Benefits of home-based foot neuromuscular electrical stimulation on self-reported function, leg pain and other leg symptoms among community-dwelling older adults: a sham-controlled randomised clinical trial.

INTRODUCTION: Lower leg pain and symptoms, and poor leg circulation are common in older adults. These can significantly affect their function and quality of life. Neuromuscular electrical stimulation (NMES) applied via the feet as 'foot NMES' activates the leg musculovenous pump. This study investigated the effects of foot NMES administered at home using Revitive® among community-dwelling older adults with lower leg pain and/or other lower leg symptoms such as cramps, or sensations of tired, aching, and heavy feeling legs. METHODS: A randomised placebo-controlled study with three groups (2 NMES, 1 Sham) and three assessments (baseline, week 8, week 12 follow-up) was carried out. Self-reported function using Canadian occupational performance measure (COPM), leg pain, overall leg symptoms score (heaviness, tiredness, aching, or cramps), and ankle blood flow were assessed. Analysis of covariance (ANCOVA) and logistic regression were used to compare the groups. Statistical significance was set at p < 0.05 (two-sided 5%). RESULTS: Out of 129 participants enrolled, 114 completed the study. The improvement in all outcomes were statistically significant for the NMES interventions compared to Sham at both week 8 (p < 0.01) and week 12 (p < 0.05). The improvement in COPM met the minimal clinically important difference (MCID) for the NMES interventions compared to Sham at both week 8 (p < 0.005) and week 12 (p < 0.05). Improvement in leg pain met MCID at week 8 compared to Sham (p < 0.05). Ankle blood flow increased approximately 3-fold during treatment compared to Sham. Compliance with the interventions was high and no device-related adverse events were reported. CONCLUSIONS: The home-based foot NMES is safe, and significantly improved self-reported function, leg pain and overall leg symptoms, and increased ankle blood flow compared to a Sham among older adults. TRIAL REGISTRATION: The trial was prospectively registered in ISRCTN on 17/06/2019 with registration number ISRCTN10576209. It can be accessed at https://www.isrctn.com/ISRCTN10576209 .

Using joint probability density to create most informative unidimensional indices: a new method using pain and psychiatric severity as examples.

BACKGROUND: Dimension reduction methods do not always reduce their underlying indicators to a single composite score. Furthermore, such methods are usually based on optimality criteria that require discarding some information. We suggest, under some conditions, to use the joint probability density function (joint pdf or JPD) of p-dimensional random variable (the p indicators), as an index or a composite score. It is proved that this index is more informative than any alternative composite score. In two examples, we compare the JPD index with some alternatives constructed from traditional methods. METHODS: We develop a probabilistic unsupervised dimension reduction method based on the probability density of multivariate data. We show that the conditional distribution of the variables given JPD is uniform, implying that the JPD is the most informative scalar summary under the most common notions of information. B. We show under some widely plausible conditions, JPD can be used as an index. To use JPD as an index, in addition to having a plausible interpretation, all the random variables should have approximately the same direction(unidirectionality) as the density values (codirectionality). We applied these ideas to two data sets: first, on the 7 Brief Pain Inventory Interference scale (BPI-I) items obtained from 8,889 US Veterans with chronic pain and, second, on a novel measure based on administrative data for 912 US Veterans. To estimate the JPD in both examples, among the available JPD estimation methods, we used its conditional specifications, identified a well-fitted parametric model for each factored conditional (regression) specification, and, by maximizing the corresponding likelihoods, estimated their parameters. Due to the non-uniqueness of conditional specification, the average of all estimated conditional specifications was used as the final estimate. Since a prevalent common use of indices is ranking, we used measures of monotone dependence [e.g., Spearman's rank correlation (rho)] to assess the strength of unidirectionality and co-directionality. Finally, we cross-validate the JPD score against variance-covariance-based scores (factor scores in unidimensional models), and the "person's parameter" estimates of (Generalized) Partial Credit and Graded Response IRT models. We used Pearson Divergence as a measure of information and Shannon's entropy to compare uncertainties (informativeness) in these alternative scores. RESULTS: An unsupervised dimension reduction was developed based on the joint probability density (JPD) of the multi-dimensional data. The JPD, under regularity conditions, may be used as an index. For the well-established Brief Pain Interference Inventory (BPI-I (the short form with 7 Items) and for a new mental health severity index (MoPSI) with 6 indicators, we estimated the JPD scoring. We compared, assuming unidimensionality, factor scores, Person's scores of the Partial Credit model, the Generalized Partial Credit model, and the Graded Response model with JPD scoring. As expected, all scores' rankings in both examples were monotonically dependent with various strengths. Shannon entropy was the smallest for JPD scores. Pearson Divergence of the estimated densities of different indices against uniform distribution was maximum for JPD scoring. CONCLUSIONS: An unsupervised probabilistic dimension reduction is possible. When appropriate, the joint probability density function can be used as the most informative index. Model specification and estimation and steps to implement the scoring were demonstrated. As expected, when the required assumption in factor analysis and IRT models are satisfied, JPD scoring agrees with these established scores. However, when these assumptions are violated, JPD scores preserve all the information in the indicators with minimal assumption.

