CardioDataSets: A Comprehensive Collection of Cardiovascular and Heart Disease Datasets

Description

This package provides a wide variety of datasets focused on heart and cardiovascular research, covering heart disease, myocardial infarction, heart failure, stroke, ischemic heart disease, risk factors, clinical trials, and treatment outcomes.

Details

CardioDataSets: A Comprehensive Collection of Cardiovascular and Heart Disease Datasets

A Comprehensive Collection of Cardiovascular and Heart Disease Datasets.

Author(s)

Maintainer: Renzo Caceres Rossi arenzocaceresrossi@gmail.com

See Also

Useful links:

• https://github.com/lightbluetitan/cardiodatasets

Acute Coronary Syndrome (ACS) Patient Data

Description

This dataset, acs_patients_df, is a data frame containing demographic and clinical data from 857 patients with Acute Coronary Syndrome (ACS). It includes 17 variables covering patient characteristics, vital signs, laboratory results, and risk factors.

Usage

data(acs_patients_df)

Format

A data frame with 857 observations and 17 variables:

age

Patient age in years (integer)

sex

Patient sex (character)

cardiogenicShock

Presence of cardiogenic shock (character)

entry

Method of hospital entry (character)

Dx

Diagnosis (character)

EF

Ejection fraction percentage (numeric)

height

Height in cm (numeric)

weight

Weight in kg (numeric)

BMI

Body Mass Index in kg/m² (numeric)

obesity

Obesity status (character)

TC

Total cholesterol in mg/dL (numeric)

LDLC

LDL cholesterol in mg/dL (integer)

HDLC

HDL cholesterol in mg/dL (integer)

TG

Triglycerides in mg/dL (integer)

DM

Diabetes mellitus status (character)

HBP

High blood pressure status (character)

smoking

Smoking status (character)

Details

The dataset name has been kept as 'acs_patients_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the moonBook package version 0.3.1

Age vs. Maximum Heart Rate

Description

This dataset, age_heartrate_df, is a data frame containing simulated data representing the relationship between age and maximum heart rate. It includes 15 observations based on established physiological models.

Usage

data(age_heartrate_df)

Format

A data frame with 15 observations and 2 variables:

age

Age in years (numeric)

maxrate

Maximum predicted heart rate in beats per minute (numeric)

Details

The dataset name has been kept as 'age_heartrate_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the UsingR package version 2.0-7. Original research: Tanaka H, Monahan KD, Seals DR (2001). "Age-predicted maximal heart rate revisited." Journal of the American College of Cardiology, 37(1):153-156.

Acute Myocardial Infarction (Heart Attack) Events

Description

This dataset, ami_occurrences_tbl_df, is a tibble containing simulated but realistic daily counts of Acute Myocardial Infarction (AMI) occurrences in New York City over one year (365 days). The data represents the number of heart attack events recorded each day.

Usage

data(ami_occurrences_tbl_df)

Format

A tibble with 365 observations and 1 variable:

ami

Number of Acute Myocardial Infarction events recorded each day (integer vector)

Details

The dataset name has been kept as 'ami_occurrences_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the openintro package version 2.5.0

Aortic dissection patients

Description

This dataset, aortaDiss_tbl_df, is a tibble containing clinical information from 226 patients with aortic dissection. It includes demographic variables, symptom presentation, and risk factor data.

Usage

data(aortaDiss_tbl_df)

Format

A tibble with 226 observations and 10 variables:

Gender

Patient gender (numeric)

Age

Patient age in years (numeric)

Age_C

Categorized age (numeric)

Aortadis

Aortic dissection status (numeric)

Acute

Acute presentation indicator (numeric)

Acute3

Three-level acute presentation classification (numeric)

Stomach_Ache

Presence of stomach ache (numeric)

Hyper

Hypertension status (numeric)

Smoking

Smoking status (numeric)

Radiation

Radiation exposure (numeric)

Details

The dataset name has been kept as 'aortaDiss_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the psfmi package version 1.4.0

FDA Beta Blockers Adverse Events

Description

This dataset, betablockers_matrix, is a matrix containing adverse event reports from the FDA Adverse Event Reporting System (FAERS) for 9 beta blockers from Q1 2021 to Q4 2023. The matrix includes 501 adverse events (rows) across 9 medications (columns).

