High Respiratory Drive and Excessive Respiratory Efforts Predict Relapse of Respiratory Failure in Critically Ill Patients with COVID-19.
Ontology highlight
ABSTRACT:
SUBMITTER: Esnault P
PROVIDER: S-EPMC7560807 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
Publications
High Respiratory Drive and Excessive Respiratory Efforts Predict Relapse of Respiratory Failure in Critically Ill Patients with COVID-19.
Esnault Pierre P Cardinale Michael M Hraiech Sami S Goutorbe Philippe P Baumstrack Karine K Prud'homme Eloi E Bordes Julien J Forel Jean-Marie JM Meaudre Eric E Papazian Laurent L Guervilly Christophe C
American journal of respiratory and critical care medicine 20201001 8
Similar Datasets
Project description:BackgroundPatients with obesity are at increased risk of severe COVID-19, requiring mechanical ventilation due to acute respiratory failure. However, conflicting data are obtained for intensive care unit (ICU) mortality.ObjectiveTo analyze the relationship between obesity and in-hospital mortality of ICU patients with COVID-19.Subjects/methodsPatients admitted to the ICU for COVID-19 acute respiratory distress syndrome (ARDS) were included retrospectively. The following data were collected: comorbidities, body mass index (BMI), the severity of ARDS assessed with PaO2/FiO2 (P/F) ratios, disease severity measured by the Simplified Acute Physiology Score II (SAPS II), management and outcomes.ResultsFor a total of 222 patients, there were 34 patients (15.3%) with normal BMI, 92 patients (41.4%) who were overweight, 80 patients (36%) with moderate obesity (BMI:30-39.9 kg/m2), and 16 patients (7.2%) with severe obesity (BMI ≥ 40 kg/m2). Overall in-hospital mortality was 20.3%. Patients with moderate obesity had a lower mortality rate (13.8%) than patients with normal weight, overweight or severe obesity (17.6%, 21.7%, and 50%, respectively; P = 0.011. Logistic regression showed that patients with a BMI ≤ 29 kg/m2 (odds ratio [OR] 3.64, 95% CI 1.38-9.60) and those with a BMI > 39 kg/m2 (OR 10.04, 95% CI 2.45-41.09) had a higher risk of mortality than those with a BMI from 29 to 39 kg/m2. The number of comorbidities (≥2), SAPS II score, and P/F < 100 mmHg were also independent predictors for in-hospital mortality.ConclusionsCOVID-19 patients admitted to the ICU with moderate obesity had a lower risk of death than the other patients, suggesting a possible obesity paradox.
| S-EPMC8190754 | biostudies-literature
Project description:In hypoxemic patients at risk for developing respiratory failure, the decision to initiate invasive mechanical ventilation (IMV) may be extremely difficult, even more so among patients suffering from COVID-19. Delayed recognition of respiratory failure may translate into poor outcomes, emphasizing the need for stronger predictive models for IMV necessity. We developed a two-step model; the first step was to train a machine learning predictive model on a large dataset of non-COVID-19 critically ill hypoxemic patients from the United States (MIMIC-III). The second step was to apply transfer learning and adapt the model to a smaller COVID-19 cohort. An XGBoost algorithm was trained on data from the MIMIC-III database to predict if a patient would require IMV within the next 6, 12, 18 or 24 h. Patients' datasets were used to construct the model as time series of dynamic measurements and laboratory results obtained during the previous 6 h with additional static variables, applying a sliding time-window once every hour. We validated the adaptation algorithm on a cohort of 1061 COVID-19 patients from a single center in Israel, of whom 160 later deteriorated and required IMV. The new XGBoost model for the prediction of the IMV onset was trained and tested on MIMIC-III data and proved to be predictive, with an AUC of 0.83 on a shortened set of features, excluding the clinician's settings, and an AUC of 0.91 when the clinician settings were included. Applying these models "as is" (no adaptation applied) on the dataset of COVID-19 patients degraded the prediction results to AUCs of 0.78 and 0.80, without and with the clinician's settings, respectively. Applying the adaptation on the COVID-19 dataset increased the prediction power to an AUC of 0.94 and 0.97, respectively. Good AUC results get worse with low overall precision. We show that precision of the prediction increased as prediction probability was higher. Our model was successfully trained on a specific dataset, and after adaptation it showed promise in predicting outcome on a completely different dataset. This two-step model successfully predicted the need for invasive mechanical ventilation 6, 12, 18 or 24 h in advance in both general ICU population and COVID-19 patients. Using the prediction probability as an indicator of the precision carries the potential to aid the decision-making process in patients with hypoxemic respiratory failure despite the low overall precision.
