Polskie Archiwum Medycyny Wewnętrznej
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Pol. Arch. Med. Wewn. · May 2024
Comparative StudyUnattended automatic blood pressure measurements versus conventional office readings in predicting hypertension-mediated organ damage.
Hypertension is a leading cardiovascular risk factor. Accurate blood pressure (BP) measurement is pivotal in hypertension diagnosis and management. Conventional office blood pressure measurements (OBPMs) are error‑prone, exacerbated by the white‑coat effect. Unattended automated office blood pressure measurement (UAOBPM) is emerging as an alternative, mitigating the white‑coat effect. However, its ability to predict hypertension‑mediated organ damage (HMOD) remains disputable. ⋯ The UAOBPM did not prove superior to OBPM in predicting HMOD. Further research is warranted to determine the role of UAOBPM in clinical practice.
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Pol. Arch. Med. Wewn. · May 2024
ReviewDietary salt intake in chronic kidney disease. Recent studies and their practical implications.
Epidemiologic studies in the general population show that the level of dietary salt intake is associated with increases in blood pressure (BP), cardiovascular events, and mortality. According to trial data, reducing salt intake lowers the incidence of these 3 outcomes. ⋯ However, these trials have typically used resource‑intensive approaches to dietary salt reduction that are not suitable for routine clinical care, and salt intake typically remains high in people with CKD. The OxSalt care bundle is a low‑cost intervention that was demonstrated in the OxCKD1 trial to help people with CKD lower their salt intake, and could be applied in routine clinical practice.
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Pol. Arch. Med. Wewn. · May 2024
Comparative StudyA comparison of interpretable XGBoost and artificial neural network model for the prediction of severe acute pancreatitis.
Acute pancreatitis (AP) that progresses to persistent organ failure is referred to as severe acute pancreatitis (SAP). It is a condition associated with a relatively high mortality. A prediction model that would facilitate early recognition of patients at risk for SAP is crucial for improvement of patient prognosis. ⋯ An interpretable XGBoost model showed better discriminatory efficiency for predicting SAP than the ANN model, and could be used in clinical practice to identify patients at risk for SAP.