Guangxi Li

Incidence and transfusion risk factors for transfusion-associated circulatory overload among medical intensive care unit patients

BACKGROUND: Transfusion‐associated circulatory overload (TACO) is a frequent complication of blood transfusion. Investigations identifying risk factors for TACO in critically ill patients are lacking.

Derivation and Validation of Automated Electronic Search Strategies to Extract Charlson Comorbidities From Electronic Medical Records

OBJECTIVE To develop and validate automated electronic note search strategies (automated digital algorithm) to identify Charlson comorbidities. PATIENTS AND METHODS The automated digital algorithm was built by a series of programmatic queries applied to an institutional electronic medical record database. The automated digital algorithm was derived from secondary analysis of an observational cohort study of 1447 patients admitted to the intensive care unit from January 1 through December 31, 2006, and validated in an independent cohort of 240 patients. The sensitivity, specificity, and positive and negative predictive values of the automated digital algorithm and International Classification of Diseases, Ninth Revision (ICD-9) codes were compared with comprehensive medical record review (reference standard) for the Charlson comorbidities. RESULTS In the derivation cohort, the automated digital algorithm achieved a median sensitivity of 100% (range, 99%-100%) and a median specificity of 99.7% (range, 99%-100%). In the validation cohort, the sensitivity of the automated digital algorithm ranged from 91% to 100%, and the specificity ranged from 98% to 100%. The sensitivity of the ICD-9 codes ranged from 8% for dementia to 100% for leukemia, whereas specificity ranged from 86% for congestive heart failure to 100% for leukemia, dementia, and AIDS. CONCLUSION Our results suggest that search strategies that use automated electronic search strategies to extract Charlson comorbidities from the clinical notes contained within the electronic medical record are feasible and reliable. Automated digital algorithm outperformed ICD-9 codes in all the Charlson variables except leukemia, with greater sensitivity, specificity, and positive and negative predictive values.

Derivation and Diagnostic Accuracy of the Surgical Lung Injury Prediction Model

Background:Acute lung injury (ALI) is a serious postoperative complication with limited treatment options. A preoperative risk-prediction model would assist clinicians and scientists interested in ALI. The objective of this investigation was to develop a surgical lung injury prediction (SLIP) model to predict risk of postoperative ALI based on readily available preoperative risk factors. Methods:Secondary analysis of a prospective cohort investigation including adult patients undergoing high-risk surgery. Preoperative risk factors for postoperative ALI were identified and evaluated for inclusion in the SLIP model. Multivariate logistic regression was used to develop the model. Model performance was assessed with the area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test. Results:Out of 4,366 patients, 113 (2.6%) developed early postoperative ALI. Predictors of postoperative ALI in multivariate analysis that were maintained in the final SLIP model included high-risk cardiac, vascular, or thoracic surgery, diabetes mellitus, chronic obstructive pulmonary disease, gastroesophageal reflux disease, and alcohol abuse. The SLIP score distinguished patients who developed early postoperative ALI from those who did not with an area under the receiver operating characteristic curve (95% CI) of 0.82 (0.78–0.86). The model was well calibrated (Hosmer-Lemeshow, P = 0.55). Internal validation using 10-fold cross-validation noted minimal loss of diagnostic accuracy with a mean ± SD area under the receiver operating characteristic curve of 0.79 ± 0.08. Conclusions:Using readily available preoperative risk factors, we developed the SLIP scoring system to predict risk of early postoperative ALI.

The accuracy of natriuretic peptides (brain natriuretic peptide and N-terminal pro-brain natriuretic) in the differentiation between transfusion-related acute lung injury and transfusion-related circulatory overload in the critically ill.

BACKGROUND: The diagnostic workup of transfusion‐related acute lung injury (TRALI) requires an exclusion of transfusion‐associated circulatory overload (TACO). Brain natriuretic peptide (BNP) and N‐terminal pro‐brain natriuretic (NT‐pro‐BNP) accurately diagnosed TACO in preliminary studies that did not include patients with TRALI.

