients with cT1 N0 M0 rectal adenocarcinoma, local excision is associated with a higher margin-positive resection rate than low anterior resection but affords accelerated postprocedure recovery and comparable rates of overall survival.