Establishing failure predictors for the planned extubation of overweight and obese patients.
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ABSTRACT:
SUBMITTER: Chao CM
PROVIDER: S-EPMC5558963 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionDetermining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19.MethodsWe used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots.ResultsA total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure.ConclusionThe most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.
| S-EPMC8711075 | biostudies-literature
Project description:BackgroundExtubation failure is common in critically ill patients, especially those with high-risk factors, and is associated with poor prognosis. Prophylactic use of oxygen therapy after extubation has been gradually introduced. However, the best respiratory support method is still unclear.PurposeThis study aimed to evaluate the efficacy of four post-extubation respiratory support approaches in reducing reintubation and respiratory failure in patients at high-risk of extubation failure.MethodsA comprehensive search was performed in Cochrane Central Register of Controlled Trials, PubMed, EMBASE, and Web of Science from inception to June 2022. Randomized controlled trials (RCTs) comparing post-extubation preventive use of respiratory management strategies, including conventional oxygen therapy (COT), non-invasive ventilation (NIV), and high-flow nasal catheter (HFNC) in high-risk patients with extubation failure were reviewed. Primary outcomes were reintubation rate and respiratory failure. Secondary outcomes included intensive care unit (ICU) mortality, ICU stay and length of hospital stay (LOS).ResultsSeventeen RCTs comprising 2813 participants were enrolled. Compared with COT, the three respiratory support methods (NIV, HFNC, NIV + HFNC) were all effective in preventing reintubation [odds ratio (OR) 0.46, 95% confidence interval (CI) 0.32-0.67; OR 0.26, 95% CI 0.14-0.48; OR 0.62, 95% CI 0.39-0.97, respectively] and respiratory failure (OR 0.23, 95% CI 0.10-0.52; OR 0.15, 95% CI 0.04-0.60; OR 0.26, 95% CI 0.10-0.72, respectively). NIV and NIV + HFNC also reduced ICU mortality (OR 0.40, 95% CI 0.22-0.74; OR 0.32, 95% CI 0.12-0.85). NIV + HFNC ranked best in terms of reintubation rate, respiratory failure and ICU mortality based on the surface under the cumulative ranking curve (SUCRA) (99.3, 87.1, 88.2, respectively). Although there was no significant difference in shortening ICU stay and LOS among the four methods, HFNC ranked first based on the SUCRA.ConclusionPreventive use of NIV + HFNC after scheduled extubation is probably the most effective respiratory support method for preventing reintubation, respiratory failure and ICU death in high-risk patients with extubation failure. HFNC alone seems to be the best method to shorten ICU stay and LOS.Systematic review registration[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022340623].
| S-EPMC9608755 | biostudies-literature
Project description:BackgroundPrediction of extubation failure, particularly in neurocritical patients, is unique and controversial. We conducted a systematic review and meta-analysis to identify the risk factors for extubation failure in these patients.MethodsA literature search of databases (MEDLINE, EMBASE, the Cochrane Library, and Web of Science) was performed up to August of 2013 to identify trials that evaluated extubation failure predictors. Included trials were either prospective or retrospective cohort studies.ResultsNine studies involving 928 participants were included. The systematic review and meta-analysis revealed that the following were predictive for extubation failure: pneumonia, atelectasis, mechanical ventilation of >24 h, a low Glasgow Coma Scale score (7-9T) (OR = 4.96, 95% CI = 1.61-15.26, P = 0.005), the inability to follow commands (OR = 2.07, 95% CI = 1.15-3.71, P = 0.02), especially the command to close the eyes, thick secretion, and no intact gag reflex. Meanwhile, the following were not predictive for extubation failure: sex, secretion volume, coughing upon suctioning, and the inability to follow one command among showing two fingers, wiggling the toes, or coughing on command. Additionally, some traditional weaning parameters were shown to poorly predict extubation failure in neurocritical patients.ConclusionsBesides pneumonia, atelectasis, and the duration of mechanical ventilation, other factors that should be taken into consideration in the prediction of extubation failure when neurocritical patients are weaned from tracheal intubation include neurologic abilities (Glasgow Coma Scale score and following commands), the secretion texture, and the presence of a gag reflex.
| S-EPMC4259297 | biostudies-literature
Project description:This study aims to construct a neural network to predict weaning difficulty among planned extubation patients in intensive care units.This observational cohort study was conducted in eight adult ICUs in a medical center about adult patients experiencing planned extubation.The data of 3602 patients with planned extubation in ICUs of Chi-Mei Medical Center (from Dec. 2009 through Dec. 2011) was used to train and test an artificial neural network (ANN) model. The input features contain 47 clinical risk factors and the outputs are classified into three categories: simple, difficult, and prolonged weaning. A deep ANN model with four hidden layers of 30 neurons each was developed. The accuracy is 0.769 and the area under receiver operating characteristic curve for simple weaning, prolonged weaning, and difficult weaning are 0.910, 0.849, and 0.942 respectively.The results revealed that the ANN model achieved a good performance in prediction the weaning difficulty in planned extubation patients. Such a model will be helpful for predicting ICU patients' successful planned extubation.
