def get_trial_criteria(nct): """ Returns JSON containing HTML formatted eligibility criteria for one trial. """ trial = Trial(nct) trial.load() return {'criteria': trial.eligibility.formatted_html}
def trials_filter_by(run_id, filter_by): runner = Runner.get(run_id) if runner is None: bottle.abort(404) if not runner.done: bottle.abort(400, "Trial results are not available") ncts = runner.get_ncts(restrict='none') sess = _get_session() run_data = sess.get('runs', {}).get(run_id, {}) # demographics - get age and gender if 'demographics' == filter_by: f_gender = run_data.get('gender') f_age = int(run_data.get('age', 0)) for tpl in ncts: nct = tpl[0] reason = tpl[1] if len(tpl) > 1 else None if not reason: trial = Trial(nct) trial.load() # filter gender if f_gender: if 'male' == f_gender: if trial.eligibility.gender == 2: reason = "Limited to women" else: if trial.eligibility.gender == 1: reason = "Limited to men" # filter age if f_age > 0: if trial.eligibility.min_age and trial.eligibility.min_age > f_age: reason = "Patient is too young (min age %d)" % trial.eligibility.min_age elif trial.eligibility.max_age and trial.eligibility.max_age < f_age: reason = "Patient is too old (max age %d)" % trial.eligibility.max_age # TODO: REFACTOR into runner class! if reason: runner.write_trial_reason(nct, reason) runner.commit_transactions() # problems (only if NLP is on) elif 'problems' == filter_by: if USE_NLP: probs = problems().get('problems', []) # extract snomed codes from patient's problem list snomed = SNOMEDLookup() exclusion_codes = [] for problem in probs: snomed_url = problem.get('sp:problemName', {}).get('sp:code', {}).get('@id') if snomed_url is not None: snomed_code = os.path.basename(snomed_url) exclusion_codes.append(snomed_code) # look at trial criteria for tpl in ncts: nct = tpl[0] reason = tpl[1] if len(tpl) > 1 else None # if we already have a reason, this trial has already been filtered if not reason: trial = Trial(nct) trial.load() # exclusion criterion matched if trial.filter_snomed(exclusion_codes) is not None: reason = 'Matches exclusion criterium "%s" (SNOMED %s)' % ( snomed.lookup_code_meaning(match, True, True), match) break # TODO: REFACTOR # runner.write_trial_reason(nct, reason) # unknown filtering property else: return '{"error": "We can not filter by %s"}' % filter_by return '{"status": "ok"}'
def trials_json(self, restrict='reason', filter_interventions=None, filter_phases=None): """ Returns an array of trial JSON for the matching trials, optionally filtered by intervention type and/or drug phases. """ if not self.done: raise Exception("Trial results are not yet available") sqlite = SQLite.get(self.sqlite_db) if sqlite is None: raise Exception("No SQLite handle, please set up properly") # look up trials. Currently cheaply filtering by string comparison qry = "SELECT nct FROM trials WHERE run_id = ? AND reason IS NULL" if 'reason' == restrict: qry += ' AND reason IS NULL' tpls = [self.run_id] if filter_interventions is not None: ored = [] for inter in filter_interventions: ored.append('types LIKE "%%%s%%"' % inter) # ored.append('instr(types, ?)') # tpls.append(inter) if len(ored) > 0: qry = qry + ' AND (' + ' OR '.join(ored) + ')' if filter_phases is not None: ored = [] for phase in filter_phases: ored.append('phases LIKE "%%%s%%"' % phase) # ored.append('instr(phases, ?)') # tpls.append(phase) if len(ored) > 0: qry = qry + ' AND (' + ' OR '.join(ored) + ')' trials = [] fields = ['keyword', 'phase', 'overall_contact'] lat = float( self.reference_location[0]) if self.reference_location else 0 lng = float( self.reference_location[1]) if self.reference_location else 0 # retrieve ncts qry += ' ORDER BY distance ASC' for row in sqlite.execute(qry, tuple(tpls)): trial = Trial(row[0]) trial.load() trial_dict = trial.json(fields) # add trial locations if lat and lng: closest = [] for loc in trial.locations_closest_to(lat, lng, open_only=True): closest.append(loc[0].json()) trial_dict['location'] = closest trials.append(trial_dict) # grab trial data in batch from db - PROBLEM: distance order is not preserved # for trial in Trial.retrieve(ncts): # trials.append(trial.json(fields)) return trials