WEDNESDAY, Dec. 20, 2023 (HealthDay News) -- For individuals with chronic obstructive pulmonary disease (COPD), dietary nitrate supplementation in the form of beetroot juice results in a sustained reduction in systolic blood pressure (SBP), according to a study published online Dec. 19 in the European Respiratory Journal.

Ali M. Alasmari, from the National Heart and Lung Institute at Imperial College London, and colleagues conducted a randomized trial involving stable COPD patients with home SBP measurement ≥130 mm Hg. Participants were randomly assigned to 70 mL of nitrate-rich beetroot juice (400 mg NO3) or an identical nitrate-depleted placebo juice once daily for 12 weeks (40 and 41 patients, respectively).

The researchers found that active treatment lowered SBP (Hodges-Lemman treatment effect mean difference, −4.5 mm Hg), improved 6-minute walk distance (+30.0 m), and improved measures of endothelial function (reactive hyperemia index [+0.34] and augmentation index [−7.61 percent]) compared with placebo.

"There is some evidence that beetroot juice as a source of nitrate supplementation could be used by athletes to improve their performance, as well as a few short-term studies looking at blood pressure. Higher levels of nitrate in the blood can increase the availability of nitric oxide, a chemical that helps blood vessels relax. It also increases the efficiency of muscles," lead author Nicholas Hopkinson, Ph.D., also of Imperial College London, said in a statement. "This is one of the longest-duration studies in this area so far. The results are very promising, but will need to be confirmed in larger, longer-term studies."

Abstract/Full Text (subscription or payment may be required)

Copyright © 2020 HealthDay. All rights reserved.

TUESDAY, Dec. 19, 2023 (HealthDay News) -- Standard artificial intelligence (AI) models improve diagnostic accuracy, but systematically biased AI models reduce this accuracy, according to a study published in the Dec. 19 issue of the Journal of the American Medical Association.

Sarah Jabbour, from the University of Michigan in Ann Arbor, and colleagues examined the impact of systematically biased AI on clinician diagnostic accuracy in a randomized clinical vignette survey study. Clinicians were shown nine clinical vignettes of patients hospitalized with acute respiratory failure and were asked to determine the likelihood of pneumonia, heart failure, or chronic obstructive pulmonary disease as the underlying cause. Clinicians were shown two vignettes without AI model input to establish baseline diagnostic accuracy and were then randomly assigned to see six vignettes with AI model input: three standard-model predictions and three systematically biased model predictions.

Overall, 457 clinicians were randomly assigned: 231 and 226 to AI model predictions without and with explanations, respectively. The researchers found that for the three diagnoses, clinicians' baseline diagnostic accuracy was 73.0 percent. Clinician accuracy increased over baseline by 2.9 and 4.4 percentage points when shown a standard AI model without and with explanations. Clinician accuracy was reduced by 11.3 percentage points with systematically biased AI model predictions compared with baseline; providing biased AI model predictions with explanations reduced accuracy by 9.1 percentage points, representing a nonsignificant improvement of 2.3 percentage points compared with the systematically biased model.

"Although the findings of the study suggest that clinicians may not be able to serve as a backstop against flawed AI, they can play an essential role in understanding AI's limitations," the authors write.

One author reported receiving royalties from a patent from Airstrip.

Abstract/Full Text (subscription or payment may be required)

Editorial (subscription or payment may be required)

Copyright © 2020 HealthDay. All rights reserved.