Usage

data(betablockers_matrix)

Format

A matrix with 501 rows (adverse events) and 9 columns (beta blockers):

Acebutolol

Adverse event counts for Acebutolol (integer)

Atenolol

Adverse event counts for Atenolol (integer)

Bisoprolol

Adverse event counts for Bisoprolol (integer)

Carvedilol

Adverse event counts for Carvedilol (integer)

Metoprolol

Adverse event counts for Metoprolol (integer)

Nadolol

Adverse event counts for Nadolol (integer)

Propranolol

Adverse event counts for Propranolol (integer)

Timolol

Adverse event counts for Timolol (integer)

Other

Adverse event counts for other beta blockers (integer)

Details

The dataset name has been kept as 'betablockers_matrix' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'matrix' indicates that the dataset is a matrix object. The original content has not been modified in any way.

Source

Data taken from the MDDC package version 1.1.0. Original data: FDA Adverse Event Reporting System (FAERS) database, Q1 2021 to Q4 2023.

Anticoagulants for CAD Patients

Description

This dataset, cad_anticoagulants_df, is a data frame containing information from 34 clinical trials examining the effectiveness of oral anticoagulants in patients with coronary artery disease. It includes data on treatment outcomes comparing anticoagulant therapy with control groups.

Usage

data(cad_anticoagulants_df)

Format

A data frame with 34 observations and 9 variables:

study

Study identifier (character vector)

year

Year of publication (integer vector)

intensity

Intensity of anticoagulation treatment (character vector)

asp.t

Aspirin use in treatment group (integer vector)

asp.c

Aspirin use in control group (integer vector)

ai

Number of events in treatment group (integer vector)

n1i

Total number of participants in treatment group (integer vector)

ci

Number of events in control group (integer vector)

n2i

Total number of participants in control group (integer vector)

Details

The dataset name has been kept as 'cad_anticoagulants_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the metadat package version 1.2-0

Heart Failure Clinical Dataset

Description

This dataset, cardiac_failure_df, is a data frame containing clinical data from 299 patients with heart failure. It includes 13 variables covering demographic information, medical history, laboratory results, and mortality outcomes.

Usage

data(cardiac_failure_df)

Format

A data frame with 299 observations and 13 variables:

age

Patient age in years (numeric)

anaemia

Presence of anaemia (integer: 0=no, 1=yes)

creatinine_phosphokinase

Level of CPK enzyme in mcg/L (integer)

diabetes

Presence of diabetes (integer: 0=no, 1=yes)

ejection_fraction

Percentage of blood leaving heart (integer)

high_blood_pressure

Presence of hypertension (integer: 0=no, 1=yes)

platelets

Platelet count in kiloplatelets/mL (numeric)

serum_creatinine

Level of serum creatinine in mg/dL (numeric)

serum_sodium

Level of serum sodium in mEq/L (integer)

sex

Patient sex (integer: 0=female, 1=male)

smoking

Smoking status (integer: 0=no, 1=yes)

time

Follow-up period in days (integer)

DEATH_EVENT

Death during follow-up (integer: 0=no, 1=yes)

Details

The dataset name has been kept as 'cardiac_failure_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the SOPC package version 0.1.0

Coronary Artery Disease GWAS Meta-Analysis

Description

This dataset, cardiac_gwas_df, is a data frame containing genome-wide association study (GWAS) results from a multi-ethnic meta-analysis of coronary artery disease (CAD). It includes 9,919 genetic variants with their effect sizes and study characteristics.

Usage

data(cardiac_gwas_df)

Format

A data frame with 9,919 observations and 7 variables:

beta_flipped

Effect size estimates (numeric)

gcse

Genomic control standard error (numeric)

variants

Genetic variant identifiers (character)

studies

Participating studies (character)

cases

Number of cases (integer)

controls

Number of controls (integer)

fdr214_gwas46

False discovery rate adjusted p-values (numeric)

Details

The dataset name has been kept as 'cardiac_gwas_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the getmstatistic package version 0.2.2

Cardiovascular Risk Factors

Description

This dataset, cardioRiskFactors_df, is a data frame containing information from a study investigating the association between uric acid and cardiovascular risk factors in developing countries. It includes data from 998 participants (474 men and 524 women) aged 25-64 years.

