Research, Development, and Application of Intelligent Diagnostic System for Orthostatic Hypotension

Overview

Orthostatic hypotension (OH) has a high incidence rate of 30%-50% in the elderly and populations with neurodegenerative diseases. The resulting cerebral hypoperfusion significantly increases the risk of cerebral ischemia, falls, and cognitive decline. Traditional OH diagnosis primarily relies on intermittent cuff blood pressure measurements, leading to low detection rates and an inability to provide scientifically effective OH classification. Furthermore, existing research often overlooks cerebral hemodynamic mechanisms, particularly the assessment of dynamic cerebral autoregulation (dCA), making it difficult to study the mechanisms behind OH and its associated symptoms. To address these issues, the research team has preliminarily developed an "Intelligent Diagnostic System for Orthostatic Hypotension". This system innovatively integrates synchronous and continuous monitoring of multiple parameters, including non-invasive beat-to-beat blood pressure, transcranial Doppler (TCD) cerebral blood flow velocity, and electrocardiogram (ECG). It also enables the quantitative assessment of dynamic cerebral autoregulation function. The project will collaborate with fifteen high-level clinical centers in China to collect data from 2000 patients with orthostatic hypotension. The aim is to establish and externally validate a risk stratification model for OH. By integrating multimodal clinical and hemodynamic data, the investigators intend to construct an automated, precise intelligent system for the classification, subtyping, and risk stratification of OH. This initiative will establish a standardized diagnostic and management pathway covering early screening, precise classification, early warning, and stratified intervention. The goal is to provide key technological support for enhancing the early identification and standardized management of OH, thereby reducing its associated disability and mortality rates.

Detailed description

This prospective, multicenter, observational cohort study aims to develop and validate an intelligent diagnostic and risk stratification system for orthostatic hypotension (OH). The study plans to enroll approximately 2000 participants from 15 tertiary clinical centers in China between March 2026 and February 2029. The target population comprises adult patients (≥18 years) with Parkinson's disease (PD) or multiple system atrophy (MSA), and patients aged ≥50 years with diabetes mellitus who are suspected or diagnosed with OH. A key technical inclusion criterion is the presence of adequate bilateral temporal bone windows for reliable transcranial Doppler (TCD) monitoring.

The core methodology involves synchronous, continuous, and non-invasive monitoring of beat-to-beat blood pressure (BP), bilateral cerebral blood flow velocity (CBFv) in the middle cerebral arteries, electrocardiogram (ECG), and end-tidal carbon dioxide (PetCO₂) during a standardized active standing test. Following a 10-minute supine rest, participants rapidly stand and remain upright for up to 10 minutes. Using this integrated data stream, OH is classified as Initial, Classic, or Delayed per consensus hemodynamic thresholds. Dynamic cerebral autoregulation (dCA) is quantitatively assessed offline via transfer function analysis (TFA) of the BP and CBFv signals, deriving phase, gain (absolute and normalized), and coherence parameters in very low frequency (VLF) and low frequency (LF) bands.

Participants are followed for 24 months, with a telephone follow-up at 12 months and an in-person visit at 24 months that includes a repeat stand test and cognitive assessment. The primary technical endpoints are the algorithm-based classification of OH subtype/etiology and the quantitative dCA parameters. Secondary endpoints include the performance (sensitivity, specificity, area under the curve \[AUC\]) of the derived multimodal risk model in predicting clinical events such as falls, syncope, cognitive decline, and all-cause mortality.

Data analysis will involve machine learning/statistical modeling on a development cohort to generate the risk stratification model, followed by external validation on a separate cohort to assess generalizability and clinical utility.

