Preoperative measures of pain at rest and movement-evoked pain in knee arthroplasty: Associations with pain and function outcome trajectories from a prospective multicentre longitudinal cohort study.

BACKGROUND: The study of pain at rest (PAR) and movement-evoked pain (MEP) in persons with musculoskeletal pain has received substantial attention. Despite strong interest, relatively little attention has been directed to the psychometric development of these constructs. Our purpose was to explore the relationship between PAR and MEP and to examine the prognostic utility of these measures in persons with knee arthroplasty. METHODS: We used prospectively collected data from persons scheduled for knee arthroplasty who had moderate to high levels of pain catastrophizing. Preoperative latent variables for PAR and MEP were developed and used to determine if they were associated with a binary latent variable of good versus poor pain and function outcome trajectories. Factor correlations were used to determine the extent to which the variance for PAR and MEP was overlapping. RESULTS: PAR and MEP are significant predictors of good versus poor pain and function classes. Odds ratios ranged from 1.21 to 1.64 (p < 0.001) indicating a significant increase in the likelihood of poor outcome. Correlation between PAR and MEP latent variables was high (r = 0.89; 95% CI: 0.86-0.92) indicating substantially overlapping variance. CONCLUSIONS: PAR and MEP, as defined in our study, can be used to make prognostic judgements regarding risk of poor postoperative outcome trajectory following knee arthroplasty. However, PAR and MEP showed substantially overlapping variance indicating that measurements of both are not necessary when making prognostic assessments. SIGNIFICANCE STATEMENT: Preoperative PAR and MEP latent variables, as defined in our study, had prognostic significance for 1 year pain and function outcome trajectories. PAR and MEP latent variables had substantially overlapping variance which suggested that only one is needed to make prognostic judgements. The prognostic significance of PAR and MEP as well as their substantially overlapping variance is new to the field prognostic research in knee arthroplasty.

The measurement of "high-impact chronic pain": Limitations and alternative methods.

OBJECTIVE: Chronic pain is known to be an important construct in clinical practice and a particular form of chronic pain, high-impact chronic pain (HICP), has gained recent interest and attention by pain clinicians, epidemiologists, and clinical researchers. The purpose of our Topical Review is to describe the historical development of measures of HICP and to explore the psychometric properties of HICP as well as to present alternative measurement methods. METHODS: We identified strengths and weaknesses of the psychometric characteristics of HICP measures. Limitations of existing HICP measures were discussed and summarized and alternatives to current methods were proposed. RESULTS: HICP operational definitions show variability across studies. All definitions cannot be correct, but which ones are incorrect cannot be determined as there is no gold standard. Random measurement error and recall bias are among the other limitations of current HICP measures. Model-based definitions of HICP, the discrete (for epidemiologic applications) and continuous (for clinical applications) latent variable models are discussed as likely superior alternatives to current methods. CONCLUSIONS: Limitations of existing HICP methods are discussed and alternative development approaches to HICP measures are presented. The use of either discrete or continuous latent variable models would improve upon the psychometric characteristics of current HICP evidence. Examples are used to illustrate the benefits of latent variable models over traditional observed variable conceptualizations as the measurement of HICP continues to develop. SIGNIFICANCE STATEMENT: This work takes the position that current methods of measuring high impact chronic pain (HICP) likely contain substantial error. We have endorsed an alternative approach for several psychometrically grounded reasons. We recommend that future work consider the discrete latent variable framework for dichotomous measures of HICP and the continuous latent variable framework for continuous measures of HICP. The paper provides illustrative examples of these methods for a different patient reported measure that is lacking a gold standard, much like HICP measures.

The Association Between a Neighborhood Adverse Childhood Experiences Index and Body Mass Index Among New York City Youth.

