Risk Of Prolonged Mechanical Ventilation Research Articles

The impact of comorbidities on prolonged mechanical ventilation in patients with chronic obstructive pulmonary disease

BackgroundIn patients with chronic obstructive pulmonary disease (COPD) and acute respiratory failure, approximately 10% of them are considered to be at high risk for prolonged mechanical ventilation (PMV, > 21 days). PMV have been identified as independent predictors of unfavorable outcomes. Our previous study revealed that patients aged 70 years older and COPD severity were at a significantly higher risk for PMV. We aimed to analyze the impact of comorbidities and their associated risks in patients with COPD who require PMV.MethodsThe data used in this study was collected from Kaohsiung Medical University Hospital Research Database. The COPD subjects were the patients first diagnosed COPD (index date) between January 1, 2012 and December 31, 2020. The exclusion criteria were the patients with age less than 40 years, PMV before the index date or incomplete records. COPD and non-COPD patients, matched controls were used by applying the propensity score matching method.ResultsThere are 3,744 eligible patients with COPD in the study group. The study group had a rate of 1.6% (60 cases) patients with PMV. The adjusted HR of PMV was 2.21 (95% CI 1.44–3.40; P < 0.001) in the COPD patients than in non-COPD patients. Increased risks of PMV were found significantly for patients with diabetes mellitus (aHR 4.66; P < 0.001), hypertension (aHR 3.20; P = 0.004), dyslipidemia (aHR 3.02; P = 0.015), congestive heart failure (aHR 6.44; P < 0.001), coronary artery disease (aHR 3.11; P = 0.014), stroke (aHR 6.37; P < 0.001), chronic kidney disease (aHR 5.81 P < 0.001) and Dementia (aHR 5.78; P < 0.001).ConclusionsAge, gender, and comorbidities were identified as significantly higher risk factors for PMV occurrence in the COPD patients compared to the non-COPD patients. Beyond age, comorbidities also play a crucial role in PMV in COPD.

A Predictive Model for Prolonged Mechanical Ventilation After Triple-Branched Stent Graft for Acute Type A Aortic Dissection

IntroductionThe aim of this study is to develop a model for predicting the risk of prolonged mechanical ventilation (PMV) following surgical repair of acute type A aortic dissection (AAAD). MethodsWe retrospectively collected clinical data from 381 patients with AAAD who underwent emergency surgery. Clinical features variables for predicting postoperative PMV were selected through univariate analysis, least absolute shrinkage and selection operator regression analysis, and multivariate logistic regression analysis. A risk prediction model was established using a nomogram. The model’s accuracy and reliability were evaluated using the area under the curve of the receiver operating characteristic curve and the calibration curve. Internal validation of the model was performed using bootstrap resampling. The clinical applicability of the model was assessed using decision curve analysis and clinical impact curve. ResultsAmong the 381 patients, 199 patients (52.2%) experienced postoperative PMV. The predictive model exhibited good discriminative ability (area under the curve = 0.827, 95% confidence interval: 0.786-0.868, P < 0.05). The calibration curve confirmed that the predicted outcomes of the model closely approximated the ideal curve, indicating agreement between the predicted and actual results (with an average absolute error of 0.01 based on 1000 bootstrap resampling). The decision curve analysis curve demonstrated that the model has significant clinical value. ConclusionsThe nomogram model established in this study can be used to predict the risk of postoperative PMV in patients with AAAD. It serves as a practical tool to assist clinicians in adjusting treatment strategies promptly and implementing targeted therapeutic measures.

Estimating risk of prolonged mechanical ventilation after liver transplantation in children: PROVE-ALT score.

