Abnormalities of Aspiration and Swallowing Function in Survivors of Acute Respiratory Failure.

The mechanisms responsible for aspiration are relatively unknown in patients recovering from acute respiratory failure (ARF) who required mechanical ventilation. Though many conditions may contribute to swallowing dysfunction, alterations in laryngeal structure and swallowing function likely play a role in the development of aspiration. At four university-based tertiary medical centers, we conducted a prospective cohort study of ARF patients who required intensive care and mechanical ventilation for at least 48 h. Within 72 h after extubation, a Fiberoptic Flexible Endoscopic Evaluation of Swallowing (FEES) examination was performed. Univariate and multivariable analyses examined the relationship between laryngeal structure and swallowing function abnormalities. Aspiration was the primary outcome, defined as a Penetration- Aspiration Scale (PAS) score of 6 or greater. Two other salient signs of dysphagia-spillage and residue-were secondary outcomes. A total of 213 patients were included in the final analysis. Aspiration was detected in 70 patients (33%) on at least one bolus. The most commonly aspirated consistency was thin liquids (27%). In univariate analyses, several abnormalities in laryngeal anatomy and structural movement were significantly associated with aspiration, spillage, and residue. In a multivariable analysis, the only variables that remained significant with aspiration were pharyngeal weakness (Odds ratio = 2.57, 95%CI = 1.16-5.84, p = 0.019) and upper airway edema (Odds ratio = 3.24, 95%CI = 1.44-7.66, p = 0.004). These results demonstrated that dysphagia in ARF survivors is multifactorial and characterized by both anatomic and physiologic abnormalities. These findings may have important implications for the development of novel interventions to treat dysphagia in ARF survivors.Clinical Trials Registration ClinicalTrials.gov Identifier: NCT02363686, Aspiration in Acute Respiratory Failure Survivors.

The Association Between Ventilator Dyssynchrony, Delivered Tidal Volume, and Sedation Using a Novel Automated Ventilator Dyssynchrony Detection Algorithm.

OBJECTIVE: Ventilator dyssynchrony is potentially harmful to patients with or at risk for the acute respiratory distress syndrome. Automated detection of ventilator dyssynchrony from ventilator waveforms has been difficult. It is unclear if certain types of ventilator dyssynchrony deliver large tidal volumes and whether levels of sedation alter the frequency of ventilator dyssynchrony. DESIGN: A prospective observational study. SETTING: A university medical ICU. PATIENTS: Patients with or at risk for acute respiratory distress syndrome. INTERVENTIONS: Continuous pressure-time, flow-time, and volume-time data were directly obtained from the ventilator. The level of sedation and the use of neuromuscular blockade was extracted from the medical record. Machine learning algorithms that incorporate clinical insight were developed and trained to detect four previously described and clinically relevant forms of ventilator dyssynchrony. The association between normalized tidal volume and ventilator dyssynchrony and the association between sedation and the frequency of ventilator dyssynchrony were determined. MEASUREMENTS AND MAIN RESULTS: A total of 4.26 million breaths were recorded from 62 ventilated patients. Our algorithm detected three types of ventilator dyssynchrony with an area under the receiver operator curve of greater than 0.89. Ventilator dyssynchrony occurred in 34.4% (95% CI, 34.41-34.49%) of breaths. When compared with synchronous breaths, double-triggered and flow-limited breaths were more likely to deliver tidal volumes greater than 10 mL/kg (40% and 11% compared with 0.2%; p < 0.001 for both comparisons). Deep sedation reduced but did not eliminate the frequency of all ventilator dyssynchrony breaths (p < 0.05). Ventilator dyssynchrony was eliminated with neuromuscular blockade (p < 0.001). CONCLUSION: We developed a computerized algorithm that accurately detects three types of ventilator dyssynchrony. Double-triggered and flow-limited breaths are associated with the frequent delivery of tidal volumes of greater than 10 mL/kg. Although ventilator dyssynchrony is reduced by deep sedation, potentially deleterious tidal volumes may still be delivered. However, neuromuscular blockade effectively eliminates ventilator dyssynchrony.

Development of an Accurate Bedside Swallowing Evaluation Decision Tree Algorithm for Detecting Aspiration in Acute Respiratory Failure Survivors.

BACKGROUND: The bedside swallowing evaluation (BSE) is an assessment of swallowing function and airway safety during swallowing. After extubation, the BSE often is used to identify the risk of aspiration in acute respiratory failure (ARF) survivors. RESEARCH QUESTION: We conducted a multicenter prospective study of ARF survivors to determine the accuracy of the BSE and to develop a decision tree algorithm to identify aspiration risk. STUDY DESIGN AND METHODS: Patients extubated after ≥ 48 hours of mechanical ventilation were eligible. Study procedures included the BSE followed by a gold standard evaluation, the flexible endoscopic evaluation of swallowing (FEES). RESULTS: Overall, 213 patients were included in the final analysis. Median time from extubation to BSE was 25 hours (interquartile range, 21-45 hours). The FEES was completed 1 hour after the BSE (interquartile range, 0.5-2 hours). A total of 33% (70/213; 95% CI, 26.6%-39.2%) of patients aspirated on at least one FEES bolus consistency test. Thin liquids were the most commonly aspirated consistency: 27% (54/197; 95% CI, 21%-34%). The BSE detected any aspiration with an accuracy of 52% (95% CI, 45%-58%), a sensitivity of 83% (95% CI, 74%-92%), and negative predictive value (NPV) of 81% (95% CI, 72%-91%). Using recursive partitioning analyses, a five-variable BSE-based decision tree algorithm was developed that improved the detection of aspiration with an accuracy of 81% (95% CI, 75%-87%), sensitivity of 95% (95% CI, 90%-98%), and NPV of 97% (95% CI, 95%-99%). INTERPRETATION: The BSE demonstrates variable accuracy to identify patients at high risk for aspiration. Our decision tree algorithm may enhance the BSE and may be used to identify patients at high risk for aspiration, yet requires further validation. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT02363686; URL: www.clinicaltrials.gov.