Remotely monitored physical activity from older people with cardiac devices associates with physical functioning.

INTRODUCTION: Accelerometer-derived physical activity (PA) from cardiac devices are available via remote monitoring platforms yet rarely reviewed in clinical practice. We aimed to investigate the association between PA and clinical measures of frailty and physical functioning. METHODS: The PATTErn study (A study of Physical Activity paTTerns and major health Events in older people with implantable cardiac devices) enrolled participants aged 60 + undergoing remote cardiac monitoring. Frailty was measured using the Fried criteria and gait speed (m/s), and physical functioning by NYHA class and SF-36 physical functioning score. Activity was reported as mean time active/day across 30-days prior to enrolment (30-day PA). Multivariable regression methods were utilised to estimate associations between PA and frailty/functioning (OR = odds ratio, ß = beta coefficient, CI = confidence intervals). RESULTS: Data were available for 140 participants (median age 73, 70.7% male). Median 30-day PA across the analysis cohort was 134.9 min/day (IQR 60.8-195.9). PA was not significantly associated with Fried frailty status on multivariate analysis, however was associated with gait speed (ß = 0.04, 95% CI 0.01-0.07, p = 0.01) and measures of physical functioning (NYHA class: OR 0.73, 95% CI 0.57-0.92, p = 0.01, SF-36 physical functioning: ß = 4.60, 95% CI 1.38-7.83, p = 0.005). CONCLUSIONS: PA from cardiac devices was associated with physical functioning and gait speed. This highlights the importance of reviewing remote monitoring PA data to identify patients who could benefit from existing interventions. Further research should investigate how to embed this into clinical pathways.

Defining trajectories of response in patients with psoriasis treated with biologic therapies.

BACKGROUND: The effectiveness and cost-effectiveness of biologic therapies for psoriasis are significantly compromised by variable treatment responses. Thus, more precise management of psoriasis is needed. OBJECTIVES: To identify subgroups of patients with psoriasis treated with biologic therapies, based on changes in their disease activity over time, that may better inform patient management. METHODS: We applied latent class mixed modelling to identify trajectory-based patient subgroups from longitudinal, routine clinical data on disease severity, as measured by the Psoriasis Area and Severity Index (PASI), from 3546 patients in the British Association of Dermatologists Biologics and Immunomodulators Register, as well as in an independent cohort of 2889 patients pooled across four clinical trials. RESULTS: We discovered four discrete classes of global response trajectories, each characterized in terms of time to response, size of effect and relapse. Each class was associated with differing clinical characteristics, e.g. body mass index, baseline PASI and prevalence of different manifestations. The results were verified in a second cohort of clinical trial participants, where similar trajectories following the initiation of biologic therapy were identified. Further, we found differential associations of the genetic marker HLA-C*06:02 between our registry-identified trajectories. CONCLUSIONS: These subgroups, defined by change in disease over time, may be indicative of distinct endotypes driven by different biological mechanisms and may help inform the management of patients with psoriasis. Future work will aim to further delineate these mechanisms by extensively characterizing the subgroups with additional molecular and pharmacological data.

Assessing the severity of Type 2 diabetes using clinical data-based measures: a systematic review.

AIMS: To identify and critically appraise measures that use clinical data to grade the severity of Type 2 diabetes. METHODS: We searched MEDLINE, Embase and PubMed between inception and June 2018. Studies reporting on clinical data-based diabetes-specific severity measures in adults with Type 2 diabetes were included. We excluded studies conducted solely in participants with other types of diabetes. After independent screening, the characteristics of the eligible measures including design and severity domains, the clinical utility of developed measures, and the relationship between severity levels and health-related outcomes were assessed. RESULTS: We identified 6798 studies, of which 17 studies reporting 18 different severity measures (32 314 participants in 17 countries) were included: a diabetes severity index (eight studies, 44%); severity categories (seven studies, 39%); complication count (two studies, 11%); and a severity checklist (one study, 6%). Nearly 89% of the measures included diabetes-related complications and/or glycaemic control indicators. Two of the severity measures were validated in a separate study population. More severe diabetes was associated with increased healthcare costs, poorer cognitive function and significantly greater risks of hospitalization and mortality. The identified measures differed greatly in terms of the included domains. One study reported on the use of a severity measure prospectively. CONCLUSIONS: Health records are suitable for assessment of diabetes severity; however, the clinical uptake of existing measures is limited. The need to advance this research area is fundamental as higher levels of diabetes severity are associated with greater risks of adverse outcomes. Diabetes severity assessment could help identify people requiring targeted and intensive therapies and provide a major benchmark for efficient healthcare services.

