Feasibility of Endotracheal Extubation Evaluation Form in Predicting Successful Extubation in Neonatal Intensive Care Units: A Retrospective Study.

Given the limited availability of evidence-based methods for assessing the timing of extubation in intubated preterm infants, we aimed to standardize the extubation protocol in this single-center, retrospective study. To accomplish this, we established an extubation evaluation form to assess the suitability of extubation in preterm infants. The form comprises six indicators: improved clinical condition, spontaneous breath rate ≥ 30 breaths per minute, peak inspiratory pressure (PIP) ≤ 15 cmH2O, fraction of inspired oxygen (FiO2) ≤ 30%, blood pH ≥ 7.2, and mixed venous carbon dioxide tension (PvCO2) < 70 mmHg. Each positive answer is given one point, indicating a maximum of six points. We enrolled 41 intubated preterm infants (gestational age < 32 weeks, birth weight < 1500 g) who were receiving mechanical ventilation support for over 24 h. Among them, 35 were successfully extubated, and 6 were not. After completing the extubation evaluation form and adjusting for birth weight and postextubation device, we observed that the total score of the form was significantly associated with successful extubation; the higher the score, the greater the chance of successful extubation. Thus, we infer that the extubation evaluation form may provide a more objective standard for extubation assessment in preterm infants.

Toward Evaluating Critical Factors of Extubation Outcome with XCSR-Generated Rules.

Predicting the correct timing for extubation is pivotal for critically ill patients with mechanical ventilation support. Evidence suggests that extubation failure occurs in approximately 15-20% of patients, despite their passing of the extubation evaluation, necessitating reintubation. For critically ill patients, reintubation invariably increases mortality risk and medical costs. The numerous parameters that have been proposed for extubation decision-making, which constitute the key predictors of successful extubation, remains unclear. In this study, an extended classifier system capable of processing real-value inputs was proposed to select features of successful extubation. In total, 40 features linked to clinical information and variables acquired during spontaneous breathing trial (SBT) were used as the environmental inputs. According to the number of "don't care" rules in a population set, Probusage, the probability of the feature not being classified as above rules, can be calculated. A total of 228 subjects' results showed that Probusage was higher than 90% for minute ventilation at the 1st, 30th, 60th, and 90th minutes; respiratory rate at the 90th minute; and body weight, indicating that the variance in respiratory parameters during an SBT are critical predictors of successful extubation. The present XCSR model is useful to evaluate critical factors of extubation outcomes. Additionally, the current findings suggest that SBT duration should exceed 90 min, and that clinicians should consider the variance in respiratory variables during an SBT before making extubation decisions.

Is the asynchronous phase of thoracoabdominal movement a novel feature of successful extubation? A preliminary result.

Mechanical ventilation is necessary to maintain patients' life in intensive care units. However, too early or too late extubation may injure the muscles or lead to respiratory failure. Therefore, the spontaneous breathing trial (SBT) is applied for testing whether the patients can spontaneously breathe or not. However, previous evidence still reported 15%~20% of the rate of extubation fail. The monitor only considers the ventilation variables during SBT. Therefore, this study measures the asynchronization between thoracic and abdomen wall movement (TWM and AWM) by using instantaneous phase difference method (IPD) during SBT for 120 minutes. The respiratory inductive plethysmography were used for TWM and AWM measurement. The preliminary result recruited 31 signals for further analysis. The result showed that in successful extubation group can be classified into two groups, IPD increase group, and IPD decrease group; but in extubation fail group, the IPD value only increase. Therefore, the IPD decrease group can almost perfectly be discriminated with extubation fail group, especially after 70 minutes (Area under curve of operating characteristic curve was 1). These results showed IPD is an important key factor to find whether the patient is suitable for extubation or not. These finding suggest that the asynchronization between TWM and AWM should be considered as a predictor of extubation outcome. In future work, we plan to recruit 150 subjects to validate the result of this preliminary result. In addition, advanced machine learning method is considered to apply for building effective models to discriminate the IPD increase group and extubation fail group.Clinical Relevance- The finding of this study is that the patients whose average IPD of 95 to 100 minutes was smaller than average IPD of first 5 minutes of SBT could be 100% successful extubation. In addition, ability of discrimination of average IPD after 70 minutes presents AUC 1.

Novel mechanical ventilator weaning predictive model.

Mechanical ventilation (MV) is a common life support system in intensive care units. Accurate identification of patients who are capable of being extubated can shorten the MV duration and potentially reduce MV-related complications. Therefore, prediction of patients who can successfully be weaned from the mechanical ventilator is an important issue. The electronic medical record system (EMRs) has been applied and developed in respiratory therapy in recent years. It can increase the quality of critical care. However, there is no perfect index available that can be used to determine successful MV weaning. Our purpose was to establish a novel model that can predict successful weaning from MV. Patients' information was collected from the Kaohsiung Medical University Hospital respiratory therapy EMRs. In this retrospective study, we collected basic information, classic weaning index, and respiratory parameters during spontaneous breathing trials of patients eligible for extubation. According to the results of extubation, patients were divided into successful extubation and extubation failure groups. This retrospective cohort study included 169 patients. Statistical analysis revealed successful extubation predictors, including sex; height; oxygen saturation; Glasgow Coma Scale; Acute Physiology and Chronic Health Evaluation II score; pulmonary disease history; and the first, 30th, 60th, and 90th minute respiratory parameters. We built a predictive model based on these predictors. The area under the curve of this model was 0.889. We established a model for predicting the successful extubation. This model was novel to combine with serial weaning parameters and thus can help intensivists to make extubation decisions easily.