Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.

Q: Context: The aim of the present study was to evaluate baseline regional cerebral oxygen saturation (rSO2) values and identify factors influencing preoperative rSO2 in elective minor surgery.', 'Observational analysis post-hoc.', 'Observational post-hoc analysis of data for the patient sample (n=50) of a previously conducted clinical trial in patients undergoing tumourectomy for breast cancer or inguinal hernia repair. Exclusion criteria included pre-existing cerebrovascular diseases, anaemia, baseline pulse oximetry <97% and low quality rSO2 sensor signals. Demographic data, comorbidities, and ASA physical status as well as height and weight were collected prospectively from all patients. Baseline rSO2 values were recorded while the patient breathed room air, using the INVOS 5100C monitor™ (Covidien, Dublin, Ireland).', 'Thirty-seven women (72%) and 13 men (28%) 48 ± 13 years of age were enrolled in this study. Baseline rSO2 was 62.01 ± 10.38%. Baseline rSO2 was significantly different between men (67.6 ± 11.2%) and women (60 ± 9.4%), (P=0.023). There were also differences between baseline rSO2 and ASA physical status (ASA I: 67.6 ± 10.7%, ASA II: 61.6 ± 8.4%, ASA III: 55.8 ± 13.9%, P=0.045). Baseline rSO2 had a positive correlation with body weight (r=0.347, P=0.014) and height (r=0.345, P=0.014). We also found significant differences in baseline rSO2 among patients with and without chronic renal failure (P=0.005). No differences were found in any other studied variables.
Answer: Non-modifiable patient characteristics (ASA physical status, sex, chronic renal failure, body weight and height) influence baseline rSO2.

A: Do baseline cerebral oximetry values depend on non-modifiable patient characteristics?
****
Q: Context: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders.', 'We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order.', 'A large university teaching hospital using a locally developed CPOE system with an extensive audit database.', 'We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012.', 'The geometric mean time taken to generate a prescription order within the CPOE system was 11.75\u2005s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59\u2005s (24.43 to 24.76); p<0.001) or previously unseen (18.87\u2005s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29\u2005s (11.23 to 11.35)) than on weekdays (11.88\u2005s (11.84 to 11.91); p<0.001), in the first (11.25\u2005s (11.16 to 11.34); p<0.001) and final (11.56\u2005s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system.
Answer: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency.

A: Do temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system?
****
Q: Context: There is controversy as to whether migraine is associated with white matter abnormalities (WMAs) on magnetic resonance images. These abnormalities may be important as a risk factor for future stroke. Further, it is controversial whether any increased risk of WMAs is attributable to comorbidities such as vascular disease.', 'A meta-analysis of published case-control studies was undertaken to address the relationship between migraine and magnetic resonance imaging WMAs. Seven studies were identified. Data from studies reporting the incidence of magnetic resonance imaging WMAs in those with migraine and appropriate control populations were used to calculate odds ratios for WMAs in migraine for each study. A stratified meta-analysis was performed using studies that did and did not exclude subjects with disease comorbidities.', 'The summary odds ratio shows that those with migraine are at increased risk for WMAs (odds ratio, 3.9 [95% confidence interval, 2.26-6.72]). The risk does not differ between studies that included subjects with comorbidities and those that did not.
Answer: This meta-analysis demonstrates that subjects with migraine are at higher risk of having WMAs on magnetic resonance images than those without migraine. This increased risk is present even in younger individuals who do not have co-occurring cerebrovascular disease risk factors. Prospective studies are needed to determine whether the increased risk of stroke in migraine is mediated or foreshadowed by the presence of WMAs.

A:
Is migraine associated with magnetic resonance imaging white matter abnormalities : a meta-analysis?
****