Children at high risk for prolonged mechanical ventilation (PMV) after liver transplantation (LT) need to be identified early to optimize pulmonary support, allocate resources, and improve surgical outcomes. We aimed to develop and validate a metric that can estimate risk for Prolonged Ventilation After LT (PROVE-ALT). We identified preoperative risk factors for PMV by univariable analysis in a retrospective cohort of pediatric LT recipients between 2011 and 2017 (n = 205; derivation cohort). We created the PROVE-ALT score by mapping multivariable logistic regression coefficients as integers, with cutoff values using the Youden Index. We validated the score by C-statistic in a retrospectively collected separate cohort of pediatric LT recipients between 2018 and 2021 (n = 133, validation cohort). Among total 338 patients, 21% (n = 72) were infants; 49% (n = 167) had cirrhosis; 8% (n = 27) required continuous renal replacement therapy (CRRT); and 32% (n = 111) required management in hospital (MIH) before LT. Incidence of PMV post-LT was 20% (n = 69) and 3% (n = 12) required tracheostomy. Independent risk factors (OR [95% CI]) for PMV were cirrhosis (3.8 [1-14], p = .04); age <1-year (8.2 [2-30], p = .001); need for preoperative CRRT (6.3 [1.2-32], p = .02); and MIH before LT (12.4 [2.1-71], p = .004). PROVE-ALT score ≥8 [Range = 0-21] accurately predicted PMV in the validation cohort with 73% sensitivity and 80% specificity (AUC: 0.81; 95% CI: 0.71-0.91). PROVE-ALT can predict PMV after pediatric LT with a high degree of sensitivity and specificity. Once externally validated in other centers, PROVE-ALT will empower clinicians to plan patient-specific ventilation strategies, provide parental anticipatory guidance, and optimize hospital resources.

Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation.

Prolonged mechanical ventilation (PMV) after lung transplantation poses several risks, including higher tracheostomy rates and increased in-hospital mortality. Mechanical power (MP) of artificial ventilation unifies the ventilatory variables that determine gas exchange and may be related to allograft function following transplant, affecting ventilator weaning. We retrospectively analyzed consecutive double lung transplant recipients at a national transplant center, ventilated through endotracheal tubes upon ICU admission, excluding those receiving extracorporeal support. MP and derived indexes assessed up to 36h after transplant were correlated with invasive ventilation duration using Spearman's coefficient, and we conducted receiver operating characteristic (ROC) curve analysis to evaluate the accuracy in predicting PMV (>72h), expressed as area under the ROC curve (AUROC). PMV occurred in 82 (35%) out of 237 cases. MP was significantly correlated with invasive ventilation duration (Spearman's ρ = 0.252 [95% CI 0.129-0.369], p < 0.01), with power density (MP normalized to lung-thorax compliance) demonstrating the strongest correlation (ρ = 0.452 [0.345-0.548], p < 0.01) and enhancing PMV prediction (AUROC 0.78 [95% CI 0.72-0.83], p < 0.01) compared to MP (AUROC 0.66 [0.60-0.72], p < 0.01). Mechanical power density may help identify patients at risk for PMV after double lung transplantation.

Congenital heart diseases with airway stenosis: a predictive nomogram to risk-stratify patients without airway intervention

BackgroundThis study focused on congenital heart disease (CHD) patients complicated with airway stenosis (AS) without airway intervention and aimed to identify the patients with potential risks.MethodsPatients diagnosed with CHD and AS were enrolled in this retrospective study. The primary outcome was defined as a postoperative mechanical ventilation duration of more than two weeks. We constructed a prediction model to predict the risk of prolonged mechanical ventilation (PMV).ResultsA total of 185 patients diagnosed with CHD and AS in Fuwai Hospital from July 2009 to December 2022 were included in the study. Weight at CHD surgery, cardiopulmonary bypass (CPB) duration, complex CHD and comorbid tracheobronchomalacia were identified as risk factors and included in the model. The ROC curve showed a good distinguishing ability, with an AUC of 0.847 (95% CI: 0.786–0.908). According to the optimal cut-off value of the ROC curve, patients were divided into high- and low-risk groups, and the subsequent analysis showed significant differences in peri-operative characteristics and in-hospital deaths.ConclusionsWith the predictive model, several factors could be used to assess the risky patients with PMV. More attention should be paid to these patients by early identification and routine surveillance.

