Get the first laboratory measurements for patients admitted to the ICU. Plot the distribution of measurements for survival and non-survival groups.
In [17]:
# Import libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import psycopg2
from scipy.stats import ks_2samp
%matplotlib inline
plt.style.use('ggplot')
In [18]:
# create a database connection
sqluser = 'postgres'
dbname = 'mimic'
schema_name = 'mimiciii'
'Normal' ranges for lab values:
| Lab Value | Lower limit | Upper Limit | Units |
|---|---|---|---|
| Bicarbonate | 22 | 32 | mEq/L |
| BUN | 6 | 20 | mEq/L |
| Calcium | 8.4 | 10.3 | mg/dL |
| Chloride | 96 | 108 | mEq/L |
| Creatinine | 0.4 | 1.1 | mEq/L |
| Hemoglobin | 11.2 | 15.7 | g/dL |
| Lactate | 0.5 | 2 | mmol/L |
| Magnesium | 1.6 | 2.6 | mg/dL |
| Phosphate | 2.7 | 4.5 | mg/dL |
| Platelet count | 150 | 400 | K/uL |
| Potassium | 3.3 | 5.1 | mEq/L |
| Sodium | 133 | 145 | mEq/L |
In [19]:
# Create dictionary of ranges
# Keys should match the lab names in the query below
# Are these values correct given the units? Need to check.
lab_ranges = {'BICARBONATE': [22,32],
'BUN': [6,20],
'CALCIUM': [8.4,10.3],
'CHLORIDE': [96,108],
'CREATININE': [0.4,1.1],
'HEMOGLOBIN': [11.2,15.7],
'LACTATE': [0.5,2.0],
'MAGNESIUM': [1.6,2.6],
'PHOSPHATE': [2.7,4.5],
'PLATELET': [150,400],
'POTASSIUM': [3.3,5.1],
'SODIUM': [133,145]
}
In [20]:
# Connect to local postgres version of mimic
con = psycopg2.connect(dbname=dbname, user=sqluser)
cur = con.cursor()
cur.execute('SET search_path to ' + schema_name)
# Modify first day labs code:
# https://github.com/MIT-LCP/mimic-code/tree/master/etc/firstday
query = \
"""
WITH pvt AS (
SELECT ie.subject_id, ie.hadm_id, ie.outtime, ie.icustay_id, le.charttime, ad.deathtime
, CASE when ad.deathtime between ie.intime and ie.outtime THEN 1 ELSE 0 END AS mort_icu
, CASE when ad.deathtime between ad.admittime and ad.dischtime THEN 1 ELSE 0 END AS mort_hosp
-- here we assign labels to ITEMIDs
-- this also fuses together multiple ITEMIDs containing the same data
, CASE
when le.itemid = 50868 then 'ANION GAP'
when le.itemid = 50862 then 'ALBUMIN'
when le.itemid = 50882 then 'BICARBONATE'
when le.itemid = 50885 then 'BILIRUBIN'
when le.itemid = 50912 then 'CREATININE'
when le.itemid = 50806 then 'CHLORIDE'
when le.itemid = 50902 then 'CHLORIDE'
when itemid = 50809 then 'GLUCOSE'
when itemid = 50931 then 'GLUCOSE'
when itemid = 50810 then 'HEMATOCRIT'
when itemid = 51221 then 'HEMATOCRIT'
when itemid = 50811 then 'HEMOGLOBIN'
when itemid = 51222 then 'HEMOGLOBIN'
when itemid = 50813 then 'LACTATE'
when itemid = 50960 then 'MAGNESIUM'
when itemid = 50970 then 'PHOSPHATE'
when itemid = 51265 then 'PLATELET'
when itemid = 50822 then 'POTASSIUM'
when itemid = 50971 then 'POTASSIUM'
when itemid = 51275 then 'PTT'
when itemid = 51237 then 'INR'
when itemid = 51274 then 'PT'
when itemid = 50824 then 'SODIUM'
when itemid = 50983 then 'SODIUM'
when itemid = 51006 then 'BUN'
when itemid = 51300 then 'WBC'
when itemid = 51301 then 'WBC'
ELSE null
END AS label
, -- add in some sanity checks on the values
