STS Intermacs de identified datasets - onetomapanalytics/Meta_Data GitHub Wiki

STS Intermacs De-identified Datasets

General description

  1. Database primary purpose - Collect clinical data regarding patients who receive an FDA-approved mechanical circulatory support (MCS) device to treat advanced heart failure, aiming at helping cardiothoracic surgeons measure and improve patient care
  2. Overall data type - Health outcomes
  3. Dataset type - Longitudinal
  4. Data source - Registry
  5. Data level - Patient level
  6. Geographic location of the data collection sites - United States
  7. Sponsor, manager, or home institution - A joint effort among the National Heart, Lung, and Blood Institute, the Food and Drug Administration, the Centers for Medicare & Medicaid Services, and others, established at the University of Alabama at Birmingham
  8. Date range - 2019 - 2020
  9. Dates - Incomplete dates of admission, transplant, adverse events, bleeding, cardiac arrhythmia, and discharge
  10. Clinical areas of interest - Heart diseases
  11. Number of records - 184 active sites; 38,429 patients enrolled (November, 2022)
  12. Variables that are uniquely present in this dataset - Clinical outcomes of patients who receive an FDA-approved MCS device to treat advanced heart failure
  13. Database caveats and limitations - Can not be linked to other datasets

Applicable methods

  1. Association methods, such as multivariate Cox regression (1, 2), multivariable regression (3), logistic regression (4), and inferential tests (5)
  2. Time to event (1, 6, 7)
  3. Propensity scores (8)
  4. Time-series (9)

High-impact designs

  • Determine prevalence and severity of right heart failure (RHF) over time ()

Data dictionary

To access the STS Intermacs data dictionary, click here

Variable categories

  1. Patient demographics (e.g., age, sex, race, ethnicity)
  2. Hospital discharge records (e.g., incomplete dates of admission and discharge, LOS, patient discharge status)
  3. Diagnosis (admitting, principal, and other diagnosis)
  4. Surgery (e.g., transplant date, concomitant surgeries)
  5. Test results (e.g., total bilirubin, brain natriuretic peptide, creatinine, diastolic blood pressure)
  6. Device (e.g., type, strategy)