scholarly journals Model-based neuro-fuzzy control of FiO2 for intensive care mechanical ventilation

Critical Care ◽  
2001 ◽  
Vol 5 (Suppl 1) ◽  
pp. P002
Author(s):  
HF Kwok ◽  
GH Mills ◽  
M Mahfouf ◽  
DA Linkens
Keyword(s):  
Mechanical Ventilation ◽  
Intensive Care ◽  
Fuzzy Control ◽  
Model Based ◽  
Neuro Fuzzy

scholarly journals Serum Creatinine and Serum Cystatin C are Both Relevant Renal Markers to Estimate Vancomycin Clearance in Critically Ill Neonates

2021 ◽  
Vol 12 ◽  
Author(s):  
Stéphanie Leroux ◽  
Valérie Biran ◽  
John van den Anker ◽  
Verena Gotta ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Intensive Care ◽  
Serum Creatinine ◽  
Kidney Function ◽  
Cystatin C ◽  
Therapeutic Drug ◽  
Serum Cystatin C ◽  
Serum Cystatin ◽  
Final Model ◽  
Model Based

Purpose: Serum creatinine (SCr) is used as a marker of kidney function to guide dosing of renally eliminated drugs. Serum Cystatin C (S-CysC) has been suggested as a more reliable kidney marker than SCr in adults and children. Purpose of this study was to investigate S-CysC as alternative renal marker to SCr for estimating vancomycin clearance in neonates undergoing intensive care.Methods: Vancomycin pharmacokinetics (PK), SCr and S-CysC data were collected in patients undergoing vancomycin treatment in the neonatal intensive care unit of Robert Debré Hospital - Paris. A population PK analysis was performed utilizing routine therapeutic drug monitoring samples. S-CysC and SCr were compared as covariates on vancomycin clearance using stepwise covariate modeling (forward inclusion [p < 0.05] and backward elimination [p < 0.01]). Model performance was evaluated by graphical and statistical criteria.Results: A total of 108 vancomycin concentrations from 66 patients (postmenstrual age [PMA] of 26–46 weeks) were modeled with an allometric one-compartment model. The median (range) values for SCr and S-CysC were 41 (12–153) µmol/l and 1.43 (0.95–2.83) mg/l, respectively. Following stepwise covariate model building, SCr was retained as single marker of kidney function (after accounting for weight and PMA) in the final model. Compared to the final model based on SCr, the alternative model based on S-CysC showed very similar performance (e.g. BIC of 578.3 vs. 576.4) but included one additional covariate: impact of mechanical ventilation on vancomycin clearance, in addition to the effects of size and maturation.Conclusion: ill neonates. However, if using S-CysC for this purpose mechanical ventilation needs to be taken into account.

scholarly journals Predictive Biomarkers of Intensive Care Unit and Mechanical Ventilation Duration in Critically-Ill Coronavirus Disease 2019 Patients

2021 ◽  
Vol 8 ◽  
Author(s):  
Sara Taleb ◽  
Hadi M. Yassine ◽  
Fatiha M. Benslimane ◽  
Maria K. Smatti ◽  
Sven Schuchardt ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Critically Ill ◽  
Pearson Correlation ◽  
Invasive Mechanical Ventilation ◽  
Predictive Biomarkers ◽  
Published Data ◽  
Metabolomics Data ◽  
Model Based

