];
ITEM_PREFIXES = \
[ "A","B","C","D","E","F","G","H","I",
];
specificArgvList = \
[
];
for categoryName in CATEGORY_LIST:
for itemPrefix in ITEM_PREFIXES:
specificArgv = ["-c", categoryName, "-i", itemPrefix, "results/queryResults.%s.%s.tab.gz" % (itemPrefix, categoryName) ];
specificArgvList.append(specificArgv);
prog = ProgressDots(1,1,"Processes",total=len(specificArgvList));
for specificArgv in specificArgvList:
key = "%.3d.%s" % (prog.getCounts(), str.join("_",specificArgv) );
key = key.replace("/",".."); # Don't want to use directory separator in temp log file name
argv = list(baseArgv)
argv.extend(specificArgv);
log.info( "Starting: "+str.join(" ", argv) );
logFile = stdOpen(LOG_FILE_TEMPLATE % key,"w")
# Blocking sub-process call if want serial processes.
#subprocess.call(argv, stderr=logFile);
# Non-blocking subprocess.Popen to spawn parallel processes
process = subprocess.Popen(argv, stderr=logFile);
log.info("Process ID: %s" % process.pid);
# Print command lines to effectively generate a .sh script
#print "nohup",
'LABNTBNP', 'LABOSM', 'LABPALB', 'LABPCCG4O', 'LABPCCR', 'LABPCTNI',
'LABPHOS', 'LABPLTS', 'LABPROCT', 'LABPT', 'LABPTEG', 'LABPTT', 'LABRESP',
'LABRESPG', 'LABRETIC', 'LABSPLAC', 'LABSTLCX', 'LABSTOBGD', 'LABTNI',
'LABTRFS', 'LABTRIG', 'LABTSH', 'LABUCR', 'LABUOSM', 'LABUA', 'LABUAPRN',
'LABUPREG', 'LABURIC', 'LABURNA', 'LABURNC', 'LABUSPG'
]
labs_to_test = ["LABLACWB"]
# [#"LABMGN, #"LABPTT", #"LABPHOS", "LABTNI", #"LABLACWB",
# #"LABA1C", #"LABHEPAR", #"LABPLTS", "LABLAC","LABLIPS",
# "LABTSH", "LABHCTX", "LABLDH", "LABK", "LABNTBNP",
# "LABCRP", "LABCK", #"LABFER",
# "LABUSPG"]
baseArgv = \
["python","LabChangePredictionPipeline.py"]
prog = ProgressDots(1, 1, "Processes", total=len(labs_to_test))
for lab_name in labs_to_test:
key = "%.3d.%s" % (prog.getCounts(), lab_name)
key = key.replace(
"/",
"..") # Don't want to use directory separator in temp log file name
argv = list(baseArgv)
argv.append(lab_name)
log.info("Starting: " + str.join(" ", argv))
logFile = stdOpen(LOG_FILE_TEMPLATE % key, "w")
p = subprocess.Popen(argv, stderr=logFile)
# Blocking sub-process call. Can just run multiple instances to parallelize, or consider subprocess.Popen objects instead
def main(argv):
medIdsByActiveRx = dict()
medIdsByActiveRx['Buprenorphine'] = ('125498', '114474', '212560',
'114475', '114467', '114468')
medIdsByActiveRx['Fentanyl Patch'] = ('2680', '27908', '125379', '27905',
'27906', '540107', '540638',
'540101', '27907')
medIdsByActiveRx['Methadone'] = ('540483', '4953', '4951', '10546',
'214468', '15996', '41938', '4954',
'4952')
medIdsByActiveRx['Hydrocodone'] = ('3724', '4579', '8576', '8577', '8951',
'10204', '12543', '13040', '14963',
'14965', '14966', '17061', '17927',
'19895', '20031', '28384', '29486',
'29487', '34505', '34544', '35613',
'117862', '204249', '206739')
medIdsByActiveRx['Hydromorphone'] = ('2458', '2459', '2464', '2465',
'3757', '3758', '3759', '3760',
'3761', '10224', '10225', '10226',
'10227', '200439', '201094', '201096',
'201098', '540125', '540179',
'540666')
medIdsByActiveRx['Morphine'] = (
'5167', '5168', '5172', '5173', '5176', '5177', '5178', '5179', '5180',
'5183', '6977', '10655', '15852', '20908', '20909', '20910', '20914',
'20915', '20919', '20920', '20921', '20922', '29464', '30138', '31413',
'36140', '36141', '79691', '87820', '89282', '91497', '95244', '96810',
'112562', '112564', '115335', '115336', '126132', '198543', '198544',