| S-EPMC6783239 | biostudies-literature
Project description:Extubation failure (EF) is a significant concern in mechanically ventilated newborns, and predicting its occurrence is an ongoing area of research. To investigate the predictors of EF in newborns undergoing planned extubation, we conducted a systematic review and meta-analysis. A systematic literature search was conducted in PubMed, Web of Science, Embase, and Cochrane Library for studies published in English from the inception of each database to March 2023. The PRISMA guidelines were followed in all phases of this systematic review. The Risk of Bias Assessment for Nonrandomized Studies tool was used to assess methodological quality. Thirty-four studies were included, 10 of which were overall low risk of bias, 15 of moderate risk of bias, and 9 of high risk of bias. The studies reported 43 possible predictors in six broad categories (intrinsic factors; maternal factors; diseases and adverse conditions of the newborn; treatment of the newborn; characteristics before and after extubation; and clinical scores and composite indicators). Through a qualitative synthesis of 43 predictors and a quantitative meta-analysis of 19 factors, we identified five definite factors, eight possible factors, and 22 unclear factors related to EF. Definite factors included gestational age, sepsis, pre-extubation pH, pre-extubation FiO2, and respiratory severity score. Possible factors included age at extubation, anemia, inotropic use, mean airway pressure, pre-extubation PCO2, mechanical ventilation duration, Apgar score, and spontaneous breathing trial. With only a few high-quality studies currently available, well-designed and more extensive prospective studies investigating the predictors affecting EF are still needed. In the future, it will be important to explore the possibility of combining multiple predictors or assessment tools to enhance the accuracy of predicting extubation outcomes in clinical practice.
| S-EPMC10546653 | biostudies-literature
Project description:The aim of our study was to investigate a large cohort of overweight subjects consuming a homogeneous diet to identify the genetic factors associated with weight loss that could be used as predictive markers in weight loss interventions. We retrospectively recruited subjects (N = 788) aged over 18 years with a Body Mass Index (BMI) between 25 and 40 kg/m2 who were treated at our lipid unit for at least one year from 2008 to 2016, and we also recruited a control group (168 patients) with normal BMIs. All participants received counselling from a nutritionist that included healthy diet and physical activity recommendations. We genotyped 25 single nucleotide variants (SNVs) in 25 genes that were previously associated with obesity and calculated genetic scores that were derived from 25 SNVs. The risk allele in CADM2 showed a higher frequency in overweight and obese subjects than in controls (p = 0.007). The mean follow-up duration was 5.58 ± 2.68 years. Subjects with lower genetic scores showed greater weight loss during the follow-up period. The genetic score was the variable that best explained the variations in weight from the baseline. The genetic score explained 2.4% of weight change variance at one year and 1.6% of weight change variance at the end of the follow-up period after adjusting for baseline weight, sex, age and years of follow-up.
| S-EPMC6656717 | biostudies-literature
Project description:PurposeWalking may improve health in obese patients with multimorbidity. We aimed to identify predictors associated with achieving <5000 steps per day after 4 months.Patients and methodsWe conducted a cohort study of 125 adult patients with a body mass index >25 kg/m2 and ≥7 comorbidities. We evaluated potential predictors for <5000 steps per day using logistic regression and adjusting for age >65 years and sex.ResultsThe mean (range) age was 63.6 (20.3-89.8) years. Daily step counts <5000 at baseline showed the highest risk of <5000 daily steps at 4 months (odds ratio [OR] 31.82, 95% confidence interval [CI]: 12.14-95.50). Other significant characteristics were physical quality of life (OR 6.21, 95% CI: 2.32-18.54), gait speed <1 m/s (OR 2.57, 95% CI: 1.18-5.71), age ≥65 years (OR 2.21, 95% CI: 1.05-4.77), waist circumference ≥102 cm (OR 2.48, 95% CI: 1.05-6.06), and body mass index ≥30 kg/m2 (OR 2.69, 95% CI: 1.20-6.26).ConclusionNew models to increase walking may be required for higher-risk patients.