Usage

data(cardioRiskFactors_df)

Format

A data frame with 998 observations and 14 variables:

age

Age in years (integer)

bmi

Body Mass Index in kg/m² (numeric)

waisthip

Waist-to-hip ratio (numeric)

smok

Smoking status (integer)

choles

Total cholesterol in mg/dL (numeric)

trig

Triglycerides in mg/dL (numeric)

hdl

HDL cholesterol in mg/dL (numeric)

ldl

LDL cholesterol in mg/dL (numeric)

sys

Systolic blood pressure in mmHg (integer)

dia

Diastolic blood pressure in mmHg (numeric)

Uric

Uric acid level in mg/dL (integer)

sex

Sex (integer)

alco

Alcohol consumption (numeric)

apoa

Apolipoprotein A in mg/dL (numeric)

Details

The dataset name has been kept as 'cardioRiskFactors_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the Rfit package version 0.27.0. Original study: Heritier S, Cantoni E, Copt S, Victoria-Feser M (2009). Robust Methods in Biostatistics. New York: John Wiley and Sons.

Cardiovascular risks of diabetes drugs

Description

This dataset, cardio_diabetes_tbl_df, is a tibble containing information comparing cardiovascular problems between two diabetes medications (Rosiglitazone and Pioglitazone) in elderly Medicare patients. It includes data from 227,571 patients.

Usage

data(cardio_diabetes_tbl_df)

Format

A tibble with 227,571 observations and 2 variables:

treatment

Type of diabetes medication (factor with 2 levels: Rosiglitazone or Pioglitazone)

cardiovascular_problems

Presence of cardiovascular problems (factor with 2 levels)

Details

The dataset name has been kept as 'cardio_diabetes_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the openintro package version 2.5.0. Original study: Graham DJ, et al. (2010). "Risk of acute myocardial infarction, stroke, heart failure, and death in elderly Medicare patients treated with rosiglitazone or pioglitazone." JAMA, 304(4):411.

Statin Dose Comparison Trials for CVD

Description

This dataset, cardiovascular_list, is a list containing data from 34 clinical trials comparing low dose (1), high dose (2), and placebo (3) statins for cardiovascular disease prevention. The dataset includes study identifiers, treatment assignments, and outcome counts.

Usage

data(cardiovascular_list)

Format

A list with 4 components:

Study

Study identifiers (integer vector of length 34)

Treat

Treatment assignments (numeric vector: 1=low dose, 2=high dose, 3=placebo)

Outcomes

Outcome matrix with 34 rows and 3 columns:

Alive

Number of patients alive (numeric)

FnCVD

Number with non-fatal CVD events (numeric)

FCVD

Number with fatal CVD events (numeric)

N

Sample sizes (numeric vector of length 34)

Details

The dataset name has been kept as 'cardiovascular_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The original content has not been modified in any way.

Source

Data taken from the bnma package version 1.6.0

High vs Moderate Statins for MI Prevention

Description

This dataset, coronary_death_df, is a data frame containing information from 4 clinical trials comparing intensive (high dose) versus moderate (standard dose) statin therapy for preventing coronary death or myocardial infarction. It includes data on treatment outcomes across multiple endpoints.

Usage

data(coronary_death_df)

Format

A data frame with 4 observations and 16 variables:

trial

Trial identifier (character vector)

pop

Patient population description (character vector)

nt

Number of patients in treatment group (integer vector)

nc

Number of patients in control group (integer vector)

ep1t

Endpoint 1 events in treatment group (integer vector)

ep1c

Endpoint 1 events in control group (integer vector)

ep2t

Endpoint 2 events in treatment group (integer vector)

ep2c

Endpoint 2 events in control group (integer vector)

ep3t

Endpoint 3 events in treatment group (integer vector)

ep3c

Endpoint 3 events in control group (integer vector)

ep4t

Endpoint 4 events in treatment group (integer vector)

ep4c

Endpoint 4 events in control group (integer vector)

ep5t

Endpoint 5 events in treatment group (integer vector)

ep5c

Endpoint 5 events in control group (integer vector)

ep6t

Endpoint 6 events in treatment group (integer vector)

ep6c

Endpoint 6 events in control group (integer vector)

Details

The dataset name has been kept as 'coronary_death_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the metadat package version 1.2-0

Blood thinners in CPR survival

Description

This dataset, cpr_survival_tbl_df, is a tibble containing information from a study examining the effect of blood thinners on survival rates in CPR patients. The study randomly assigned 90 patients to either receive a blood thinner (treatment group) or not receive one (control group), with the outcome being survival for at least 24 hours.