Interventions

• Other Intelligent diagnostic system for orthostatic hypotension
  All participants will undergo a standardized multi-parameter monitoring protocol. After resting in the supine position for at least 10 minutes, participants will perform an active standing test. During this protocol, the following parameters are continuously and synchronously recorded using the integrated intelligent diagnostic system: non-invasive beat-to-beat blood pressure, cerebral blood flow velocity in the middle cerebral artery (assessed via transcranial Doppler, TCD), electrocardiogram (

Primary outcome measures

• Classification of Orthostatic Hypotension [Time frame: 2years]
• Dynamic Cerebral Autoregulation Parameters [Time frame: 2years]

Secondary outcome measures (2)

• Performance of the Risk Stratification Model [Time frame: At the end of the 24-month follow-up period, when outcome data for all participants are available for model validation.]
• Incidence of Adverse Clinical Events [Time frame: Assessed at 12-month and 24-month follow-up visits.]

Eligibility criteria

Inclusion criteria

• Adult patients (≥18 years old).
• Clinical diagnosis of Parkinson's disease (PD) OR multiple system atrophy (MSA) OR diabetes mellitus (if diabetic, must be aged ≥50 years).
• Suspected or diagnosed with orthostatic hypotension (OH).
• Presence of adequate acoustic temporal bone windows for Transcranial Doppler (TCD) monitoring.
• Willing and able to provide informed consent.

Exclusion criteria

• Significant intracranial or extracranial arterial stenosis (≥70% confirmed by ultrasound).
• Recent stroke or intracerebral hemorrhage (confirmed by CT/MRI).
• Severe cardiac arrhythmias (e.g., atrial fibrillation) or severe valvular heart disease.
• Bilateral temporal bone windows insufficient for TCD monitoring.
• Pregnancy or lactation.
• Inability to cooperate with the testing procedures.
• Other systemic diseases that significantly affect cerebral blood flow regulation (e.g., severe thyroid or renal dysfunction).

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Study design

Observational model

Case-control

Study locations

China · 1 center

• Xuanwu Hospital, Capital Medical University — Beijing

Publications

• Wieling W, Kaufmann H, Claydon VE, van Wijnen VK, Harms MPM, Juraschek SP, Thijs RD. Diagnosis and treatment of orthostatic hypotension. Lancet Neurol. 2022 Aug;21(8):735-746. doi: 10.1016/S1474-4422(22)00169-7. PMID 35841911
• Freeman R, Abuzinadah AR, Gibbons C, Jones P, Miglis MG, Sinn DI. Orthostatic Hypotension: JACC State-of-the-Art Review. J Am Coll Cardiol. 2018 Sep 11;72(11):1294-1309. doi: 10.1016/j.jacc.2018.05.079. PMID 30190008
• Thijs RD, Brignole M, Falup-Pecurariu C, Fanciulli A, Freeman R, Guaraldi P, Jordan J, Habek M, Hilz M, Pavy-LeTraon A, Stankovic I, Struhal W, Sutton R, Wenning G, van Dijk JG. Recommendations for tilt table testing and other provocative cardiovascular autonomic tests in conditions that may cause transient loss of consciousness : Consensus statement of the European Federation of Autonomic Societi PMID 33752997
• Juraschek SP, Daya N, Rawlings AM, Appel LJ, Miller ER 3rd, Windham BG, Griswold ME, Heiss G, Selvin E. Association of History of Dizziness and Long-term Adverse Outcomes With Early vs Later Orthostatic Hypotension Assessment Times in Middle-aged Adults. JAMA Intern Med. 2017 Sep 1;177(9):1316-1323. doi: 10.1001/jamainternmed.2017.2937. PMID 28738139
• Panerai RB, Brassard P, Burma JS, Castro P, Claassen JA, van Lieshout JJ, Liu J, Lucas SJ, Minhas JS, Mitsis GD, Nogueira RC, Ogoh S, Payne SJ, Rickards CA, Robertson AD, Rodrigues GD, Smirl JD, Simpson DM; Cerebrovascular Research Network (CARNet). Transfer function analysis of dynamic cerebral autoregulation: A CARNet white paper 2022 update. J Cereb Blood Flow Metab. 2023 Jan;43(1):3-25. doi: 1 PMID 35962478

Identifiers

NCT: NCT07309666 · AF-SW-01-01.0

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