Trajectories of pain and their associations with long-term cognitive decline in older adults: evidence from two longitudinal cohorts.

BACKGROUND: Pain is a dynamic experience that varies over time, but it remains unknown whether trajectories of pain are associated with subsequent cognitive decline. The purpose of this study was to identify distinct trajectories of pain presence and activity-limiting pain and investigate their longitudinal associations with the rate of subsequent cognitive decline in older adults. METHODS: A total of 5685 participants from the English Longitudinal Study of Ageing (ELSA) and 7619 participants from the Health and Retirement Study (HRS) were included. Pain presence trajectories were identified over eight years in the ELSA and 10 years in the HRS, while trajectories of activity-limiting pain were identified over 10 years in the HRS. We utilised linear mixed-effects models to investigate the long-term relationship between pain trajectories and the rate of cognitive decline across various domains, including memory, orientation, executive function and global cognition. RESULTS: Three pain presence trajectories were identified. Moderate-increasing and high-stable groups exhibited steeper declines in global cognition than the low-stable group. Furthermore, individuals in the moderate-increasing group experienced a more rapid decline in executive function, while the high-stable group showed a faster decline in orientation function. Two trajectories of activity-limiting pain were identified, with the moderate-increasing group experiencing a faster decline in orientation function and global cognition. CONCLUSIONS: The trajectories of both pain presence and activity-limiting pain are linked to the rate of subsequent cognitive decline among older people. Interventions for specific pain trajectories might help to delay the decline rate of cognition in specific domains.

Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights.

OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm. MATERIALS AND METHODS: A fine-tuned, domain-specific, transformer-based clinical text deep learning model was used to interpret free-text nursing assessments in the electronic medical records of 235,789 adult presentations to the ED over a three-year period. The model classified presentations according to whether the patient had pain on arrival at the ED. Interrupted time series analysis was used to determine the incidence of pain in patients on arrival over time. We described the changes in the population characteristics and incidence of patients with pain on arrival occurring with the start of the Covid-19 pandemic. RESULTS: 55.16% (95%CI 54.95%-55.36%) of all patients presenting to this ED had pain on arrival. There were differences in demographics and arrival and departure patterns between patients with and without pain. The Covid-19 pandemic initially precipitated a decrease followed by a sharp, sustained rise in pain on arrival, with concurrent changes to the population arriving in pain and their treatment. DISCUSSION: Applying a clinical text deep learning model has successfully identified the incidence of pain on arrival. It represents an automated, reproducible mechanism to identify pain from routinely collected medical records. The description of this population and their treatment forms the basis of intervention to improve care for patients with pain. The combination of the clinical text deep learning models and interrupted time series analysis has reported on the effects of the Covid-19 pandemic on pain care in the ED, outlining a methodology to assess the impact of significant events or interventions on pain care in the ED. CONCLUSION: Applying a novel deep learning approach to identifying pain guides methodological approaches to evaluating pain care interventions in the ED, giving previously unavailable population-level insights.

Development of PainFace software to simplify, standardize, and scale up mouse grimace analyses.

ABSTRACT: Facial grimacing is used to quantify spontaneous pain in mice and other mammals, but scoring relies on humans with different levels of proficiency. Here, we developed a cloud-based software platform called PainFace ( http://painface.net ) that uses machine learning to detect 4 facial action units of the mouse grimace scale (orbitals, nose, ears, whiskers) and score facial grimaces of black-coated C57BL/6 male and female mice on a 0 to 8 scale. Platform accuracy was validated in 2 different laboratories, with 3 conditions that evoke grimacing-laparotomy surgery, bilateral hindpaw injection of carrageenan, and intraplantar injection of formalin. PainFace can generate up to 1 grimace score per second from a standard 30 frames/s video, making it possible to quantify facial grimacing over time, and operates at a speed that scales with computing power. By analyzing the frequency distribution of grimace scores, we found that mice spent 7x more time in a "high grimace" state following laparotomy surgery relative to sham surgery controls. Our study shows that PainFace reproducibly quantifies facial grimaces indicative of nonevoked spontaneous pain and enables laboratories to standardize and scale-up facial grimace analyses.

The Relationship Between Patient Perceived Pain and the Numerical Rating System: A Prospective Validation Using Electronic Health Record Data.