| S-EPMC9216294 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2022-02-28 | GSE197259 | GEO
Project description:ObjectivesThis study describes the development and deployment of a machine learning (ML) model called Vent.io to predict mechanical ventilation (MV).Materials and methodsWe trained Vent.io using electronic health record data of adult patients admitted to the intensive care units (ICUs) of the University of California San Diego (UCSD) Health System. We prospectively deployed Vent.io using a real-time platform at UCSD and evaluated the performance of Vent.io for a 1-month period in silent mode and on the MIMIC-IV dataset. As part of deployment, we included a Predetermined Changed Control Plan (PCCP) for continuous model monitoring that triggers model fine-tuning if performance drops below a specified area under the receiver operating curve (AUC) threshold of 0.85.ResultsThe Vent.io model had a median AUC of 0.897 (IQR: 0.892-0.904) with specificity of 0.81 (IQR: 0.812-0.841) and positive predictive value (PPV) of 0.174 (IQR: 0.148-0.176) at a fixed sensitivity of 0.6 during 10-fold cross validation and an AUC of 0.908, sensitivity of 0.632, specificity of 0.849, and PPV of 0.235 during prospective deployment. Vent.io had an AUC of 0.73 on the MIMIC-IV dataset, triggering model fine-tuning per the PCCP as the AUC was below the minimum of 0.85. The fine-tuned Vent.io model achieved an AUC of 0.873.DiscussionDeterioration of model performance is a significant challenge when deploying ML models prospectively or at different sites. Implementation of a PCCP can help models adapt to new patterns in data and maintain generalizability.ConclusionVent.io is a generalizable ML model that has the potential to improve patient care and resource allocation for ICU patients with need for MV.
| S-EPMC11633942 | biostudies-literature
Project description:Systemic inflammatory illnesses (such as sepsis) are marked by degradation of the endothelial glycocalyx, a layer of glycosaminoglycans (including heparan sulfate, chondroitin sulfate, and hyaluronic acid) lining the vascular lumen. We hypothesized that different pathophysiologic insults would produce characteristic patterns of released glycocalyx fragments. We collected plasma from healthy donors as well as from subjects with respiratory failure due to altered mental status (intoxication, ischemic brain injury), indirect lung injury (non-pulmonary sepsis, pancreatitis), or direct lung injury (aspiration, pneumonia). Mass spectrometry was employed to determine the quantity and sulfation patterns of circulating glycosaminoglycans. We found that circulating heparan sulfate fragments were significantly (23-fold) elevated in patients with indirect lung injury, while circulating hyaluronic acid concentrations were elevated (32-fold) in patients with direct lung injury. N-Sulfation and tri-sulfation of heparan disaccharides were significantly increased in patients with indirect lung injury. Chondroitin disaccharide sulfation was suppressed in all groups with respiratory failure. Plasma heparan sulfate concentrations directly correlated with intensive care unit length of stay. Serial plasma measurements performed in select patients revealed that circulating highly sulfated heparan fragments persisted for greater than 3 days after the onset of respiratory failure. Our findings demonstrate that circulating glycosaminoglycans are elevated in patterns characteristic of the etiology of respiratory failure and may serve as diagnostic and/or prognostic biomarkers of critical illness.
