README — Cardiovascular Heart Failure Dataset
File: cardiovascular_hf_dataset-3.csv
Rows: 50,000 patients
Columns: 68 features
Domain: Cardiovascular medicine — Heart Failure risk prediction
Overview
This dataset contains multimodal patient-level data for heart failure (HF) risk modelling. Each row represents one patient encounter with demographic, clinical, laboratory, echocardiographic, symptomatic, pharmacological, and longitudinal variables. Three outcome targets are provided: a binary HF risk label, a future hospitalisation probability, and a 12-month survival probability.
Data Sources
| Source |
N |
% |
| Preventive_Cardiology |
20,094 |
40.2% |
| Hospital_Inpatient |
15,052 |
30.1% |
| Annual_Checkup |
14,854 |
29.7% |
Column Dictionary
1. Patient Identifiers
| Column |
Type |
Description |
Patient_ID |
str |
Unique patient identifier (PT000001 – PT050000) |
Source |
str |
Clinical setting of data collection |
2. Demographics
| Column |
Type |
Range / Categories |
Description |
Age |
int |
18 – 90 |
Age in years |
Gender |
str |
Female, Male, Other |
Self-reported gender |
Ethnicity |
str |
White, Black, Hispanic, Asian, Native_American, Other |
Self-reported ethnicity |
3. Lifestyle & Socioeconomic
| Column |
Type |
Range |
Description |
BMI |
float |
14.0 – 58.0 |
Body mass index (kg/m²) |
Activity_Level |
str |
Sedentary / Low / Moderate / High / Very_High |
Self-reported physical activity category |
SES_Score |
float |
1.0 – 10.0 |
Socioeconomic status composite score |
SES_Category |
str |
Low / Middle / High |
Derived SES category |
Smoking_Status |
str |
Never / Former / Current |
Tobacco smoking history |
Alcohol_Units_Week |
float |
0.2 – 50.0 |
Alcohol consumption (units/week) |
Physical_Activity_Min_Week |
float |
0 – 448 |
Weekly moderate-intensity exercise (minutes); ~5% missing |
Sleep_Hours |
float |
3.0 – 11.9 |
Average nightly sleep duration; ~4.9% missing |
Diet_Score |
float |
1.0 – 10.0 |
Dietary quality composite score; ~5% missing |
Stress_Score |
float |
1.0 – 10.0 |
Perceived stress score; ~4.9% missing |
4. Comorbidities (binary flags: 0 = absent, 1 = present)
| Column |
Prevalence |
Hypertension |
44.8% |
Diabetes |
28.4% |
CAD (Coronary Artery Disease) |
23.9% |
Prior_MI (Myocardial Infarction) |
4.9% |
Arrhythmia |
19.8% |
CKD (Chronic Kidney Disease) |
20.5% |
Family_HF_History |
24.0% |
5. Vital Signs
| Column |
Type |
Range |
Description |
Heart_Rate_bpm |
int |
38 – 135 |
Resting heart rate (bpm) |
SBP_mmHg |
int |
72 – 210 |
Systolic blood pressure (mmHg) |
DBP_mmHg |
int |
43 – 132 |
Diastolic blood pressure (mmHg) |
Respiratory_Rate |
int |
8 – 33 |
Respiratory rate (breaths/min) |
SpO2_pct |
float |
87.7 – 100.0 |
Peripheral oxygen saturation (%) |
6. Biomarkers & Laboratory Values (~9–10% missing)
| Column |
Unit |
Description |
BNP_pgmL |
pg/mL |
B-type natriuretic peptide — primary HF biomarker |
NT_proBNP_pgmL |
pg/mL |
N-terminal pro-BNP — HF severity marker |
Troponin_I_ngmL |
ng/mL |
Cardiac troponin I — myocardial injury marker |
HbA1c_pct |
% |
Glycated haemoglobin — glycaemic control |
LDL_mgdL |
mg/dL |
Low-density lipoprotein cholesterol |
HDL_mgdL |
mg/dL |
High-density lipoprotein cholesterol |
Triglycerides_mgdL |
mg/dL |
Serum triglycerides |
Creatinine_mgdL |
mg/dL |
Serum creatinine — renal function |
eGFR_mLmin |
mL/min |
Estimated glomerular filtration rate |
Sodium_mEqL |
mEq/L |
Serum sodium — electrolyte |
Potassium_mEqL |
mEq/L |
Serum potassium — electrolyte |
CRP_mgL |
mg/L |
C-reactive protein — systemic inflammation |
7. Electrocardiographic (ECG) Variables
| Column |
Type |
Description |
QTc_Interval_ms |
int |
Corrected QT interval (ms); range 340–574 |
QRS_Duration_ms |
int |
QRS complex duration (ms); range 60–171 |
ST_Abnormality |
binary |
ST-segment abnormality present (22.0%) |
