Journal of clinical medicine
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Developing a decision support system based on advances in machine learning is one area for strategic innovation in healthcare. Predicting a patient's progression to septic shock is an active field of translational research. The goal of this study was to develop a working model of a clinical decision support system for predicting septic shock in an acute care setting for up to 6 h from the time of admission in an integrated healthcare setting. ⋯ This study corroborated that machine learning models can be developed to predict septic shock using clinical and administrative data. However, the use of clinical information to define septic shock outperformed models developed based on only administrative data. Intelligent decision support tools can be developed and integrated into the EHR and improve clinical outcomes and facilitate the optimization of resources in real-time.
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There are no reliable, non-invasive methods to accurately measure cardiac output (CO) in septic patients. MostCare (Vytech Health™, Vygon, Padova, Italy), is a beat-to-beat, self calibrated method for CO measurement based on continuous analysis of reflected arterial pressure waveforms. We enrolled 40 patients that were suffering from septic shock and requiring norepinephrine infusion to target blood pressure in order to to evaluate the level of agreement between a calibrated transpulmonary thermodilution device (PiCCO System, Pulsion Medical Systems, Feldkirchen, Germany) and the MostCare system in detecting and tracking changes in CO measurements related to norepinephrine reduction in septic shock patients,. ⋯ The polar plot diagram seems to confirm the trending ability of MostCare system versus the reference method. In septic patients, when the arterial waveform is accurate, MostCare and PiCCO transpulmonary thermodilution exhibit good agreement even after the reduction of norepinephrine and changes in vascular tone or volume expansion. MostCare could be a rapid to set, reliable, and useful tool to monitor hemodynamic variations in septic patients in emergency contexts where thermodilution methods or other advanced systems are not easily available.
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Given the rising rate of opioid-related adverse drug events during postsurgical pain management, a nonpharmacologic therapy that could decrease analgesic medication requirements would be of immense value. We designed a prospective, placebo-and-randomized controlled trial to assess the clinical effect of transcutaneous acupoint electrical stimulation (TEAS) on the postoperative patient-controlled analgesia (PCA) requirement for morphine, as well as side effects and recovery profile after inguinal hernia repair. Seventy-one subjects undergoing inguinal hernia repair with a standardized anesthetic technique were randomly assigned to one of three analgesic treatment regimens: PCA + TEAS (n = 24); PCA + sham-TEAS (no electrical stimulation) (n = 24), and PCA only (n = 23). ⋯ TEAS treatment resulted in a twofold decrease in the analgesic requirement and decreased pain level reported by the patients. In addition, a significant reduction of cortisol level was reported in the TEAS group at 24 h postoperatively compared to the sham and control groups. We conclude that TEAS is a safe and effective option for reducing analgesic consumption and postoperative pain following inguinal hernia repair.
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Predictors and Prognostic Implications of Cardiac Arrhythmias in Patients Hospitalized for COVID-19.
Cardiac manifestation of COVID-19 has been reported during the COVID pandemic. The role of cardiac arrhythmias in COVID-19 is insufficiently understood. This study assesses the incidence of cardiac arrhythmias and their prognostic implications in hospitalized COVID-19-patients. ⋯ Arrhythmia was the most common cardiac event in association with hospitalization for COVID-19. Older age and cardiovascular disease predisposed for arrhythmia during hospitalization. Whereas in-hospital mortality is affected by underlying cardiovascular conditions, arrhythmia during hospitalization for COVID-19 is independently associated with prolonged hospitalization and mechanical ventilation. Thus, incident arrhythmia may indicate a patient subgroup at risk for a severe course of disease.