| S-EPMC3961648 | biostudies-literature
Project description:BackgroundPatients with chronic known or unknown interstitial lung disease (ILD) may present with severe respiratory flares that require intensive management. Outcome data in these patients are scarce.Patients and methodsClinical and radiological features were collected in 83 patients with ILD-associated acute respiratory failure (ARF). Determinants of hospital mortality and response to corticosteroid therapy were identified by logistic regression.ResultsHospital and 1-year mortality rates were 41% and 54% respectively. Pulmonary hypertension, computed tomography (CT) fibrosis and acute kidney injury were independently associated with mortality (odds ratio (OR) 4.55; 95% confidence interval (95%CI) (1.20-17.33); OR, 7.68; (1.78-33.22) and OR 10.60; (2.25-49.97) respectively). Response to steroids was higher in patients with shorter time from hospital admission to corticosteroid therapy. Patients with fibrosis on CT had lower response to steroids (OR, 0.03; (0.005-0.21)). In mechanically ventilated patients, overdistension induced by high PEEP settings was associated with CT fibrosis and hospital mortality.ConclusionMortality is high in ILD-associated ARF. CT and echocardiography are valuable prognostic tools. Prompt corticosteroid therapy may improve survival.
| S-EPMC4130629 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) has affected individuals worldwide, and patients with cancer are particularly vulnerable to COVID-19-related severe illness, respiratory failure, and mortality. The relationship between COVID-19 and cancer remains a critical concern, and a comprehensive investigation of the factors affecting survival among patients with cancer who develop COVID-19-related respiratory failure is warranted. We aim to compare the characteristics and outcomes of COVID-19-related acute respiratory failure in patients with and without underlying cancer, while analyzing factors affecting in-hospital survival among cancer patients.MethodsWe conducted a retrospective observational study at Taipei Veterans General Hospital in Taiwan from May to September 2022, a period during which the omicron variant of the severe acute respiratory syndrome coronavirus 2 was circulating. Eligible patients had COVID-19 and acute respiratory failure. Clinical data, demographic information, disease severity markers, treatment details, and outcomes were collected and analyzed.ResultsOf the 215 enrolled critically ill patients with COVID-19, 65 had cancer. The patients with cancer were younger and had lower absolute lymphocyte counts, higher ferritin and lactate dehydrogenase (LDH) concentrations, and increased vasopressor use compared with those without cancer. The patients with cancer also received more COVID-19 specific treatments but had higher in-hospital mortality rate (61.5% vs 36%, P = 0.002) and longer viral shedding (13 vs 10 days, P = 0.007) than those without cancer did. Smoking [odds ratio (OR): 5.804, 95% confidence interval (CI): 1.847-39.746], elevated LDH (OR: 1.004, 95% CI: 1.001-1.012), vasopressor use (OR: 5.437, 95% CI: 1.202-24.593), and new renal replacement therapy (OR: 3.523, 95% CI: 1.203-61.108) were independent predictors of in-hospital mortality among patients with cancer and respiratory failure.ConclusionCritically ill patients with cancer experiencing COVID-19-related acute respiratory failure present unique clinical features and worse clinical outcomes compared with those without cancer. Smoking, elevated LDH, vasopressor use, and new renal replacement therapy were risk factors for in-hospital mortality in these patients.
| S-EPMC10789018 | biostudies-literature
Project description:Subcutaneous emphysema, pneumothorax and pneumomediastinum are well-known complications of invasive ventilation in patients with acute hypoxemic respiratory failure. We determined the incidences of air leaks that were visible on available chest images in a cohort of critically ill patients with acute hypoxemic respiratory failure due to coronavirus disease of 2019 (COVID-19) in a single-center cohort in the Netherlands. A total of 712 chest images from 154 patients were re-evaluated by a multidisciplinary team of independent assessors; there was a median of three (2-5) chest radiographs and a median of one (1-2) chest CT scans per patient. The incidences of subcutaneous emphysema, pneumothoraxes and pneumomediastinum present in 13 patients (8.4%) were 4.5%, 4.5%, and 3.9%. The median first day of the presence of an air leak was 18 (2-21) days after arrival in the ICU and 18 (9-22)days after the start of invasive ventilation. We conclude that the incidence of air leaks was high in this cohort of COVID-19 patients, but it was fairly comparable with what was previously reported in patients with acute hypoxemic respiratory failure in the pre-COVID-19 era.
