Checks performed

The following variable checks were performed, depending on the data type of each variable:

Please note that all numerical values in the following have been rounded to 2 decimals.

X1

AGE

• Note that the following possible outlier values were detected: "22".

SEX

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

HOSPITAL_STAY

• Note that the following possible outlier values were detected: "3".

NYHA_CLASS_AT_ADMISSION

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "1".

NYHA_CLASS_AT_DISCHARGE

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

DM

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "4".

HTN

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

CAD

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

CVA

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "1".

CKD

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

COPD

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

HEART_RATE

SBP

• Note that the following possible outlier values were detected: "76", "78", "80", "82", "84", "86".

DBP

• Note that the following possible outlier values were detected: "40", "44", "46", "110", "120".

HEMOGLOBIN_GM_DL

• Note that the following possible outlier values were detected: "2.6", "16".

SERUM_UREA_MG_DL

• Note that the following possible outlier values were detected: "14".

S_CREATININE_MG_DL

• Note that the following possible outlier values were detected: "0.7", "0.8", "6.4", "6.5", "6.8".

S_SODIUM_M_EQ_L

• Note that the following possible outlier values were detected: "148".

S_POTASSIUM_M_EQ_L

• Note that the following possible outlier values were detected: "6".

BNP_AT_ADMISSION

• Note that the following possible outlier values were detected: "450", "520", "540", "550", "560", "600".

BNP_AT_DISCHARGE

• Note that the following possible outlier values were detected: "70", "100", "112", "120".

TROPONIN_AT_ADMISSION

TROPONIN_AT_DISCHARGE

• Note that the following possible outlier values were detected: "0.3", "0.4", "0.5", "0.7".

ECG

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

CXR_PA_VIEW

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

EF_PERCENT

MR_GRADE

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

BETA_BLOCKER

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "2".

ACE_INHIBITORS

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

ALD_ANTA

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

DIURETICS

• The variable only takes one (non-missing) value: "1". The variable contains 0 % missing observations.

DIGOXIN

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

ARNI

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

ICD

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

CRTD

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

CRTP

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "1".

PRECIPITATING_FACTOR_FOR_ACUTE_HEART_FAILURE

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "4".

DEATH_DURING_CURRENT_HOSPITAL_STAY

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

HOSPITALISATION_OR_DEATH_AFTER_DISCHARGE

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "3".

CAUSE_FOR_HOSPITALISATION_OR_DEATH_AFTER_DISCHARGE

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "2", "3", "4", "5".

CARDIAC_CAUSE_FOR_REHOSPITALISATION

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "0", "2", "3".

DEATH_AFTER_DISCHARGE

• Note that this variable is treated as a factor variable below, as it only takes a few unique values.

• Note that the following levels have at most five observations: "1".

outcome

Report generation information:

• Created by anupamsingh81 (username: anupam).

• Report creation time: Wed Aug 07 2019 16:54:17

• Report was run from directory: /home/anupam/Documents/hf

• dataMaid v1.2.0 [Pkg: 2018-10-03 from CRAN (R 3.4.3)]

• R version 3.5.3 (2019-03-11).

• Platform: x86_64-pc-linux-gnu (64-bit)(Ubuntu 16.04.5 LTS).

• Function call: makeDataReport(data = hf)