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Distribution data extraction
import numpy as np
import pickle
import logging
import psycopg2
import concurrent.futures
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
np_data = np.load('data_extraction/get_list_of_hadm_id.npy')
list_adm_id = np_data.tolist()
print(len(list_adm_id))
# SpO2 - 646, 220277
# HR - 211, 220045
# RR - 618, 615, 220210, 224690
# SBP - 51,442,455,6701,220179,220050
# DBP - 8368,8440,8441,8555,220180,220051
# EtCO2 - 1817, 228640
# Temp(F) - 223761,678
# Temp(C) - 223762,676
# TGCS - 198, 226755, 227013
# CRR - 3348
# Urine Output - 43647, 43053, 43171, 43173, 43333, 43347,
# 43348, 43355, 43365, 43373, 43374, 43379, 43380, 43431,
# 43519, 43522, 43537, 43576, 43583, 43589, 43638, 43654,
# 43811, 43812, 43856, 44706, 45304, 227519,
# FiO2 - 2981, 3420, 3422, 223835,
# Glucose - 807,811,1529,3745,3744,225664,220621,226537
# pH - 780, 860, 1126, 1673, 3839, 4202, 4753, 6003, 220274, 220734, 223830, 228243,
def preprocess_vitals(list_adm_id: list, number: int):
data = []
for id in range(len(list_adm_id)):
# print(id, list_adm_id[id][0])
print(f"Processing admission {id}")
hadm_id = list_adm_id[id][0]
vitals = []
conn = psycopg2.connect(dbname='mimic', user='postgres', host='localhost', port='5432', password='p13240!')
cur = conn.cursor()
# Set the search path for this connection
cur.execute("SET search_path TO mimiciii;")
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(646) +
" or itemid = " + str(220277) + ") order by charttime")
vitals.append(cur.fetchall())
# Heart Rate
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(211) +
" or itemid = " + str(220045) + ") order by charttime")
vitals.append(cur.fetchall())
# Respiratory Rate
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(618) +
" or itemid = " + str(615) + " or itemid = " + str(220210) +
" or itemid = " + str(224690) + ") order by charttime")
vitals.append(cur.fetchall())
# Systolic Blood Pressure
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(51) +
" or itemid = " + str(442) + " or itemid = " + str(455) +
" or itemid = " + str(6701) + " or itemid = " + str(220179) +
" or itemid = " + str(220050) + ") order by charttime")
vitals.append(cur.fetchall())
# Diastolic Blood Pressure
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(8368) +
" or itemid = " + str(8440) + " or itemid = " + str(8441) +
" or itemid = " + str(8555) + " or itemid = " + str(220180) +
" or itemid = " + str(220051) + ") order by charttime")
vitals.append(cur.fetchall())
# End-tidal carbon dioxide
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(1817) +
" or itemid = " + str(228640) + ") order by charttime")
vitals.append(cur.fetchall())
# Temperature
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(678) +
" or itemid = " + str(223761) + ") order by charttime")
vitals.append(cur.fetchall())
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(676) +
" or itemid = " + str(223762) + ") order by charttime")
vitals.append(cur.fetchall())
# Total Glasgow coma score
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(198) +
" or itemid = " + str(226755) + " or itemid = " + str(227013)
+ ") order by charttime")
vitals.append(cur.fetchall())
# Peripheral capillary refill rate
cur.execute("select charttime, value from chartevents where hadm_id = "
+ str(hadm_id) + " and itemid = " + str(3348) +
" order by charttime")
vitals.append(cur.fetchall())
cur.execute("select charttime, value from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(115) +
" or itemid = 223951) order by charttime")
vitals.append(cur.fetchall())