Factors that drive insulin-dosing decisions of diabetes care providers: a vignette-based study in the Netherlands.

AIM: To test how certain patient factors would influence the decision of Dutch care providers regarding insulin dose adjustments. We hypothesize that some of these decisions would diverge from recent evidence and consensus statements. METHODS: We developed narrative vignettes describing clinical scenarios of patients receiving basal insulin therapy. For each vignette, the respondents were asked to indicate whether they would advise a change in insulin dose. A total of 520 paper questionnaires were distributed among physicians and nurses in primary and secondary care in the Netherlands. Multivariate linear and logistic regression analyses were performed to identify factors associated with dosing decisions. RESULTS: A total of 190 (37%) questionnaires were returned. In cases of a severe rather than mild hypoglycaemic event, care providers were nearly five times more likely to decrease the dose (odds ratio 4.77, 95% CI 1.65-13.75). Care providers were six times more likely to increase the dose when the patient's current dose was low (30 units) rather than high (90 units) (odds ratio 6.38, 95% CI 3.04-13.37). The plasma glucose concentration during a hypoglycaemic event and a known history of cardiovascular disease did not influence the care providers' dosing decisions. CONCLUSION: Evidence regarding the optimum insulin titration is not always translated into clinical practice. When formulating guidelines, misconceptions should be identified and addressed.

Using personas to tailor educational messages to the preferences of coronary heart disease patients.

PURPOSE: Although tailoring health education messages to individual characteristics of patients has shown promising results, most patient education materials still take a one-size-fits-all approach. The aim of this study was to develop a method for tailoring health education messages to patients' preferences for various message features, using the concept of personas. This is a preliminary study focused on education for coronary heart disease (CHD) patients. METHODS: This study used a three-step approach. First, we created personas by (i) performing k-means cluster analysis on data from an online survey that assessed the preferences of 213 CHD patients for various message features and, (ii) creating a vivid description of the preferences per patient cluster in an iterative process with the research team. Second, we developed adaptation rules to tailor existing educational messages to the resulting personas. Third, we conducted a pilot validation by adapting nine existing educational messages to each of the personas. These messages and the resulting personas were then presented to a separate group of 38 CHD patients who visited the cardiology outpatient clinic. They were first asked to choose their most preferred, second most preferred, and least preferred persona. Subsequently, they were asked to rate three of the adapted messages; one for every of the persona choices. RESULTS: We created five personas that pertained to five patient clusters. Personas varied mainly on preferences for medical or lay language, current or future temporal perspective, and including or excluding explicit health risks. Fifty-five different adaptation rules were developed, primarily describing adaptations to the message's perspective, level of detail, sentence structure, and terminology. Most participants in the validation study could identify with one of the five personas, although some of them found it hard to choose. On average, 68.5% of all participants rated the messages that matched their most preferred persona more positively than, or in the same way as, the messages that matched their least preferred persona. CONCLUSIONS: The persona-based method developed in this study can be used to create a manageable set of patient-centered tailored messages, while additionally using the developed personas to assess patients' preferences.

Development of evidence-based clinical algorithms for prescription of exercise-based cardiac rehabilitation.