Derivation and Validation of Automated Electronic Search Strategies to Identify Pertinent Risk Factors for Postoperative Acute Lung Injury

OBJECTIVE To develop and validate time-efficient automated electronic search strategies for identifying preoperative risk factors for postoperative acute lung injury. PATIENTS AND METHODS This secondary analysis of a prospective cohort study included 249 patients undergoing high-risk surgery between November 1, 2005, and August 31, 2006. Two independent data-extraction strategies were compared. The first strategy used a manual review of medical records and the second a Web-based query-building tool. Web-based searches were derived and refined in a derivation cohort of 83 patients and subsequently validated in an independent cohort of 166 patients. Agreement between the 2 search strategies was assessed with percent agreement and Cohen κ statistics. RESULTS Cohen κ statistics ranged from 0.34 (95% confidence interval, 0.00-0.86) for amiodarone to 0.85 for cirrhosis (95% confidence interval, 0.57-1.00). Agreement between manual and automated electronic data extraction was almost complete for 3 variables (diabetes mellitus, cirrhosis, H(2)-receptor antagonists), substantial for 3 (chronic obstructive pulmonary disease, proton pump inhibitors, statins), moderate for gastroesophageal reflux disease, and fair for 2 variables (restrictive lung disease and amiodarone). Automated electronic queries outperformed manual data collection in terms of sensitivities (median, 100% [range, 77%-100%] vs median, 87% [range, 0%-100%]). The specificities were uniformly high (≥ 96%) for both search strategies. CONCLUSION Automated electronic query building is an iterative process that ultimately results in accurate, highly efficient data extraction. These strategies may be useful for both clinicians and researchers when determining the risk of time-sensitive conditions such as postoperative acute lung injury.

Long-Term Survival and Quality of Life After Transfusion-Associated Pulmonary Edema in Critically III Medical Patients

BACKGROUND Transfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO) commonly complicate transfusion in critically ill patients. Prior outcome studies of TACO and TRALI have focused on short-term morbidity and mortality, but the long-term survival and quality of life (QOL) of these patients remain unknown. METHODS In a nested case-control study, we compared survival and QOL between critically ill medical patients who developed pulmonary edema after transfusion (TRALI or TACO) and medical critically ill transfused controls, matched by age, gender, and admission diagnostic group. QOL in survivors was assessed with a 36-item short form health survey 1 year after initial hospitalization. RESULTS Hospital, 1-year, and 2-year mortality among the 74 TRALI cases and 74 matched controls were 43.2% vs 24.3% (P = .020), 63.8% vs 46.4% (P = .037) and 74.3% vs 54.3% (P = .031), whereas among the 51 TACO cases and 51 matched controls these values were 7.8% vs 11.8% (P = .727), 38.0% vs 28.0% (P = .371), and 44.9% vs 38.8% (P = .512). When adjusted for age and baseline severity of illness in a Cox proportional hazard analysis, the development of TRALI remained associated with decreased survival (hazard ratio 1.86; 95% CI, 1.19-2.93; P = .006). Both TRALI (P = .006, P = .03) and TACO (P = .03, P = .049) were associated with prolonged ICU and hospital lengths of stay. CONCLUSIONS In critically ill medical patients, development of TRALI, but not TACO, is independently associated with decreased long-term survival.

Practice of Excessive FIO2 and Effect on Pulmonary Outcomes in Mechanically Ventilated Patients With Acute Lung Injury

BACKGROUND: Optimal titration of inspired oxygen is important to prevent hyperoxia in mechanically ventilated patients in ICUs. There is mounting evidence of the deleterious effects of hyperoxia; however, there is a paucity of data about FIO2 practice and oxygen exposure among patients in ICUs. We therefore sought to assess excessive FIO2 exposure in mechanically ventilated patients with acute lung injury and to evaluate the effect on pulmonary outcomes. METHODS: From a database of ICU patients with acute lung injury identified by prospective electronic medical record screening, we identified those who underwent invasive mechanical ventilation for > 48 hours from January 1 to December 31, 2008. Ventilator settings, including FIO2 and corresponding SpO2, were collected from the electronic medical record at 15-min intervals for the first 48 hours. Excessive FIO2 was defined as FIO2 > 0.5 despite SpO2 > 92%. The association between the duration of excessive exposure and pulmonary outcomes was assessed by change in oxygenation index from baseline to 48 hours and was analyzed by univariate and multivariate linear regression analysis. RESULTS: Of 210 patients who met the inclusion criteria, 155 (74%) were exposed to excessive FIO2 for a median duration of 17 hours (interquartile range 7.5–33 h). Prolonged exposure to excessive FIO2 correlated with worse oxygenation index at 48 hours in a dose-response manner (P < .001.). Both exposure to higher FIO2 and longer duration of exposure were associated with worsening oxygenation index at 48 hours (P < .001), more days on mechanical ventilation, longer ICU stay, and longer hospital stay (P = .004). No mortality difference was noted. CONCLUSIONS: Excessive oxygen supplementation is common in mechanically ventilated patients with ALI and may be associated with worsening lung function.

