Use of Actigraphy (Wearable Digital Sensors to Monitor Activity) in Heart Failure Randomized Clinical Trials: A Scoping Review

Anchouche, Khalil; Elharram, Malik; Oulousian, Emily; Razaghizad, Amir; Avram, Robert; Marquis‐Gravel, Guillaume; Randhawa, Varinder K.; Nkulikiyinka, Richard; Ni, Wei; Fiuzat, Mona; O’Connor, Christopher M.; Psotka, Mitchell A.; Fox, Jonathan; Tyl, Benoît; Kao, David; Sharma, Abhinav

doi:10.1016/j.cjca.2021.07.001

Cited by 22 publications

(8 citation statements)

References 43 publications

(84 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While they recommend the use of actigraphy outcomes to assess treatment effects in clinical trials in patient populations with limited activity, they found substantial heterogeneity in the use and methodology employed. Similar findings have also been reported more recently in the context of clinical trials in heart failure, 6 Huntington's disease ,7 and in Parkinson's disease. 8 The idea of developing actigraphy endpoints imitates what is usually done with health outcomes, where a clinical assessment is performed to collect data on a specific endpoint (continuous, categorical, etc.)…”

Section: Introductionsupporting

confidence: 86%

Statistical analysis of actigraphy data with generalised additive models

Lisi,

Abellan

2023

Pharmaceutical Statistics

View full text Add to dashboard Cite

There is a growing interest in the use of physical activity data in clinical studies, particularly in diseases that limit mobility in patients. High‐frequency data collected with digital sensors are typically summarised into actigraphy features aggregated at epoch level (e.g., by minute). The statistical analysis of such volume of data is not straightforward. The general trend is to derive metrics, capturing specific aspects of physical activity, that condense (say) a week worth of data into a single numerical value. Here we propose to analyse the entire time‐series data using Generalised Additive Models (GAMs). GAMs are semi‐parametric models that allow inclusion of both parametric and non‐parametric terms in the linear predictor. The latter are smooth terms (e.g., splines) and, in the context of actigraphy minute‐by‐minute data analysis, they can be used to assess daily patterns of physical activity. This in turn can be used to better understand changes over time in longitudinal studies as well as to compare treatment groups. We illustrate the application of GAMs in two clinical studies where actigraphy data was collected: a non‐drug, single‐arm study in patients with amyotrophic lateral sclerosis, and a physical‐activity sub‐study included in a phase 2b clinical trial in patients with chronic obstructive pulmonary disease.

show abstract

Section: Introductionsupporting

confidence: 86%

Statistical analysis of actigraphy data with generalised additive models

Lisi,

Abellan

2023

Pharmaceutical Statistics

View full text Add to dashboard Cite

show abstract

“…19 Also, regarding results, it's well known from the literature that functional capacity mostly correlates positively with sleep outcomes. 8 9 10 However, in this case, we have noticed that the functional capacity improved dramatically on doing the combined aerobic and resistance training for 8 weeks, however, his sleep outcomes deteriorated. Therefore, unexpectedly, there is no association/correlation between functional capacity and sleep outcomes.…”

Section: Discussionmentioning

confidence: 75%

Would the Actigraph Always be Sufficient for Sleep Analysis in Exercise-Based Studies? A Case Report of Negative Response of Sleep to Exercise

Atef

Gaber

2023

Sleep Sci

View full text Add to dashboard Cite

Introduction Sleep deprivation is common after coronary artery bypass grafting (CABG). It is mostly managed well by exercise. The number of reported post-CABG cases that respond negatively to exercise is scanty. The etiology is usually associated with the underlying sleep pathology, and how it responds to exercise. Cases with undiagnosed central sleep apnea post CABG have not been reported before. Case description A medically stable male patient, 63 years old, hypertensive, but not diabetic, had entered coronary artery bypass grafting (CABG) 8 weeks before attending the outpatient cardiac rehabilitation unit and was referred for a cardiac rehabilitation program at this time. He entered a study in the cardiac rehabilitation center utilizing either aerobic or combined aerobic and resistance training for 10 weeks to improve sleep architecture and functional capacity post-CABG. After randomization, he entered the group doing combined aerobic and resistance exercises. All of the patients in this group improved except him, his sleep quality worsened, but his functional capacity improved. After a complete analysis of sleep on polysomnography, it was revealed that the patient had central sleep apnea that was mostly worsened by resistance training. The patient was withdrawn from the study by the 8th week, and his sleep condition improved gradually. After then, he was asked to attend the cardiac rehabilitation center again to share in aerobic exercise, having evidence that central sleep apnea does not respond negatively to this form of training. After 12 months of follow-up, the patient still shows no signs of sleep deprivation. Conclusion Sleep deprivation is prevalent in post-CABG patients, but with different presentations and it can generally improve by exercise. Identification of the underlying cause of the sleeping difficulty is a cornerstone of targeted treatment.

