American Journal of Critical Care最新文献

Background: Therapeutic activity after stroke is a component of early recovery strategies. Interactive video games have been shown to be safe as an adjunct rehabilitation therapy in the medical intensive care setting, but patients with neurologic disease were often excluded from those protocols.

Objectives: To evaluate the feasibility and safety of individualized interactive video game therapy in critically ill neurologic patients.

Methods: Adults admitted to the neurosciences critical care unit during the observation period were eligible for inclusion. Wii sports games with the potential to target common neurologic deficits were categorized by our interprofessional team. We collected information regarding the number of sessions attempted, time for setup, indications of use, patient/staff experience, and predefined safety events.

Results: Twelve sessions were completed in 9 patients, mean (SD) age 48.6 (18.1) years, and sessions were led by nursing and therapy teams. Prescribed video game therapy sessions targeted the following recovery domains: coordination (70%), balance (50%), endurance (30%), cognition (30%), fine motor control (30%), neglect (20%), engagement in activity (10%), and vision (30%). On average, 4.7 minutes were spent for setup and 18.8 minutes were spent playing video games. No safety issues were identified. All patients indicated that they enjoyed participating in video game therapy.

Conclusions: In this pilot study, prescriptive interactive video game therapy in early rehabilitation was feasible and safe in the neurosciences critical care setting. Video game therapy may be a valuable complement to existing rehabilitation for critically ill neurologic patients and warrants validation in a larger patient sample.

Background: Enteral feeding intolerance, a common type of gastrointestinal dysfunction leading to underfeeding, is associated with increased mortality. Tracheal pepsin A, an indicator of microaspiration, was found in 39% of patients within 24 hours of enteral feeding. Tracheal pepsin A is a potential biomarker of enteral feeding intolerance.

Objective: To identify predictors of microaspiration (tracheal or oral pepsin A). It was hypothesized that variables predicting the presence of tracheal pepsin A might be similar to predictors of enteral feeding intolerance.

Methods: In this secondary analysis, machine learning models were fit for 283 adults receiving mechanical ventilation who had tracheal and oral aspirates obtained every 12 hours for up to 14 days. Pepsin A levels were measured using the proteolytic enzyme assay method, and values of 6.25 ng/mL or higher were classified as indicating microaspiration. Demographics, comorbidities, and variables associated with enteral feeding were analyzed with 3 machine learning models-random forest, XGBoost, and support vector machines with recursive feature elimination-using 5-fold cross-validation tuning.

Results: Random forest for tracheal pepsin A was the best-performing model (area under the curve, 0.844 [95% CI, 0.792-0.897]; accuracy, 87.55%). The top 20 predictors of tracheal pepsin A were identified.

Conclusion: Four predictor variables for tracheal pepsin A (microaspiration) are also reported predictors of enteral feeding intolerance, supporting the exploration of tracheal pepsin A as a potential biomarker of enteral feeding intolerance. Identification of predictor variables using machine learning models may facilitate treatment of patients at risk for enteral feeding intolerance.

Background: For patients with head and neck cancer who have undergone microvascular free flap surgery, securing a tracheostomy collar onto the neck using the traditional method (ie, with tracheostomy ties) is contraindicated because the ties may compress the newly vascularized tissue. However, no clear guidance exists for the use of other methods in these patients. Current techniques often use safety pins, which can cause injury to staff members.

Objective: To identify 1 or more methods of securing a tracheostomy collar that would maximize patient mobility, minimize the risk of staff injury, and be easy to use.

Methods: This pilot study had a descriptive design, with data collected from staff members caring for patients with head and neck cancer after microvascular free flap surgery. Three models of tracheostomy securement were evaluated, with each used for 10 postoperative patients with head and neck cancer (n = 30). Staff members rated each model on a 4-point Likert scale.

Results: The overall median score of all models was 3.5. Model 2 (collar secured to tubular bandages using binder rings) was rated significantly higher than model 3 (collar secured to tubular bandages using tracheostomy ties) overall (P = .04) as well as for staying in place when the patient was mobile (P = .04) and for ease of changing out parts (P = .01).

Conclusion: Several practical methods exist for securing a tracheostomy collar in patients with head and neck cancer who have undergone free flap surgery. These methods may be good alternatives to the use of safety pins.

Background: Hyperkalemia can be detected by point-of-care (POC) blood testing and by artificial intelligence- enabled electrocardiography (ECG). These 2 methods of detecting hyperkalemia have not been compared.

Objective: To determine the accuracy of POC and ECG potassium measurements for hyperkalemia detection in patients with critical illness.

Methods: This retrospective study involved intensive care patients in an academic medical center from October 2020 to September 2021. Patients who had 12-lead ECG, POC potassium measurement, and central laboratory potassium measurement within 1 hour were included. The POC potassium measurements were obtained from arterial blood gas analysis; ECG potassium measurements were calculated by a previously developed deep learning model. Hyperkalemia was defined as a central laboratory potassium measurement of 5.5 mEq/L or greater.

Results: Fifteen patients with hyperkalemia and 252 patients without hyperkalemia were included. The POC and ECG potassium measurements were available about 35 minutes earlier than central laboratory results. Correlation with central laboratory potassium measurement was better for POC testing than for ECG (mean absolute errors of 0.211 mEq/L and 0.684 mEq/L, respectively). For POC potassium measurement, area under the receiver operating characteristic curve (AUC) to detect hyperkalemia was 0.933, sensitivity was 73.3%, and specificity was 98.4%. For ECG potassium measurement, AUC was 0.884, sensitivity was 93.3%, and specificity was 63.5%.

Conclusions: The ECG potassium measurement, with its high sensitivity and coverage rate, may be used initially and followed by POC potassium measurement for rapid detection of life-threatening hyperkalemia.