2.2. Patient selection
Patients admitted to ICU who were diagnosed with ICH (ICD-9 = 431) were
eligible for inclusion. In the MIMIC-III database, each patient has its
ID (SUBJECT_ID), and each admission is reassigned with an ID
(HADM_ID). We screened out the variables of each ICH patient at the
time of the last admission in the database record period (that is, each
SUBJECT_ID corresponds to a HADM_ID). After extracting, the data of
1143 ICH patients older than 18 years were included and divided into the
dead (383 people) and the alive group (760 people).
2.3. Predictors and outcomevariables
For each ICH patient, we collected variables including, patient
physiological characteristics, laboratory parameters, and CT findings.
For variables with temporal information, the maximum and minimum values
of daily variables within three days after admission were extracted, and
we took them as the parallel input of the model, because we believed
that these variables with time information could more directly reflect
the limiting condition of the patient’s body and had a more obvious
influence on whether the patient died or not. After consulting with
experts in this area, we selected variables: Gender, marital status,
ethnicity, age, complication (high blood pressure, diabetes, ischemic
heart disease, heart failure, pneumonia), and ICH location (basal
ganglia, lobe, infratentorial). In addition, variables with temporal
information (the maximum and minimum values of the first, second and
third days of admission) included: systolic pressure, diastolic
pressure, mean blood pressure, heart rate, body temperature, GCS score,
white blood cells, lymphocytes, neutrophils, eosinophils, basophils, red
blood cells, hemoglobin, platelet count, hematocrit, glucose, potassium,
sodium, creatinine, and urea nitrogen. The outcome of this study was
in-hospital mortality of ICH patients. If the variable’s missing values
were more than 20% of the total, we removed it.