Prediction prolonged mechanical ventilation in trauma patients of the intensive care unit according to initial medical factors: a machine learning approach

The goal of this study was to develop a predictive machine learning model to predict the risk of prolonged mechanical ventilation (PMV) in patients admitted to the intensive care unit (ICU), with a focus on laboratory and Arterial Blood Gas (ABG) data. This retrospective cohort study included ICU patients admitted to Rajaei Hospital in Shiraz between 2016 and March 20, 2022. All adult patients requiring mechanical ventilation and seeking ICU admission had their data analyzed. Six models were created in this study using five machine learning models (PMV more than 3, 5, 7, 10, 14, and 23 days). Patients’ demographic characteristics, Apache II, laboratory information, ABG, and comorbidity were predictors. This study used Logistic regression (LR), artificial neural networks (ANN), support vector machines (SVM), random forest (RF), and C.5 decision tree (C.5 DT) to predict PMV. The study enrolled 1138 eligible patients, excluding brain-dead patients and those without mechanical ventilation or a tracheostomy. The model PMV > 14 days showed the best performance (Accuracy: 83.63–98.54). The essential ABG variables in our two optimal models (artificial neural network and decision tree) in the PMV > 14 models include FiO2, paCO2, and paO2. This study provides evidence that machine learning methods outperform traditional methods and offer a perspective for achieving a consensus definition of PMV. It also introduces ABG and laboratory information as the two most important variables for predicting PMV. Therefore, there is significant value in deploying such models in clinical practice and making them accessible to clinicians to support their decision-making.

Characterization of children receiving mechanical ventilation at the Pediatric Centre, Hue Central Hospital

Methods: A cross-sectional study with convenient samples of 33 children receiving mechanical ventilation at the Pediatric Center of Hue Central Hospital from May, 2018 to February, 2019. Results: The most common age category (63.6%) was under 12 months, with a median age of 6.0 months. After failing to respond to oxygen therapy or NCPAP, 60.6% of pediatric patients were placed on mechanical ventilation. The most common causes were respiratory diseases (63.6%); shock (24.2%); and neurological diseases (9.1%), with pneumonia and septic shock being the most common diseases (57.6% and 18.2%, respectively). The mortality rate was 63.6%, and it was not related to age group. However, it varied dramatically by disease group, which was particularly high in the pneumonia group associated with congenital heart disease (72.7%) and in the septic shock group (100%). Prolonged mechanical ventilation was recorded at 15.2% of children, primarily those with pneumonia associated with other chronic illnesses (80%). Conclusion: Because of the high risk of prolonged mechanical ventilation and the high mortality rate in mechanical ventilation, pneumonia associated with with congenital heart disease and septic shock were conditions that required to be remarked. Key words: mechanical ventilation, children

Comment on the Need to Fill a Gap in the Assessment of Neurological Status Before Elective Surgery.

Comment on the Need to Fill a Gap in the Assessment of Neurological Status Before Elective Surgery.

A Hemodynamic Echocardiographic Evaluation Predicts Prolonged Mechanical Ventilation in Septic Patients: A Pilot Study.

Prolonged mechanical ventilation (PMV) is common among critically ill septic patients and leads to serious adverse effects. Transthoracic echocardiography (TTE) is an efficient tool for the assessment of septic shock. Our study investigated the relationship between TTE parameters and PMV in mechanically ventilated septic shock patients. TTE was performed in the first 24 h of intensive care unit admission, acquiring data on cardiac output (CO), cardiac index (CI), s' wave (s'), E wave (E), e' wave (e') and E/e' ratio. We compared data on patients who met the criteria for PMV with data on patients who did not. Sixty-four patients were included, 26 of whom met the criteria for PMV. CO, CI and s' were higher in patients who required PMV (5.49 vs. 4.20, p=0.02; 2.95 vs. 2.34, p=0.04; and 12.56 vs. 9.81, p=0.01, respectively). CI correlated with s' (r=0.37, p < 0.01). The areas under the receiver operating characteristic curves for CO, CI and s' in assessing the need for PMV were, respectively, 0.7 (fair results), 0.69 and 0.68 (poor results). Despite a lack of a prognostic model, the observed differences suggest that hemodynamic TTE could provide information on the risk of PMV in septic shock.