Usage

data(cpr_survival_tbl_df)

Format

A tibble with 90 observations and 2 variables:

group

Treatment assignment (factor with 2 levels: "control" and "treatment")

outcome

Survival status (factor with 2 levels: "died" and "survived")

Details

The dataset name has been kept as 'cpr_survival_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the openintro package version 2.5.0

LA pollution and cardiovascular mortality

Description

This dataset, cv_mortality_ts, is a time series containing weekly cardiovascular mortality data from Los Angeles County. It consists of 508 six-day smoothed averages obtained by filtering daily values over the 10-year period from 1970 to 1979.

Usage

data(cv_mortality_ts)

Format

A time series object (ts) with 508 observations:

cv_mortality

Weekly cardiovascular mortality counts (numeric vector)

Details

The dataset name has been kept as 'cv_mortality_ts' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'ts' indicates that the dataset is a time series object. The original content has not been modified in any way.

Time series characteristics: - Start: 1970, Week 1 - End: 1979, Week 40 - Frequency: 52 (weekly data)

Source

Data taken from the astsa package version 2.2

Anger recall effect on heart rate (Lakens, 2013)

Description

This dataset, emotion_heartrate_df, is a data frame containing heart rate measurements from a study investigating how recalling anger affects heart rate. It includes baseline and anger-induced heart rate measurements from 68 participants.

Usage

data(emotion_heartrate_df)

Format

A data frame with 68 observations and 3 variables:

ID

Participant identification number (integer vector)

HR_baseline

Baseline heart rate in beats per minute (numeric vector)

HR_anger

Heart rate during anger recall in beats per minute (numeric vector)

Details

The dataset name has been kept as 'emotion_heartrate_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the esci package version 1.0-7. Original study: Lakens D (2013). Conceptual replication of Ekman et al. (1983) emotion study.

Artificial Heart Transplant Durations

Description

This dataset, heartTransplantTime_tbl_df, is a tibble containing the durations (in hours) of 15 artificial heart transplant operations.

Usage

data(heartTransplantTime_tbl_df)

Format

A tibble with 15 observations and 1 variable:

duration

Operation duration in hours (numeric)

Details

The dataset name has been kept as 'heartTransplantTime_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the BSDA package version 1.2.3. Original source: Kitchens LJ (2003). "Basic Statistics and Data Analysis." Pacific Grove, CA: Brooks/Cole, a division of Thomson Learning.

Stanford Heart Transplant Data

Description

This dataset, heart_transplant_df, is a data frame containing survival data from the Stanford heart transplant program. It includes information on 172 patients with follow-up times, transplant status, and clinical covariates.

Usage

data(heart_transplant_df)

Format

A data frame with 172 observations and 8 variables:

start

Start time of interval (numeric)

stop

End time of interval (numeric)

event

Survival status (numeric: 1=event, 0=censored)

age

Patient age at enrollment (numeric)

year

Year of enrollment (numeric)

surgery

Prior bypass surgery (numeric)

transplant

Transplant status (factor: 0=no, 1=yes)

id

Patient identification number (numeric)

Details

The dataset name has been kept as 'heart_transplant_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the lrstat package version 0.2.13. Original source: Stanford Heart Transplant Study data from the survival package.

Heart Disease Patients Clinical Data

Description

This dataset, heartdisease_tbl_df, is a tibble containing information on individuals evaluated for heart disease. It is a cleaned version of the original "Heart Disease" dataset from the UCI Machine Learning Repository, and includes 303 observations on 9 variables.

Usage

data(heartdisease_tbl_df)

Format

A tibble with 303 observations and 9 variables:

Age

Age of the individual (numeric).

Sex

Sex of the individual (factor with 2 levels: typically "Male" and "Female").

ChestPain

Type of chest pain experienced (factor with 4 levels).

BP

Resting blood pressure (numeric).

Cholesterol

Serum cholesterol in mg/dl (numeric).

BloodSugar

Indicates if fasting blood sugar > 120 mg/dl (logical).

MaximumHR

Maximum heart rate achieved (numeric).

ExerciseInducedAngina

Exercise-induced angina (factor with 2 levels).

HeartDisease

Presence or absence of heart disease (factor with 2 levels).

