scholarly journals Semiquantitative Cough Strength Score for Predicting Reintubation After Planned Extubation

2015 ◽  
Vol 24 (6) ◽  
pp. e86-e90 ◽  
Author(s):  
Jun Duan ◽  
Lintong Zhou ◽  
Meiling Xiao ◽  
Jinhua Liu ◽  
Xiangmei Yang
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Spontaneous Breathing ◽  
Operating Characteristic ◽  
Peak Flow ◽  
Characteristic Curve ◽  
Spontaneous Breathing Trial ◽  
Extubation Outcome ◽  
Cough Strength ◽  
Operating Characteristic Curve

Background Semiquantitative cough strength score (SCSS, graded 0–5) and cough peak flow (CPF) have been used to predict extubation outcome in patients in whom extubation is planned; however, the correlation of the 2 assessments is unclear. Methods In the intensive care unit of a university-affiliated hospital, 186 patients who were ready for extubation after a successful spontaneous breathing trial were enrolled in the study. Both SCSS and CPF were assessed before extubation. Reintubation was recorded 72 hours after extubation. Results Reintubation rate was 15.1% within 72 hours after planned extubation. Patients in whom extubation was successful had higher SCSSs than did reintubated patients (mean [SD], 3.2 [1.6] vs 2.2 [1.6], P = .002) and CPF (74.3 [40.0] vs 51.7 [29.4] L/min, P = .005). The SCSS showed a positive correlation with CPF (r = 0.69, P < .001). Mean CPFs were 38.36 L/min, 39.51 L/min, 44.67 L/min, 57.54 L/min, 78.96 L/min, and 113.69 L/min in patients with SCSSs of 0, 1, 2, 3, 4, and 5, respectively. The discriminatory power for reintubation, evidenced by area under the receiver operating characteristic curve, was similar: 0.677 for SCSS and 0.678 for CPF (P = .97). As SCSS increased (from 0 to 1 to 2 to 3 to 4 to 5), the reintubation rate decreased (from 29.4% to 25.0% to 19.4% to 16.1% to 13.2% to 4.1%). Conclusions SCSS was convenient to measure at the bedside. It was positively correlated with CPF and had the same accuracy for predicting reintubation after planned extubation.

scholarly journals Artificial neural network approach for acute poisoning mortality prediction in emergency departments

2021 ◽  
Vol 8 (3) ◽  
pp. 229-236
Author(s):  
Seon Yeong Park ◽  
Kisung Kim ◽  
Seon Hee Woo ◽  
Jung Taek Park ◽  
Sikyoung Jeong ◽  
...  
Keyword(s):  
Neural Network ◽  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Acute Poisoning ◽  
Mortality Prediction ◽  
Ann Model ◽  
Operating Characteristic Curve

Objective The number of deaths due to acute poisoning (AP) is on the increase. It is crucial to predict AP patient mortality to identify those requiring intensive care for providing appropriate patient care as well as preserving medical resources. The aim of this study is to predict the risk of in-hospital mortality associated with AP using an artificial neural network (ANN) model.Methods In this multicenter retrospective study, ANN and logistic regression models were constructed using the clinical and laboratory data of 1,304 patients seeking emergency treatment for AP. The ANN model was first trained on 912/1,304 (70%) randomly selected patients and then tested on the remaining 392/1,304 (30%). Receiver operating characteristic curve analysis was used to evaluate the mortality prediction of the two models.Results Age, endotracheal intubation status, and intensive care unit admission were significant predictors of mortality in patients with AP in the multivariate logistic regression model. The ANN model indicated age, Glasgow Coma Scale, intensive care unit admission, and endotracheal intubation status were critical factors among the 12 independent variables related to in-hospital mortality. The area under the receiver operating characteristic curve for mortality prediction was significantly higher in the ANN model compared to the logistic regression model.Conclusion This study establishes that the ANN model could be a valuable tool for predicting the risk of death following AP. Thus, it may facilitate effective patient triage and improve the outcomes.

scholarly journals Evaluation of N/LP Ratio as a Predictor of Disease Progression and Mortality in COVID-19 Patients Admitted to the Intensive Care Unit

2021 ◽  
Author(s):  
Başak Çakır Güney ◽  
Mert Hayıroğlu ◽  
Didar Şenocak ◽  
Vedat Çiçek ◽  
Tufan Çınar ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
Hospital Death ◽  
Survival Status ◽  
Inflammatory Index ◽  
Icu Stay