The Fontan procedures – early outcomes and predictive factors

Objectives: the aim of this study was to describe the early outcomes after the extracardiac conduit Fontan procedure and evaluate predictive factors related to these results.&#x0D; Methods: a cross – sectional study. We retrospectively reviewed the perioperative medical records of 71 patients with Fontan surgery at Hanoi Heart Hospital between January 2017 and December 2020. Data processing using SPSS 22 software&#x0D; Results: the early mortality and early failure rates with Fontan circulation were 4.2%. High postoperative pulmonary artery pressure was a risk factor for early mortality and early Fontan failure. The mean duration of mechanical ventilation was 62.86±108.17 hours; female, short height, and common atrioventricular valve or double­inlet atrioventricular connection increased the risk of prolonged mechanical ventilation. The mean intensive care unit (ICU) length of stay was 6.46±6.32 days, female, short height, and moderate to severe postoperative atrioventricular valve regurgitation increased the risk of prolonged duration in ICU. The mean time of pleural drainage was 16.96±10.23 days, low weight was a risk factor for prolonged pleural drainage. The mean postoperative hospital stay was 23.89±11.83 days, age at the Fontan surgery, preoperative oxygen saturation, concomitant atrioventricular valve repair, and postoperative atrioventricular valve regurgitation were factors associated with prolonged postoperative hospital stay.&#x0D; Conclusion: the early outcomes after Fontan surgery have been consistent with our condition. There have been many risk factors that influenced early results after surgery, and identifying those factors may help with our treatment.

Risk Factors of Prolonged Mechanical Ventilation in Patients Undergoing Redo Valve Surgery.

Prolonged mechanical ventilation (PMV) after cardiac surgery is associated with high morbidity and mortality. Patients following redo valve surgery possess many attributes that place them at risk for PMV, yet few studies particularly focused on them. The purpose of this study was to identify perioperative variables associated with PMV in redo valve surgery. A retrospective study, including 117 patients who underwent redo valve surgery from November 2017 to September 2021, was performed. The potential perioperative risk factors for PMV were collected. PMV was defined as the need for intubation and mechanical ventilation for >24 h, after completion of the operation. The clinical data were analyzed with univariate and multivariate analyses to identify risk factors for PMV following redo valve surgery. The incidence of PMV was 38.5% (N = 45). Multiple logistic regression analysis showed perioperative risk factors for PMV included advanced age (age>57 years) [odds ratio (OR) 3.043, 95% confidence interval (CI) 1.172-7.905, P = 0.022], low weight (weight ≤58 kg) (OR 2.798, 95% CI: 1.088-7.199, P = 0.033), EuroSCORE II ≥6.8% (OR 3.467, 95% CI: 1.364-8.817, P = 0.009), and VIS at 12 hours post ICU admission (VIS12) >10 (OR 5.613, 95% CI: 2.211-14.249, P < 0.001). In adult patients undergoing redo valve surgery, advanced age, low weight, high EuroSCORE II and a high VIS at 12 hours post-ICU admission were associated with PMV. Hemodynamic status after operation were more important than preoperative and intraoperative variables in predicting PMV.

Risk factors for prolonged mechanical ventilation after congenital heart surgery in pediatric patients

Introduction. Prolonged mechanical ventilation (PMV) is a well-recognized factor as a quality metric for pediatric cardiac surgical programs. Most of the risk factors for PMV are described and analyzed. Some authors had established predictive models to detect proactively patients in risk for PMV. This study aims to develop a new predictive model, based on vasoactive-ventilation-renal (VVR) score, for PMV after congenital heart surgery (CHS) in pediatric patients. Material and Methods. Medical &amp;#64257; les of patients 0-18 y who underwent heart surgery in 2016 and 2017 were reviewed. Patients that met the inclusion criteria were studied. PMV was de&amp;#64257; ned as invasive mechanical ventilation &amp;ge; 96 h. The patients were divided in two groups according to duration of mechanical ventilation: group 1-patients with PMV, group 2-patients without PMV. The focus was set on VVR score and &amp;#64258; uid overload in the &amp;#64257; rst 48 hours after the operation. Data were presented as medians with IQR or as means &amp;plusmn; standard deviation. A non-parametric Mann-Whitney U test, binary logistic regression test and ROC&amp;nbsp;curve analysis integrated in the statistical software SPSS 24.0 were used. A value of P &lt; 0.05 was considered signi&amp;#64257; cant. Results. 438 patients were operated in 2016 and 2017 and 384 of them were included in the study. 80 patients (20.8%) needed PMV (group 1) and 304 (79.2%) did not need PMV (group 2). There was a statistical signi&amp;#64257; cance between group 1 and group 2 concerning the peak VVR for the day of operation 58,25(33,48) vs. 25,65(19,8) and cumulative &amp;#64258; uid overload in % for the &amp;#64257; rst 48hours +2,54(13,29) vs. &amp;ndash; 1,19(3,4). After combining this two factors in a predictive model, the ROC curve analysis showed AUC 0,903 (95% CI 0,863-0,944) with sensitivity of 86.25% and speci&amp;#64257; city of 82,57%. Conclusion. Combining VVR and cumulative &amp;#64258; uid overload, resulted in establishment of a new reliable predictive model for PMV after CHS in pediatric patients in our Center.