We developed a method of using the Clinically Aligned Pain Assessment (CAPA) measures to reconstruct the Numeric Rating System (NRS). We used an observational retrospective cohort study design with prospective validation using de-identified adult patient data derived from a major health system. Data between 2011-2017 were used for development and 2018-2020 for validation. All included patients had at least one NRS and CAPA measurement at the same time. An ordinal regression model was built with CAPA components to predict NRS scores. We identified 6,414 and 3,543 simultaneous NRS-CAPA pairs in the development and validation dataset, respectively. All CAPA components were significantly related to NRS, with RMSE of 1.938 and Somers' D of 0.803 on the development dataset, and RMSE of 2.1 and Somers' D of 0.74 when prospectively validated. Our model was capable of accurately reconstructing NRS based on CAPA and was exact when the NRS was [0,7].

Digital Glomus Tumor - A Commonly Undiagnosed Cause of Finger Pain: Case Report.

Glomus tumors are rare vascular hamartomas most commonly found in the subungual region of the fingers. They present with a classic triad of paroxysmal pain, point tenderness, and cold sensitivity. The diagnosis is often missed for several years due to under recognition of this condition. A 42-year-old female presented with a several year history of pain in the middle finger when it was struck or exposed to cold. She had point tenderness on the fingernail, and increased curvature of the nail. Magnetic Resonance Imaging (MRI) revealed a 7mm subungual glomus tumor. The tumor was surgically excised via a transungual approach, resulting in complete relief of her pain. Glomus tumors are diagnosed clinically based on the presence of classic symptoms and positive provocative tests. These tests include point tenderness on palpation and pain when ice is placed on the digit. MRI imaging can be used when the diagnosis is unclear or to localize the tumor prior to surgery. Increased awareness of this condition among physicians could reduce the time to diagnosis and treatment.

Development of the neonatal pain response variable set: a mixed methods consensus process.

While over 40 neonatal pain assessment scales have been published, owing to a lack of consensus and standardized metrics, there are more than 100 assessment indicators with varying descriptors and quality differences. This study aims to reach a consensus on optimal and comprehensive variables for neonatal pain assessment, leading to the development of a multidimensional neonatal pain response variable set. This study consisted of three phases: (1) A literature review was conducted to identify influencing factors and assessment indicators of neonatal pain response. (2) Panel meetings involving neonatal healthcare professionals evaluated and screened factors and indicators to develop an initial draft of the variable set. (3) Through two rounds of Delphi study achieved consensus, and determined the neonatal pain response variable set. Through a literature review and a panel meeting, the identified factors and indicators were categorized into contextual, physiological, and behavioral variables, forming an initial draft of the variable set. Sixteen professionals participated in two rounds of the Delphi study, with response rates exceeding 70%, and authority coefficients surpassing 0.7 in both rounds. The final iteration of the variable set includes 9 contextual variables, 2 physiological variables, and 5 behavioral variables.   Conclusion: Neonatal pain response variable set developed in this study is scientific, comprehensive, and multidimensional, aligning with the characteristics of neonatal pain response and clinically applicable. The inclusion of contextual variables enhances the ability to confront the complexity of clinical environments and individual differences. It can provide a practical and theoretical basis for clinical research on neonatal pain assessment. What is Known: • Neonatal pain assessment relies on scales used by healthcare professionals currently. But there is no "gold standard" for neonatal pain assessment. • While over 40 neonatal pain assessment scales have been published, owing to a lack of consensus and standardized metrics, there are more than 100 assessment indicators with varying descriptors and quality differences. Most of scales overlook the clinical environment complexity individual differences in pain responses, diminishing the accuracy and applicability. What is New: • In addition to the commonly used physiological and behavioral variables in the scales, we have incorporated contextual variables to better address the complexity of clinical environments and individual differences in pain responses. • Through an evidence-based approach, developed a neonatal pain response variable set comprising 9 contextual variables, 2 physiological variables, and 5 behavioral variables.

Physiological Biomarkers for Assessment of Pain during Routine Blood Tests for Older Adults with Dementia in Long-Term Residential Care.

