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Vallelonga F, Romagnolo A, Merola A, Sobrero G, Di Stefano C, Milazzo V, Burrello J, Burrello A, Zibetti M, Milan A, Veglio F, Maule S. Detection of orthostatic hypotension with ambulatory blood pressure monitoring in parkinson's disease. Hypertens Res 2019; 42:1552-1560. [PMID: 31118487 DOI: 10.1038/s41440-019-0267-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Revised: 04/10/2019] [Accepted: 04/17/2019] [Indexed: 01/07/2023]
Abstract
We sought to test the accuracy of 24-hours ambulatory blood pressure (BP) monitoring (ABPM) for the detection of orthostatic hypotension (OH) in Parkinson's disease (PD). A total of 113 patients referred for autonomic testing between January 2015 and June 2017 underwent ABPM and office BP measurements in supine and standing positions. The study population consisted of 81 males and 32 females with PD duration of 6.5 ± 4.1 years and Hoehn and Yahr staging of 1 (13.3%), 1.5 (20.4%), 2 (27.4%), 2.5 (23.9%), 3 (13.3%), and 4 (1.8%). Motor fluctuations were present in 44% of patients. The data from office BP recordings were compared to selected ABPM parameters, and the results showed an association between OH and (a) ABPM-detected hypotensive episodes (Hypo-ep) and (b) ABPM-detected awakening hypotension (Hypo-aw). Having 2 or more Hypo-ep episodes ≤15 mmHg (systolic) compared to average 24-h systolic BP [Formula: see text] yielded 75% diagnostic accuracy for OH, while the presence of at least one [Formula: see text] within 90 min after getting up [Formula: see text] yielded 93% specificity for OH. A diagnostic accuracy of 87.6% was achieved when including daytime and nighttime ABPM values, weighted BP variability, systolic and diastolic BP loads, nocturnal dipping, and postprandial hypotension in a computerized prediction algorithm. In conclusion, our findings suggest that selected ABPM parameters, such as the number of hypotensive episodes and the presence of awakening hypotension, may be used to screen patients for OH, while using a computerized prediction algorithm that includes all ABPM parameters provides the greatest diagnostic accuracy.
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Affiliation(s)
- Fabrizio Vallelonga
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy.
| | - Alberto Romagnolo
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, via Cherasco 15, 10124, Turin, Italy
| | - Aristide Merola
- Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, OH, USA
| | - Gabriele Sobrero
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy
| | - Cristina Di Stefano
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy
| | - Valeria Milazzo
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy
| | - Jacopo Burrello
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy
| | - Alessio Burrello
- Department of Electronics and telecommunications, Polytechnic University of Turin, Turin, Italy
| | - Maurizio Zibetti
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, via Cherasco 15, 10124, Turin, Italy
| | - Alberto Milan
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy
| | - Franco Veglio
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy
| | - Simona Maule
- Autonomic Unit and Hypertension Unit, Department of Medical Sciences, University of Turin, via Genova 3, 10126, Turin, Italy
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