Background: The role of neighborhood factors in the association between adverse childhood experiences (ACEs) and body mass index (BMI) has not been widely studied. A neighborhood ACEs index (NAI) captures neighborhood environment factors associated with ACE exposure. This study examined associations between BMI and an NAI among New York City (NYC) youth. An exploratory objective examined the NAI geographic distribution across NYC neighborhoods. Methods: Data for students attending NYC public general education schools in kindergarten-12th grade from 2006-2017 (n = 1,753,867) were linked to 25 geospatial datasets capturing neighborhood characteristics for every census tract in NYC. Multivariable hierarchical linear regression tested associations between BMI and the NAI; analyses also were conducted by young (<8 years), school age (8-12 years), and adolescent (>12 years) subgroups. In addition, NAI was mapped by census tract, and local Moran's I identified clusters of high and low NAI neighborhoods. Results: Higher BMI was associated with higher NAI across all sex and age groups, with largest magnitude of associations for girls (medium NAI vs. low NAI: unstandardized ß = 0.112 (SE 0.008), standardized ß [effect size]=0.097, p < 0.001; high NAI vs. low NAI: unstandardized ß = 0.195 (SE 0.008), standardized ß = 0.178, p < 0.001) and adolescents (medium NAI vs. low NAI: unstandardized ß = 0.189 (SE 0.014), standardized ß = 0.161, p < 0.001, high NAI vs. low NAI: unstandardized ß = 0.364 (SE 0.015), standardized ß = 0.334, p < 0.001 for adolescent girls; medium NAI vs. low NAI: unstandardized ß = 0.122 (SE 0.014), standardized ß = 0.095, p < 0.001, high NAI vs. low NAI: unstandardized ß = 0.217 (SE 0.015), standardized ß = 0.187, p < 0.001 for adolescent boys). Each borough of NYC included clusters of neighborhoods with higher and lower NAI exposure, although clusters varied in size and patterns of geographic dispersion across boroughs. Conclusions: A spatial index capturing neighborhood environment factors associated with ACE exposure is associated with higher BMI among NYC youth. Findings complement prior literature about relationships between neighborhood environment and obesity risk, existing research documenting ACE-obesity associations, and the potential for neighborhood factors to be a source of adversity. Collectively, evidence suggests that trauma-informed place-based obesity reduction efforts merit further exploration as potential means to interrupt ACE-obesity associations.

Head-to-head comparison of appropriate use criteria for knee arthroplasty: A multicenter cohort study.

Objective: To determine, in a head-to-head comparison, which of two RAND-based knee replacement appropriateness criteria is optimal based on comparison to an externally validated method of judging good versus poor outcome. Design: Longitudinal data from the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST) were combined to produce a dataset of 922 persons with knee arthroplasty, 602 of which had adequate data for RAND classification and had their surgery within one year prior to a study visit. Data were used to determine appropriateness classification (i.e., Appropriate, Inconclusive, Rarely Appropriate) using modified versions of the first-generation and second-generation Escobar system. Growth curve analyses and multivariable regression were used to compare the two systems. Results: Neither system associated with the gold standard measure of good versus poor outcome. Distributions of appropriateness categories for the second-generation system were inconsistent with current evidence for knee arthroplasty outcome. For example, 16% of participants were classified as Appropriate and 64% as Rarely Appropriate for pain outcome. Distributions for the first-generation system aligned with current evidence. Conclusion: The first-generation modified version of the Escobar appropriateness system is superior to the newer version but neither version associated with our gold standard growth curve analyses. Both systems only differentiate between patient classification groups preoperatively and up to ten months following surgery. Reliance on appropriateness criteria to inform long-term outcome is not warranted.

Using Two Predictive Models to Capture Two Types of Poor Outcomes in Knee Arthroplasty: A Multisite Longitudinal Cohort Study.