| S-EPMC5633315 | biostudies-literature
Project description:AimsThe definition of sarcopenia based on appendicular lean mass/height (2) (ALM/height (2) ) is often used, although it can underestimate the prevalence of sarcopenia in overweight/obese patients with heart failure. Therefore, new methods have been proposed to overcome this limitation. We aimed to evaluate the prevalence of sarcopenia by three methods and compare body composition in this population.Methods and resultsWe enrolled 168 male patients with heart failure (left ventricular ejection fraction <40%). Sixty-six patients (39.3%) were identified with sarcopenia by at least one method. The lower 20th percentile defined as the cut-off point for sarcopenia was 7.03 kg/m2 , -2.32 and 0.76 for Baumgartner's (20.8%), Newman's (21.4%), and Studenski's methods (21.4%), respectively. Patients with body mass index (BMI) <25 kg/m2 were more likely to be identified by Baumgartner's than Studenski's method (P < 0.001). However, in patients with BMI ≥ 25 kg/m2 , Studenski's and Newman's methods were more likely to detect sarcopenia than Baumgartner's method (both P < 0.005). Patients were further divided into three subgroups: (i) patients classified in all indexes (n = 8), (ii) patients classified in Baumgartner's (sarcopenic; n = 27), and (iii) patients classified in both Newman's and Studenski's methods (sarcopenic obesity; n = 31). Comparing body composition among groups, all sarcopenic groups presented lower total lean mass compared with non-sarcopenic patients, whereas sarcopenic obese patients had higher total lean mass than lean sarcopenic patients.ConclusionsOur results demonstrate that the prevalence of sarcopenia in overweight/obese patients is similar to lean sarcopenic patients when other methods are considered. In patients with higher BMI, Studenski's method seems to be more feasible to detect sarcopenia.
| S-EPMC7083394 | biostudies-literature
Project description:A high prevalence of obesity has been increasingly recognized in survivors of pediatric ALL. However, longitudinal patterns of weight change during and after treatment, and associated factors, are less well elucidated.In a retrospective cohort of 83 pediatric patients with ALL diagnosed between 1985 and 2010, we examined body mass index (BMI) status at several key time points: diagnosis; end of induction; end of consolidation; every 6 months during maintenance; and yearly for up to 5 years post-treatment.At diagnosis, 21% were overweight (BMI = 85-94.9th percentile) or obese (BMI ≥ 95th percentile). At the end of treatment and 5 years post-treatment, approximately 40% were overweight or obese. The mean BMI z-score was 0.2 (58th percentile) at diagnosis and increased significantly during induction (Δ = 0.5, P < 0.0001). It increased again during the first 6 months of maintenance (Δ = 0.2, P < 0.01) and did not significantly change over the remainder of maintenance (BMI z-score at the end of treatment = 0.8, 79th percentile) and 5 years post-treatment (BMI z-score = 0.7, 76th percentile). High BMI z-score at diagnosis was associated with an increased risk of being overweight/obese at treatment completion (OR = 2.9, 95% CI: 1.6-5.1). Weight gain during treatment was associated with being overweight/obese 5 years post-treatment (OR = 3.8, 95% CI: 1.1-12.5).Children with ALL are at risk of becoming overweight/obese early in treatment. Increases in weight are maintained throughout treatment and beyond. Lifestyle interventions are needed targeting weight control early during treatment, particularly for patients overweight/obese at diagnosis and those who experience substantial weight gain during treatment.
| S-EPMC4435552 | biostudies-other
Project description:BackgroundElderly patients are being increasingly admitted to the intensive care unit (ICU) for mechanical ventilation. Previous studies demonstrated that 20% to 35% of elderly patients were reintubated within 48 to 72 hours after extubation. Given the age-related physiologic changes and multiple comorbidities in elderly patients, the current conventional parameters for predicting extubation outcomes may not be applicable to this population. This study was performed to identify the association between age-related parameters and extubation failure in elderly patients.MethodsIntubated elderly patients (age of ?60 years) admitted to the medical ICU of a university-based hospital from October 2014 to July 2015 were included. Failed extubation was defined as reintubation within 48 hours after the first extubation. The associations of extubation failure with demographic data, vital signs, cognition and anxiety, and ventilator parameters at the time of intubation and extubation were analyzed.ResultsIn total, 127 intubated elderly patients were recruited. Extubation failure occurred in 15 patients (11.8%). Patients with failed extubation had a lower body temperature (37.0°C vs. 37.3°C, P < 0.05) but a higher Facial Anxiety Scale (FAS) score than those with successful extubation (3 vs. 2, P < 0.05). Patients with extubation failure had significantly higher levels of blood urea nitrogen (BUN) (39.88 vs. 58.47 g/dL), serum sodium (137.66 vs. 141.47 mmol/L), and serum calcium (9.52 vs. 10.0 g/dL) but a wider anion gap (12.23 vs. 9.97), but no significant differences in respiratory parameters were found between the two groups. Multiple logistic regression revealed no independent factors associated with successful extubation.ConclusionThis study revealed no strong predictive factors. However, several physiological parameters (lower body temperature and higher FAS scores) and metabolic parameters (BUN, sodium, calcium, and anion gap) were significantly associated with the rate of extubation failure.
| S-EPMC6245685 | biostudies-literature