A Multicenter Trial of Vena Cava Filters in Severely Injured Patients.

BACKGROUND: Whether early placement of an inferior vena cava filter reduces the risk of pulmonary embolism or death in severely injured patients who have a contraindication to prophylactic anticoagulation is not known. METHODS: In this multicenter, randomized, controlled trial, we assigned 240 severely injured patients (Injury Severity Score >15 [scores range from 0 to 75, with higher scores indicating more severe injury]) who had a contraindication to anticoagulant agents to have a vena cava filter placed within the first 72 hours after admission for the injury or to have no filter placed. The primary end point was a composite of symptomatic pulmonary embolism or death from any cause at 90 days after enrollment; a secondary end point was symptomatic pulmonary embolism between day 8 and day 90 in the subgroup of patients who survived at least 7 days and did not receive prophylactic anticoagulation within 7 days after injury. All patients underwent ultrasonography of the legs at 2 weeks; patients also underwent mandatory computed tomographic pulmonary angiography when prespecified criteria were met. RESULTS: The median age of the patients was 39 years, and the median Injury Severity Score was 27. Early placement of a vena cava filter did not result in a significantly lower incidence of symptomatic pulmonary embolism or death than no placement of a filter (13.9% in the vena cava filter group and 14.4% in the control group; hazard ratio, 0.99; 95% confidence interval [CI], 0.51 to 1.94; P = 0.98). Among the 46 patients in the vena cava filter group and the 34 patients in the control group who did not receive prophylactic anticoagulation within 7 days after injury, pulmonary embolism developed in none of those in the vena cava filter group and in 5 (14.7%) in the control group, including 1 patient who died (relative risk of pulmonary embolism, 0; 95% CI, 0.00 to 0.55). An entrapped thrombus was found in the filter in 6 patients. CONCLUSIONS: Early prophylactic placement of a vena cava filter after major trauma did not result in a lower incidence of symptomatic pulmonary embolism or death at 90 days than no placement of a filter. (Funded by the Medical Research Foundation of Royal Perth Hospital and others; Australian New Zealand Clinical Trials Registry number, ACTRN12614000963628.).

Biological age is superior to chronological age in predicting hospital mortality of the critically ill.

Biological age is increasingly recognized as being more accurate than chronological age in determining chronic health outcomes. This study assessed whether biological age, assessed on intensive care unit (ICU) admission, can predict hospital mortality. This retrospective cohort study, conducted in a tertiary multidisciplinary ICU in Western Australia, used the Levine PhenoAge model to estimate each patient's biological age (also called PhenoAge). Each patient's PhenoAge was calibrated to generate a regression residual which was equivalent to biological age unexplained by chronological age in the local context. PhenoAgeAccel was a dichotomized measure of the residuals, and its presence suggested that one was biologically older than the corresponding chronological age. Of the 2950 critically ill adult patients analyzed, 291 died (9.9%) before hospital discharge. Both PhenoAge and its residuals (after regressing on chronological age) had a significantly better ability to differentiate between hospital survivors and non-survivors than chronological age (area under the receiver-operating-characteristic curve 0.648 and 0.654 vs. 0.547 respectively). Being phenotypically older than one's chronological age was associated with an increased risk of mortality (PhenoAgeAccel hazard ratio [HR] 1.997, 95% confidence interval [CI] 1.568-2.542; p = 0.001) in a dose-related fashion and did not reach a plateau until at least a 20-year gap. This adverse association remained significant (adjusted HR 1.386, 95% CI 1.077-1.784; p = 0.011) after adjusted for severity of acute illness and comorbidities. PhenoAgeAccel was more prevalent among those with pre-existing chronic cardiovascular disease, end-stage renal failure, cirrhosis, immune disease, diabetes mellitus, or those treated with immunosuppressive therapy. Being phenotypically older than one's chronological age was more common among those with comorbidities, and this was associated with an increased risk of mortality in a dose-related fashion in the critically ill that was not fully explained by comorbidities and severity of acute illness.

Using machine learning to predict bleeding after cardiac surgery.

OBJECTIVES: The primary objective was to predict bleeding after cardiac surgery with machine learning using the data from the Australia New Zealand Society of Cardiac and Thoracic Surgeons Cardiac Surgery Database, cardiopulmonary bypass perfusion database, intensive care unit database and laboratory results. METHODS: We obtained surgical, perfusion, intensive care unit and laboratory data from a single Australian tertiary cardiac surgical hospital from February 2015 to March 2022 and included 2000 patients undergoing cardiac surgery. We trained our models to predict either the Papworth definition or Dyke et al.'s universal definition of perioperative bleeding. Our primary outcome was the performance of our machine learning algorithms using sensitivity, specificity, positive and negative predictive values, accuracy, area under receiver operating characteristics curve (AUROC) and area under precision-recall curve (AUPRC). RESULTS: Of the 2000 patients undergoing cardiac surgery, 13.3% (226/2000) had bleeding using the Papworth definition and 17.2% (343/2000) had moderate to massive bleeding using Dyke et al.'s definition. The best-performing model based on AUPRC was the Ensemble Voting Classifier model for both Papworth (AUPRC 0.310, AUROC 0.738) and Dyke definitions of bleeding (AUPRC 0.452, AUROC 0.797). CONCLUSIONS: Machine learning can incorporate routinely collected data from various datasets to predict bleeding after cardiac surgery.