BACKGROUND: Guideline adherence with respect to exercise-based cardiac rehabilitation (CR) is hampered by a large variety of complex guidelines and position statements, and the fact that these documents are not specifically designed for healthcare professionals prescribing exercise-based CR programs. This study aimed to develop clinical algorithms that can be used in clinical practice for prescription and evaluation of exercise-based CR in patients with coronary artery disease (CAD) and chronic heart failure (CHF). METHODS: The clinical algorithms were developed using a systematic approach containing four steps. First, all recent Dutch and European cardiac rehabilitation guidelines and position statements were reviewed and prioritised. Second, training goals requiring a differentiated training approach were selected. Third, documents were reviewed on variables to set training intensity, modalities, volume and intensity and evaluation instruments. Finally, the algorithms were constructed. RESULTS: Three Dutch guidelines and three European position statements were reviewed. Based on these documents, five training goals were selected and subsequently five algorithms for CAD patients and five for CHF patients were developed. CONCLUSIONS: This study presents evidence-based clinical algorithms for exercise-based CR in patients with CAD and CHF according to their training goals. These algorithms may serve to improve guideline adherence and the effectiveness of exercise-based CR.

An Overview of Real-World Data Infrastructure for Cancer Research.

AIMS: There is increasing interest in the opportunities offered by Real World Data (RWD) to provide evidence where clinical trial data does not exist, but access to appropriate data sources is frequently cited as a barrier to RWD research. This paper discusses current RWD resources and how they can be accessed for cancer research. MATERIALS AND METHODS: There has been significant progress on facilitating RWD access in the last few years across a range of scales, from local hospital research databases, through regional care records and national repositories, to the impact of federated learning approaches on internationally collaborative studies. We use a series of case studies, principally from the UK, to illustrate how RWD can be accessed for research and healthcare improvement at each of these scales. RESULTS: For each example we discuss infrastructure and governance requirements with the aim of encouraging further work in this space that will help to fill evidence gaps in oncology. CONCLUSION: There are challenges, but real-world data research across a range of scales is already a reality. Taking advantage of the current generation of data sources requires researchers to carefully define their research question and the scale at which it would be best addressed.

Exercise training programs in Dutch cardiac rehabilitation centres.

PURPOSE: To assess methods for determination of exercise intensity, and to investigate practice variation with respect to the contents, volume and intensity of exercise training programs in Dutch cardiac rehabilitation (CR) centres. METHODS: A paper questionnaire was sent to all Dutch CR centres, consisting of 85 questions for patients with an acute coronary syndrome (ACS) or after coronary revascularisation (Group 1) and for patients with chronic heart failure (CHF, Group 2). RESULTS: CR professionals from 45 centres completed the questionnaires (58 %). Symptom-limited exercise testing was used to determine exercise capacity in 76 % and 64 % of the CR centres in group 1 and group 2, respectively; in these centres, a percentage of the maximum heart rate was the most frequently used exercise parameter (65 % and 56 %, respectively). All CR centres applied aerobic training and the majority applied strength training (64 % in group 1 and 92 % in group 2, respectively). There was a considerable variation in training intensity for both aerobic and strength training, as well as in training volume (1-20 h and 1-18 h respectively). CONCLUSION: Among Dutch CR centres, considerable variation exists in methods for determination of exercise intensity. In addition, there is no uniformity in training volume and intensity.

Healthcare utilisation in patients with long-term conditions during the COVID-19 pandemic: a population-based observational study of all patients across Greater Manchester, UK.