Objective: This research aimed to evaluate whether the neutrophil to lymphocyte and platelet (N/LP) ratio may be used to predict the risk of admission to the intensive care unit (ICU), the need for mechanical ventilation and in-hospital mortality in Coronavirus disease 2019 (COVID-19) cases. Methods: The study was conducted retrospectively on the data of 134 COVID-19 patients who were admitted to the ICU. The N/LP ratio was calculated as follows: neutrophil count x 100 / (lymphocyte count x platelet count). Each member of the research cohort was categorised into 1 of 2 groups based on their survival status (survivor and non-survivor groups). Results: In total, 82 (61%) patients died during the ICU stay. Patients who required mechanical ventilation and died in the ICU stay had significantly higher N/LP ratio than those who did not require it and survived [10 (IQR=4.94-19.38) vs 2.51 (IQR=1.67-5.49), p<0.001] and [11.27 (IQR=4.53-30.02) vs 1.65 (IQR=1-3.24), p<0.001], respectively. The N/LP ratio was linked with the requirement of mechanical ventilation and in-hospital death according to multivariable analysis. In receiver operating characteristic curve analysis, we found that N/LP in predicting admission to the ICU was >4.18 with 61% sensitivity and 62% specificity, it was >5.07 with 74% sensitivity and 73% specificity for the need for mechanical ventilation, and >3.69 with 81% sensitivity and 81% specificity to predict in-hospital death. Conclusion: To our knowledge, this is the first study showing that the N/LP ratio, which is a novel and widely applicable inflammatory index, may be used to predict the risk of ICU admission, mechanical ventilation and in-hospital death in patients with COVID-19 disease.

Complications and risk factors for severe outcome in children with measles

2019 ◽  
Vol 105 (9) ◽  
pp. 896-899 ◽  
Author(s):  
Andrea Lo Vecchio ◽  
Andrzej Krzysztofiak ◽  
Carlotta Montagnani ◽  
Piero Valentini ◽  
Nadia Rossi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Retrospective Study ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Operating Characteristic Curve ◽  
Organ Complications

Objective and designRisk factors for severe measles are poorly investigated in high-income countries. The Italian Society for Paediatric Infectious Diseases conducted a retrospective study in children hospitalised for measles from January 2016 to August 2017 to investigate the risk factors for severe outcome defined by the presence of long-lasting sequelae, need of intensive care or death.ResultsNineteen hospitals enrolled 249 children (median age 14.5 months): 207 (83%) children developed a complication and 3 (1%) died. Neutropaenia was more commonly reported in children with B3-genotype compared with other genotypes (29.5% vs 7.7%, p=0.01). Pancreatitis (adjusted OR [aOR] 9.19, p=0.01) and encephalitis (aOR 7.02, p=0.04) were related to severe outcome in multivariable analysis, as well as C reactive protein (CRP) (aOR 1.1, p=0.028), the increase of which predicted severe outcome (area under the receiver operating characteristic curve 0.67, 95% CI 0.52 to 0.82). CRP values >2 mg/dL were related to higher risk of complications (OR 2.0, 95% CI 1.15 to 3.7, p=0.01) or severe outcome (OR 4.13, 95% CI 1.43 to 11.8, p<0.01).ConclusionThe risk of severe outcome in measles is independent of age and underlying conditions, but is related to the development of organ complications and may be predicted by CRP value.

Cough strength, secretions and extubation outcome in burn patients who have passed a spontaneous breathing trial

Burns ◽  
2013 ◽  
Vol 39 (2) ◽  
pp. 236-242 ◽  
Author(s):  
Sarah T. Smailes ◽  
Andrew J. McVicar ◽  
Rebecca Martin
Keyword(s):  
Spontaneous Breathing ◽  
Spontaneous Breathing Trial ◽  
Burn Patients ◽  
Extubation Outcome ◽  
Cough Strength

Prevalence and Impact on Weaning of Pleural Effusion at the Time of Liberation from Mechanical Ventilation

2017 ◽  
Vol 126 (6) ◽  
pp. 1107-1115 ◽  
Author(s):  
Martin Dres ◽  
Damien Roux ◽  
Tài Pham ◽  
Alexandra Beurton ◽  
Jean-Damien Ricard ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Pleural Effusion ◽  
Spontaneous Breathing ◽  
Odds Ratio ◽  
Spontaneous Breathing Trial ◽  
Ventilatory Support ◽  
Weaning Failure ◽  
Weaning Outcome

Abstract Background Pleural effusion is frequent in intensive care unit patients, but its impact on the outcome of weaning remains unknown. Methods In a prospective study performed in three intensive care units, pleural ultrasound was performed at the first spontaneous breathing trial to detect and quantify pleural effusion (small, moderate, and large). Weaning failure was defined by a failed spontaneous breathing trial and/or extubation requiring any form of ventilatory support within 48 h. The primary endpoint was the prevalence of pleural effusion according to weaning outcome. Results Pleural effusion was detected in 51 of 136 (37%) patients and was quantified as moderate to large in 18 (13%) patients. As compared to patients with no or small pleural effusion, their counterparts were more likely to have chronic renal failure (39 vs. 7%; P = 0.01), shock as the primary reason for admission (44 vs. 19%; P = 0.02), and a greater weight gain (+4 [0 to 7] kg vs. 0 [−1 to 5] kg; P = 0.02). The prevalence of pleural effusion was similar in weaning success and weaning failure patients (odds ratio, 1.23; 95% CI, 0.61 to 2.49; P = 0.56), as was the prevalence of moderate to large pleural effusion (odds ratio, 0.89; 95% CI, 0.33 to 2.41; P = 1.00). Duration of mechanical ventilation and intensive care unit length of stay were similar between patients with no or small pleural effusion and those with moderate to large pleural effusion. Conclusions Significant pleural effusion was observed in 13% of patients at the time of liberation from mechanical ventilation and was not associated with an alteration of weaning outcome. (Anesthesiology 2017; 126:1107–15)

scholarly journals Validation of Three Postoperative Risk Prediction Models for Intensive Care Unit Mortality after Cardiac Surgery