Modelling survival in acute severe illness: Cox versus accelerated failure time models.

BACKGROUND: The Cox model has been the mainstay of survival analysis in the critically ill and time-dependent covariates have infrequently been incorporated into survival analysis. OBJECTIVES: To model 28-day survival of patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), and compare the utility of Cox and accelerated failure time (AFT) models. METHODS: Prospective cohort study of 168 adult patients enrolled at diagnosis of ALI in 21 adult ICUs in three Australian States with measurement of survival time, censored at 28 days. Model performance was assessed as goodness-of-fit [GOF, cross-products of quantiles of risk and time intervals (P > or = 0.1), Cox model] and explained variation ('R2', Cox and ATF). RESULTS: Over a 2-month study period (October-November 1999), 168 patients with ALI were identified, with a mean (SD) age of 61.5 (18) years and 30% female. Peak mortality hazard occurred at days 7-8 after onset of ALI/ARDS. In the Cox model, increasing age and female gender, plus interaction, were associated with an increased mortality hazard. Time-varying effects were established for patient severity-of-illness score (decreasing hazard over time) and multiple-organ-dysfunction score (increasing hazard over time). The Cox model was well specified (GOF, P > 0.34) and R2 = 0.546, 95% CI: 0.390, 0.781. Both log-normal (R2 = 0.451, 95% CI: 0.321, 0.695) and log-logistic (R2 0.470, 95% CI: 0.346, 0.714) AFT models identified the same predictors as the Cox model, but did not demonstrate convincingly superior overall fit. CONCLUSIONS: Time dependence of predictors of survival in ALI/ARDS exists and must be appropriately modelled. The Cox model with time-varying covariates remains a flexible model in survival analysis of patients with acute severe illness.

Isolated left atrial amyloidosis: acute premitral stenosis secondary to spontaneous intramural left atrial hemorrhagic dissection.

This case presentation describes the very rare condition of isolated atrial amyloidosis and it's associated complications. A 53-year-old male presented to hospital in severe pulmonary edema secondary to spontaneous intramural left atrial hemorrhage and subsequent wall dissection causing acute "pre-mitral valve" obstruction. The patient was subsequently found to have AL subtype amyloid, which has never before been reported in isolated atrial amyloidosis. The prognosis is poor in AL type amyloidosis with cardiac involvement.

Incidence and mortality of acute lung injury and the acute respiratory distress syndrome in three Australian States.

To determine the incidence and 28-d mortality rate for acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) using the 1994 American-European Consensus Conference definitions, we prospectively screened every admission to all 21 adult intensive care units in the States of South Australia, Western Australia, and Tasmania (total population older than 15 yr of age estimated as 2,941,137), between October 1 and November 30, 1999. A total of 1,977 admissions were screened of which 168 developed ALI and 148 developed ARDS, which represents a first incidence of 34 and 28 cases per 100,000 per annum, respectively. The respective 28-d mortality rates were 32% and 34%. The most common predisposing factors for ALI were nonpulmonary sepsis (31%) and pneumonia (28%). Although the incidences of ALI and ARDS are higher and the mortality rates are lower than those reported from studies in other countries, multicenter international studies are required to exclude methodological differences as the cause for this finding.

Effect of inspiratory flow pattern and inspiratory to expiratory ratio on nonlinear elastic behavior in patients with acute lung injury.

Ventilatory modes employing different inspiratory flow patterns and inspiratory to expiratory ratios may alter lung strain in acute lung injury patients. To determine whether variations in lung strain existed between pressure-controlled, volume-controlled, and pressure-controlled inverse ratio modes of ventilation, we randomly applied each for 30 minutes in 18 acute lung injury patients, keeping tidal volume, respiratory rate, fractional inspired oxygen, and total positive end-expiratory pressure constant. After each mode, a multiple linear regression analysis of dynamic airway pressure and airflow was performed with a volume-dependent single compartment model of the equation of motion, and an index of nonlinear elastic behavior was calculated. In five additional patients, concurrent dynamic computerized axial tomography scanning at juxtadiaphragmatic and subcarinal levels was added. Although static mechanics, oxygenation, and hemodynamics were no different between pressure-controlled, volume-controlled, and pressure-controlled inverse ratio ventilation, we found significant differences in nonlinear behavior. This was least with pressure-controlled followed by volume-controlled ventilation, and pressure-controlled inverse ratio ventilation had the greatest nonlinear elastic behavior. Dynamic computerized axial tomography analysis revealed more overinflated units in the left subcarinal slice with pressure-controlled inverse ratio ventilation. Ventilator flow pattern and inspiratory to expiratory ratio independently influence lung strain in acute lung injury; however, further studies are needed to determine the biologic significance.