Publications by authors named "A R Maw"

Lung ultrasound (LUS) is a simple, fast and non-invasive tool for pulmonary congestion assessment with higher accuracy for the detection of acute heart failure (HF) compared to clinical examination and chest radiography. The integrated assessment with other ultrasound and echocardiographic parameters can lead to a better systemic and pulmonary congestion characterization. Additionally, the combination of echocardiographic and pulmonary features can identify patients at higher risk for adverse outcomes, potentially facilitating both acute and chronic HF management and prognostic stratification.

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With the widespread implementation of electronic health records (EHRs), there has been significant progress in developing learning health systems (LHSs) aimed at improving health and health care delivery through rapid and continuous knowledge generation and translation. To support LHSs in achieving these goals, implementation science (IS) and its frameworks are increasingly being leveraged to ensure that LHSs are feasible, rapid, iterative, reliable, reproducible, equitable, and sustainable. However, 6 key challenges limit the application of IS to EHR-driven LHSs: barriers to team science, limited IS experience, data and technology limitations, time and resource constraints, the appropriateness of certain IS approaches, and equity considerations.

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Article Synopsis
  • Point-of-care lung ultrasound (LUS) is more accurate than chest X-rays for diagnosing issues causing difficulty breathing and is recommended in clinical guidelines.
  • A study analyzing 820 LUS cases at a major hospital found that 90% of LUS procedures were clinically relevant, with nearly 40% leading to changes in patient management.
  • The research highlights the significant role of LUS in real-world clinical settings and the need for better documentation and education in its application among medical professionals.
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Reliable and accurate estimates of body composition are essential when studying the various health correlates of disease. Bioelectrical impedance analysis (BIA) is an affordable and feasible body composition assessment technique for clinical and field settings. Total body water (TBW) and hence fat-free mass is estimated by predictive regression algorithms using anthropometric measurements plus the resistance index.

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Background: Stoma reversal is associated with a relatively high risk of surgical site infection (SSI), occurring in up to 40% of cases. This may be explained by the presence of microorganisms around the stoma site, and possible contamination with the intestinal contents during the open-end manipulation of the bowel, making the stoma closure site a clean-contaminated wound. The conventional technique for stoma reversal is linear skin closure (LSC).

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