IMPORTANCEIntraoperative hypotension is associated with increased morbidity and mortality. A machine learning-derived early warning system to predict hypotension shortly before it occurs has been developed and validated.OBJECTIVE To test whether the clinical application of the early warning system in combination with a hemodynamic diagnostic guidance and treatment protocol reduces intraoperative hypotension.DESIGN, SETTING, AND PARTICIPANTS Preliminary unblinded randomized clinical trial performed in a tertiary center in Amsterdam, the Netherlands, among adult patients scheduled for elective noncardiac surgery under general anesthesia and an indication for continuous invasive blood pressure monitoring, who were enrolled between May 2018 and March 2019. Hypotension was defined as a mean arterial pressure (MAP) below 65 mm Hg for at least 1 minute.INTERVENTIONS Patients were randomly assigned to receive either the early warning system (n = 34) or standard care (n = 34), with a goal MAP of at least 65 mm Hg in both groups. MAIN OUTCOMES AND MEASURESThe primary outcome was time-weighted average of hypotension during surgery, with a unit of measure of millimeters of mercury. This was calculated as the depth of hypotension below a MAP of 65 mm Hg (in millimeters of mercury) × time spent below a MAP of 65 mm Hg (in minutes) divided by total duration of operation (in minutes). RESULTS Among 68 randomized patients, 60 (88%) completed the trial (median age, 64 [interquartile range {IQR}, 57-70] years; 26 [43%] women). The median length of surgery was 256 minutes (IQR,. The median time-weighted average of hypotension was 0.10 mm Hg (IQR, 0.01-0.43 mm Hg) in the intervention group vs 0.44 mm Hg (IQR, 0.23-0.72 mm Hg) in the control group, for a median difference of 0.38 mm Hg (95% CI, 0.14-0.43 mm Hg; P = .001). The median time of hypotension per patient was 8.0 minutes (IQR, 1.33-26.00 minutes) in the intervention group vs 32.7 minutes (IQR, 11.5-59.7 minutes) in the control group, for a median difference of 16.7 minutes (95% CI, 7.7-31.0 minutes; P < .001). In the intervention group, 0 serious adverse events resulting in death occurred vs 2 (7%) in the control group. CONCLUSIONS AND RELEVANCEIn this single-center preliminary study of patients undergoing elective noncardiac surgery, the use of a machine learning-derived early warning system compared with standard care resulted in less intraoperative hypotension. Further research with larger study populations in diverse settings is needed to understand the effect on additional patient outcomes and to fully assess safety and generalizability.
Objective: To develop evidence-based clinical practice recommendations regarding transfusion practices in nonbleeding, critically ill adults. Design: A task force involving 13 international experts and three methodologists used the GRADE approach for guideline development. Methods: The task force identified four main topics: red blood cell transfusion thresholds, red blood cell transfusion avoidance strategies, platelet transfusion, and plasma transfusion. The panel developed structured guideline questions using population, intervention, comparison, and outcomes (PICO) format. Results: The task force generated 16 clinical practice recommendations (3 strong recommendations, 13 conditional recommendations), and identified five PICOs with insufficient evidence to make any recommendation. Conclusions: This clinical practice guideline provides evidence-based recommendations and identifies areas where further research is needed regarding transfusion practices and transfusion avoidance in non-bleeding, critically ill adults.
The bedside hemodynamic assessment of the critically ill remains challenging since blood volume, arterial–venous interaction and compliance are not measured directly. Mean circulatory filling pressure (Pmcf) is the blood pressure throughout the vascular system at zero flow. Animal studies have shown Pmcf provides information on vascular compliance, volume responsiveness and enables the calculation of stressed volume. It is now possible to measure Pmcf at the bedside. We performed a systematic review of the current Pmcf measurement techniques and compared their clinical applicability, precision, accuracy and limitations. A comprehensive search strategy was performed in PubMed, Embase and the Cochrane databases. Studies measuring Pmcf in heart-beating patients at the bedside were included. Data were extracted from the articles into predefined forms. Quality assessment was based on the Newcastle–Ottawa Scale for cohort studies. A total of 17 prospective cohort studies were included. Three techniques were described: Pmcf hold, based on inspiratory hold-derived venous return curves, Pmcf arm, based on arterial and venous pressure equilibration in the arm as a model for the entire circulation, and Pmcf analogue, based on a Guytonian mathematical model of the circulation. The included studies show Pmcf to accurately follow intravascular fluid administration and vascular compliance following drug-induced hemodynamic changes. Bedside Pmcf measures allow for more direct assessment of circulating blood volume, venous return and compliance. However, studies are needed to determine normative Pmcf values and their expected changes to therapies if they are to be used to guide clinical practice.Electronic supplementary materialThe online version of this article (10.1186/s13613-018-0418-2) contains supplementary material, which is available to authorized users.
Purpose: To develop evidence-based clinical practice recommendations regarding transfusion practices and transfusion in bleeding critically ill adults. Methods:A taskforce involving 15 international experts and 2 methodologists used the GRADE approach to guideline development. The taskforce addressed three main topics: transfusion support in massively and non-massively bleeding critically ill patients (transfusion ratios, blood products, and point of care testing) and the use of tranexamic acid. The panel developed and answered structured guideline questions using population, intervention, comparison, and outcomes (PICO) format. Results:The taskforce generated 26 clinical practice recommendations (2 strong recommendations, 13 conditional recommendations, 11 no recommendation), and identified 10 PICOs with insufficient evidence to make a recommendation. Conclusions:This clinical practice guideline provides evidence-based recommendations for the management of massively and non-massively bleeding critically ill adult patients and identifies areas where further research is needed.
IntroductionAbnormal coagulation tests have been observed in patients with primary hyperparathyroidism (HPT) suggesting a prothrombotic effect of parathyroid hormone (PTH). Vitamin D deficiency (VIDD) is the most frequent cause of secondary HPT. Aim of our study was to investigate the influence of HPT secondary to moderate-to-severe VIDD and vitamin D replacement on the coagulation and fibrinolysis system.Subjects and methodsProspective cohort study of patients with vitamin D <25 nmol/L with and without HPT, and a control group of patients on vitamin D suppletion. At baseline and after 2 months of vitamin D suppletion (900,000 IU in 2 months), endocrine and coagulation markers were measured.Results59 patients with VIDD of which 34 had secondary HPT and 36 controls were included. After 2 months of suppletion, vitamin D increased by 399% (VIDD with HPT), 442% (all patients with VIDD) and 6% (controls). PTH decreased by 34% (VIDD with HPT, P < 0.01 for decrease), 32% (all VIDD, P < 0.01) and increased by 8% in the controls (P-values: <0.01 for relative changes between VIDD with HPT or all VIDD patients vs controls). Relative changes in PT, aPTT, fibrinogen, Von Willebrand factor, factors VII, VIII and X, thrombin generation, TAFI, clot-lysis time and d-dimer were not different between patients with VIDD with HPT or all VIDD vs controls.DiscussionSecondary HPT due to VIDD does not have a prothrombotic effect. In contrast with previous reports, PTH does not seem to influence coagulation or fibrinolysis, which is relevant because of the high prevalence of VIDD.
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