OBJECTIVE: Poor outcome after knee arthroplasty (KA), a common major surgery worldwide, reportedly occurs in approximately 20% of patients. These patients demonstrate minimal improvement, at least moderate knee pain, and difficulty performing many routine daily activities. The purposes of our study were to comprehensively determine poor outcome risk after KA and to identify predictors of poor outcome. METHODS: Data from 565 participants with KA in the Osteoarthritis Initiative and the Multicenter Osteoarthritis studies were used. Previously validated latent class analyses (LCAs) of good versus poor outcome trajectories of Western Ontario and McMaster Universities Arthritis Index (WOMAC) Pain and Disability were generated to describe minimal improvement and poor final outcome. The modified Escobar RAND appropriateness system was used to generate classifications of appropriate, inconclusive, and rarely appropriate. Multivariable prediction models included LCA-based good versus poor outcome, modified Escobar classifications, and evidence-driven preoperative prognostic variables. RESULTS: Modified Escobar appropriateness classifications were nonsignificant predictors of WOMAC Pain good versus poor outcomes, indicating the methods provide independent outcome estimates. For WOMAC Pain and WOMAC Disability, approximately 34% and 45% of participants, respectively, had a high probability of either minimal improvement via "rarely appropriate" classifications or poor outcome via LCA. In multivariable prediction models, greater contralateral knee pain consistently predicted poor outcome (eg, odds ratio 1.21, 95% confidence interval 1.10-1.33). CONCLUSION: Appropriateness criteria and LCA estimates provided combined poor outcome estimates that were approximately double the commonly reported poor outcome of 20%. Rates of poor outcome could be reduced if clinicians screened patients using appropriateness criteria and LCA predictors before surgery to optimize outcome.

Perioperative Opioid Use and Dosage Trajectories Vary Depending on Pain Outcome Classification and Bodily Pain in Patients who Catastrophize About Their Pain: A Secondary Analysis of a Randomized Trial in Knee Arthroplasty.

Opioid use and dosage following knee arthroplasty (KA) has not been reported for subgroups with persistent moderate pain versus rapidly improving mild pain, externally validated from prior work. We determined if opioid use and dosage varied for persons classified into these externally validated subgroups. A secondary purpose determined if bodily pain scores are associated with the outcome subgroup. This was a secondary analysis of a prospective no-effect randomized clinical trial conducted on 384 participants with pain catastrophizing and scheduled for KA. Data were collected preoperatively and at 2-, 6-, and 12-month following surgery. Two-piece latent class growth curve analyses applied previously validated pain outcomes to determine subgroup outcome trajectories for the proportion of opioid users and oral morphine equivalent (OME) dosages. Substantial trajectory separation was found for opioid use and OME. Specifically, the average OME dosage for the persistent moderate pain subgroup was more than double that for the other outcome subgroup. The average preoperative opioid daily OME dosage for 170 patients reporting opioid use was 24.94 (95% [confidence interval] CI = 20.52, 29.38). Bodily pain was consistently higher for the persistent moderate pain subgroup compared to the other subgroup. Outcome subgroups in patients with pain catastrophizing demonstrated substantial differences in opioid use and dosage and were predicted by high pain catastrophizing, more bodily pain, and changes in bodily pain over time. The persistent moderate pain subgroup is at greater risk of opioid use and greater opioid dosages and should be targeted for preoperative screening and interventions to reduce opioid use and potential opioid misuse. PERSPECTIVE: More frequent and higher opioid dosage following KA was found for the persistent moderate pain subgroup compared to the other subgroup. Patients with persistent pain had worse catastrophizing, contralateral and ipsilateral lower extremity pain, low back pain, and whole body pain compared to the rapidly improving mild pain subgroup.

A Latent Change Score Approach to Understanding Chronic Bodily Pain Outcomes Following Knee Arthroplasty: A Secondary Analysis of Longitudinal Data.