cur.execute("select charttime, value from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(8377) +
" or itemid = 224308) order by charttime")
vitals.append(cur.fetchall())
# Urine output
cur.execute("select charttime, VALUE from outputevents where hadm_id = "
+ str(hadm_id) + " and ( itemid = 40405 or itemid = " +
" 40428 or itemid = 41857 or itemid = 42001 or itemid = 42362 or itemid = " +
" 42676 or itemid = 43171 or itemid = 43173 or itemid = 42042 or itemid = " +
" 42068 or itemid = 42111 or itemid = 42119 or itemid = 40715 or itemid = " +
" 40056 or itemid = 40061 or itemid = 40085 or itemid = 40094 or itemid = " +
" 40096 or itemid = 43897 or itemid = 43931 or itemid = 43966 or itemid = " +
" 44080 or itemid = 44103 or itemid = 44132 or itemid = 44237 or itemid = " +
" 43348 or itemid = " +
" 43355 or itemid = 43365 or itemid = 43372 or itemid = 43373 or itemid = " +
" 43374 or itemid = 43379 or itemid = 43380 or itemid = 43431 or itemid = " +
" 43462 or itemid = 43522 or itemid = 44706 or itemid = 44911 or itemid = " +
" 44925 or itemid = 42810 or itemid = 42859 or itemid = 43093 or itemid = " +
" 44325 or itemid = 44506 or itemid = 43856 or itemid = 45304 or itemid = " +
" 46532 or itemid = 46578 or itemid = 46658 or itemid = 46748 or itemid = " +
" 40651 or itemid = 40055 or itemid = 40057 or itemid = 40065 or itemid = " +
" 40069 or itemid = 44752 or itemid = 44824 or itemid = 44837 or itemid = " +
" 43576 or itemid = 43589 or itemid = 43633 or itemid = 43811 or itemid = " +
" 43812 or itemid = 46177 or itemid = 46727 or itemid = 46804 or itemid = " +
" 43987 or itemid = 44051 or itemid = 44253 or itemid = 44278 or itemid = " +
" 46180 or itemid = 45804 or itemid = 45841 or itemid = 45927 or itemid = " +
" 42592 or itemid = 42666 or itemid = 42765 or itemid = 42892 or itemid = " +
" 43053 or itemid = 43057 or itemid = 42130 or itemid = 41922 or itemid = " +
" 40473 or itemid = 43333 or itemid = 43347 or itemid = 44684 or itemid = " +
" 44834 or itemid = 43638 or itemid = 43654 or itemid = 43519 or itemid = " +
" 43537 or itemid = 42366 or itemid = 45991 or itemid = 43583 or itemid = " +
" 43647) order by charttime ")
vitals.append(cur.fetchall())
# Fraction inspired oxygen
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(2981) +
" or itemid = " + str(3420) + " or itemid = " + str(3422) +
" or itemid = " + str(223835) + ") order by charttime")
vitals.append(cur.fetchall())
# Glucose
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(807) +
" or itemid = " + str(811) + " or itemid = " + str(1529) +
" or itemid = " + str(3745) + " or itemid = " + str(3744) +
" or itemid = " + str(225664) + " or itemid = " + str(220621) +
" or itemid = " + str(226537) + ") order by charttime")
vitals.append(cur.fetchall())
# pH
cur.execute("select charttime, valuenum from chartevents where hadm_id = "
+ str(hadm_id) + " and (itemid = " + str(780) +
" or itemid = " + str(860) + " or itemid = " + str(1126) +
" or itemid = " + str(1673) + " or itemid = " + str(3839) +
" or itemid = " + str(4202) + " or itemid = " + str(4753) +
" or itemid = " + str(6003) + " and itemid = " + str(220274) +
" or itemid = " + str(220734) + " or itemid = " + str(223830) +
" or itemid = " + str(228243) + ") order by charttime")
vitals.append(cur.fetchall())
# Append the vitals for this admission ID to the main data list
print("Vitals: ", len(vitals))
data.append(vitals)
cur.close()
conn.close()
pickle.dump(data, open(f'vitals_records_{number}.p', 'wb'))
if __name__ == "__main__":
# len(list_adm_id)=58976
# 58976/1000=58.976
# 59 chunks
chunk1 = list_adm_id[:5000]