Introduction: Detection of early metabolic changes in critically-ill coronavirus disease 2019 (COVID-19) patients under invasive mechanical ventilation (IMV) at the intensive care unit (ICU) could predict recovery patterns and help in disease management.Methods: Targeted metabolomics of serum samples from 39 COVID-19 patients under IMV in ICU was performed within 48 h of intubation and a week later. A generalized linear model (GLM) was used to identify, at both time points, metabolites and clinical traits that predict the length of stay (LOS) at ICU (short ≤ 14 days/long >14 days) as well as the duration under IMV. All models were initially trained on a set of randomly selected individuals and validated on the remaining individuals in the cohort. Further validation in recently published metabolomics data of COVID-19 severity was performed.Results: A model based on hypoxanthine and betaine measured at first time point was best at predicting whether a patient is likely to experience a short or long stay at ICU [area under curve (AUC) = 0.92]. A further model based on kynurenine, 3-methylhistidine, ornithine, p-cresol sulfate, and C24.0 sphingomyelin, measured 1 week later, accurately predicted the duration of IMV (Pearson correlation = 0.94). Both predictive models outperformed Acute Physiology and Chronic Health Evaluation II (APACHE II) scores and differentiated COVID-19 severity in published data.Conclusion: This study has identified specific metabolites that can predict in advance LOS and IMV, which could help in the management of COVID-19 cases at ICU.

scholarly journals Respiratory Modalities in Preventing Reintubation in a Pediatric Intensive Care Unit

2021 ◽  
Vol 8 ◽  
pp. 2333794X2199153
Author(s):  
Ameer Al-Hadidi ◽  
Morta Lapkus ◽  
Patrick Karabon ◽  
Begum Akay ◽  
Paras Khandhar
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Pediatric Intensive Care Unit ◽  
Noninvasive Positive Pressure Ventilation ◽  
Pediatric Intensive Care ◽  
Nasal Cannula ◽  
Respiratory Support ◽  
Positive Pressure ◽  
P Value

Post-extubation respiratory failure requiring reintubation in a Pediatric Intensive Care Unit (PICU) results in significant morbidity. Data in the pediatric population comparing various therapeutic respiratory modalities for avoiding reintubation is lacking. Our objective was to compare therapeutic respiratory modalities following extubation from mechanical ventilation. About 491 children admitted to a single-center PICU requiring mechanical ventilation from January 2010 through December 2017 were retrospectively reviewed. Therapeutic respiratory support assisted in avoiding reintubation in the majority of patients initially extubated to room air or nasal cannula with high-flow nasal cannula (80%) or noninvasive positive pressure ventilation (100%). Patients requiring therapeutic respiratory support had longer PICU LOS (10.92 vs 6.91 days, P-value = .0357) and hospital LOS (16.43 vs 10.20 days, P-value = .0250). Therapeutic respiratory support following extubation can assist in avoiding reintubation. Those who required therapeutic respiratory support experienced a significantly longer PICU and hospital LOS. Further prospective clinical trials are warranted.

Determinants of the Need for Intensive Care and Prolonged Mechanical Ventilation in Patients Undergoing Bariatric Surgery

2004 ◽  
Vol 14 (8) ◽  
pp. 1036-1041 ◽  
Author(s):  
Thomas S. Helling ◽  
Thomas L. Willoughby ◽  
Daniel M. Maxfield ◽  
Patricia Ryan
Keyword(s):  
Bariatric Surgery ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Prolonged Mechanical Ventilation

scholarly journals Healthcare trajectories before and after critical illness: population-based insight on diverse patients clusters

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Youenn Jouan ◽  
Leslie Grammatico-Guillon ◽  
Noémie Teixera ◽  
Claire Hassen-Khodja ◽  
Christophe Gaborit ◽  
...  
Keyword(s):  
Septic Shock ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Critical Illness ◽  
Length Of Stay ◽  
Population Based ◽  
Hospital Length Of Stay ◽  
Healthcare Use ◽  
Icu Admission ◽  
Icu Discharge