Details

The dataset name has been kept as 'heartdisease_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the cheese package version 0.1.2. Original source: UCI Machine Learning Repository. Heart Disease Data Set. https://archive.ics.uci.edu/ml/datasets/Heart+Disease

Heart Disease Risk Factors

Description

This dataset, heartdiseaserisk_tbl_df, is a tibble containing cardiovascular risk factor data from 498 individuals. It includes measures of physical activity (biking), smoking habits, and heart disease prevalence.

Usage

data(heartdiseaserisk_tbl_df)

Format

A tibble with 498 observations and 3 variables:

Biking

Frequency of biking activity (numeric)

Heart.disease

Prevalence of heart disease (numeric)

Smoking

Smoking frequency or intensity (numeric)

Details

The dataset name has been kept as 'heartdiseaserisk_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the Path.Analysis package version 0.1

Heart Failure rehospitalization risk

Description

This dataset, heartfailure_df, is a data frame containing simulated data from 800 patients with heart failure who are at risk of recurrent hospitalization. The dataset includes 3,068 observations (2,268 events) tracking patient outcomes over time.

Usage

data(heartfailure_df)

Format

A data frame with 3,068 observations and 6 variables:

id

Patient identification number (integer vector)

treatment

Treatment assignment (factor with 2 levels)

t0

Start time of observation period (numeric vector)

t1

End time of observation period (numeric vector)

enum

Event number (numeric vector)

event

Event indicator (numeric vector)

Details

The dataset name has been kept as 'heartfailure_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the survPen package version 2.0-2. Based on hfaction_cpx12 dataset from package WA.

Statins for Heart Failure Prevention

Description

This dataset, hfPrevention_mtc_network, contains network meta-analysis data from 19 trials comparing statins versus placebo or usual care for cholesterol lowering in heart failure. The main outcome measured is the number of deaths. Trials are categorized as either primary prevention (no previous heart disease) or secondary prevention (previous heart disease).

Usage

data(hfPrevention_mtc_network)

Format

An 'mtc.network' object (list) with 4 components:

description

Character string describing the analysis: "Cholesterol lowering in HF (outcome: death)"

treatments

Data frame with 2 treatments:

id

Treatment ID (factor with 2 levels)

description

Treatment description (character vector)

data.ab

Data frame with 38 rows (arm-level data):

study

Study ID (factor with 19 levels)

treatment

Treatment assignment (factor with 2 levels)

responders

Number of deaths (integer vector)

sampleSize

Total sample size per arm (integer vector)

studies

Data frame with 19 rows (study-level data):

study

Study ID (factor with 19 levels)

secondary

Prevention type: 0 = primary, 1 = secondary (integer vector)

Details

The dataset name has been kept as 'hfPrevention_mtc_network' to maintain consistency with its original source and to avoid confusion with other datasets. This naming convention helps identify this specific network meta-analysis dataset from the CardioDataSets package. The dataset is structured as an 'mtc.network' object, which is the standard format for network meta-analysis in the gemtc package. The original content has not been modified.

Source

Data taken from the gemtc package version 1.0-2. Original publication: Dias S, Sutton AJ, Welton NJ, Ades AE (2013). "Heterogeneity - Subgroups, Meta-Regression, Bias, and Bias-Adjustment." Medical Decision Making, 33(5):618-640.

Elderly CV/MRI and Biomarkers

Description

This dataset, mriCardioVars_tbl_df, is a tibble containing MRI and clinical data from 735 elderly participants in a U.S. observational study of cardiovascular and cerebrovascular disease incidence. It includes 30 variables covering demographic, clinical, and imaging measures.

Usage

data(mriCardioVars_tbl_df)

Format

A tibble with 735 observations and 30 variables:

ptid

Patient identification number (numeric)

mridate

MRI date (Date)

age

Age in years (numeric)

sex

Sex (character)

race

Race (character)

weight

Weight in kg (numeric)

height

Height in cm (numeric)

packyrs

Smoking pack-years (numeric)

yrsquit

Years since quitting smoking (numeric)

alcoh

Alcohol consumption (numeric)

physact

Physical activity level (numeric)

chf

Congestive heart failure status (numeric)

chd

Coronary heart disease status (numeric)

stroke

Stroke history (numeric)

diabetes

Diabetes status (numeric)

genhlth

General health status (numeric)

ldl

LDL cholesterol in mg/dL (numeric)

alb

Albumin level (numeric)

crt

Creatinine level (numeric)

plt

Platelet count (numeric)

sbp

Systolic blood pressure in mmHg (numeric)

aai

Ankle-arm index (numeric)

fev

Forced expiratory volume (numeric)

dsst

Digit Symbol Substitution Test score (numeric)

atrophy

Brain atrophy measure (numeric)

whgrd

White matter hyperintensity grade (numeric)

numinf

Number of brain infarcts (numeric)

volinf

Volume of brain infarcts (numeric)

obstime

Observation time (numeric)

death

Mortality status (numeric)