chunk2 = list_adm_id[5000:10000]
chunk3 = list_adm_id[10000:15000]
chunk4 = list_adm_id[15000:20000]
chunk5 = list_adm_id[20000:25000]
chunk6 = list_adm_id[25000:30000]
chunk7 = list_adm_id[30000:35000]
chunk8 = list_adm_id[35000:40000]
chunk9 = list_adm_id[40000:45000]
chunk10 = list_adm_id[45000:50000]
chunk11 = list_adm_id[50000:55000]
chunk12 = list_adm_id[55000:58976]
with concurrent.futures.ThreadPoolExecutor(max_workers=15) as executor:
futures = [
executor.submit(preprocess_vitals, chunk1, 5000),
executor.submit(preprocess_vitals, chunk2, 10000),
executor.submit(preprocess_vitals, chunk3, 15000),
executor.submit(preprocess_vitals, chunk4, 20000),
executor.submit(preprocess_vitals, chunk5, 25000),
executor.submit(preprocess_vitals, chunk6, 30000),
executor.submit(preprocess_vitals, chunk7, 35000),
executor.submit(preprocess_vitals, chunk8, 40000),
executor.submit(preprocess_vitals, chunk9, 45000),
executor.submit(preprocess_vitals, chunk10, 50000),
executor.submit(preprocess_vitals, chunk11, 55000),
executor.submit(preprocess_vitals, chunk12, 58976)
]
# Wait for all futures to complete
concurrent.futures.wait(futures)
2024-09-15 12:16:14,727 [INFO] Processing admission 3642 in chunk 10, hadm_id: 168708
2024-09-15 12:16:14,727 [INFO] Processing admission 3643 in chunk 10, hadm_id: 168712
2024-09-15 12:16:14,727 [INFO] Processing admission 3672 in chunk 6, hadm_id: 143702
2024-09-15 12:16:14,727 [INFO] Processing admission 3644 in chunk 10, hadm_id: 168713
2024-09-15 12:16:14,727 [INFO] Processing admission 3673 in chunk 6, hadm_id: 143705
2024-09-15 12:16:14,727 [INFO] Processing admission 3674 in chunk 6, hadm_id: 143707
2024-09-15 12:16:14,727 [INFO] Processing admission 3645 in chunk 10, hadm_id: 168714
2024-09-15 12:16:14,727 [INFO] Processing admission 3675 in chunk 6, hadm_id: 143708
2024-09-15 12:16:14,727 [INFO] Processing admission 3646 in chunk 10, hadm_id: 168715
2024-09-15 12:16:14,727 [INFO] Processing admission 3676 in chunk 6, hadm_id: 143710
2024-09-15 12:16:14,727 [INFO] Processing admission 3647 in chunk 10, hadm_id: 168716
2024-09-15 12:16:14,727 [INFO] Processing admission 3677 in chunk 6, hadm_id: 143711
2024-09-15 12:16:14,727 [INFO] Processing admission 3648 in chunk 10, hadm_id: 168718
2024-09-15 12:16:14,727 [INFO] Processing admission 3678 in chunk 6, hadm_id: 143712
2024-09-15 12:16:14,727 [INFO] Processing admission 3649 in chunk 10, hadm_id: 168721
2024-09-15 12:16:14,727 [INFO] Processing admission 3679 in chunk 6, hadm_id: 143714
2024-09-15 12:16:14,727 [INFO] Processing admission 3650 in chunk 10, hadm_id: 168722
2024-09-15 12:16:14,727 [INFO] Processing admission 3680 in chunk 6, hadm_id: 143716
2024-09-15 12:16:14,727 [INFO] Processing admission 3651 in chunk 10, hadm_id: 168723
2024-09-15 12:16:14,727 [INFO] Processing admission 3681 in chunk 6, hadm_id: 143719
2024-09-15 12:16:14,727 [INFO] Processing admission 3652 in chunk 10, hadm_id: 168725
2024-09-15 12:16:14,727 [INFO] Processing admission 3682 in chunk 6, hadm_id: 143720
2024-09-15 12:16:14,727 [INFO] Processing admission 3653 in chunk 10, hadm_id: 168726
2024-09-15 12:16:14,727 [INFO] Processing admission 3683 in chunk 6, hadm_id: 143721
2024-09-15 12:16:14,727 [INFO] Processing admission 3654 in chunk 10, hadm_id: 168728
2024-09-15 12:16:14,727 [INFO] Processing admission 3684 in chunk 6, hadm_id: 143722
2024-09-15 12:16:14,727 [INFO] Processing admission 3655 in chunk 10, hadm_id: 168729
2024-09-15 12:16:14,727 [INFO] Processing admission 3685 in chunk 6, hadm_id: 143725
2024-09-15 12:16:14,727 [INFO] Processing admission 3656 in chunk 10, hadm_id: 168730
