STRATEGIES TO MANAGE POSTURAL ORTHOSTATIC TACHYCARDIA SYNDROME (POTS) IN A CARDIAC REHABILITATION MODEL.
Bibliographic record
Abstract
Postural Orthostatic Tachycardia Syndrome (POTS) is a form of dysautonomia and a clinical syndrome of orthostatic intolerance. This chronic debilitating condition most prevalent in premenopausal women is characterized by both cardiac and non-cardiac symptoms, including exercise intolerance. Patients may benefit from a multidisciplinary approach to assist with non-pharmacological management, such as lifestyle modification and exercise, the only intervention currently shown to induce clinical remission. A cardiac rehabilitation (CR) program has supported these patients as part of their current model of care. A traditional CR setting has been challenging and there is a need to develop novel and effective ways to support these patients. PURPOSE: To describe the creation of a self-management intervention tailored to the needs of women living with POTS. METHODS: Retrospective chart reviews, literature review, patient surveys and staff feedback were completed and integrated with evidence-based guidelines to inform the creation of a program focusing on best practice and patient needs. RESULTS: Between 2016-2019, 42 women aged 18-62 years (mean=35 ± 13.02) were referred to CR with 68% exhibiting below average age-predicted fitness in Metabolic Equivalents (METS ml/min/kg, (9.7 ± 10.42). 62% of participants attended onsite CR while 33% of patients opted for a home program. A multidisciplinary team developed content and selected outcome measures better suited to evaluate this population. Based on the literature, recumbent aerobic exercise, resistance training and counter pressure maneuvers are important components to physical activity participation. Strategies to manage postural intolerance such as pacing, hydration, salt intake and compression garments are included to promote first line non-pharmacological approaches to POTS management. Based on feedback from past participants in the traditional CR model, peer-support and stress/anxiety management are highly valued and therapeutic. CONCLUSIONS: The self-management and peer support model for POTS was developed with up-to-date recommendations and non-pharmacologic interventions. Effectiveness and feasibility of this new model of care will be evaluated. Future developments in virtual care will be explored to enhance access to the program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".