BACKGROUND: The extent to which chronic bodily pain changes following total knee arthroplasty (TKA) is unknown. We determined the extent of chronic bodily pain changes at 1 year following TKA. METHODS: Data from our randomized trial of pain coping skills, which revealed no effect of the studied interventions, were used. The presence and severity of chronic pain in 16 body regions, excluding the surgically treated knee, were determined prior to and 1 year following surgery. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain scale was used to quantify the extent of surgical knee pain. Latent change score (LCS) models were used to determine the extent to which true chronic bodily pain scores change after TKA. RESULTS: The mean age of the sample of 367 participants was 63.4 ± 8.0 years, and 247 (67%) were female. LCS analyses showed significant 20% to 54% reductions in pain in the surgically treated lower limb (not including the surgically treated knee), pain in the non-surgically treated lower limb, and whole body pain. In bivariate LCS analyses, greater improvement in the WOMAC pain score, indicating surgical benefit of TKA, led to greater improvement in all 4 bodily pain areas beyond the surgically treated knee, even after controlling for the latent change in pain catastrophizing. CONCLUSIONS: Clinically important chronic bodily pain reductions occurred following TKA and may be causally linked to the surgical procedure. Reduction in chronic bodily pain in sites other than the surgically treated knee is an additional benefit of TKA. LEVEL OF EVIDENCE: Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

Validation and Psychometric Properties of the Tobacco Urge Management Scale (TUMS).

BACKGROUND: During quit attempts, smokers must overcome smoking urges triggered by environmental cues and nicotine withdrawal symptoms. This study investigates the psychometric properties of the 12-item Tobacco Urge Management Scale (TUMS), a new measure of smoking urge management behaviors. METHODS: We analyzed secondary data (n = 327) from a behavioral smoking cessation intervention trial, Kids Safe and Smokefree (KiSS). RESULTS: Confirmatory factor analysis of the TUMS indicated that a one-factor model and a correlated two-factor model had similar model fit indices, and a Chi-square difference test supported the one-factor model. Further study of the parsimonious one-factor scale provided evidence of reliability and construct validity. Known group validity was evidenced by significantly higher TUMS scores in the KiSS intervention arm receiving urge management skills training than in the control arm (p < 0.001). Concurrent validity was evidenced by TUMS's inverse association with cigarettes smoked per day and positive associations with nonsmoking days, 7-day abstinence, and self-efficacy to control smoking behaviors (p's < 0.05). CONCLUSION: The TUMS is a reliable, valid measure of smoking urge management behaviors. The measure can support theory-driven research on smoking-specific coping mechanisms, inform clinical practice by identifying coping strategies that might be under-utilized in treatment-seeking smokers, and function as a measure of treatment adherence in cessation trials that target urge management behaviors.

Patient Acceptable Symptom State Versus Latent Class Analysis Outcome Classification: A Comparative Longitudinal Study of Knee Arthroplasty.

OBJECTIVE: To determine whether Patient Acceptable Symptom State (PASS), a single-item deterministic binary measure of pain and function outcome satisfaction, leads to better differentiation of outcome classification versus latent class analysis probability-based outcome subgroups 1 year after knee arthroplasty (KA). METHODS: We used data from Knee Arthroplasty Skills Training for Pain (KASTPain), a 1-year no-effect multicenter randomized clinical trial of participants with KA, along with prior work that developed and externally validated good and poor outcome trajectories. Confirmatory latent class analyses were conducted on 2 exemplar outcome measures (Euroquol visual analog scale single-item self-rated health and 4-item pain ratings) and compared with PASS scores. Separation of trajectories were used to compare good and poor latent class self-rated health/4-item pain trajectories and PASS score trajectories. RESULTS: Prevalence rates for poor outcomes were 10% for self-rated health and 20% for 4-item pain and PASS. Probabilistic latent class-derived classifications of self-rated health and 4-item pain outcomes outperformed PASS in separating growth trajectories. The effect size point estimates for 12-month 4-item pain scale score separation was approximately 3 times larger for latent class analyses as compared with PASS. CONCLUSIONS: When used for outcome classification, observed PASS scores consistently underperform relative to probabilistic latent class-derived subgroups of pain and self-rated health outcome. PASS is a weak substitute for probabilistic classification of other patient-reported outcome measures of KA outcome. Clinicians and researchers should rely on latent class analyses over PASS to differentiate between outcome subgroups after KA.

A latent class analysis of cognitive decline in US adults, BRFSS 2015-2020.