An in-depth look at ventilator-associated pneumonia in trauma patients and efforts to increase bundle compliance, education and documentation in a surgical trauma critical care unit

BackgroundVentilator-associated pneumonia (VAP) is considered the most common hospital acquired infection seen in critical care settings and leading cause of death in Intensive Care Units (ICU). The objective of this study was to assess whether specimen collection impacted diagnosis and if implementation of a VAP bundle would decrease rates at our center. MethodsThis single center study design is a retrospective chart review from 2017 to 2020 utilizing the electronic medical record. A pre-/postintervention comparison was performed following implementation of a unit wide VAP bundle and nursing education. Descriptive statistics and continuous variables were analyzed with independent group t -tests, and categorical variables were analyzed with chi-squared tests. ResultsVentilator-associated pneumonia rates decreased in the postimplementation time (20.8%, n = 74 vs 12.2%, n = 15; P = .03). There were no significant differences in the patient profile of those who acquired VAP (ie, males 79.7% vs 86.7%, blunt injuries 63.5% vs 86.7% and severity scores 24.8 vs 25.1, pre vs postimplementation, respectively, all P-values greater than .05). Discussion/ConclusionsReduction in VAP rates were achieved by implementing a standardized, evidence based, prevention protocol. Further research is warranted as studies have noted that patients requiring mechanical ventilation are at greater risk for VAP than other ICU patients due to the nature of their injuries and increased risk of prolonged mechanical ventilation ≥ 21 days.

Peri-operative outcomes of mitral valve surgery at Charlotte Maxeke Johannesburg Academic Hospital

Background: The distribution and determinants of heart disease vary greatly between high-income countries and sub-Saharan Africa where rheumatic heart disease (RHD) is a major public health challenge. Studies from Africa report that RHD is the main cause of cardiovascular morbidity and mortality in the young. Data on mitral valve surgery outcomes in South Africa are limited. The aim of this study was to describe the peri-operative outcomes of patients that have undergone mitral valve surgery at the Charlotte Maxeke Johannesburg Academic Hospital (CMJAH). Methods: All patients older than 18 years who underwent mitral valve surgery at CMJAH between 1 January 2015 and 31 December 2018 were retrospectively included. Cardiac intensive care records including anaesthesia charts were assessed to describe preoperative, intra-operative and post-operative data of each patient. Pre-operative data included patient demographics and comorbidities. Intra-operative data included aortic clamp and bypass times. Post-operative variables included outcomes such as sepsis, bleeding, re-operation, and the development of acute kidney injury (AKI). The pre-operative, intra-operative and post-operative outcomes were compared to determine the effect each variable had on post-operative mortality. Results: Two hundred and seventeen patients underwent mitral valve surgery at CMJAH between 1 January 2015 and 31 December 2018. Four patients’ records were incomplete. RHD was found to be the primary aetiology for mitral valve surgery at CMJAH with a mortality rate of 6.1%. Pre-operative findings that contributed to mortality were: EuroSCORE&gt;2%, preoperative ventilation, dialysis dependence, pre-operative inotropic support, chronic obstructive pulmonary disease, congestive cardiac failure, renal insufficiency, low ejection fraction and New York Heart Association functional class ≥III. Post-operative findings that contributed to increased mortality were prolonged mechanical ventilation, pneumonia, re-operation, AKI, sepsis, bleeding, and transfusion. Increased aortic clamping and cardiopulmonary bypass times increased the risk of prolonged mechanical ventilation, re-operations, pacemaker implantations, AKI, and bleeding. Conclusions: RHD was found to be the primary aetiology for mitral valve surgery at CMJAH with a mortality of 6.1%. Pre-operative, intra-operative and post-operative predictors of outcomes in this study confirm observations made in other parts of the world.