2018 ◽  
Vol 66 (08) ◽  
pp. 651-660 ◽  
Author(s):  
Camila Caiado ◽  
Charles McCollum ◽  
Michael Goldstein ◽  
Ignacio Malagon ◽  
Rajamiyer Venkateswaran ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Cardiac Surgery ◽  
Risk Prediction ◽  
Operating Characteristic ◽  
Prediction Models ◽  
Characteristic Curve ◽  
Icu Mortality ◽  
Risk Prediction Models ◽  
Postoperative Risk ◽  
Operating Characteristic Curve

Background Several cardiac surgery risk prediction models based on postoperative data have been developed. However, unlike preoperative cardiac surgery risk prediction models, postoperative models are rarely externally validated or utilized by clinicians. The objective of this study was to externally validate three postoperative risk prediction models for intensive care unit (ICU) mortality after cardiac surgery. Methods The logistic Cardiac Surgery Scores (logCASUS), Rapid Clinical Evaluation (RACE), and Sequential Organ Failure Assessment (SOFA) scores were calculated over the first 7 postoperative days for consecutive adult cardiac surgery patients between January 2013 and May 2015. Model discrimination was assessed using receiver operating characteristic curve analyses. Calibration was assessed using the Hosmer–Lemeshow (HL) test, calibration plots, and observed to expected ratios. Recalibration of the models was performed. Results A total of 2255 patients were included with an ICU mortality rate of 1.8%. Discrimination for all three models on each postoperative day was good with areas under the receiver operating characteristic curve of >0.8. Generally, RACE and logCASUS had better discrimination than SOFA. Calibration of the RACE score was better than logCASUS, but ratios of observed to expected mortality for both were generally <0.65. Locally recalibrated SOFA, logCASUS and RACE models all performed well. Conclusion All three models demonstrated good discrimination for the first 7 days after cardiac surgery. After recalibration, logCASUS and RACE scores appear to be most useful for daily risk prediction after cardiac surgery. If appropriately calibrated, postoperative cardiac surgery risk prediction models have the potential to be useful tools after cardiac surgery.

An Integrative Index for Predicting Extubation Outcomes After Successful Completion of a Spontaneous Breathing Trial in an Adult Medical Intensive Care Unit

2017 ◽  
Vol 34 (8) ◽  
pp. 640-645 ◽  
Author(s):  
Tsung-Ju Wu ◽  
Judith Shu-Chu Shiao ◽  
Hsin-Liang Yu ◽  
Ruay-Sheng Lai
Keyword(s):  
Mechanical Ventilation ◽  
Intensive Care ◽  
Serum Albumin ◽  
Spontaneous Breathing ◽  
Characteristic Curve ◽  
Spontaneous Breathing Trial ◽  
Invasive Mechanical Ventilation ◽  
Extubation Failure ◽  
Rapid Shallow Breathing Index ◽  
Medical Intensive Care

Background: Among respiratory predictors, rapid shallow breathing index (RSBI) has been a commonly used respiratory parameter to predict extubation outcomes. However, the outcome of prediction remains inconsistent. Regarding nonrespiratory predictors, serum albumin, hemoglobin, bicarbonate, and patients’ alertness have been reported to be associated with successful weaning or extubation. We aimed to develop an integrative index combining commonly used predictors in the adult medical intensive care units (MICUs) and to compare the predictability of the index with RSBI. Methods: This prospective observational study with retrospective data collection of planned extubations was conducted in a 14-bed adult MICU. We enrolled patients who received mechanical ventilation via an endotracheal tube in the adult MICU for >24 hours and passed a 2-hour spontaneous breathing trial and underwent extubation. Extubation failure was defined as reinstitution of invasive mechanical ventilation within 48 hours of extubation. Respiratory parameters and Glasgow Coma Scale (GCS) scores of patients were recorded prospectively. Nonrespiratory parameters were recorded retrospectively. Logistic regression was used to determine significant predictors of extubation outcomes. Results: Fifty-nine patients comprising 70 extubations were enrolled. Extubation failure was significantly and positively associated with lower serum albumin (albumin < 2.6 g/dL, odds ratio [OR] = 5.1; 95% confidence interval [CI], 1.04-24.66), lower hemoglobin (hemoglobin < 10.0 g/dL, OR = 10.8; 95% CI, 2.00-58.04), and lower GCS scores (GCS score ≤ 8, OR = 6.1; 95% CI = 1.15-32.34). By using an integrative index combining the 3 parameters together, the sensitivity and specificity to predict extubation outcomes were 78.6% and 75.9%, respectively. The area under the receiver operating characteristic curve of the index was significantly higher than RSBI (0.84 vs 0.61, P = .026). Conclusion: The integrative index combining serum albumin, hemoglobin, and GCS scores could predict extubation outcomes better than RSBI in an adult MICU.

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