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Norweg A, Hofferber B, Oh C, Spinner M, Stavrolakes K, Pavol M, DiMango A, Raveis VH, Murphy CG, Allegrante JP, Buchholz D, Zarate A, Simon N. Capnography-Assisted Learned, Monitored (CALM) breathing therapy for dysfunctional breathing in COPD: A bridge to pulmonary rehabilitation. Contemp Clin Trials 2023; 134:107340. [PMID: 37730198 DOI: 10.1016/j.cct.2023.107340] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/20/2023] [Accepted: 09/15/2023] [Indexed: 09/22/2023]
Abstract
BACKGROUND Although dyspnea is a primary symptom of chronic obstructive pulmonary disease (COPD), its treatment is suboptimal. In both COPD and acute anxiety, breathing patterns become dysregulated, contributing to abnormal CO2, dyspnea, and inefficient recovery from breathing challenges. While pulmonary rehabilitation (PR) improves dyspnea, only 1-2% of patients access it. Individuals with anxiety who use PR have worse outcomes. METHODS We present the protocol of a randomized controlled trial designed to determine the feasibility and acceptability of a new, four-week mind-body intervention that we developed, called "Capnography-Assisted Learned, Monitored (CALM) Breathing," as an adjunct to PR. Eligible participants are randomized in a 1:1 ratio to either CALM Breathing program or Usual Care. CALM Breathing consists of 10 core, slow breathing exercises combined with real time biofeedback (of end-tidal CO2, respiratory rate, and airflow) and motivational interviewing. CALM Breathing promotes self-regulated breathing, linking CO2 changes to dyspnea and anxiety symptoms and targeting breathing efficiency and self-efficacy in COPD. Participants are randomized to CALM Breathing or a Usual Care control group. RESULTS Primary outcomes include feasibility and acceptability metrics of recruitment efficiency, participant retention, intervention adherence and fidelity, PR facilitation, patient satisfaction, and favorable themes from interviews. Secondary outcomes include breathing biomarkers, symptoms, health-related quality of life, six-minute walk distance, lung function, mood, physical activity, and PR utilization and engagement. CONCLUSION By disrupting the cycle of dyspnea and anxiety, and providing a needed bridge to PR, CALM Breathing may address a substantive gap in healthcare and optimize treatment for patients with COPD.
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Affiliation(s)
- Anna Norweg
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA.
| | - Brittany Hofferber
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Cheongeun Oh
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Michael Spinner
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Kimberly Stavrolakes
- Outpatient Pulmonary Rehabilitation Program, New York Presbyterian Hospital, New York, NY, USA
| | - Marykay Pavol
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA; Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Angela DiMango
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Victoria H Raveis
- Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York, NY, USA
| | - Charles G Murphy
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - John P Allegrante
- Department of Health and Behavior Studies, Teachers College, Columbia University, New York, NY, USA; Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - David Buchholz
- Department of Primary Care, Columbia University Irving Medical Center, New York, NY, USA
| | - Alejandro Zarate
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Naomi Simon
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
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MacKinnon DF. Bipolar disorder as maladaptive arousal: a behavioral model and evidence. Ann N Y Acad Sci 2008; 1129:185-9. [PMID: 18591479 DOI: 10.1196/annals.1417.000] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Bipolar disorder can be understood as a disorder of behavioral regulation. Manic and depressed individuals are impaired in the titration of appetitive arousal, possibly at the level of neuronal plasticity. An experiment in which fixed 5% CO2 stimulates respiration and blocks satiety tests the regulation of appetitive arousal. In preliminary analysis of data from 35 individuals (24 with bipolar disorder) individuals with bipolar disorder were more likely to fail to find a stable state of respiratory adjustment to CO2. If confirmed, the unstable respiratory response to CO2 may prove useful as a bipolar-disorder endophenotype.
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Affiliation(s)
- Dean F MacKinnon
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Meyer 3-181, 600 N. Wolfe Street, Baltimore, MD 21287, USA.
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Poon CS, Tin C, Yu Y. Homeostasis of exercise hyperpnea and optimal sensorimotor integration: the internal model paradigm. Respir Physiol Neurobiol 2007; 159:1-13; discussion 14-20. [PMID: 17416554 PMCID: PMC2225386 DOI: 10.1016/j.resp.2007.02.020] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2007] [Revised: 02/28/2007] [Accepted: 02/28/2007] [Indexed: 11/16/2022]
Abstract
Homeostasis is a basic tenet of biomedicine and an open problem for many physiological control systems. Among them, none has been more extensively studied and intensely debated than the dilemma of exercise hyperpnea - a paradoxical homeostatic increase of respiratory ventilation that is geared to metabolic demands instead of the normal chemoreflex mechanism. Classical control theory has led to a plethora of "feedback/feedforward control" or "set point" hypotheses for homeostatic regulation, yet so far none of them has proved satisfactory in explaining exercise hyperpnea and its interactions with other respiratory inputs. Instead, the available evidence points to a far more sophisticated respiratory controller capable of integrating multiple afferent and efferent signals in adapting the ventilatory pattern toward optimality relative to conflicting homeostatic, energetic and other objectives. This optimality principle parsimoniously mimics exercise hyperpnea, chemoreflex and a host of characteristic respiratory responses to abnormal gas exchange or mechanical loading/unloading in health and in cardiopulmonary diseases - all without resorting to a feedforward "exercise stimulus". Rather, an emergent controller signal encoding the projected metabolic level is predicted by the principle as an exercise-induced 'mental percept' or 'internal model', presumably engendered by associative learning (operant conditioning or classical conditioning) which achieves optimality through continuous identification of, and adaptation to, the causal relationship between respiratory motor output and resultant chemical-mechanical afferent feedbacks. This internal model self-tuning adaptive control paradigm opens a new challenge and exciting opportunity for experimental and theoretical elucidations of the mechanisms of respiratory control - and of homeostatic regulation and sensorimotor integration in general.
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Affiliation(s)
- Chi-Sang Poon
- Harvard-MIT Division of Health Sciences and Technology, Bldg. 56-046, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
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