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Objective: This study aims to identify the factors influencing decannulation in patients with stroke who underwent tracheostomy during the early subacute phase. Methods: A retrospective analysis was conducted on 219 patients with stroke who underwent a tracheostomy at a tertiary hospital between January 2020 and December 2023. Among them, there were 155 males and 64 females. The age distribution ranged from 13 to 90 years old (average, 54.32 ± 14.96). There were 189 patients diagnosed with cerebral hemorrhage and 30 patients diagnosed with cerebral infarction. The patients were categorized into 2 groups: Those who achieved decannulation during the early subacute phase and those who did not. The decannulation group comprised 69 individuals, while the non-decannulation group comprised 150 individuals. Data collected included general patient demographics, stroke types, levels of consciousness, the presence of airway polyps, and outcomes of the modified Evan's blue dye test (MEBDT). Multivariate logistic regression analysis was employed to identify independent factors influencing early decannulation. The predictive value of these factors was further evaluated using the area under the curve (AUC) from the receiver operating characteristic (ROC) curve analysis. Results: Logistic regression analysis identified Glasgow Coma Scale scores, MEBDT results, and cough ability as independent factors influencing decannulation. ROC curve analysis demonstrated that a predictive model incorporating these 3 factors had a high predictive accuracy, with an AUC of 0.975 ( P < .001, 95% CI 0.958-0.993). The model's cut-off value of 0.19 yielded a sensitivity of 95.6% and a specificity of 87.3%. Conclusion: The Glasgow Coma Scale score, MEBDT results, and cough ability are independent determinants of early decannulation is patients with stroke. The combined assessment of these factors offers strong predictive accuracy for early decannulation., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The purpose of this study was to determine the correlation between change in respiratory muscle strength and change in cough ability in patients submitted to open-heart surgery. An observational cross-sectional study was conducted among 52 participants. Respiratory muscle strength was assessed by maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) using a respiratory pressure meter. Cough ability was evaluated by voluntary expiratory peak flow (PEF) using a digital spirometer. Evaluations were performed on the day of admission and discharge. Post-operative MIP, MEP, and PEF were significantly lower than those evaluated preoperatively (all p < 0.001). The difference of MIP and MEP was substantial positively correlated with the change in PEF in both absolute and predicted values (all p < 0.001) with the changes in MIP was highly relation. This study demonstrated that weakness of respiratory muscles, especially inspiratory muscle, was correlated to declining in cough ability in patients who had undergone open-heart surgery. [ABSTRACT FROM AUTHOR]

Cough peak flow (CPF) is a measurement for evaluating the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on both patients and their caregivers. Therefore, this study develops a novel cough strength evaluation method using cough sounds. This paper presents an exponential model to estimate CPF from the cough peak sound pressure level (CPSL). We investigated the relationship between cough sounds and cough flows and the effects of a measurement condition of cough sound, microphone type and participant’s height and gender on CPF estimation accuracy. The results confirmed that the proposed model estimated CPF with a high accuracy. The absolute error between CPFs and estimated CPFs were significantly lower when the microphone distance from the participant’s mouth was within 30 cm than when the distance exceeded 30 cm. Analysis of the model parameters showed that the estimation accuracy was not affected by participant’s height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF.

Cough peak flow (CPF) is a measurement for evaluating the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on both patients and their caregivers. Therefore, this study develops a novel cough strength evaluation method using cough sounds. This paper presents an exponential model to estimate CPF from the cough peak sound pressure level (CPSL). We investigated the relationship between cough sounds and cough flows and the effects of a measurement condition of cough sound, microphone type and participant’s height and gender on CPF estimation accuracy. The results confirmed that the proposed model estimated CPF with a high accuracy. The absolute error between CPFs and estimated CPFs were significantly lower when the microphone distance from the participant’s mouth was within 30 cm than when the distance exceeded 30 cm. Analysis of the model parameters showed that the estimation accuracy was not affected by participant’s height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF. [ABSTRACT FROM AUTHOR]