Given a passage, 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.

Example Input: Changes of volume status can be readily inferred from variations in diameter of the inferior vena cava (IVC) measured by ultrasound. However the effect of IVC changes following acute blood loss are not fully established. In this study, three different approaches to measuring IVC variables were compared in healthy blood donors, as a model of acute volume depletion, in order to establish their relative ability to detect acute blood loss.', 'Inspiratory and expiratory IVC diameters were measured before and after blood donation in hepatic long axis, hepatic short axis and renal short axis views using a 2-5\xa0MHz curvilinear probe. All measurements were recorded and examined in real-time and post-processing sessions.', 'All windows performed satisfactorily but the renal window approach was feasible in only 30 out of 47 subjects. After blood donation, IVC diameters decreased in hepatic long axis, hepatic short axis and renal short axis (expiratory: -19.9, -18.0, -26.5\xa0%; CI 95\xa0%: 14.5-24.1; 13.1-22.9; 16.0-35.9, respectively) (inspiratory: -31.1, -31.6, -36.5\xa0%; CI 95\xa0%: 21.3-40.1; 18.8-45.2; 23.4-46.0, respectively), whereas the IVC collapsibility index increased by 21.6, 22.6 and 19.3\xa0% (CI 95\xa0%: 11.6-42.9; 18.5-39.5; 7.7-30.0). IVC diameters appeared to return to pre-donation values within 20\xa0min but this was only detected by the hepatic long axis view.
Example Output: Do inferior vena cava diameters and collapsibility index reveal early volume depletion in a blood donor model?

Example Input: We investigated whether a computed tomography (CT)-based score could predict a large infarct (≥ 80 mL) on early diffusion-weighted magnetic resonance imaging (DWI).', 'Acute stroke patients considered for endovascular therapy within 8 hours of the onset of symptoms were included. The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) was determined on noncontrast CT and computed tomography angiography source images (CTA-SI). Limited collateral flow was defined as less than 50% collateral filling on CTA-SI.', 'Fifty-six patients were analyzed. National Institutes of Health Stroke Scale score was 20 (15-24) in the large infarct group and 16 (11-20) in the small infarct group (P = .049). ASPECTS on noncontrast CT and CTA-SI was 5 (3-8) and 3 (2-6) in the large infarct group and 9 (8-10) and 8 (7-9) in the small infarct group (both P < .001), respectively. Limited collateral flow was frequent in the large infarct group than in the small infarct group (92% vs. 11%, P < .001). Multivariate analysis found that CTA-SI ASPECTS less than or equal to 5 (odds ratio [OR], 40.55; 95% confidence interval [CI], 1.10-1493.44; P = .044) and limited collateral flow (OR, 114.64; 95% CI, 1.93-6812.79; P = .023) were associated with a large infarct. Absence of ASPECTS less than or equal to 5 and limited collateral flow on CTA-SI predicted absence of a large infarct with a sensitivity of .89, specificity of 1.00, positive predictive value of 1.00, and negative predictive value of .71.
Example Output: Do collateral flow and brain changes on computed tomography angiography predict infarct volume on early diffusion-weighted imaging?

Example Input: To establish a non-invasive model for the assessment of portal venous pressure (PVP) based on the magnetic resonance (MR) parameters.', 'In this prospective study, contrast-enhanced magnetic resonance imaging (MRI) scan was performed in 109 patients indicated for upper abdominal surgeries after their written consents were obtained, and intraoperative PVP measurements were completed in 92 patients. Altogether 17 patients were excluded for not undergoing surgery or unsuccessful catheterization. A linear model was constructed for estimating PVP levels in 56 patients and further validation was conducted in the other 36 patients.', "The PVP levels were significantly correlated with MR parameters, including splenic volume (SV), splenic venous diameter (SVD), liver/splenic volume ratio, portal venous diameter, hepatic diameter, portal venous cross-sectional area, ascites, varices and arterial portal shunts. A linear model was established as follows: PVP (mmHg) = 2.529 + 1.572 × SVD (mm) + 0.231 × SV/body mass index (× 10(4) cm(5) /kg) + 3.44\u2009×\u2009aspartate aminotransferase-to-platelet ratio index. This model showed excellent accuracy in the detection of portal hypertension, with the area under the receiver operating characteristic curve (AUROC) of 0.945 (95% CI 0.867-1.000), with the sensitivity and specificity of 91.7% and 93.7%, respectively. The agreement analysis revealed that the predictive value using this formula closely reflected the patients' actual PVP level. Moreover, the validation confirmed the accuracy of this model for the assessment of portal hypertension [AUROC 0.935 (95% CI 0.856-1.000)].
Example Output:
Does a non-invasive magnetic resonance imaging-based model predict portal venous pressure?