OBJECTIVES: Data on population healthcare utilisation (HCU) across both primary and secondary care during the COVID-19 pandemic are lacking. We describe primary and secondary HCU stratified by long-term conditions (LTCs) and deprivation, during the first 19 months of COVID-19 pandemic across a large urban area in the UK. DESIGN: A retrospective, observational study. SETTING: All primary and secondary care organisations that contributed to the Greater Manchester Care Record throughout 30 December 2019 to 1 August 2021. PARTICIPANTS: 3 225 169 patients who were registered with or attended a National Health Service primary or secondary care service during the study period. PRIMARY OUTCOMES: Primary care HCU (incident prescribing and recording of healthcare information) and secondary care HCU (planned and unplanned admissions) were assessed. RESULTS: The first national lockdown was associated with reductions in all primary HCU measures, ranging from 24.7% (24.0% to 25.5%) for incident prescribing to 84.9% (84.2% to 85.5%) for cholesterol monitoring. Secondary HCU also dropped significantly for planned (47.4% (42.9% to 51.5%)) and unplanned admissions (35.3% (28.3% to 41.6%)). Only secondary care had significant reductions in HCU during the second national lockdown. Primary HCU measures had not recovered to prepandemic levels by the end of the study. The secondary admission rate ratio between multi-morbid patients and those without LTCs increased during the first lockdown by a factor of 2.40 (2.05 to 2.82; p<0.001) for planned admissions and 1.25 (1.07 to 1.47; p=0.006) for unplanned admissions. No significant changes in this ratio were observed in primary HCU. CONCLUSION: Major changes in primary and secondary HCU were observed during the COVID-19 pandemic. Secondary HCU reduced more in those without LTCs and the ratio of utilisation between patients from the most and least deprived areas increased for the majority of HCU measures. Overall primary and secondary care HCU for some LTC groups had not returned to prepandemic levels by the end of the study.

Safety of a web-based insulin titration system for patients with type 2 diabetes mellitus - pilot study.

The treatment of type 2 diabetes patients with insulin requires active dose titration to obtain optimal glycemic control. We developed a web-based decision support system to guide patients in performing the titration task autonomously, at their homes. The system is based on a clinically validated algorithm. The aim of this study was to test the safety of the system in a pilot implementation in clinical practice. Patients were blinded from the advice given by the system and instead received insulin dosing advice given by caregivers. At the end of the pilot, advice of the system were evaluated on safety by an expert panel. In this pilot study six patients used the web-based system at their home. In total, 48 advice were logged in the system resulting in eighteen deviating systems dosing advice as compared to the advice of the caregiver. Evaluation of the eighteen deviating systems advice lead to the detection of one unsafe advice indicating a need to extend the algorithm with an additional safety decision rule.

Development of a web-based decision support system for insulin self-titration.

Insulin is the most potent agent for the treatment of diabetes mellitus. However insulin treatment requires frequent evaluation of blood glucose levels and adjustment of the insulin dose. This process is called titration. To guide patients with type 2 diabetes using once-daily long-acting insulin, we have developed a web-based decision support system for insulin self-titration. The purpose of this paper is to provide an overview of the phases of development and the final design of the system. We reviewed the literature, consulted an expert panel, and conducted interviews with patients to elicit system requirements. This revealed four important aspects: the insulin titration algorithm, the handling of hypoglycemic events, telemedicine functionalities, and visiting frequency monitoring. We used these requirements to develop a fully functional system.

Denitrification Studies with 13N-Labeled Nitrate.

Nitrate labeled with (13)N ((13)NO(3)(-)) was produced in a cyclotron by the (16)O(p, alpha)(13)N reaction with protons having energies of 14.5 million electron volts. The (13)NO(3)(-) was used as a tracer for direct quantitative measurements of denitrification rates in soils from flooded rice fields. The (13)N technique provides a new tracer method for the measurement of denitrification rates in natural systems over short time intervals, without changing the concentration of NO(3)(-)in the system.

Nitrogen-13-labeled nitrite and nitrate: distribution and metabolism after intratracheal administration.