-- the where clause below requires all valuenum to be > 0,
-- so these are only upper limit checks
CASE
when le.itemid = 50862 and le.valuenum > 10 then null -- g/dL 'ALBUMIN'
when le.itemid = 50868 and le.valuenum > 10000 then null -- mEq/L 'ANION GAP'
when le.itemid = 50882 and le.valuenum > 10000 then null -- mEq/L 'BICARBONATE'
when le.itemid = 50885 and le.valuenum > 150 then null -- mg/dL 'BILIRUBIN'
when le.itemid = 50806 and le.valuenum > 10000 then null -- mEq/L 'CHLORIDE'
when le.itemid = 50902 and le.valuenum > 10000 then null -- mEq/L 'CHLORIDE'
when le.itemid = 50912 and le.valuenum > 150 then null -- mg/dL 'CREATININE'
when le.itemid = 50809 and le.valuenum > 10000 then null -- mg/dL 'GLUCOSE'
when le.itemid = 50931 and le.valuenum > 10000 then null -- mg/dL 'GLUCOSE'
when le.itemid = 50810 and le.valuenum > 100 then null -- % 'HEMATOCRIT'
when le.itemid = 51221 and le.valuenum > 100 then null -- % 'HEMATOCRIT'
when le.itemid = 50811 and le.valuenum > 50 then null -- g/dL 'HEMOGLOBIN'
when le.itemid = 51222 and le.valuenum > 50 then null -- g/dL 'HEMOGLOBIN'
when le.itemid = 50813 and le.valuenum > 50 then null -- mmol/L 'LACTATE'
when le.itemid = 50960 and le.valuenum > 60 then null -- mmol/L 'MAGNESIUM'
when le.itemid = 50970 and le.valuenum > 60 then null -- mg/dL 'PHOSPHATE'
when le.itemid = 51265 and le.valuenum > 10000 then null -- K/uL 'PLATELET'
when le.itemid = 50822 and le.valuenum > 30 then null -- mEq/L 'POTASSIUM'
when le.itemid = 50971 and le.valuenum > 30 then null -- mEq/L 'POTASSIUM'
when le.itemid = 51275 and le.valuenum > 150 then null -- sec 'PTT'
when le.itemid = 51237 and le.valuenum > 50 then null -- 'INR'
when le.itemid = 51274 and le.valuenum > 150 then null -- sec 'PT'
when le.itemid = 50824 and le.valuenum > 200 then null -- mEq/L == mmol/L 'SODIUM'
when le.itemid = 50983 and le.valuenum > 200 then null -- mEq/L == mmol/L 'SODIUM'
when le.itemid = 51006 and le.valuenum > 300 then null -- 'BUN'
when le.itemid = 51300 and le.valuenum > 1000 then null -- 'WBC'
when le.itemid = 51301 and le.valuenum > 1000 then null -- 'WBC'
ELSE le.valuenum
END AS valuenum
FROM icustays ie
LEFT JOIN labevents le
ON le.subject_id = ie.subject_id
AND le.hadm_id = ie.hadm_id
AND le.charttime between (ie.intime - interval '6' hour)
AND (ie.intime + interval '1' day)
AND le.itemid IN
(
-- comment is: LABEL | CATEGORY | FLUID | NUMBER OF ROWS IN LABEVENTS
50868, -- ANION GAP | CHEMISTRY | BLOOD | 769895
50862, -- ALBUMIN | CHEMISTRY | BLOOD | 146697
50882, -- BICARBONATE | CHEMISTRY | BLOOD | 780733
50885, -- BILIRUBIN, TOTAL | CHEMISTRY | BLOOD | 238277
50912, -- CREATININE | CHEMISTRY | BLOOD | 797476
50902, -- CHLORIDE | CHEMISTRY | BLOOD | 795568
50806, -- CHLORIDE, WHOLE BLOOD | BLOOD GAS | BLOOD | 48187
50931, -- GLUCOSE | CHEMISTRY | BLOOD | 748981
50809, -- GLUCOSE | BLOOD GAS | BLOOD | 196734
51221, -- HEMATOCRIT | HEMATOLOGY | BLOOD | 881846
50810, -- HEMATOCRIT, CALCULATED | BLOOD GAS | BLOOD | 89715
51222, -- HEMOGLOBIN | HEMATOLOGY | BLOOD | 752523