2024-09-15 12:16:14,727 [INFO] Processing admission 3657 in chunk 10, hadm_id: 168732
2024-09-15 12:16:14,727 [INFO] Processing admission 3658 in chunk 10, hadm_id: 168733
2024-09-15 12:16:14,727 [INFO] Processing admission 3659 in chunk 10, hadm_id: 168736
2024-09-15 12:16:14,727 [INFO] Processing admission 3660 in chunk 10, hadm_id: 168738
2024-09-15 12:16:14,727 [INFO] Processing admission 3661 in chunk 10, hadm_id: 168739
2024-09-15 12:16:14,727 [INFO] Processing admission 3662 in chunk 10, hadm_id: 168744
2024-09-15 12:16:14,728 [INFO] Processing admission 3663 in chunk 10, hadm_id: 168745
2024-09-15 12:16:14,728 [INFO] Processing admission 3664 in chunk 10, hadm_id: 168747
2024-09-15 12:16:14,728 [INFO] Processing admission 3665 in chunk 10, hadm_id: 168750
2024-09-15 12:16:14,728 [INFO] Processing admission 3666 in chunk 10, hadm_id: 168752
2024-09-15 12:16:14,728 [INFO] Processing admission 3667 in chunk 10, hadm_id: 168753
2024-09-15 12:16:14,728 [INFO] Processing admission 3668 in chunk 10, hadm_id: 168754
2024-09-15 12:16:14,728 [INFO] Processing admission 3669 in chunk 10, hadm_id: 168755
2024-09-15 12:16:14,728 [INFO] Processing admission 3670 in chunk 10, hadm_id: 168757
2024-09-15 12:16:14,728 [INFO] Processing admission 3671 in chunk 10, hadm_id: 168758
2024-09-15 12:16:14,728 [INFO] Processing admission 3672 in chunk 10, hadm_id: 168759
2024-09-15 12:16:14,728 [INFO] Processing admission 3673 in chunk 10, hadm_id: 168760
2024-09-15 12:16:14,728 [INFO] Processing admission 3674 in chunk 10, hadm_id: 168761
2024-09-15 12:16:14,728 [INFO] Processing admission 3675 in chunk 10, hadm_id: 168762
2024-09-15 12:16:14,728 [INFO] Processing admission 3676 in chunk 10, hadm_id: 168763
2024-09-15 12:16:14,728 [INFO] Processing admission 3677 in chunk 10, hadm_id: 168764
2024-09-15 12:16:14,728 [INFO] Processing admission 3678 in chunk 10, hadm_id: 168765
2024-09-15 12:16:14,728 [INFO] Processing admission 3679 in chunk 10, hadm_id: 168766
2024-09-15 12:16:14,728 [INFO] Processing admission 3680 in chunk 10, hadm_id: 168767
2024-09-15 12:16:14,728 [INFO] Processing admission 3681 in chunk 10, hadm_id: 168768
2024-09-15 12:16:14,728 [INFO] Processing admission 3682 in chunk 10, hadm_id: 168769
2024-09-15 12:16:14,728 [INFO] Processing admission 3683 in chunk 10, hadm_id: 168770
2024-09-15 12:16:14,728 [INFO] Processing admission 3684 in chunk 10, hadm_id: 168771
2024-09-15 12:16:14,728 [INFO] Processing admission 3685 in chunk 10, hadm_id: 168774
2024-09-15 12:16:14,736 [INFO] Chunk 2 saved with 3686 admissions.
2024-09-15 12:16:14,751 [INFO] Chunk 0 saved with 3686 admissions.
2024-09-15 12:16:14,764 [INFO] Chunk 1 saved with 3686 admissions.
2024-09-15 12:16:14,776 [INFO] Chunk 14 saved with 3686 admissions.
2024-09-15 12:16:14,777 [INFO] Chunk 9 saved with 3686 admissions.
2024-09-15 12:16:14,777 [INFO] Chunk 4 saved with 3686 admissions.
2024-09-15 12:16:14,781 [INFO] Chunk 12 saved with 3686 admissions.
2024-09-15 12:16:14,790 [INFO] Chunk 13 saved with 3686 admissions.
2024-09-15 12:16:14,795 [INFO] Chunk 7 saved with 3686 admissions.
2024-09-15 12:16:14,801 [INFO] Chunk 15 saved with 3686 admissions.
2024-09-15 12:16:14,802 [INFO] Chunk 11 saved with 3686 admissions.
2024-09-15 12:16:14,810 [INFO] Chunk 5 saved with 3686 admissions.
2024-09-15 12:16:14,815 [INFO] Chunk 8 saved with 3686 admissions.
2024-09-15 12:16:14,817 [INFO] Chunk 6 saved with 3686 admissions.
2024-09-15 12:16:14,821 [INFO] Chunk 10 saved with 3686 admissions.
2024-09-15 12:16:14,824 [INFO] All chunks processed and saved.
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