Radioactive nitrogen-13 from nitrite (NO2-) or nitrate (NO3-) administered intratracheally or intravenously without added carrier to mice or rabbits was distributed evenly throughout most organs and tissues regardless of the entry route or the anion administered. Nitrogen-13 from both anions was distributed uniformly between plasma and blood cells. We found rapid in vivo oxidation of NO2- to NO3- at concentrations of 2 to 3 nanomoles per liter in blood. Over 50 percent oxidation within 10 minutes accounted for the similar nitrogen-13 distributions from both parent ions. The oxidation rates were animal species-dependent. No reduction of 13NO3- to 13NO2- was observed. A mechanistic hypothesis invoking oxidation of 13NO2- by a catalase-hydrogen peroxide complex accounts for the results. These results imply a concentration dependence for the in vivo fate of NO2- or nitrogen dioxide.

A community-based survey of posttraumatic stress disorder in the Netherlands.

In this study, the lifetime prevalence of stressful events and current posttraumatic stress disorder (PTSD) in the general adult population in the Netherlands were examined, and risk groups for PTSD were determined. A representative sample of 2,238 adults (>or=18 years) in the Netherlands completed digital questionnaires by computer-assisted self-interviewing. In total, 52.2% of the population reported at least one stressful event throughout their life. The estimated prevalence of current PTSD in the total population was 3.8%. Rape and physical assault were the stressful events most likely to be associated with PTSD, witness of injury the least likely. Stressful medical events were moderately associated with PTSD. Prevalence of PTSD was elevated among single women and middle-aged men.

Engaging cancer patients in clinical practice guideline development: a pilot study.

Background: Patient engagement is a key quality component of cancer guideline development; however, the optimal strategy for engaging patients in guideline development remains unclear. The feasibility and efficacy of two patient engagement models was tested by Cancer Care Ontario's cancer guideline development program, the Program in Evidence-Based Care (pebc). Methods: In model 1, patients participated in the guideline development process as active members of a working group. In model 2, patients formed a separate consultation group to review project plans and recommendations generated by multiple working groups. Training included online resources (model 1) and an in-person orientation (model 2). The pebc's standard patient engagement process acted as a control. The study was conducted for 1 year. Surveys measured the satisfaction of patients and members of the guideline working groups with the process and the outcome of each model. Results: Three guideline projects used model 1 to engage patients, six projects used model 2 to receive feedback, and one project was used as a control group (14 patients total). Most participants, whatever the model, reported satisfaction with their experience. Key challenges to implementation included patient recruitment and long wait times between meetings (model 1), and difficulty focusing on the discussion topic and poor meeting attendance on the part of patients (model 2). Conclusions: The pilot study demonstrated that, although both models are feasible and effective for the engagement of patients in cancer guideline development, modifications are required to optimize their continued interest. The pebc will use the study results to inform the implementation of a patient engagement strategy for its program.

External validation of prognostic models for critically ill patients required substantial sample sizes.

OBJECTIVE: To investigate the behavior of predictive performance measures that are commonly used in external validation of prognostic models for outcome at intensive care units (ICUs). STUDY DESIGN AND SETTING: Four prognostic models (Simplified Acute Physiology Score II, the Acute Physiology and Chronic Health Evaluation II, and the Mortality Probability Models II) were evaluated in the Dutch National Intensive Care Evaluation registry database. For each model discrimination (AUC), accuracy (Brier score), and two calibration measures were assessed on data from 41,239 ICU admissions. This validation procedure was repeated with smaller subsamples randomly drawn from the database, and the results were compared with those obtained on the entire data set. RESULTS: Differences in performance between the models were small. The AUC and Brier score showed large variation with small samples. Standard errors of AUC values were accurate but the power to detect differences in performance was low. Calibration tests were extremely sensitive to sample size. Direct comparison of performance, without statistical analysis, was unreliable with either measure. CONCLUSION: Substantial sample sizes are required for performance assessment and model comparison in external validation. Calibration statistics and significance tests should not be used in these settings. Instead, a simple customization method to repair lack-of-fit problems is recommended.

Modeling length of stay as an optimized two-class prediction problem.

