Articles: intensive-care-units.
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J Clin Monit Comput · Oct 2024
Early prediction of ventricular peritoneal shunt dependency in aneurysmal subarachnoid haemorrhage patients by recurrent neural network-based machine learning using routine intensive care unit data.
Aneurysmal subarachnoid haemorrhage (aSAH) can lead to complications such as acute hydrocephalic congestion. Treatment of this acute condition often includes establishing an external ventricular drainage (EVD). However, chronic hydrocephalus develops in some patients, who then require placement of a permanent ventriculoperitoneal (VP) shunt. ⋯ At that point, the accuracy of the prediction was 76% (CI: 75.98-83.09%), with a sensitivity of 85% (CI: 83-88%) and a specificity of 74% (CI: 71-78%). RNN-based machine learning has the potential to predict VP shunt dependency on Day 4 after ictus in aSAH patients using routine data collected in the ICU. The use of machine learning may allow early identification of patients with specific therapeutic needs and accelerate the execution of required procedures.
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Journal of critical care · Oct 2024
Impact of AKI on metabolic compensation for respiratory acidosis in ICU patients with AECOPD.
Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) can result in severe respiratory acidosis. Metabolic compensation is primarily achieved by renal retention of bicarbonate. The extent to which acute kidney injury (AKI) impairs the kidney's capacity to compensate for respiratory acidosis remains unclear. ⋯ AKI leads to poor outcomes and compromises metabolic compensation of respiratory acidosis in ICU patients with AECOPD. While buffering agents may aid compensation for severe AKI, their use should be approached with caution.
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Journal of critical care · Oct 2024
ReviewBehind the scenes: Key lessons learned from the RELIEVE-AKI clinical trial.
Continuous kidney replacement therapy (CKRT) is commonly used to manage critically ill patients with severe acute kidney injury. While recent trials focused on the correct dosing and timing of CKRT, our understanding regarding the optimum dose of net ultrafiltration is limited to retrospective data. The Restrictive versus Liberal Rate of Extracorporeal Volume Removal Evaluation in Acute Kidney Injury (RELIEVE-AKI) trial has been conducted to assess the feasibility of a prospective randomized trial in determining the optimum net ultrafiltration rate. ⋯ Several difficulties were encountered, starting with clinical issues related to conducting a trial on patients with rapidly changing hemodynamics, low patient recruitment rates, increased nursing workload, and the enormous volume of data generated by patients undergoing prolonged CKRT. Following several brainstorming sessions, several points were highlighted to be considered, including the need to streamline the intervention, add more flexibility in the trial protocols, ensure comprehensive a priori planning, particularly regarding nursing roles and their compensation, and enhance data management systems. These insights are critical for guiding future ICU-based dynamically titrated intervention trials, leading to more efficient trial management, improved data quality, and enhanced patient safety.