Abstract Background The post intensive care syndrome (PICS) gathers various disabilities, associated with a substantial healthcare use. However, patients’ comorbidities and active medical conditions prior to intensive care unit (ICU) admission may partly drive healthcare use after ICU discharge. To better understand retative contribution of critical illness and PICS—compared to pre-existing comorbidities—as potential determinant of post-critical illness healthcare use, we conducted a population-based evaluation of patients’ healthcare use trajectories. Results Using discharge databases in a 2.5-million-people region in France, we retrieved, over 3 years, all adult patients admitted in ICU for septic shock or acute respiratory distress syndrome (ARDS), intubated at least 5 days and discharged alive from hospital: 882 patients were included. Median duration of mechanical ventilation was 11 days (interquartile ranges [IQR] 8;20), mean SAPS2 was 49, and median hospital length of stay was 42 days (IQR 29;64). Healthcare use (days spent in healthcare facilities) was analyzed 2 years before and 2 years after ICU admission. Prior to ICU admission, we observed, at the scale of the whole study population, a progressive increase in healthcare use. Healthcare trajectories were then explored at individual level, and patients were assembled according to their individual pre-ICU healthcare use trajectory by clusterization with the K-Means method. Interestingly, this revealed diverse trajectories, identifying patients with elevated and increasing healthcare use (n = 126), and two main groups with low (n = 476) or no (n = 251) pre-ICU healthcare use. In ICU, however, SAPS2, duration of mechanical ventilation and length of stay were not different across the groups. Analysis of post-ICU healthcare trajectories for each group revealed that patients with low or no pre-ICU healthcare (which represented 83% of the population) switched to a persistent and elevated healthcare use during the 2 years post-ICU. Conclusion For 83% of ARDS/septic shock survivors, critical illness appears to have a pivotal role in healthcare trajectories, with a switch from a low and stable healthcare use prior to ICU to a sustained higher healthcare recourse 2 years after ICU discharge. This underpins the hypothesis of long-term critical illness and PICS-related quantifiable consequences in healthcare use, measurable at a population level.

scholarly journals 375. COVID 19 infection in a Massachusetts community hospital

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S257-S258
Author(s):  
Raul Davaro ◽  
alwyn rapose
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Essential Hypertension ◽  
Severe Acute Respiratory Syndrome ◽  
High Mortality ◽  
Case Series ◽  
World Health ◽  
Minimal Risk ◽  
The Impact

Abstract Background The ongoing pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has led to 105690 cases and 7647 deaths in Massachusetts as of June 16. Methods The study was conducted at Saint Vincent Hospital, an academic health medical center in Worcester, Massachusetts. The institutional review board approved this case series as minimal-risk research using data collected for routine clinical practice and waived the requirement for informed consent. All consecutive patients who were sufficiently medically ill to require hospital admission with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample were included. Results A total of 109 consecutive patients with COVID 19 were admitted between March 15 and May 31. Sixty one percent were men, the mean age of the cohort was 67. Forty one patients (37%) were transferred from nursing homes. Twenty seven patients died (24%) and the majority of the dead patients were men (62%). Fifty one patients (46%) required admission to the medical intensive care unit and 34 necessitated mechanical ventilation, twenty two patients on mechanical ventilation died (63%). The most common co-morbidities were essential hypertension (65%), obesity (60%), diabetes (33%), chronic kidney disease (22%), morbid obesity (11%), congestive heart failure (16%) and COPD (14%). Five patients required hemodialysis. Fifty five patients received hydroxychloroquine, 24 received tocilizumab, 20 received convalescent plasma and 16 received remdesivir. COVID 19 appeared in China in late 2019 and was declared a pandemic by the World Health Organization on March 11, 2020. Our study showed a high mortality in patients requiring mechanical ventilation (43%) as opposed to those who did not (5.7%). Hypertension, diabetes and obesity were highly prevalent in this aging population. Our cohort was too small to explore the impact of treatment with remdesivir, tocilizumab or convalescent plasma. Conclusion In this cohort obesity, diabetes and essential hypertension are risk factors associated with high mortality. Patients admitted to the intensive care unit who need mechanical ventilation have a mortality approaching 50 %. Disclosures All Authors: No reported disclosures

scholarly journals Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit

2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Nathan J Smischney ◽  
Venu M Velagapudi ◽  
James A Onigkeit ◽  
Brian W Pickering ◽  
Vitaly Herasevich ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Search Algorithm
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