OBJECTIVES: To develop a predictive model for the outcome length of stay at the Intensive Care Unit (ICU LOS), including the choice of an optimal dichotomization threshold for this outcome. Reduction of prediction problems of this type of outcome to a two-class problem is a common strategy to identify high-risk patients. METHODS: Threshold selection and model development are performed simultaneously. From the range of possible threshold values, the value is chosen for which the corresponding predictive model has maximal precision based on the data. To compare the precision of models for different dichotomizations of the outcome, the MALOR performance statistic is introduced. This statistic is insensitive to the prevalence of positive cases in a two-class prediction problem. RESULTS: The procedure is applied to data from cardiac surgery patients to dichotomize the outcome ICU LOS. The class probability tree method is used to develop predictive models. Within our data, the best model precision is found at the threshold of seven days. CONCLUSIONS: The presented method extends existing procedures for predictive modeling with optimization of the outcome definition for predictive purposes. The method can be applied to all prediction problems where the outcome variable needs to be dichotomized, and is insensitive to changes in the prevalence of positive cases with different dichotomization thresholds.

Secondary Use and Analysis of Big Data Collected for Patient Care.

Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on "Data mining and Big Data analytics" focuses on the literature published during the last two years, covering the timeframe since the working group's last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

The added value of clinical geriatric assessment prior to geriatric rehabilitation.

BACKGROUND: Community dwelling elderly who are temporarily unable to live independently due to functional decline can be referred for geriatric rehabilitation care at a nursing home. This referral is always preceded by a comprehensive geriatric assessment (CGA) by a geriatrician in hospital to rule out an indication for clinical admission and to evaluate geriatric multimorbidity. Because there is little evidence of the effectiveness of this procedure, we aimed to evaluate the results of this assessment and to elaborate on its relevance. METHODS: All patients who were referred by their general practitioner for a CGA in our hospital prior to geriatric rehabilitation care between March and December 2016 were included prospectively. Data were analysed retrospectively. Our primary aim was to describe the percentage of patients with an indication for hospital admission. Other outcomes included new diagnostic findings from the geriatric assessment and recommendations given to the elderly care physician in the geriatric rehabilitation facility. RESULTS: Of the 32 assessed patients, 25% required admission to hospital, either due to somatic illness, mainly infections or suspected neurological disorders, needing clinical treatment, or for further diagnostics. New findings by geriatric assessment mostly concerned vitamin deficiency and infection, for which treatment recommendations were given to the elderly care physician. CONCLUSION: Geriatric assessment prior to geriatric rehabilitation referral is essential as it identifies patients needing hospital care, which cannot be provided at a nursing home. Furthermore, the assessment results in important recommendations to the elderly care physician in the geriatric rehabilitation facility.

The influence of training characteristics on the effect of aerobic exercise training in patients with chronic heart failure: A meta-regression analysis.

Although aerobic exercise training has shown to be an effective treatment for chronic heart failure patients, there has been a debate about the design of training programs and which training characteristics are the strongest determinants of improvement in exercise capacity. Therefore, we performed a meta-regression analysis to determine a ranking of the individual effect of the training characteristics on the improvement in exercise capacity of an aerobic exercise training program in chronic heart failure patients. We focused on four training characteristics; session frequency, session duration, training intensity and program length, and their product; total energy expenditure. A systematic literature search was performed for randomized controlled trials comparing continuous aerobic exercise training with usual care. Seventeen unique articles were included in our analysis. Total energy expenditure appeared the only training characteristic with a significant effect on improvement in exercise capacity. However, the results were strongly dominated by one trial (HF-action trial), accounting for 90% of the total patient population and showing controversial results compared to other studies. A repeated analysis excluding the HF-action trial confirmed that the increase in exercise capacity is primarily determined by total energy expenditure, followed by session frequency, session duration and session intensity. These results suggest that the design of a training program requires high total energy expenditure as a main goal. Increases in training frequency and session duration appear to yield the largest improvement in exercise capacity.