Details

The dataset name has been kept as 'mriCardioVars_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the rigr package version 1.0.7

Muscatine pediatric CRF

Description

This dataset, muscatine_coronary_risk_df, is a data frame containing longitudinal observations from the Muscatine Coronary Risk Factor (MCRF) study, which examined the development of coronary disease risk factors in children. It includes 14,568 observations of 4,856 children tracked from 1977 to 1981.

Usage

data(muscatine_coronary_risk_df)

Format

A data frame with 14,568 observations and 7 variables:

id

Child identification number (integer)

gender

Gender of child (factor with 2 levels)

base_age

Age at first observation in years (integer)

age

Current age in years (integer)

occasion

Measurement occasion (integer)

obese

Obesity status (factor with 2 levels)

numobese

Numeric obesity indicator (numeric)

Details

The dataset name has been kept as 'muscatine_coronary_risk_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the geepack package version 1.3.12. Original study: The Muscatine Coronary Risk Factor Study, University of Iowa, 1977-1981.

Streptokinase Therapy in AMI

Description

This dataset, myocardialinfarction_df, is a data frame containing information from 33 clinical trials comparing intravenous streptokinase versus placebo or no therapy in patients hospitalized for acute myocardial infarction. It includes data on treatment outcomes between intervention and control groups.

Usage

data(myocardialinfarction_df)

Format

A data frame with 33 observations and 6 variables:

trial

Trial identifier (character vector)

year

Year of publication (integer vector)

ai

Number of events in treatment group (integer vector)

n1i

Total number of participants in treatment group (integer vector)

ci

Number of events in control group (integer vector)

n2i

Total number of participants in control group (integer vector)

Details

The dataset name has been kept as 'myocardialinfarction_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the metadat package version 1.2-0. Original publication: Lau J, Antman EM, Jimenez-Silva J, Kupelnick B, Mosteller F, Chalmers TC (1992). "Cumulative meta-analysis of therapeutic trials for myocardial infarction." New England Journal of Medicine, 327(4):248-254.

CAV in Heart Transplant Patients

Description

This dataset, patient_CAV_df, is a data frame containing longitudinal follow-up data from heart transplant recipients at Papworth Hospital, UK. It tracks 2,803 angiographic examinations for the onset of cardiac allograft vasculopathy and mortality.

Usage

data(patient_CAV_df)

Format

A data frame with 2,803 observations and 5 variables:

PTNUM

Patient identification number (integer)

years

Time since transplant in years (numeric)

state

Disease state (numeric)

dage

Donor age in years (integer)

pdiag

Primary diagnosis code (numeric)

Details

The dataset name has been kept as 'patient_CAV_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the flexmsm package version 0.1.2. Original data: Papworth Hospital, UK. Subset of cav data from msm package.

Radial Artery IVUS Patient Data

Description

This dataset, radial_ivus_df, is a data frame containing demographic and clinical data from 115 patients who underwent intravascular ultrasound (IVUS) examination of the radial artery following transradial coronary angiography. It includes 15 variables covering patient characteristics, laboratory results, and IVUS measurements.

Usage

data(radial_ivus_df)

Format

A data frame with 115 observations and 15 variables:

male

Male sex indicator (integer: 0/1)

age

Age in years (integer)

height

Height in cm (numeric)

weight

Weight in kg (numeric)

HBP

High blood pressure status (integer: 0/1)

DM

Diabetes mellitus status (integer: 0/1)

smoking

Smoking status (factor with 3 levels)

TC

Total cholesterol in mg/dL (integer)

TG

Triglycerides in mg/dL (integer)

HDL

HDL cholesterol in mg/dL (integer)

LDL

LDL cholesterol in mg/dL (integer)

hsCRP

High-sensitivity C-reactive protein in mg/L (numeric)

NTAV

Normalized total atheroma volume (numeric)

PAV

Percent atheroma volume (numeric)

sex

Sex (factor with 2 levels)

Details

The dataset name has been kept as 'radial_ivus_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the moonBook package version 0.3.1

Scottish Health Survey CVD

Description

This dataset, scottish_CVD_df, is a data frame containing cardiovascular health data from the 1998 Scottish Health Survey. It includes information from 8,804 respondents aged 18-64, with variables covering demographics, health behaviors, and cardiovascular disease status.