Acute Gastrointestinal Injury and Feeding Intolerance as Prognostic Factors in Critically Ill COVID-19 Patients

BackgroundAlthough acute gastrointestinal injury (AGI) and feeding intolerance (FI) are known independent determinants of worse outcomes and high mortality in intensive care unit (ICU) patients, the incidence of AGI and FI in critically ill COVID-19 patients and their prognostic importance have not been thoroughly studied. MethodsWe reviewed 218 intubated patients at Stony Brook University Hospital and stratified them into three groups based on AGI severity, according to data collected in the first 10 days of ICU course. We used chi-square test to compare categorical variables such as age and sex and two-sample t-test or Mann-Whitney U-tests for continuous variables, including important laboratory values. Cox proportional hazards regression models were utilized to determine whether AGI score was an independent predictor of survival, and multivariable analysis was performed to compare risk factors that were deemed significant in the univariable analysis. We performed Kaplan-Meier survival analysis based on the AGI score and the presence of FI. ResultsThe overall incidence of AGI was 95% (45% AGI I/II, 50% AGI III/IV), and FI incidence was 63%. Patients with AGI III/IV were more likely to have prolonged mechanical ventilation (22 days vs 16 days, P-value <0.002) and higher mortality rate (58% vs 28%, P-value <0.001) compared to patients with AGI 0/I/II. This was confirmed with multivariable analysis which showed that AGI score III/IV was an independent predictor of higher mortality (AGI III/IV vs AGI 0/I/II hazard ratio (HR), 2.68; 95% confidence interval (CI), 1.69–4.25; P-value <0.0001). Kaplan-Meier survival analysis showed that both AGI III/IV and FI (P-value <0.001) were associated with worse outcomes. Patients with AGI III/IV had higher daily and mean D-dimer and CRP levels compared to AGI 0/I/II (P-value <0.0001). ConclusionsThe prevalence of AGI and FI among critically ill COVID-19 patients was high. AGI grades III/IV were associated with higher risk for prolonged mechanical ventilation and mortality compared to AGI 0/I/II, while it also correlated with higher D-dimer and C-reactive protein (CRP) levels. FI was independently associated with higher mortality. The development of high-grade AGI and FI during the first days of ICU stay can serve as prognostic tools to predict outcomes in critically ill COVID-19 patients.

Thickness of rectus abdominis measured by ultrasound in critically ill patients after abdominal surgery: A retrospective cohort study.

Early identification of patients at high risk of prolonged mechanical ventilation is important in critical care. Sarcopenia, the loss of muscle mass and function, has been reported to be associated with extended mechanical ventilation and prolonged ICU stay. Although ultrasound is noninvasive and widely used in critical care, there is no standard method of using it to assess sarcopenia. The study aims to investigate the relationship between outcomes of critically ill patients and the ratio of BMI to the thickness of rectus abdominis measured by a standardised ultrasound examination. A retrospective cohort study. Surgical ICU of a tertiary referral hospital, from October 2017 to June 2018. The thickness of rectus abdominis (RA) was measured while performing extended focused assessment sonography for trauma. BMI was divided by the thickness of rectus abdominis over the upper abdomen to derive the BMI-RA thickness ratio. Sixteen male and 11 female patients admitted to ICU after major abdominal surgery. The primary outcome was in-hospital mortality, and the secondary outcomes were durations of mechanical ventilation, ICU stay and hospital stay. The disease severity, serum albumin level and BMI-RA thickness ratio were also analysed. Ultrasound measurement was easy to perform without adverse effects. The BMI-RA thickness ratio was significantly higher in nonsurvivors and was associated with ICU stay, hospital stay and duration of mechanical ventilation. Multivariable logistic regression showed that the BMI-RA thickness ratio was a predictor of in-hospital mortality. The BMI-RA thickness ratio is related to the outcomes of patients transferred to ICU after major abdominal surgery. Measuring the thickness of rectus abdominis by ultrasound is well tolerated and easy to perform in surgical ICU. Larger prospective studies are required to confirm current findings.

