BACKGROUND:Swallowing disorder is a common clinical symptom that can lead to a series of complications,including aspiration,aspiration pneumonia,and malnutrition.This study aimed to investigate risk factors of post-ex...BACKGROUND:Swallowing disorder is a common clinical symptom that can lead to a series of complications,including aspiration,aspiration pneumonia,and malnutrition.This study aimed to investigate risk factors of post-extubation dysphagia(PED)in intensive care unit(ICU)patients with endotracheal intubation,and to develop a risk-predictive model for PED,which could serve as an assessment tool for the prevention and control of PED.METHODS:Patients retrospectively selected from June to December 2021 in a tertiary hospital served as the derivation cohort.Patients recruited from the same hospital from March to June 2022served as the external validation cohort for the predictive model.We used a combination of variable screening and least absolute shrinkage and selection operator(LASSO)regression to select the most useful candidate predictors and checked the multicollinearity of independent variables using the variance inflation factor method.Multivariate logistic regression analysis was performed to calculate the odds ratio(OR;95%confidence interval[95%CI])and P-value for each variable to predict diagnosis.The screened risk factors were introduced into R software to build a nomogram model.The performance of the model,including discrimination ability,calibration,and clinical benefit,was evaluated by plotting the receiver operating characteristic(ROC),calibration,and decision curves.RESULTS:A total of 305 patients were included in this study.Among them,235 patients(53PED vs.182 non-PED)were enrolled in the derivation cohort,while 70 patients(17 PED vs.53 nonPED)were enrolled in the validation cohort.The independent predictors included age,pause of sedatives,level of consciousness,activities of daily living(ADL)score,nasogastric tube,sore throat,and voice disorder.These predictors were used to establish the predictive nomogram model.The model demonstrated good discriminative ability,and the area under the ROC curve(AUC)was 0.945(95%CI 0.904-0.970).Applying the predictive model to the validation cohort demonstrated good discrimination with an AUC of 0.907(95%CI 0.831-0.983)and good calibration.The decision-curve analysis of this nomogram showed a net benefit of the model.CONCLUSION:A predictive model that incorporates age,pause of sedatives,level of consciousness,ADL score,nasogastric tube,sore throat,and voice disorder may have the potential to predict PED in ICU patients.展开更多
BACKGROUND: The effect of blood eosinophils(EOSs) on mortality in acute respiratory distress syndrome(ARDS) patients and whether corticosteroids affect this effect are unclear.METHODS: The Medical Information Mart for...BACKGROUND: The effect of blood eosinophils(EOSs) on mortality in acute respiratory distress syndrome(ARDS) patients and whether corticosteroids affect this effect are unclear.METHODS: The Medical Information Mart for Intensive Care III database(version 1.4) was used to extract data. Patients with ARDS were selected for inclusion. Cox regression models using the backward stepwise method and propensity score matching(PSM) were used to assess the relationship between blood EOS counts and 28-day mortality. RESULTS: A total of 2,567 patients with ARDS were included, and the 28-day mortality rate was 24.19%. The crude 28-day mortality was significantly lower in patients with EOS counts ≥2%(18.60% [85/457] vs. 25.40% [536/2,110], P=0.002) than in those with EOS counts <2%. In the Cox regression model, the EOS counts ≥2% showed a significant association with the decreased 28-day mortality(hazard ratio [HR] 0.731;95% confidence interval [95% CI] 0.581–0.921, P=0.008). In the corticosteroid non-use subgroup, EOS counts ≥2% was significantly related to decreased 28-day mortality(HR 0.697, 95% CI 0.535–0.909, P=0.008), but the result was not significant in the corticosteroid non-use subgroup model(P=0.860). A total of 457 well-matched pairs were obtained by a 1:1 matching algorithm after PSM. The 28-day mortality remained significantly lower in the EOS counts ≥2% group(18.60% [85/457] vs. 26.70% [122/457], P=0.003).CONCLUSIONS Higher EOS counts are related to lower 28-day mortality in ARDS patients, and this relationship can be counteracted by using corticosteroids.展开更多
文摘BACKGROUND:Swallowing disorder is a common clinical symptom that can lead to a series of complications,including aspiration,aspiration pneumonia,and malnutrition.This study aimed to investigate risk factors of post-extubation dysphagia(PED)in intensive care unit(ICU)patients with endotracheal intubation,and to develop a risk-predictive model for PED,which could serve as an assessment tool for the prevention and control of PED.METHODS:Patients retrospectively selected from June to December 2021 in a tertiary hospital served as the derivation cohort.Patients recruited from the same hospital from March to June 2022served as the external validation cohort for the predictive model.We used a combination of variable screening and least absolute shrinkage and selection operator(LASSO)regression to select the most useful candidate predictors and checked the multicollinearity of independent variables using the variance inflation factor method.Multivariate logistic regression analysis was performed to calculate the odds ratio(OR;95%confidence interval[95%CI])and P-value for each variable to predict diagnosis.The screened risk factors were introduced into R software to build a nomogram model.The performance of the model,including discrimination ability,calibration,and clinical benefit,was evaluated by plotting the receiver operating characteristic(ROC),calibration,and decision curves.RESULTS:A total of 305 patients were included in this study.Among them,235 patients(53PED vs.182 non-PED)were enrolled in the derivation cohort,while 70 patients(17 PED vs.53 nonPED)were enrolled in the validation cohort.The independent predictors included age,pause of sedatives,level of consciousness,activities of daily living(ADL)score,nasogastric tube,sore throat,and voice disorder.These predictors were used to establish the predictive nomogram model.The model demonstrated good discriminative ability,and the area under the ROC curve(AUC)was 0.945(95%CI 0.904-0.970).Applying the predictive model to the validation cohort demonstrated good discrimination with an AUC of 0.907(95%CI 0.831-0.983)and good calibration.The decision-curve analysis of this nomogram showed a net benefit of the model.CONCLUSION:A predictive model that incorporates age,pause of sedatives,level of consciousness,ADL score,nasogastric tube,sore throat,and voice disorder may have the potential to predict PED in ICU patients.
文摘BACKGROUND: The effect of blood eosinophils(EOSs) on mortality in acute respiratory distress syndrome(ARDS) patients and whether corticosteroids affect this effect are unclear.METHODS: The Medical Information Mart for Intensive Care III database(version 1.4) was used to extract data. Patients with ARDS were selected for inclusion. Cox regression models using the backward stepwise method and propensity score matching(PSM) were used to assess the relationship between blood EOS counts and 28-day mortality. RESULTS: A total of 2,567 patients with ARDS were included, and the 28-day mortality rate was 24.19%. The crude 28-day mortality was significantly lower in patients with EOS counts ≥2%(18.60% [85/457] vs. 25.40% [536/2,110], P=0.002) than in those with EOS counts <2%. In the Cox regression model, the EOS counts ≥2% showed a significant association with the decreased 28-day mortality(hazard ratio [HR] 0.731;95% confidence interval [95% CI] 0.581–0.921, P=0.008). In the corticosteroid non-use subgroup, EOS counts ≥2% was significantly related to decreased 28-day mortality(HR 0.697, 95% CI 0.535–0.909, P=0.008), but the result was not significant in the corticosteroid non-use subgroup model(P=0.860). A total of 457 well-matched pairs were obtained by a 1:1 matching algorithm after PSM. The 28-day mortality remained significantly lower in the EOS counts ≥2% group(18.60% [85/457] vs. 26.70% [122/457], P=0.003).CONCLUSIONS Higher EOS counts are related to lower 28-day mortality in ARDS patients, and this relationship can be counteracted by using corticosteroids.