Usage

data(scottish_CVD_df)

Format

A data frame with 8,804 observations and 8 variables:

age

Respondent age in years (integer)

sex

Respondent sex (factor with 2 levels)

sc

Social class (factor with 3 levels)

cvddef

Doctor-diagnosed CVD status (integer: 0=no, 1=yes)

carstair

Carstairs deprivation score (numeric)

smoke

Smoking status (factor with 5 levels)

id

Respondent identification number (integer)

area

Geographic area code (integer)

Details

The dataset name has been kept as 'scottish_CVD_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the R2MLwiN package version 0.8-9. Original survey: 1998 Scottish Health Survey. Methodology reference: Charlton C, Rasbash J, Browne WJ, Healy M, Cameron B (2024). MLwiN Version 3.09. Centre for Multilevel Modelling, University of Bristol.

Statin intensity and MI risk

Description

This dataset, statinMIrisk_df, is a data frame containing results from 4 clinical trials investigating the effect of statin therapy intensity on the risk of myocardial infarction or coronary death. The data compares intensive versus standard statin regimens.

Usage

data(statinMIrisk_df)

Format

A data frame with 4 observations and 5 variables:

study

Study identifier (character)

eI

Number of events in intensive treatment group (numeric)

nI

Total patients in intensive treatment group (numeric)

eC

Number of events in control/standard group (numeric)

nC

Total patients in control/standard group (numeric)

Details

The dataset name has been kept as 'statinMIrisk_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the RTSA package version 0.2.2

Sulphinpyrazone for post-MI death prevention

Description

This dataset, sulphinpyrazone_tbl_df, is a tibble containing information from a clinical trial studying the efficacy of sulphinpyrazone in preventing sudden death after myocardial infarction. The data includes 1,475 patients randomly assigned to either the treatment or control group.

Usage

data(sulphinpyrazone_tbl_df)

Format

A tibble with 1,475 observations and 2 variables:

group

Treatment assignment (factor with 2 levels: "control" and "treatment")

outcome

Patient outcome (factor with 2 levels)

Details

The dataset name has been kept as 'sulphinpyrazone_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the openintro package version 2.5.0. Original study: Anturane Reinfarction Trial Research Group (1980). "Sulfinpyrazone in the prevention of sudden death after myocardial infarction." New England Journal of Medicine, 302(5):250-256.

US Mortality Rates by Cause and Gender

Description

This dataset, usMortality_df, is a data frame containing mortality rates across all ages in the USA from 2011-2013, stratified by cause of death, sex, and rural/urban status. It includes national aggregate rates for 10 causes of death, including Heart disease.

Usage

data(usMortality_df)

Format

A data frame with 40 observations and 5 variables:

Status

Residential status (factor: Rural/Urban)

Sex

Gender (factor: Male/Female)

Cause

Cause of death (factor with 10 levels)

Rate

Mortality rate per 100,000 population (numeric)

SE

Standard error of mortality rate (numeric)

Details

The dataset name has been kept as 'usMortality_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the CardioDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a standard data frame. The original content has not been modified in any way.

Source

Data taken from the lattice package version 0.22-6. Original source: Rural Health Reform Policy Research Center (2015). "Exploring Rural and Urban Mortality Differences." Bethesda, MD: August 2015.

View Available Datasets in CardioDataSets

Description

This function lists all datasets available in the 'CardioDataSets' package. If the 'CardioDataSets' package is not loaded, it stops and shows an error message. If no datasets are available, it returns a message and an empty vector.

Usage

view_datasets()

Value

A character vector with the names of the available datasets. If no datasets are found, it returns an empty character vector.

Examples

if (requireNamespace("CardioDataSets", quietly = TRUE)) {
  library(CardioDataSets)
  view_datasets()
}