198. Infective Endocarditis Among Solid Organ Transplant Recipients in the United States

BackgroundWith over 30,000 solid organ transplants (SOT) performed annually the United States alone, there is an urgent need to understand the risks and outcomes of infective endocarditis (IE) in SOT recipients.MethodsWe used data from the 2013–2017 Nationwide Readmissions Database (NRD). Hospitalizations associated with IE were identified using diagnosis and procedure codes. The cohort included all patients with IE, stratified by history of solid organ transplant (heart, liver, kidney, lung, intestines, pancreas). Outcomes included 60-day rates of mortality, (extracorporeal membrane oxygenation) ECMO deployment, thromboembolic events, length of stay, and inpatient costs. Regression models, weighted to account for the NRD sample design, were used to model associations between outcomes and transplant history, adjusting for patient age, sex, facility characteristics, comorbid conditions, and potential IE organism.ResultsA total of 175,682 hospitalizations associated with IE, corresponding to a national estimate of 345,236, were included. Of these, 1,299 (weighted estimate = 2,511) were associated with history of transplant. Transplant recipients were younger (54.2 vs. 59.4 years, p < 0.001), less likely to be female (33.2% vs. 40.1%), had higher rates of renal and liver disease (93.1% vs. 39.2% and 16.2% vs. 8.6%, respectively, p < 0.001 for both). The most common SOT organ (allowing for multiple organs) was kidney (75%) followed by liver (11.5%) and heart (10.5%). Compared to non-SOT patients with IE, SOT recipients with IE were associated with lower risk of mortality [adjusted relative risk (aRR): 0.74, 95% confidence interval (CI) (0.61, 0.89)], lower risk of prolonged mechanical ventilation [aRR 0.80 (0.68, 0.93)], 2.2 fewer inpatient days (-3.5 to -0.8) and $7,000 lower charges (-$9,700, -$4,300), after adjustment. ConclusionIE complicated by SOT history was associated with paradoxically better outcomes than IE in patients without SOT history. The selection process underlying receipt of transplant may partially explain these differences in outcomes.Disclosures Vance G. Fowler, Jr., MD, MHS, Achaogen (Consultant)Actavis (Grant/Research Support)Advanced Liquid Logics (Grant/Research Support)Affinergy (Consultant, Research Grant or Support)Affinium (Consultant)Allergan (Grant/Research Support)Ampliphi Biosciences (Consultant)Basilea (Consultant, Research Grant or Support)Bayer (Consultant)C3J (Consultant)Cerexa (Consultant, Research Grant or Support)Contrafect (Consultant, Research Grant or Support)Cubist (Grant/Research Support)Debiopharm (Consultant)Destiny (Consultant)Durata (Consultant)Forest (Grant/Research Support)Genentech (Consultant, Research Grant or Support)Integrated Biotherapeutics (Consultant)Janssen (Consultant, Research Grant or Support)Karius (Grant/Research Support)Locus (Grant/Research Support)Medical Biosurfaces (Grant/Research Support)Medicines Co. (Consultant)Medimmune (Consultant, Research Grant or Support)Merck (Consultant, Research Grant or Support)NIH (Grant/Research Support)Novadigm (Consultant)Novartis (Consultant, Research Grant or Support)Pfizer (Grant/Research Support)Regeneron (Consultant, Research Grant or Support)Tetraphase (Consultant)Theravance (Consultant, Research Grant or Support)Trius (Consultant)xBiotech (Consultant)

Association between procalcitonin levels and duration of mechanical ventilation in COVID-19 patients.