| S-EPMC10046975 | biostudies-literature
Project description:ObjectivesIn mechanically ventilated patients, deep sedation is often assumed to induce "respirolysis," that is, lyse spontaneous respiratory effort, whereas light sedation is often assumed to preserve spontaneous effort. This study was conducted to determine validity of these common assumptions, evaluating the association of respiratory drive with sedation depth and ventilator-free days in acute respiratory failure.DesignProspective cohort study.SettingPatients were enrolled during 2 month-long periods in 2016-2017 from five ICUs representing medical, surgical, and cardiac specialties at a U.S. academic hospital.PatientsEligible patients were critically ill adults receiving invasive ventilation initiated no more than 36 hours before enrollment. Patients with neuromuscular disease compromising respiratory function or expiratory flow limitation were excluded.InterventionsRespiratory drive was measured via P0.1, the change in airway pressure during a 0.1-second airway occlusion at initiation of patient inspiratory effort, every 12 ± 3 hours for 3 days. Sedation depth was evaluated via the Richmond Agitation-Sedation Scale. Analyses evaluated the association of P0.1 with Richmond Agitation-Sedation Scale (primary outcome) and ventilator-free days.Measurements and main resultsFifty-six patients undergoing 197 bedside evaluations across five ICUs were included. P0.1 ranged between 0 and 13.3 cm H2O (median [interquartile range], 0.1 cm H2O [0.0-1.3 cm H2O]). P0.1 was not significantly correlated with the Richmond Agitation-Sedation Scale (RSpearman, 0.02; 95% CI, -0.12 to 0.16; p = 0.80). Considering P0.1 terciles (range less than 0.2, 0.2-1.0, and greater than 1.0 cm H2O), patients in the middle tercile had significantly more ventilator-free days than the lowest tercile (incidence rate ratio, 0.78; 95% CI, 0.65-0.93; p < 0.01) or highest tercile (incidence rate ratio, 0.58; 95% CI, 0.48-0.70; p < 0.01).ConclusionsSedation depth is not a reliable marker of respiratory drive during critical illness. Respiratory drive can be low, moderate, or high across the range of routinely targeted sedation depth.
| S-EPMC8602777 | biostudies-literature
Project description:Objective: Adiponectin, an anti-inflammatory cytokine produced by adipose tissue, has been shown to modulate survival in animal models of critical illness. We examined the association between plasma adiponectin and clinical outcomes in critically ill patients with acute respiratory failure.Design: Secondary analysis of a single-center, randomized controlled trial.Setting: Medical intensive care unit of a university-based, tertiary medical center.Patients: One hundred seventy-five subjects with acute respiratory failure enrolled in randomized, controlled pilot trial of Early versus Delayed Enternal Nutrition (EDEN pilot study).Interventions: None.Measurements and main results: Adiponectin measured within 48 hrs of respiratory failure (Apn1) was inversely correlated with body mass index (r=-0.25, p=.007) and was higher in females (median, 12.6 μg/mL; interquartile range, 7.6-17.1) than males (9.45 μg/mL; 6.2-14.2; p=.02). Adiponectin increased at day 6 (Apn1: 11.4 μg/mL [6.6-15.3] vs. Apn6: 14.1 μg/mL [10.3-18.6], p<.001). This increase was significant only in survivors (Δ adiponectin in survivors: 3.9±6 μg/mL, n=80, p<.001 vs. Δ in nonsurvivors: 1.69±4.6 μg/mL, n=14, p=.19). Higher Apn1 was significantly associated with 28-day mortality (odds ratio 1.59 per 5-μg/mL increase; 95% confidence interval 1.15-2.21; p=.006). No measured demographic, clinical, or cytokine covariates, including interleukin-6, interleukin-8, interleukin-10, interleukin-1β, interleukin-12, tumor necrosis factor-α, and interferon-γ, were confounders or effect modifiers of this association between adiponectin and mortality.Conclusions: Independent of measured covariates, increased plasma adiponectin levels measured within 48 hrs of respiratory failure are associated with mortality. This finding suggests that factors derived from adipose tissue play a role in modulating the response to critical illness.
| S-EPMC3703623 | biostudies-literature