In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Q: Context: To test device integrity and objective auditory reaction for cochlear implant patients intraoperatively.', 'Our protocol for intraoperative testing of the implant device includes device electrode impedance test and neural response telemetry (NRT), which measures the electrically evoked auditory nerve compound action potentials (ECAP).', 'We completed electrode integrity tests and NRT intraoperatively on 40 patients with the Nucleus CI24M cochlear implant. We have measured normal implant function on all 40 patients and obtained ECAP results from 39 patients. Out of 33 patients with normal inner ear, typical ECAPs were recorded in 195 electrodes in all 198 testing electrodes(98.5%). In 7 patients with inner ear Mondini dysphasia, affirmative ECAP waveforms were recorded in 26 electrodes in all 42 testing electrodes. The basal electrode ECAP threshold was higher than that of the epical one.\Question: Do [ The intraoperative application of neural response telemetry with the nucleus CI24M cochlear implant ]?

A: The intraoperative measurements of device function and NRT are quite simple, quick and with high accuracy. Inner ear malformation is an important factor that may affect NRT results.
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Q: Context: Studies in chronic noncancer pain settings have found that opioid use increases health care utilization. Despite the key role of analgesics, specifically opioids, in the setting of cancer pain, there is no literature to our knowledge about the relationship between adherence to prescribed around-the-clock (ATC) analgesics and acute health care utilization (hospitalization) among patients with cancer pain.', 'To identify adherence patterns over time for cancer patients taking ATC analgesics for pain, cluster these patterns into adherence types, combine the types into an adherence risk factor for hospitalization, identify other risk factors for hospitalization, and identify risk factors for inconsistent analgesic adherence.', 'Data from a 3-month prospective observational study of patients diagnosed with solid tumors or multiple myeloma, having cancer-related pain, and having at least one prescription of oral ATC analgesics were collected. Adherence data were collected electronically using the medication event-monitoring system. Analyses were conducted using adaptive modeling methods based on heuristic search through alternative models controlled by likelihood cross-validation scores.', 'Six adherence types were identified and combined into the risk factor for hospitalization of inconsistent versus consistent adherence over time. Twenty other individually significant risk factors for hospitalization were identified, but inconsistent analgesic adherence was the strongest of these predictors (ie, generating the largest likelihood cross-validation score). These risk factors were adaptively combined into a model for hospitalization based on six pairwise interaction risk factors with exceptional discrimination (ie, area under the receiver-operating-characteristic curve of 0.91). Patients had from zero to five of these risk factors, with an odds ratio of 5.44 (95% confidence interval 3.09-9.58) for hospitalization, with a unit increase in the number of such risk factors.\Question: Do patterns of analgesic adherence predict health care utilization among outpatients with cancer pain?

A: Inconsistent adherence to prescribed ATC analgesics, specifically the interaction of strong opioids and inconsistent adherence, is a strong risk factor for hospitalization among cancer outpatients with pain.
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Q: Context: Prolonged cardiac monitoring detects higher rates of atrial fibrillation (AF) in ischemic stroke and transient ischemic attack (TIA) but is costly and has practical implications. The use of admission troponin-I (TnI) level to identify patients at high risk of delayed AF detection was investigated.', 'Consecutive ischemic stroke and TIA cases presenting to our institute over a 13-month period were identified from the Irish Stroke and TIA Register. Electronic databases and case notes were examined. "Delayed" AF was diagnosed after a sinus rhythm admission electrocardiogram and no documented history. Group comparisons were made by AF status. The association between TnI and AF was investigated using a multivariate regression model.', 'A total of 185 cases (130 ischemic stroke) were analyzed. Mean age (standard deviation) was 73.3 (13.9) years, 47% female. Sixty-two cases (33.5%) had AF. The first documented presentation of AF was found in 21 cases, on admission electrocardiogram (n = 11) or inpatient telemetry (delayed, n = 10). TnI was higher in those with delayed AF than in those without AF (W = 194; P = .036). A higher proportion of those with an elevated TnI (30%) than those with a normal TnI (6.1%) had delayed diagnosis of AF (χ(2) = 6.41, P = .011). Having an abnormal TnI was a significant independent predictor of delayed AF detection (odds ratio, 5.8; P = .037).\Question: Is troponin-I a predictor of a delayed diagnosis of atrial fibrillation in acute ischemic stroke and transient ischemic attack?

A:
TnI elevation is associated with a higher likelihood of subsequent AF diagnosis. Identification of these higher risk stroke and TIA cases for more intensive cardiac monitoring may improve stroke secondary prevention practices.
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