Database Open Access

Cerebromicrovascular Disease in Elderly with Diabetes

Vera Novak Rodrigo Quispe

Published: Oct. 9, 2020. Version: 1.0.0

When using this resource, please cite: (show more options)
Novak, V., & Quispe, R. (2020). Cerebromicrovascular Disease in Elderly with Diabetes (version 1.0.0). PhysioNet.

Additionally, please cite the original publication:

Novak V, Zhao P, Manor B, Sejdic E, Alsop D, Abduljalil A, Roberson PK, Munshi M, Novak P. (2011). Adhesion molecules, altered vasoreactivity, and brain atrophy in type 2 diabetes. Diabetes Care. 34(11):2438-41. doi: 10.2337/dc11-0969. Epub 2011 Sep 16.

Please include the standard citation for PhysioNet: (show more options)
Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.


This dataset was collected as part of a prospective observational study to evaluate the effects of type 2 diabetes mellitus (DM) on cerebral vasoregulation, perfusion and functional outcomes, measured by blood flow responses to hypocapnia and hypercapnia, Valsalva maneuver, head-up tilt, and sit-to-stand test. The dataset comprises of observations from 69 diabetic and control participants (aged 55 to 75 years) with continuous measurements of cerebral blood flow using transcranial Doppler and MRI (magnetic resonance imaging), heart rate, blood pressure, and respiratory parameters, balance, walking, laboratory and retinopathy measures at baseline, and 41 subjects who completed the two-years of follow-up. Regional gray, white matter and cerebrospinal fluid volumes were quantified using a segmentation method applied on T1- and T2- weighted images and perfusion maps, using a continuous arterial spin labeling (CASL) images at 3 Tesla MRI. White matter integrity was determined from fluid attenuated inversion recovery (FLAIR) and diffusion tensor imaging (DTI) MRI. Dynamics of cerebral vasoregulation to CO2 challenge and orthostatic stress were measured using Transcranial Doppler ultrasound (TCD).


Diabetes mellitus (DM) alters the permeability of the blood-brain barrier, thus affecting regional metabolism and microcirculatory regulation. We conducted a single-center study with the aim of prospectively determining the neurovascular and neuroanatomical implications of type 2 diabetes mellitus and its consequences for cognition and balance in the elderly. Our goal was to determine the mechanisms by which diabetes alters cerebral microcirculation and contributes to brain tissue damage and cognitive decline in the elderly. 


The study was approved by Institutional Review Board of Beth Israel Deaconess Medical Center (BIDMC #2008P000286). Full details of the experimental protocol are provided in the Research Design and Method section of the GE-79_Protocol.pdf document (p13-20).


A total of 120 participants were recruited for the study based on inclusion and exclusion criteria. The group comprised of 60 people with diabetes, along with 60 people as a control group. 

Screening (First Visit)

Subjects were asked to sign informed consent form. Medical history and activity questionnaires were completed. Pre-tests, including ECG, TCD window, MMSE (Mini Mental State Exam), and laboratory tests were performed.

Blood pressure (BP) Medications Taper: To establish a baseline, blood pressure was monitored for 3 days while the subject was taking their usual dose of antihypertensive medications. Antihypertensive medications were held on Day 2 of the study.

Visit 2 (Baseline)

Day 1: Subjects were admitted to CRC (Clinical Research Center). Physical and neurological examinations and neuropathy assessments were performed. Ophthalmological and cognitive examinations were done. Vital signs, anthropometrics and adiposity measures using skin fold thickness, and waist-to-hip-ratio were obtained.  24 hour ECG (electrocardiogram) recordings were performed during Day 1 (sleep) and Day 2 (daily activities, TCD and walking test). 

Day 2: Blood was collected for fasting glucose, A1c (hemoglobin A1c), C-peptide, lipids, hematocrit, WBC (white blood cells count) , and inflammatory markers.  A renal panel was obtained using blood and urine samples. TCD and MRI studies were then done.

Follow-up visits (6, 12, 18 months)

Subjects visited biannually for a follow-up visits that included measurements of fasting glucose, A1C, renal panels, vital signs, anthropometric and body fat measures, and updates on medical history and medications.

Visit 8 (Two-year follow-up)

Identical to Visit 2 (Baseline).

Data Description

The GE-79_Protocol.pdf in the main directory contains the description of the experimental protocol.

1. The following .csv files are located in Data_Description directory:

  • The GE-79_Files_and Channels.csv file enlists the signals and calibration that are in each open-format data files from Data folder. (ECG and conberted Labview data files are presented separately in the Data directory.)
  • The GE-79_Files_per_subject.csv file enlists open-format data files from Data folder available for each subject. (ECG and converted Labview data files are presented separately in the Data directory.)
  • GE-79_Summary_Table-Demographics-MRI-Part1.csv This file contains the data summary table’s first part which includes demographics, MRI data for every subject in Visit 2 and Visit 8.
  • GE-79_Summary_Table-MRI-Part2.csv This file contains the data summary table’s second part which includes MRI data for every subject in Visit 2 and Visit 8.
  • GE-79_Summary_Table-MRI-Part3.csv This file contains the data summary table’s third part which includes MRI data for every subject in Visit 2 and Visit 8.
  • GE-79_Summary_Table-MRI-Part4.csv This file contains the data summary table’s fourth part which includes MRI data for every subject in Visit 2 and Visit 8.
  • GE-79_Summary_Table-MRI-Part5-History.csv This file contains the data summary table’s fifth part which includes MRI data and medical and medication history for every subject in Visit 2 and Visit 8.
  • GE-79_Summary_Table-Labs-BP-Ophthalmogic-Walk.csv This file contains the data summary table’s sixth part which includes labs, 24-hour blood pressure monitoring, ophthalmogical testing, and walking test for every subject in Visit 2 and Visit 8.
  • GE-79_Summary_Table-Cognitive-Testing.csv This file contains the data summary table's seventh part which includes all the of the data collected for cognitive testing.
  • GE-79_Data_Dictionary.csv This file enlists all the variables of the study (variable description and units) and provides actual values from two participants as examples.

2. The following open-format data files are located in the Data directory. See GE-79_Files_and Channels.csv for details:

  • ECG - 24 hour ECG monitoring using the ME6000 device, sampled at 1000 Hz during sleep, daily activities and walking test for 12 min during day 1.
  • Labview – DB files (s####DB-v2.dat and s####DB-v8.dat) from Visit 2 and Visit 8. Cardiovascular, respiratory and TCD ultrasonography recordings (blood flow velocity in ACA and MCA) during Valsalva maneuver, 5 min supine baseline, 3 min hyperventilation, 3 min CO2 rebreathing, 5 min supine rest, head-up tilt 10 min.

In addition, the Papers folder contains many articles published from this database.

Usage Notes

Formats in which the files are provided:

  • ECG files converted from original format to WFDB format.
  • Labview files were converted to WFDB format.


The work was supported by the National Institutes of Health (NIH-NIA1R01-AG0287601A2, NIH-NIDDK 5R21 DK084463), American Diabetes Association (Clinical 1-03-CR-23 and 1-06-CR-25 to Dr. Vera Novak). The work was also in part supported NIH-NIDDK 1R01DK103902-01A1 to Dr. Novak. The project described was supported by Harvard Clinical and Translational Science Center (Grant Number UL1 RR025758) and National Center for Research Resources (M01-RR-01032).

Conflicts of Interest

Authors report no conflict of interest. 


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