50811, -- HEMOGLOBIN | BLOOD GAS | BLOOD | 89712
50813, -- LACTATE | BLOOD GAS | BLOOD | 187124
50960, -- MAGNESIUM | CHEMISTRY | BLOOD | 664191
50970, -- PHOSPHATE | CHEMISTRY | BLOOD | 590524
51265, -- PLATELET COUNT | HEMATOLOGY | BLOOD | 778444
50971, -- POTASSIUM | CHEMISTRY | BLOOD | 845825
50822, -- POTASSIUM, WHOLE BLOOD | BLOOD GAS | BLOOD | 192946
51275, -- PTT | HEMATOLOGY | BLOOD | 474937
51237, -- INR(PT) | HEMATOLOGY | BLOOD | 471183
51274, -- PT | HEMATOLOGY | BLOOD | 469090
50983, -- SODIUM | CHEMISTRY | BLOOD | 808489
50824, -- SODIUM, WHOLE BLOOD | BLOOD GAS | BLOOD | 71503
51006, -- UREA NITROGEN | CHEMISTRY | BLOOD | 791925
51301, -- WHITE BLOOD CELLS | HEMATOLOGY | BLOOD | 753301
51300 -- WBC COUNT | HEMATOLOGY | BLOOD | 2371
)
AND le.valuenum IS NOT null
AND le.valuenum > 0 -- lab values cannot be 0 and cannot be negative
LEFT JOIN admissions ad
ON ie.subject_id = ad.subject_id
AND ie.hadm_id = ad.hadm_id
-- WHERE ie.subject_id < 10000
),
ranked AS (
SELECT pvt.*, DENSE_RANK() OVER (PARTITION BY
pvt.subject_id, pvt.hadm_id,pvt.icustay_id,pvt.label ORDER BY pvt.charttime) as drank
FROM pvt
)
SELECT r.subject_id, r.hadm_id, r.icustay_id, r.mort_icu, r.mort_hosp
, max(case when label = 'ANION GAP' then valuenum else null end) as ANIONGAP_1st
, max(case when label = 'ALBUMIN' then valuenum else null end) as ALBUMIN_1st
, max(case when label = 'BICARBONATE' then valuenum else null end) as BICARBONATE_1st
, max(case when label = 'BILIRUBIN' then valuenum else null end) as BILIRUBIN_1st
, max(case when label = 'CREATININE' then valuenum else null end) as CREATININE_1st
, max(case when label = 'CHLORIDE' then valuenum else null end) as CHLORIDE_1st
, max(case when label = 'GLUCOSE' then valuenum else null end) as GLUCOSE_1st
, max(case when label = 'HEMATOCRIT' then valuenum else null end) as HEMATOCRIT_1st
, max(case when label = 'HEMOGLOBIN' then valuenum else null end) as HEMOGLOBIN_1st
, max(case when label = 'LACTATE' then valuenum else null end) as LACTATE_1st
, max(case when label = 'MAGNESIUM' then valuenum else null end) as MAGNESIUM_1st
, max(case when label = 'PHOSPHATE' then valuenum else null end) as PHOSPHATE_1st
, max(case when label = 'PLATELET' then valuenum else null end) as PLATELET_1st
, max(case when label = 'POTASSIUM' then valuenum else null end) as POTASSIUM_1st
, max(case when label = 'PTT' then valuenum else null end) as PTT_1st
, max(case when label = 'INR' then valuenum else null end) as INR_1st
, max(case when label = 'PT' then valuenum else null end) as PT_1st
, max(case when label = 'SODIUM' then valuenum else null end) as SODIUM_1st
, max(case when label = 'BUN' then valuenum else null end) as BUN_1st
, max(case when label = 'WBC' then valuenum else null end) as WBC_1st
FROM ranked r
WHERE r.drank = 1
GROUP BY r.subject_id, r.hadm_id, r.icustay_id, r.mort_icu, r.mort_hosp, r.drank
ORDER BY r.subject_id, r.hadm_id, r.icustay_id, r.mort_icu, r.mort_hosp, r.drank;
"""
data = pd.read_sql_query(query,con)
In [ ]:
data.head()
In [22]:
# Plot first laboratory measurement on ICU admission vs ICU mortality
# Would be clearer to plot CDF
# Additional variables to be added: magnesium, phosphate, calcium
labs = {'ANIONGAP': 'mEq/L',
'ALBUMIN': 'g/dL',
'BICARBONATE': 'mEq/L',
'BILIRUBIN': 'mg/dL',
'BUN': '',
'CHLORIDE': 'mEq/L',
'CREATININE': 'mg/dL',
'GLUCOSE': 'mg/dL',
'HEMATOCRIT': '%',
'HEMOGLOBIN': 'g/dL',
'INR': '',
'LACTATE': 'mmol/L',
'MAGNESIUM': 'mmol/L',
'PHOSPHATE': 'mg/dL',
'PLATELET': 'K/uL',
'POTASSIUM': 'mEq/L',
'PT': '',
'PTT': 'sec',
'SODIUM':'mmol/L',
'WBC': ''}
for l, u in iter(sorted(labs.iteritems())):
# count patients
n_nonsurv = data[l.lower()+'_1st'][data.mort_icu==1].dropna().count()
n_surv = data[l.lower()+'_1st'][data.mort_icu==0].dropna().count()
# get median, variance, skewness
med_nonsurv = data[l.lower()+'_1st'][data.mort_icu==1].dropna().median()
med_surv = data[l.lower()+'_1st'][data.mort_icu==0].dropna().median()
var_nonsurv = data[l.lower()+'_1st'][data.mort_icu==1].dropna().var()
var_surv = data[l.lower()+'_1st'][data.mort_icu==0].dropna().var()
skew_nonsurv = data[l.lower()+'_1st'][data.mort_icu==1].dropna().skew()
skew_surv = data[l.lower()+'_1st'][data.mort_icu==0].dropna().skew()
# Are the 2 samples drawn from the same continuous distribution?
# Try Kolmogorov Smirnov test
ks_stat, p_val = ks_2samp(data[l.lower()+'_1st'][data.mort_icu==1].dropna(),
data[l.lower()+'_1st'][data.mort_icu==0].dropna())
# plot
plt.subplots(figsize=(13,6))
data[l.lower()+'_1st'][data.mort_icu==1].dropna().plot.kde(
alpha=1.0,label='Non-survival (n={})'.format(n_nonsurv))
data[l.lower()+'_1st'][data.mort_icu==0].dropna().plot.kde(
alpha=1.0,label='Survival (n={})'.format(n_surv))
# fake plots for KS test, median, etc
plt.plot([], label=' ',color='lightgray')
plt.plot([], label='KS test: p={}'.format(format(p_val,'.3f')),
color='lightgray')
plt.plot([], label='Median (non-surv): {}'.format(format(med_nonsurv,'.2f')),
color='lightgray')
plt.plot([], label='Median (surv): {}'.format(format(med_surv,'.2f')),
color='lightgray')
plt.plot([], label='Variance (non-surv): {}'.format(format(var_nonsurv,'.2f')),
color='lightgray')
plt.plot([], label='Variance (surv): {}'.format(format(var_surv,'.2f')),
color='lightgray')
plt.plot([], label='Skew (non-surv): {}'.format(format(skew_nonsurv,'.2f')),
color='lightgray')
plt.plot([], label='Skew (surv): {}'.format(format(skew_surv,'.2f')),
color='lightgray')
# add title, labels etc.
plt.title('First {} measurement on ICU admission '.format(l.lower()) +
'vs ICU mortality \n')
plt.xlabel(l + ' ' + u)
plt.legend(loc="upper left", bbox_to_anchor=(1,1),fontsize=12)
plt.xlim(0, data[l.lower()+'_1st'].quantile(0.99))
# Add lab range if available
if l in lab_ranges:
plt.axvline(lab_ranges[l][0],color='k',linestyle='--')
plt.axvline(lab_ranges[l][1],color='k',linestyle='--')
In [30]:
# Risk of patients with labs outside the normal range
data.loc[data['mort_icu']==0].head()
Out[30]:
In [37]:
for l in lab_ranges:
print l
# data.loc[(data['mort_icu']==0) & ((data['mort_icu'])]
data.loc[data[l.lower()+'_1st'] < 80]
Out[37]: