Search

Introduction Critically ill patients experience various stressful symptoms of discomfort, including dyspnea, pain, and sleep disruption. Notably, ventilated patients have difficulty self-reporting discomfort symptoms. Nurses need to assess discomfort symptoms to alleviate them, but limited research exists on discomfort symptom assessment and management in critically ill patients. Objective To identify the practices, attitudes, and barriers among nurses related to the assessment of discomfort symptoms in mechanically ventilated patients. Methods Using a cross-sectional, descriptive study design, a web-based survey was conducted between May and June 2022 with critical care nurses sampled through Japanese academic societies and social networking services. The survey contained questions relative to the above-stated objective. Descriptive statistical analysis was performed without sample size calculation because of the descriptive and exploratory nature of this study. Results There were 267 respondents to the questionnaire. The discomfort symptoms that nurses perceived as important to assess were pain (median 100 [interquartile range, IQR 90–100]), insomnia (99 [80–100]), and dyspnea (96.5 [75–100]). Most participants (89.8%) routinely assessed pain in mechanically ventilated patients using a scale; however, other discomfort symptoms were assessed by less than 40% (dyspnea [28.4%], fatigue [8.1%], thirst [13.1%], insomnia [37.3%], and anxiety [13.6%]). Two major barriers to assessing discomfort symptoms were lack of assessment culture within the intensive care unit and lack of knowledge of the relevant evaluation scales. Conclusions Nurses were aware of the importance of using scales to assess the discomfort symptoms experienced by mechanically ventilated patients. However, except for pain, most nurses did not routinely use scales to assess discomfort symptoms. Barriers to routine discomfort symptom assessment included the lack of an assessment culture and the lack of knowledge of the assessment scales. Clinicians should be educated regarding the existence of validated rating scales and develop additional rating scales utilizable for minor discomforts in mechanically ventilated patients.

Abstract Providing standardized, high-quality rehabilitation for critically ill patients is a crucial issue. In 2017, the Japanese Society of Intensive Care Medicine (JSICM) promulgated the “Evidence-Based Expert Consensus for Early Rehabilitation in the Intensive Care Unit” to advocate for the early initiation of rehabilitations in Japanese intensive care settings. Building upon this seminal work, JSICM has recently conducted a rigorous systematic review utilizing the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. This endeavor resulted in the formulation of Clinical Practice Guidelines (CPGs), designed to elucidate best practices in early ICU rehabilitation. The primary objective of this guideline is to augment clinical understanding and thereby facilitate evidence-based decision-making, ultimately contributing to the enhancement of patient outcomes in critical care settings. No previous CPGs in the world has focused specifically on rehabilitation of critically ill patients, using the GRADE approach. Multidisciplinary collaboration is extremely important in rehabilitation. Thus, the CPGs were developed by 73 members of a Guideline Development Group consisting of a working group, a systematic review group, and an academic guideline promotion group, with the Committee for the Clinical Practice Guidelines of Early Mobilization and Rehabilitation in Intensive Care of the JSICM at its core. Many members contributed to the development of the guideline, including physicians and healthcare professionals with multiple and diverse specialties, as well as a person who had been patients in ICU. Based on discussions among the group members, eight important clinical areas of focus for this CPG were identified. Fourteen important clinical questions (CQs) were then developed for each area. The public was invited to comment twice, and the answers to the CQs were presented in the form of 10 GRADE recommendations and commentary on the four background questions. In addition, information for each CQ has been created as a visual clinical flow to ensure that the positioning of each CQ can be easily understood. We hope that the CPGs will be a useful tool in the rehabilitation of critically ill patients for multiple professions. Graphical Abstract

OBJECTIVES:. To evaluate the contribution of a preextubation chest X-ray (CXR) to identify the risk of extubation failure in mechanically ventilated patients. DESIGN:. Retrospective cohort study. SETTINGS:. ICUs in a tertiary center (the Medical Information Mart for Intensive Care IV database). PATIENTS:. Patients greater than or equal to 18 years old who were mechanically ventilated and extubated after a spontaneous breathing trial. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. Among 1,066 mechanically ventilated patients, 132 patients (12%) experienced extubation failure, defined as reintubation or death within 48 hours of extubation. To predict extubation failure, we developed the following models based on deep learning (EfficientNet) and machine learning (LightGBM) with the training data: 1) model using only the rapid-shallow breathing index (RSBI), 2) model using RSBI and CXR, 3) model using all candidate clinical predictors (i.e., patient demographics, vital signs, laboratory values, and ventilator settings) other than CXR, and 4) model using all candidate clinical predictors with CXR. We compared the predictive abilities between models with the test data to investigate the predictive contribution of CXR. The predictive ability of the model using CXR as well as RSBI was not significantly higher than that of the model using only RSBI (c-statistics, 0.56 vs 0.56; p = 0.95). The predictive ability of the model using clinical predictors with CXR was not significantly higher than that of the model using all clinical predictors other than CXR (c-statistics, 0.71 vs 0.70; p = 0.12). Based on SHapley Additive exPlanations values to interpret the model using all clinical predictors with CXR, CXR was less likely to contribute to the predictive ability than other predictors (e.g., duration of mechanical ventilation, inability to follow commands, and heart rate). CONCLUSIONS:. Adding CXR to a set of other clinical predictors in our prediction model did not significantly improve the predictive ability of extubation failure in mechanically ventilated patients.

Aim Accurately calculating the Sequential Organ Failure Assessment (SOFA) score is essential for medical resource allocation and decision‐making. This study surveyed Japanese intensive care units regarding their assessment of the Glasgow Coma Scale (GCS) and PaO2/FIO2 ratio, components of the SOFA score. Methods A cross‐sectional, web‐based survey was conducted among healthcare workers. The survey consisted of questions about the intensive care units where they work and questions for respondents. It was distributed to healthcare workers by e‐mail through the Japanese Society of Intensive Care Medicine mailing list and social networking service. Results Among 414 responses, we obtained 211 valid responses and 175 survey results from unique intensive care units. When assessing GCS in patients under the influence of sedatives, 45.1% (95% confidence interval, 37.6–52.8) of intensive care units assessed GCS assuming that the sedatives had no influence. For the PaO2/FIO2 ratio in the SOFA score, calculation based on the Japanese Intensive Care Patient Database definition document and mechanical ventilator settings were the most common methods in patients with oxygen masks and on extracorporeal membrane oxygenation, respectively. Approximately 60% of respondents indicated that it was difficult to assess GCS assuming that sedatives had no influence. Conclusion In patients under the influence of sedatives, approximately half of the intensive care units assessed assumed GCS. There was variation in the methods used to assess the PaO2/FIO2 ratio. Standardized assessment methods for GCS and the PaO2/FIO2 ratio are needed to obtain valid SOFA score.

This study aimed to estimate the number of nurses who independently care for patients with severe respiratory failure receiving mechanical ventilation (MV) or veno-venous extracorporeal membrane oxygenation (VV-ECMO). Additionally, the study analyzed the actual role of nurses in the treatment of patients with MV and VV-ECMO. We performed a cross-sectional study using postal questionnaire surveys. The study included 725 Japanese intensive care units (ICUs). Data were analyzed using descriptive statistics. Among the 725 ICUs, we obtained 302 responses (41.7%) and analyzed 282 responses. The median number of nurses per bed was 3.25. The median proportion of nurses who independently cared for patients with MV was 60% (IQR: 42.3–77.3). The median proportion of nurses who independently cared for patients with VV-ECMO was 46.9 (35.7–63.3%) in the ICUs that had experience with VV-ECMO use. With regard to task-sharing, 33.8% of ICUs and nurses did not facilitate weaning from MV. Nurses always titrated sedative dosage in 44.5% of ICUs. Nurse staffing might be inadequate in all ICUs, especially for the management of patients with severe respiratory failure. The proportion of competent nurses to care for severe respiratory failure in ICUs should be considered when determining the workforce of nurses.

Determining the number of nurses required for patients with coronavirus disease receiving mechanical ventilation and/or veno-veno extracorporeal membrane oxygenation is important to provide quality care. Therefore, we conducted this cross-sectional survey of 725 intensive care units in Japan. Data from 152 units with experience of managing patients with coronavirus disease who required tracheal intubation were analyzed. The median number of nurses required for a patient receiving mechanical ventilation or veno-veno extracorporeal membrane oxygenation was two. This number was more than that according to the Japanese standard determined by government. We conclude that more nursing staff is required for caring for patients critically ill with coronavirus disease in intensive care units. [ABSTRACT FROM AUTHOR]