BackgroundPatients diagnosed with COVID-19 frequently require mechanical ventilation. Knowledge of laboratory tests associated with the prolonged need for mechanical ventilation may guide resource allocation. We hypothesized that an elevated plasma procalcitonin level (>0.1 ng/ml) would be associated with the duration of invasive mechanical ventilation.MethodsPatients diagnosed with COVID-19, who were admitted to any of our health system’s hospitals between March 9th-April 20th, 2020 and required invasive mechanical ventilation, were eligible for this observational cohort study. Demographics, comorbidities, components of the Sequential Organ Failure Assessment score, and procalcitonin levels on admission were obtained from the electronic health record. The primary outcome was the duration of mechanical ventilation; secondary outcomes included 28-day mortality and time to intubation. Outcomes were assessed within the first 28 days of admission. Baseline demographics and comorbidities were summarized by descriptive statistics. Univariate comparisons were made using Pearson’s chi-square test for binary outcomes and Mann-Whitney U test for continuous outcomes. A multiple linear regression was fitted to assess the association between procalcitonin levels and the duration of mechanical ventilation.ResultsPatients with an initial procalcitonin level >0.1 ng/ml required a significantly longer duration of mechanical ventilation than patients with a level of ≤0.1 ng/ml (p = 0.021) in the univariate analysis. There was no significant difference in 28-day mortality or time to intubation between the two groups. After adjusted analysis using multivariable linear regression, the duration of mechanical ventilation was, on average, 5.6 (p = 0.016) days longer in patients with an initial procalcitonin level >0.1 ng/ml.ConclusionIn this cohort of 93 mechanically ventilated COVID-19 patients, we found an association between an initial plasma procalcitonin level >0.1 ng/ml and the duration of mechanical ventilation. These findings may help to identify patients at risk for prolonged mechanical ventilation upon admission.

Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach.

ObjectivesWe aimed to build a machine learning predictive model to predict the risk of prolonged mechanical ventilation (PMV) for patients with Traumatic Brain Injury (TBI).MethodsThis study included TBI patients who were hospitalized in a level 1 trauma center between January 2014 and February 2019. Data were analyzed for all adult patients who received mechanical ventilation following TBI with abbreviated injury severity (AIS) score for the head region of ≥ 3. This study designed three sets of machine learning models: set A defined PMV to be greater than 7 days, set B (PMV > 10 days) and set C (PMV >14 days) to determine the optimal model for deployment. Patients’ demographics, injury characteristics and CT findings were used as predictors. Logistic regression (LR), Artificial neural networks (ANN) Support vector machines (SVM), Random Forest (RF) and C.5 Decision Tree (C.5 DT) were used to predict the PMV.ResultsThe number of eligible patients that were included in the study were 674, 643 and 622 patients in sets A, B and C respectively. In set A, LR achieved the optimal performance with accuracy 0.75 and Area under the curve (AUC) 0.83. SVM achieved the optimal performance among other models in sets B with accuracy/AUC of 0.79/0.84 respectively. ANNs achieved the optimal performance in set C with accuracy/AUC of 0.76/0.72 respectively. Machine learning models in set B demonstrated more stable performance with higher prediction success and discrimination power.ConclusionThis study not only provides evidence that machine learning methods outperform the traditional multivariate analytical methods, but also provides a perspective to reach a consensual definition of PMV.

Respiratory Neurophysiology in Intensive Care Unit.

Patients with intensive care unit-acquired weakness have an increased risk of prolonged mechanical ventilation, which is a risk factor for prolonged stay and mortality. The most common cause of this problem is weakness of the diaphragm, which can derive from phrenic nerve injury associated with critical neuropathy, or with the complex multiorgan failure/systemic respiratory response syndrome causing muscle fiber lesion. Two conventional neurophysiological techniques are useful to investigate the respiratory muscles, phrenic nerve conduction, and needle electromyography of the accessory respiratory muscles and diaphragm. Phrenic nerve stimulation is a standard noninvasive technique; amplitude of the motor response can be reduced because of muscle fiber inexcitability or axonal loss. Electromyography of the diaphragm is an invasive method but is safe if performed as indicated. It can reveal neurogenic or myopathic motor units. Although these neurophysiological methods have limitations in the investigation of intensive care unit patients with severe respiratory involvement, normal phrenic nerve responses should exclude marked axonal loss and indicate a better prognosis.