BACKGROUND: Cognitive decline can be an early indicator for dementia. Using quantitative methods and national representative survey data, we can monitor the potential burden of disease at the population-level. METHODS: BRFSS is an annual, nationally representative questionnaire in the United States. The optional cognitive decline module is a six-item self-reported scale pertaining to challenges in daily life due to memory loss and growing confusion over the past twelve months. Respondents are 45+, pooled from 2015-2020. Latent class analysis was used to determine unobserved subgroups of subjective cognitive decline (SCD) based on item response patterns. Multinomial logistic regression predicted latent class membership from socio-demographic covariates. RESULTS: A total of 54,771 reported experiencing SCD. The optimal number of latent classes was three, labeled as Mild, Moderate, and Severe SCD. Thirty-five percent of the sample belonged to the Severe group. Members of this subgroup were significantly less likely to be older (65+ vs. 45-54 OR = 0.29, 95% CI: 0.23-0.35) and more likely to be non-Hispanic Black (OR = 1.80, 95% CI: 1.53-2.11), have not graduated high school (OR = 1.60, 95% CI: 1.34-1.91), or earned <$15K a year (OR = 3.03, 95% CI: 2.43-3.77). CONCLUSIONS: This study determined three latent subgroups indicating severity of SCD and identified socio-demographic predictors. Using a single categorical indicator of SCD severity instead of six separate items improves the versatility of population-level surveillance.

Adversity and child body mass index in Fragile Families over 15 years: Do type and timing matter?

Background: Weight status has been linked to adverse childhood experiences. Existing research, however, is limited to unidimensional assessments of cumulative risk and does not account for the complex nature of adversity experienced by children in high-risk settings. We fill existing gaps by assessing how four subtypes of adversity across two primary dimensions of threat and deprivation-based adversity are associated with changes in body mass index (BMI) across child ages 3 through 15 years. Method: U.S. mothers and fathers (n = 2412) in the Fragile Families and Child Wellbeing Study were interviewed when children were born, and again at ages 1, 3, 5, 9, and 15 years. Independent variables include interpersonal (e.g., domestic violence), family (e.g., mental health), economic (e.g., housing insecurity), and community (e.g., witness/victim of violence) adversity from ages 1 through 9 years. Path analysis regressed changes in BMIz from ages 3 through 15 on past adversity exposures. Results: Increased interpersonal and community adversity subtypes from ages 3 to 5 were associated with decreased BMIz from ages 5-9 years. Increased economic adversity from age 3 to 5 was associated with increased BMIz from ages 5 to 9, adjusted for mother age, race, and education. Conclusion: Findings highlight the differential influence of past adversity type and timing on child BMI. Interpersonal and community adversity were associated with decreased BMIz, and economic adversity with increased BMIz. Differences in directionality of associations suggest research should capture multiple dimensions of adversity in early childhood and possible positive and negative trends in effects on child weight as children grow from early to mid-childhood.

The Intersection of Neighborhood Environment and Adverse Childhood Experiences: Methods for Creation of a Neighborhood ACEs Index.

This study evaluated methods for creating a neighborhood adverse childhood experiences (ACEs) index, a composite measure that captures the association between neighborhood environment characteristics (e.g., crime, healthcare access) and individual-level ACEs exposure, for a particular population. A neighborhood ACEs index can help understand and address neighborhood-level influences on health among individuals affected by ACEs. Methods entailed cross-sectional secondary analysis connecting individual-level ACEs data from the Philadelphia ACE Survey (n = 1677) with 25 spatial datasets capturing neighborhood characteristics. Four methods were tested for index creation (three methods of principal components analysis, Bayesian index regression). Resulting indexes were compared using Akaike Information Criteria for accuracy in explaining ACEs exposure. Exploratory linear regression analyses were conducted to examine associations between ACEs, the neighborhood ACEs index, and a health outcome-in this case body mass index (BMI). Results demonstrated that Bayesian index regression was the best method for index creation. The neighborhood ACEs index was associated with higher BMI, both independently and after controlling for ACEs exposure. The neighborhood ACEs index attenuated the association between BMI and ACEs. Future research can employ a neighborhood ACEs index to inform upstream, place-based interventions and policies to promote health among individuals affected by ACEs.