LVH_Flag |
binary |
Left ventricular hypertrophy on ECG (29.4%) |
AF_Presence |
binary |
Atrial fibrillation detected (26.5%) |
8. Echocardiographic Variables (~10% missing)
| Column |
Unit |
Description |
Ejection_Fraction_pct |
% |
Left ventricular ejection fraction (15–80%) |
LV_Wall_Thickness_mm |
mm |
Left ventricular wall thickness (6–18.4 mm) |
Cardiomegaly |
binary |
Cardiomegaly present (25.6%) |
Echo_Abnormalities_Score |
0–5 |
Composite echocardiographic abnormality score |
9. Symptoms (binary flags)
| Column |
Prevalence |
Description |
Dyspnea |
35.4% |
Shortness of breath |
Fatigue |
36.2% |
Fatigue or generalised weakness |
Chest_Discomfort |
29.1% |
Chest pain or pressure |
Peripheral_Edema |
31.9% |
Ankle/leg swelling |
Exercise_Intolerance |
36.3% |
Reduced exercise capacity |
Dizziness |
21.1% |
Lightheadedness or dizziness |
Symptom_Burden_Count |
int (0–6) |
Total number of symptoms present (mean 1.9) |
10. Medications (binary flags: 0 = not prescribed, 1 = prescribed)
| Column |
Prevalence |
ACE_Inhibitor |
30.5% |
Beta_Blocker |
33.9% |
Diuretic |
28.6% |
Statin |
37.0% |
Anticoagulant |
28.1% |
11. Healthcare Utilisation
| Column |
Type |
Range |
Description |
Prior_Hospitalizations |
int |
0 – 9 |
Number of prior hospital admissions |
ED_Visits_Per_Year |
int |
0 – 9 |
Emergency department visits in the past year |
12. Longitudinal / Trend Variables (~17–18% missing)
| Column |
Unit |
Description |
Weight_Fluctuation_3mo_kg |
kg |
Weight change over 3 months (− = loss, + = gain) |
BP_Trend_mmHg_month |
mmHg/month |
Blood pressure trend over recent months |
HRV_ms |
ms |
Heart rate variability (5–88 ms; higher = better autonomic tone) |
13. Outcome Variables
| Column |
Type |
Description |
HF_Risk_Binary |
0 / 1 |
Primary label — heart failure risk (26.1% positive) |
Future_Hospitalization_Risk |
float [0–1] |
Predicted probability of future hospitalisation |
Survival_Probability_12mo |
float [0–1] |
Predicted probability of survival at 12 months |
Class imbalance note: HF positive cases represent 26.1% of the dataset. Consider SMOTE, class weighting, or stratified sampling before model training.
Missing Data Summary
| Missingness tier |
Columns |
Approx. missing |
| Low (~5%) |
Physical activity, sleep, diet, stress scores |
4.9–5.0% |
| Moderate (~9–10%) |
All biomarkers, echocardiographic variables |
9.2–10.4% |
| High (~17–18%) |
Weight fluctuation, BP trend, HRV |
17.6–18.1% |
Recommended imputation strategies: median imputation or MICE for continuous variables; mode imputation for binary flags. Missing echo variables may reflect patients who did not undergo echocardiography (MCAR/MAR assumption should be validated).
Suggested Use Cases
- Binary classification: HF risk prediction (
HF_Risk_Binary)
- Regression: 12-month survival probability or future hospitalisation risk
- Survival analysis: time-to-event modelling using
Survival_Probability_12mo
- Missing data benchmarking: graduated missingness across feature tiers
- Multi-source generalisation studies: three distinct clinical settings
- Feature importance analysis: identifying key biomarker and symptom drivers of HF
Notes
- All Patient_IDs are unique (no duplicate rows).
- The dataset is synthetic or de-identified; do not attempt patient re-identification.
- Echocardiographic variables (
Ejection_Fraction_pct, LV_Wall_Thickness_mm, Cardiomegaly, Echo_Abnormalities_Score) share a correlated missingness pattern, suggesting they are collected together as part of an echo workup.
- BNP and NT-proBNP are highly correlated; consider using only one in models to avoid multicollinearity.
- Age range spans 18–90 years; consider age-stratified analyses for paediatric-excluded adult cohorts.
README generated for cardiovascular_hf_dataset-3.csv — 50,000 rows × 68 columns.
