04. Format MIMIC therapy (all)

Description…

# Generic libraries
import pandas as pd

# Show in terminal
TERMINAL = False

First, lets load and do some basic formatting on the data.

# -----------------------------
# Constants
# -----------------------------
# Path
path = './data/mimic-therapy/ICU_diagnoses_antibiotics.csv'

# -----------------------------
# Load data
# -----------------------------
# Read data
data = pd.read_csv(path,
    dayfirst=True,
    parse_dates=['starttime',
                 'stoptime'])

# Keep only useful columns
data = data[['subject_id',
             'hadm_id',
             'stay_id',
             'icd_code',
             'antibiotic',
             'route',
             'starttime',
             'stoptime']]

# Reformat (time info and str)
data.starttime = data.starttime.dt.date
data.stoptime = data.stoptime.dt.date
data.antibiotic = data.antibiotic \
    .str.lower() \
    .str.strip()

# Show
if TERMINAL:
    print("\nData:")
    print(data)
data

	subject_id	hadm_id	stay_id	icd_code	antibiotic	route	starttime	stoptime
0	10656173	25778760	30001555	J95851	ceftriaxone	IV	2177-09-27	2177-10-02
1	10656173	25778760	37985659	J95851	cefepime	IV	2177-09-19	2177-09-23
2	10656173	25778760	37985659	J95851	cefepime	IV	2177-09-11	2177-09-12
3	10656173	25778760	37985659	J95851	cefepime	IV	2177-09-10	2177-09-11
4	10656173	25778760	37985659	J95851	cefepime	IV	2177-09-12	2177-09-12
...	...	...	...	...	...	...	...	...
21541	15689523	23914765	39918058	99731	metronidazole (flagyl)	IV	2159-07-13	2159-07-25
21542	15689523	23914765	39918058	99731	metronidazole (flagyl)	IV	2159-06-27	2159-06-27
21543	15689523	23914765	39918058	99731	sulfamethoxazole-trimethoprim	IV	2159-06-25	2159-06-26
21544	15689523	23914765	39918058	99731	sulfamethoxazole-trimethoprim	IV	2159-06-26	2159-07-02
21545	15689523	23914765	39918058	99731	sulfamethoxazole-trimethoprim	IV	2159-06-29	2159-06-29

21546 rows × 8 columns

Lets transform the data

Note

You might need to add NaNs for missing days per patient. The other sample included in this repository for a single patient 04. Format MIMIC therapy (one) achieves this by using the following code: aux = aux.asfreq('1D')

Note it needs to be applied per patient!

# -----------------------------
# Transform data
# -----------------------------
# .. note: The closed parameter indicates whether to include
#          the first and/or last samples. None will keep both,
#          left will keep only start date and right will keep
#          also the right date.
# Create column with date range
data['startdate'] = data.apply(lambda x:
    pd.date_range(start=x['starttime'],
                  end=x['stoptime'],
                  closed='left',         # ignoring right
                  freq='D') ,axis=1)

# Explode such column
data = data.explode('startdate')

# Groupby
groupby = ['subject_id',
           'hadm_id',
           'stay_id',
           'startdate']

# Create daily therapies
aux = data.groupby(groupby) \
    .apply(lambda x: sorted(x.antibiotic \
        .unique().tolist()))

Lets see the formatted data

# Show
if TERMINAL:
    print("\nFormatted:")
    print(aux)
aux

Out:

subject_id  hadm_id   stay_id   startdate
10004733    27411876  39635619  2174-12-04    [piperacillin-tazobactam, vancomycin]
                                2174-12-05    [piperacillin-tazobactam, vancomycin]
                                2174-12-06    [piperacillin-tazobactam, vancomycin]
                                2174-12-07                [piperacillin-tazobactam]
                                2174-12-08    [piperacillin-tazobactam, vancomycin]
                                                              ...
19997367    20617667  35616526  2126-05-06                            [ceftriaxone]
                                2126-05-07                            [ceftriaxone]
                                2126-05-08                            [ceftriaxone]
                                2126-05-09                            [ceftriaxone]
                                2126-05-10                            [ceftriaxone]
Length: 22936, dtype: object

Lets count the number of days

# Show
if TERMINAL:
    print("\nTherapies (number of days)")
    print(aux.value_counts())
aux.value_counts()

Out:

[cefepime, vancomycin]                                                                             2630
[cefepime]                                                                                         1802
[vancomycin]                                                                                       1732
[piperacillin-tazobactam, vancomycin]                                                              1490
[meropenem]                                                                                        1378
                                                                                                   ...
[cefepime, gentamicin, gentamicin sulfate, vancomycin]                                                1
[ciprofloxacin, ciprofloxacin iv, vancomycin]                                                         1
[doxycycline hyclate, metronidazole (flagyl)]                                                         1
[cefepime, ciprofloxacin iv, metronidazole (flagyl), sulfamethoxazole-trimethoprim, vancomycin]       1
[ceftolozane-tazobactam, ceftolozane-tazobactam *nf*]                                                 1
Length: 707, dtype: int64