show abstract

“…As a result, future research may evaluate whether the extended TRS‐HF DM with the addition of NT‐proBNP can prognosticate more sensitive HF outcomes. These may include changes in accelerometry data as a proxy for mobility, or expanded HF outcomes that, for example, include the initiation of loop diuretics 35,36 . Furthermore, understanding whether the extended TRS‐HF DM can improve outcomes or identify people who may derive increased benefit from SGLT2 inhibition may be warranted.…”

Section: Discussionmentioning

confidence: 99%

“…These may include changes in accelerometry data as a proxy for mobility, or expanded HF outcomes that, for example, include the initiation of loop diuretics. 35,36 Furthermore, understanding whether the extended TRS-HF DM can improve outcomes or identify people who may derive increased benefit from SGLT2 inhibition may be warranted. Validation of the TRS-HF DM and the TIMI Biomarker Score for Heart Failure in Diabetes could also be explored in lower-risk populations and individuals with recent ACS to establish further the prognostic and clinical utility.…”

Section: Discussionmentioning

confidence: 99%

External validation and extension of the TIMI risk score for heart failure in diabetes for patients with recent acute coronary syndrome: An analysis of the EXAMINE trial

Razaghizad

Sharma

et al. 2022

Diabetes Obesity Metabolism

Self Cite

View full text Add to dashboard Cite

Aims:The Thrombolysis in Myocardial Infarction Risk Score for Heart Failure (HF) in Diabetes (TRS-HF DM ) prognosticates HF hospitalization in people with type 2 diabetes (T2D). This study aimed to externally validate and extend its use for those with recent acute coronary syndrome (ACS). Materials and Methods: The TRS-HF DM was externally validated in the Examination of Cardiovascular Outcomes with Alogliptin versus Standard of Care (EXAMINE) trial (n = 5380) and extended with natriuretic biomarkers. Missing data were multiply imputed. Initial TRS-HF DM variables were previous HF (2 points), atrial fibrillation (1 point), coronary artery disease (1 point), estimated glomerular filtration rate <60 ml/ min/1.73 m 2 (1 point), and urine albumin-to-creatinine ratio 30-300 mg/g (1 point) and >300 mg/g (2 points).Results: In total, HF hospitalization occurred in 193 (3.6%) patients. Based on the TRS-HF DM , 25% of patients were classified as intermediate risk (1 point), 30% were classified as high risk (2 points), 19% were classified as very-high risk (3 points) and 26% were classified as severe risk (≥4 points). Before model extension, discrimination (C-index 0.76, 95%ÁCI 0.73-0.80) and calibration (calibration slope 0.82, 95%ÁCI 0.65-1.0; calibration-in-the-large À0.15, 95%ÁCI À0.37-0.64) were moderate-to-good in individuals with T2D and recent ACS. The extension of TRS-HF DM with the addition of N-terminal pro-B-type natriuretic peptide (NT-ProBNP) improved discrimination (C-index 0.82, 95%ÁCI 0.79-0.85) and calibration (calibration slope 0.84, 95%ÁCI 0.66-1.02; calibration-in-the-large À0.12, 95%ÁCI À0.33-0.081) for this higher-risk population. Conclusion:The TRS-HF DM with the extension of NT-ProBNP improves risk stratification and generalizes the use of the risk score for patients with T2D and ACS.Future validation studies in ACS populations may be warranted.

show abstract

Use of Actigraphy (Wearable Digital Sensors to Monitor Activity) in Heart Failure Randomized Clinical Trials: A Scoping Review

Cited by 22 publications

References 43 publications

Statistical analysis of actigraphy data with generalised additive models

Statistical analysis of actigraphy data with generalised additive models

Would the Actigraph Always be Sufficient for Sleep Analysis in Exercise-Based Studies? A Case Report of Negative Response of Sleep to Exercise

External validation and extension of the TIMI risk score for heart failure in diabetes for patients with recent acute coronary syndrome: An analysis of the EXAMINE trial

Contact Info

Product

Resources

About