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.
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.
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.
This prospective, multicenter study aims to enroll approximately 2000 hospitalized adult patients with Parkinson's disease, multiple system atrophy, or diabetes (aged ≥50 for diabetics) who are suspected of having or are diagnosed with orthostatic hypotension (OH). Participants will be recruited from 15 high-level clinical centers in China between March 2026 and February 2029.
Case-control
Cross-sectional
Intelligent diagnostic system for orthostatic hypotension
Other interventionAll 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 (ECG), and end-tidal carbon dioxide (ETCO₂). Monitoring is conducted for a 10-minute baseline period in the supine position and continues for up to 10 minutes following standing.
Classification of Orthostatic Hypotension
Orthostatic hypotension will be subtyped according to the timing of blood pressure reduction after standing: Classical, Initial, or Delayed. Additionally, etiology will be classified as Neurogenic or Non-neurogenic, determined by the heart rate response to blood pressure change, quantified as the ratio of change in heart rate to change in systolic blood pressure (ΔHR/ΔSBP ratio).
Dynamic Cerebral Autoregulation Parameters
Quantitative assessment of dynamic cerebral autoregulation (dCA) function will be performed using Transfer Function Analysis (TFA) on continuous blood pressure and cerebral blood flow velocity signals. Parameters include phase difference, gain, and coherence in the following frequency ranges: very low frequency (VLF: 0.02-0.07 Hz), low frequency (LF: 0.07-0.20 Hz), and high frequency (HF: 0.20-0.70 Hz).
Performance of the Risk Stratification Model
The predictive accuracy of the developed risk stratification model for adverse events (e.g., falls, syncope) will be assessed using metrics including sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC).
Incidence of Adverse Clinical Events
The cumulative incidence of the following clinical events will be recorded and compared between groups: falls, syncope (fainting), fractures, cognitive decline (defined as a decrease in Montreal Cognitive Assessment \[MoCA\] or Mini-Mental State Examination \[MMSE\] score from baseline), and all-cause mortality.
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Xuanwu Hospital, Beijing
Lead sponsor
The First Hospital of Jilin University
Collaborator
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