OBJECTIVE: Evaluating pain in individuals with dementia can be difficult when verbal communication is limited. Vocalization has emerged as a potential avenue for assessments of pain in nonverbal populations. This study aimed to evaluate if physiological assessments of vocalization were correlated with observational assessments of pain during routine blood tests for persons with dementia. DESIGN: A cross-sectional descriptive study. SETTING AND PARTICIPANTS: Sixty older adults (aged ≥65 years old) with dementia requiring routine finger puncture and peripheral venipuncture for routine blood tests were recruited by purposive sampling from 3 long-term care facilities in Taiwan. METHODS: Observational assessments were conducted with the Pain Assessment in Advanced Dementia (PAINAD) instrument; physiological biomarkers of vocalization were assessed with a noninvasive sensing device and microphone (NISDM). Assessments were conducted simultaneously in one session during situations of increasing pain levels: at rest, making a sound, finger puncture, and peripheral venipuncture. PAINAD scores were compared with signal recording measures from the NISDM. Analysis of variance and Pearson correlation coefficient assessed correlations between observational and physiological measures. RESULTS: Most participants were female (63.3%); mean age was 81.27 years (SD = 9.69); Clinical Dementia Rating was 2.23 ± 0.70; and Mini-Mental State Examination was 7.07 ± 6.95. Signal recording measures using the NISDM during finger puncture and venipuncture were significantly greater compared with measures at rest and making sound, indicating higher signal levels were associated with pain. PAINAD scores were significantly correlated with physiological measures for vocalization variables of sound amplitude (r = 0.49, P < .001), shimmer (r = 0.63, P < .001), and inhalation-to-exhalation amplitude ratio (r = 0.48, P < .001). CONCLUSIONS AND IMPLICATIONS: Elevated vocalizations detected with the NISDM were correlated with increased pain scores on the PAINAD instrument. Physiological measures of pain using novel vocalization biomarkers have the potential to enhance the quality of care for individuals with dementia and limited communication abilities.

Measuring pain intensity in older patients: a comparison of five scales.

BACKGROUND AND AIMS: Pain is common in older individuals. In order to understand and treat pain in this group, reliable and valid measures are needed. This study aimed to evaluate: (1) the validity, utility, incorrect response rates and preference rates of 5 pain rating scales in older individuals; and (2) the associations between age, education level, and cognitive function and both (a) incorrect response and (b) preference rates. METHODS: Two hundred and one orthopedic clinic outpatients ≥ 65 years old were asked to rate their current pain, and least, average, and worst pain intensity in the past week using 5 scales: Verbal Numerical Rating Scale (VNRS), Faces Pain Scale - Revised (FPS-R), Verbal Rating Scale (VRS), Numerical Rating Scale (NRS), and Visual Analogue Scale (VAS). Participants were also asked to indicate scale preference. We computed the associations between each measure and a factor score representing the shared variance among the scales, the incorrect response and scale preference rates, and the associations between incorrect response and preference rates and age, education level, and cognitive function. The incorrect responses included being unable to respond, providing more than one response, responses outside a range, providing range answers rather than fixed answers, and responses indicating 'least > average,' 'least > worst,' and 'average > worst'. RESULTS: The findings support validity of all 5 scales in older individuals who are able to use all measures. The VNRS had the lowest (2%) and the VAS had the highest (6%) incorrect response rates. The NRS was the most (35%) and the VAS was the least (5%) preferred. Age was associated with the incorrect response rates of the VRS and VAS, such that older individuals were less likely to use these scales correctly. Education level was associated with the incorrect response rates of the FPS-R, NRS and VAS, such that those with less education were less likely to use these measures correctly. Cognitive function was not significantly associated with incorrect response rates. Age, education level and cognitive function were not significantly associated with scale preference. CONCLUSIONS: Although all five scales are valid, the VNRS evidences the best overall utility in this sample of older individuals with pain. The NRS or FPS-R would be fine alternatives if it is not practical or feasible to use the VNRS.

Exercise in newly diagnosed patients with multiple myeloma: A randomized controlled trial of effects on physical function, physical activity, lean body mass, bone mineral density, pain, and quality of life.

Reduced physical function caused by bone destruction, pain, anemia, infections, and weight loss is common in multiple myeloma (MM). Myeloma bone disease challenges physical exercise. Knowledge on the effects and safety of physical exercise in newly diagnosed patients with MM is limited. In a randomized, controlled trial, we studied the effect of a 10-week individualized physical exercise program on physical function, physical activity, lean body mass (LBM), bone mineral density (BMD), quality of life (QoL), and pain in patients newly diagnosed with MM. Lytic bone disease was assessed, and exercise was adjusted accordingly. Primary outcome: knee extension strength. Secondary outcomes: Six-Minute-Walk-Test, 30-s Sit-to-Stand-Test (SST), grip strength, level of physical activity, LBM, BMD, QoL, and pain. Measurements were conducted pre- and post-intervention, and after 6 and 12 months. We included 100 patients, 86 were evaluable; 44 in the intervention group (IG) and 42 in the control group (CG). No statistically significant differences between groups were observed. Knee extension strength declined in the IG (p = .02). SST, aerobic capacity, and global QoL improved in both groups. Pain decreased consistently in the IG regardless of pain outcome. No significant safety concerns of physical exercise in newly diagnosed patients with MM were observed.