'198623', '201842', '201848', '205011', '206731', '207949', '208896',
'540182', '540300')
medIdsByActiveRx['Oxycodone'] = ('5940', '5941', '6122', '6981', '10812',
'10813', '10814', '14919', '16121',
'16123', '16129', '16130', '19187',
'26637', '26638', '27920', '27921',
'27922', '27923', '28897', '28899',
'28900', '31851', '31852', '31863',
'31864', '92248', '126939', '200451',
'203690', '203691', '203692', '203705',
'203706', '203707', '204020', '204021')
query = baseQuery()
totalPatients = float(DBUtil.execute(query)[0][0])
# print"Total Patients\t%s" % totalPatients
# print"======= Dx Groups ===========";
# print"Dx Group\tPt Count\tDx Rate";
patientsPerDxGroup = dict()
query = SQLQuery()
query.addSelect("count(distinct prob.pat_id) as ptCount")
query.addSelect("prob.%s" % DX_COL)
query.addFrom("stride_problem_list as prob")
query.addWhereOp("prob.noted_date", "<", LIMIT_DATE)
query.addGroupBy("prob.%s" % DX_COL)
if DOUBLE_DX:
query.addSelect("prob2.%s" % DX_COL)
query.addFrom("stride_problem_list as prob2")
query.addWhere("prob.pat_id = prob2.pat_id")
query.addWhereOp("prob2.noted_date", "<", LIMIT_DATE)
query.addGroupBy("prob2.%s" % DX_COL)
results = DBUtil.execute(query)
for row in results:
patientCount = row[0]
dxGroup = row[1]
if DOUBLE_DX:
dxGroup = (dxGroup, row[2])
# Composite tuple including second diagnosis
patientsPerDxGroup[dxGroup] = patientCount
progress = ProgressDots()
for activeRx, medIds in medIdsByActiveRx.iteritems():
query = baseQuery()
query.addWhereIn("medication_id", medIds)
# Baseline prescription rates
rxPtCount = DBUtil.execute(query)[0][0]
# print"====== Rx Counts ======";
# print"Rx\tPt Count\tRx Rate";
# print"%s\t%s\t%s" % (activeRx, rxPtCount, (rxPtCount/totalPatients));
# print"======== Rx-Dx Association ========";
statIds = (
"P-Fisher",
"P-YatesChi2",
"oddsRatio",
"relativeRisk",
"interest",
"LR+",
"LR-",
"sensitivity",
"specificity",
"PPV",
"NPV",
)
if progress.getCounts() == 0:
headerCols = [
"Rx", "Dx", "RxDxCount", "RxCount", "DxCount", "Total"
]
if DOUBLE_DX:
headerCols.insert(2, "Dx2")
headerCols.extend(statIds)
headerStr = str.join("\t", headerCols)
print headerStr
# Query out per diagnosis group, but do as aggregate grouped query
query.addSelect("prob.%s" % DX_COL)
query.addFrom("stride_problem_list as prob")
query.addWhere("med.pat_id = prob.pat_id")
query.addWhereOp("prob.noted_date", "<", LIMIT_DATE)
#query.addWhereIn("prob.%s" % DX_COL, dxKeys );
query.addGroupBy("prob.%s" % DX_COL)
if DOUBLE_DX:
query.addSelect("prob2.%s" % DX_COL)
query.addFrom("stride_problem_list as prob2")
query.addWhere("prob.pat_id = prob2.pat_id")
query.addWhereOp("prob2.noted_date", "<", LIMIT_DATE)
query.addGroupBy("prob2.%s" % DX_COL)
results = DBUtil.execute(query)
for row in results:
rxDxPtCount = row[0]
dxGroup = row[1]
if DOUBLE_DX:
dxGroup = (dxGroup, row[2])
# Composite tuple including second diagnosis
dxPtCount = patientsPerDxGroup[dxGroup]
conStats = ContingencyStats(rxDxPtCount, rxPtCount, dxPtCount,
totalPatients)
dataCells = [
activeRx, dxGroup, rxDxPtCount, rxPtCount, dxPtCount,
totalPatients
]
if DOUBLE_DX:
dataCells[1] = dxGroup[0]
dataCells.insert(2, dxGroup[1])
for statId in statIds:
try:
dataCells.append(conStats[statId])
except ZeroDivisionError:
dataCells.append(None)
for i, value in enumerate(dataCells):
dataCells[i] = str(value)
# String conversion to allow for concatenation below
dataStr = str.join("\t", dataCells)
print dataStr
progress.update()
progress.printStatus()