Effect of endotracheal tube size on airway resistance and dynamic lung compliance

Development and validation of a nomogram for tracheotomy decannulation in individuals in a persistent vegetative state: A multicentre study

BACKGROUND

Decannulation for people in a persistent vegetative state (PVS) is challenging and relevant predictors of successful decannulation have yet to be identified.

OBJECTIVE

This study aimed to explore the predictors of tracheostomy decannulation outcomes in individuals in PVS and to develop a nomogram.

METHOD

In 2022, 872 people with tracheostomy in PVS were retrospectively enrolled and their data was randomly divided into a training set and a validation set in a 7:3 ratio. Univariate and multivariate regression analyses were performed on the training set to explore the influencing factors for decannulation and nomogram development. Internal validation was performed using 5-fold cross-validation. External validation was performed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) on both the training and validation sets.

RESULT

Data from 610 to 262 individuals were used for the training and validation sets, respectively. The multivariate regression analysis found that duration of tracheostomy tube placement≥30 days (Odds Ratio [OR] 0.216, 95 % CI 0.151-0.310), pulmonary infection (OR 0.528, 95 %CI 0.366-0.761), hypoproteinemia (OR 0.669, 95 % CI 0.463-0.967), no passive standing training (OR 0.372, 95 % CI 0.253-0.547), abnormal swallowing reflex (OR 0.276, 95 % CI 0.116-0.656), mechanical ventilation (OR 0.658, 95 % CI 0.461-0.940), intensive care unit (ICU) duration>4 weeks (OR 0.517, 95 % CI 0.332-0.805), duration of endotracheal tube (OR 0.855, 95 % CI 0.803-0.907), older age (OR 0.981, 95 % CI 0.966-0.996) were risk factors for decannulation failure. Conversely, peroral feeding (OR 1.684, 95 % CI 1.178-2.406), passive standing training≥60 min (OR 1.687, 95 % CI 1.072-2.656), private caregiver (OR 1.944, 95 % CI 1.350-2.799) and ICU duration<2 weeks (OR 1.758, 95 % CI 1.173-2.634) were protective factors conducive to successful decannulation. The 5-fold cross-validation revealed a mean area under the curve of 0.744. The ROC curve C-indexes for the training and validation sets were 0.784 and 0.768, respectively, and the model exhibited good stability and accuracy. The DCA revealed a net benefit when the risk threshold was between 0 and 0.4.

CONCLUSION

The nomogram can help adjust the treatment and reduce decannulation failure.

REGISTRATION

Clinical registration is not mandatory for retrospective studies.

Predicting dog tracheal diameter and length: A tool for improved intubation

Objective

This study aims to develop formulas for estimating tracheal diameter and length in dogs using easily measurable anatomical parameters.

Materials and Methods

The samples consisted of 20 dogs of various breeds, comprising 10 males and 10 females, sourced from cadavers. The measured parameters included occipital tuberosity to tail base (OT), eye angle to ear tragus, nose to ear tragus, inner vertical diameters (IVD), and tracheal length (TL). The study conducted correlation and linear regression analyses, and subsequently, the formulated models underwent validation using 16 live dogs. The results were compared to radiographic measurements.

Results

Linear regression recommended formulas based on OT, resulting in IVD (mm) = 0.203 × OT - 3.724 (r2 = 0.608, p < 0.001) and TL (cm) = 0.346 × OT-3.773 (r2 = 0.837, p < 0.001). The predicted tracheal diameter and length from formulas were slightly smaller than radiographic measurements (IVD = 2.76 ± 1.85 mm, p < 0.0001 and TL = 2.07 ± 1.81 cm, p < 0.0001).

Conclusion

These formulas offer a practical way to estimate tracheal dimensions in live dogs, facilitating the selection of suitable endotracheal tube sizes and insertion depth. Further studies with larger sample sizes and consistent measurement methods can enhance the accuracy of these findings.

[Relationship Between Dynamic Compliance and Airway Resistance and Infection Indicators in Elderly Patients With Lung Infection After Radiotherapy for Esophageal Cancer]

Objective

To investigate the performance of using lung dynamic compliance (Cdyn) and airway resistance (RAW) levels to predict lung infection in elderly esophageal cancer patients who have undergone radiotherapy.

Methods

A total of 298 elderly esophageal cancer patients who received radiotherapy at Shanxi Fenyang Hospital between October 2017 and July 2022 were retrospectively enrolled and their clinical data were collected. The patients were divided into an infection group (124 cases) and a non-infection group (174 cases) according to their status of lung infection. Then, in the infection group, CURB-65 score was used to assess the severity of the patients' lung infection and the patients were further divided into subgroups accordingly, with 36 cases in the mild infection subgroup, 58 cases in the moderate infection subgroup, and 30 cases in the severe infection subgroup. The levels of Cdyn, RAW, and infection indicators, including serum procalcitonin (PCT), interleukin-6 (IL-6), and angiotensin Ⅱ (Ang Ⅱ), were measured in both groups of patients and the differences in the findings were compared between the infection and the non-infection groups and among patients with infection of varying degrees of severity. The correlation between Cdyn and RAW and the levels of PCT, IL-6, and Ang Ⅱ was analyzed. Receiver operating characteristic (ROC) curve was used to evaluate the performance of predicting infection with Cdyn and RAW.

Results

The Cdyn level of patients in the infection group was lower than that of patients in the non-infection group, while the RAW level of the infection group was higher than that of the non-infection group (P<0.05). Among the infection subgroup, the level of Cdyn of the mild infection subgroup was higher than those of the moderate and severe infection subgroups, while the levels of RAW, PCT, IL-6, and Ang Ⅱ of the mild infection subgroup were lower than those of the moderate severe subgroups. The level of Cdyn of the moderate infection subgroup was higher than that of the severe infection subgroup, while the RAW, PCT, IL-6, and Ang Ⅱ levels of the moderate infection subgroup were lower than those of the severe infection subgroup, with all difference being statistically significant (P<0.05). The Cdyn level of patients with lung infection was negatively correlated with PCT, IL-6, and Ang Ⅱ levels and the severity of infection (r=-0.501, -0.430, -0.367, and -0.484, respectively, P<0.05), while RAW was positively correlated with PCT, IL-6, and Ang Ⅱ levels and the severity of infection (r=0.483, 0.395, 0.374, and 0.423, respectively, P<0.05). The area under the curve (AUC) of Cdyn and RAW for predicting lung infection in elderly patients with esophageal cancer after radiotherapy were 0.898 (95% confidence interval [CI]: 0.857-0.930) and 0.823 (95% CI: 0.775-0.865), respectively, and the AUC of combined evaluation of Cdyn and RAW was 0.959 (95% CI: 0.930-0.979), which suggested that the predictive performance of combined evaluation was better than evaluation with Cdyn or RAW alone.

Conclusion

When elderly esophageal cancer patients develop lung infection after radiotherapy, their Cdyn level is decreased, while the levels of RAW, PCT, IL-6, and Ang Ⅱ are increased. In addition, the levels of Cdyn and RAW are correlated with the PCT, IL-6, and Ang Ⅱ levels. The combined use of Cdyn and RAW shows good performance for predicting lung infection in patients.