Bedside quantification of dead-space fraction using routine clinical data in patients with acute lung injury: secondary analysis of two prospective trials

IntroductionDead-space fraction (Vd/Vt) has been shown to be a powerful predictor of mortality in acute lung injury (ALI) patients. The measurement of Vd/Vt is based on the analysis of expired CO2 which is not a part of standard practice thus limiting widespread clinical application of this method. The objective of this study was to determine prognostic value of Vd/Vt estimated from routinely collected pulmonary variables.MethodsSecondary analysis of the original data from two prospective studies of ALI patients. Estimated Vd/Vt was calculated using the rearranged alveolar gas equation: Vd/Vt=1−[(0.86×V˙CO2est)/(VE×PaCO2)] where V˙CO2est is the estimated CO2 production calculated from the Harris Benedict equation, minute ventilation (VE) is obtained from the ventilator rate and expired tidal volume and PaCO2 from arterial gas analysis. Logistic regression models were created to determine the prognostic value of estimated Vd/Vt.ResultsOne hundred and nine patients in Mayo Clinic validation cohort and 1896 patients in ARDS-net cohort demonstrated an increase in percent mortality for every 10% increase in Vd/Vt in a dose response fashion. After adjustment for non-pulmonary and pulmonary prognostic variables, both day 1 (adjusted odds ratio-OR = 1.07, 95%CI 1.03 to 1.13) and day 3 (OR = 1.12, 95% CI 1.06 to 1.18) estimated dead-space fraction predicted hospital mortality.ConclusionsElevated estimated Vd/Vt predicts mortality in ALI patients in a dose response manner. A modified alveolar gas equation may be of clinical value for a rapid bedside estimation of Vd/Vt, utilizing routinely collected clinical data.

Outcome of critically ill patients with influenza virus infection

Abstract Background Influenza is a major cause of morbidity and mortality, with its greatest burden on the elderly and patients with chronic co-morbidities in the intensive care unit (ICU). An accurate prognosis is essential for decision-making during pandemic as well as interpandemic periods. Methods A retrospective cohort study was conducted to determine prognostic factors influencing short term outcome of critically ill patients with confirmed influenza virus infection. Baseline characteristics, laboratory and diagnostic findings, ICU interventions and complications were abstracted from medical records using standard definitions and compared between hospital survivors and non-survivors with univariate and multivariate logistic regression analyses. Results 111 patients met the inclusion criteria. Acute respiratory distress syndrome (ARDS) complicated ICU course in 25 (23%) of the patients, with mortality rate of 52%. Multivariate logistic regression analysis identified the following predictors of hospital mortality: Acute Physiology and Chronic Health Evaluation (APACHE) III predicted mortality (Odds ratio [OR] 1.49, 95% confidence interval [CI] 1.1–2.1 for 10% increase), ARDS (OR 7.7, 95% CI 2.3–29) and history of immunosuppression (OR 7.19, 95% CI 1.9–28). Conclusions APACHE III predicted mortality, the development of ARDS and the history of immunosuppression are independent risk factors for hospital mortality in critically ill patients with confirmed influenza virus infection.

Timing of the Onset of Acute Respiratory Distress Syndrome: A Population-Based Study

BACKGROUND: Many patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) have had recent healthcare interventions prior to developing ALI/ARDS. OBJECTIVE: To determine the timing of ALI/ARDS onset in relation to hospital admission and other healthcare interventions. METHODS: We conducted a population-based observational cohort study with a validated electronic surveillance tool, and identified patients with possible ALI/ARDS among critically ill adults at Mayo Clinic hospitals that provide critical care services for Olmsted County, Minnesota, in 2006. Trained investigators independently reviewed electronic medical records and confirmed the presence and timing of ALI/ARDS based on the American-European consensus definition. RESULTS: Of 124 episodes of ALI in 118 patients, only 5 did not fulfill the ARDS criteria. The syndrome developed a median 30 hours (IQR 10–82 h) after hospital admission in 79 patients (67%). ARDS was present on admission in 39 patients (33%), of whom 14 had recent hospitalization, 6 were transferred from nursing homes, and 3 had recent out-patient contact (1 antibiotic prescription, 1 surgical intervention, and 1 chemotherapy). Only 16 ARDS patients (14%) did not have known recent contact with a healthcare system. Compared to ARDS on admission, hospital-acquired ARDS was more likely to occur in surgery patients (54% vs 15%, P < .001), and had longer adjusted hospital stay (mean difference 8.9 d, 95% CI 0.3–17.4, P = .04). CONCLUSIONS: ARDS in the community most often develops either during hospitalization or in patients who recently had contact with a healthcare system. These findings have important implications for potential preventive strategies.