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BACKGROUNDTransfusion‐related acute lung injury (TRALI) is a serious complication of blood transfusion and is among the leading causes of transfusion‐related morbidity and mortality in most developed countries. In the past decade, the pathophysiology of this potentially life‐threatening syndrome has been increasingly elucidated, large cohort studies have identified associated patient conditions and transfusion risk factors, and preventive strategies have been successfully implemented. These new insights provide a rationale for updating the 2004 consensus definition of TRALI.STUDY DESIGN AND METHODSAn international expert panel used the Delphi methodology to develop a redefinition of TRALI by modifying and updating the 2004 definition. Additionally, the panel reviewed issues related to TRALI nomenclature, patient conditions associated with acute respiratory distress syndrome (ARDS) and TRALI, TRALI pathophysiology, and standardization of reporting of TRALI cases.RESULTSIn the redefinition, the term “possible TRALI” has been dropped. The terminology of TRALI Type I (without an ARDS risk factor) and TRALI Type II (with an ARDS risk factor or with mild existing ARDS) is proposed. Cases with an ARDS risk factor that meet ARDS diagnostic criteria and where respiratory deterioration over the 12 hours before transfusion implicates the risk factor as causative should be classified as ARDS. TRALI remains a clinical diagnosis and does not require detection of cognate white blood cell antibodies.CONCLUSIONSClinicians should report all cases of posttransfusion pulmonary edema to the transfusion service so that further investigation can allow for classification of such cases as TRALI (Type I or Type II), ARDS, transfusion‐associated circulatory overload (TACO), or TRALI or TACO cannot distinguish or an alternate diagnosis.

BACKGROUNDIt is increasingly recognized that recipient risk factors play a prominent role in possible transfusion‐related acute lung injury (pTRALI) and transfusion‐associated circulatory overload (TACO). We hypothesized that both transfusion and recipient factors including natriuretic peptides could be used to distinguish TRALI from TACO and pTRALI.STUDY DESIGN AND METHODSWe performed a post hoc analysis of a case‐control study of pulmonary transfusion reactions conducted at the University of California at San Francisco and Mayo Clinic, Rochester. We evaluated clinical data and brain natriuretic peptides (BNP) levels drawn after transfusion in patients with TRALI (n = 21), pTRALI (n = 26), TACO (n = 22), and controls (n = 24). Logistic regression and receiver operating characteristics curve analyses were used to determine the accuracy of clinical and biomarker predictors in differentiating TRALI from TACO and pTRALI.RESULTSWe found that pTRALI and TACO were associated with older age, higher fluid balance, and elevated BNP levels relative to those of controls and TRALI. The following variables were useful in distinguishing cases of pTRALI and TACO from TRALI: age more than 70 years, BNP levels more than 1000 pg/mL, 24‐hour fluid balance of more than 3 L, and a lower number of transfused blood components. Using the above variables, our logistic model had a 91% negative predictive value in the differential diagnosis of TRALI.CONCLUSIONSModels incorporating readily available clinical and biomarker data can be used to differentiate transfusion‐related respiratory complications. Additional studies examining recipient risk factors and the likelihood of TRALI may be useful in decision making regarding donor white blood cell antibody testing.

BACKGROUND Pulmonary transfusion reactions are important complications of blood transfusion, yet differentiating these clinical syndromes is diagnostically challenging. We hypothesized that biologic markers of inflammation could be used in conjunction with clinical predictors to distinguish transfusion‐related acute lung injury (TRALI), transfusion‐associated circulatory overload (TACO), and possible TRALI. STUDY DESIGN AND METHODS In a nested case‐control study performed at the University of California at San Francisco and Mayo Clinic, Rochester, we evaluated clinical data and blood samples drawn before and after transfusion in patients with TRALI (n = 70), possible TRALI (n = 48), TACO (n = 29), and controls (n = 147). Cytokines measured included granulocyte‐macrophage–colony‐stimulating factor, interleukin (IL)‐6, IL‐8, IL‐10, and tumor necrosis factor‐α. Logistic regression and receiver operating characteristics curve analyses were used to determine the accuracy of clinical predictors and laboratory markers in differentiating TACO, TRALI, and possible TRALI. RESULTS Before and after transfusion, IL‐6 and IL‐8 were elevated in patients with TRALI and possible TRALI relative to controls, and IL‐10 was elevated in patients with TACO and possible TRALI relative to that of TRALI and controls. For all pulmonary transfusion reactions, the combination of clinical variables and cytokine measurements displayed optimal diagnostic performance, and the model comparing TACO and TRALI correctly classified 92% of cases relative to expert panel diagnoses. CONCLUSIONS Before transfusion, there is evidence of systemic inflammation in patients who develop TRALI and possible TRALI but not TACO. A predictive model incorporating readily available clinical and cytokine data effectively differentiated transfusion‐related respiratory complications such as TRALI and TACO.

Background Possible transfusion‐related acute lung injury (p TRALI ) cases by definition have a clear temporal relationship to an alternative recipient risk factor for acute respiratory distress syndrome ( ARDS ). We questioned whether transfusion factors are important for the development of p TRALI . Study Design and Methods In this nested case‐control study, we prospectively identified 145 consecutive patients with p TRALI and randomly selected 163 transfused controls over a 4‐year period at the U niversity of C alifornia at S an F rancisco and the M ayo C linic ( R ochester, M innesota). Results For p TRALI , we found evidence against transfusion being important: receipt of plasma from female donors (odds ratio [ OR ], 0.82; 95% confidence interval [ CI ], 0.29‐2.3; p = 0.70), total number of units transfused ( OR , 0.99; 95% CI , 0.89‐1.10; p = 0.86), and number of red blood cell and whole blood units transfused ( OR , 0.78; 95% CI , 0.59‐1.03; p = 0.079). In contrast, we found that risk for p TRALI was associated with additional recipient factors: chronic alcohol abuse ( OR , 12.5; 95% CI , 2.8‐55; p < 0.001), current smoker ( OR , 4.2; 95% CI , 1.67‐10.8; p = 0.0024), shock before transfusion ( OR , 4.6; 95% CI , 2.0‐10.7; p < 0.001), and positive fluid balance before transfusion ( OR , 1.32/ L ; 95% CI , 1.20‐1.44; p < 0.001). Conclusion Recipient risk factors for ARDS rather than transfusion risk factors predominate in p TRALI .

BackgroundIdentifying antibodies to HLA (anti‐HLA) by solid‐phase assays is used to screen blood donors to mitigate transfusion‐related acute lung injury risk. Various cutoffs for detection assays have been proposed in the literature; however, these do not take into consideration lot‐to‐lot variability of commercially available assays.Study Design and MethodsSamples from 93 nontransfused males were tested using five different lots of a multiplex bead‐based anti‐HLA detection kit. A subset of 17 samples was tested on 5 days using a single lot. An additional 96 samples from donations with varied anti‐HLA levels were tested using kits from two different lots. Results were reported as a normalized background (NBG) ratio.ResultsFor the 93 nontransfused donors, NBG values generated using the reference lot were significantly higher than those obtained with three of the four comparator lots. However, for the 96 samples with low‐, moderate‐, and higher‐level anti‐HLA, Class I (CL‐I) values were 1.4 times lower and Class II (CL‐II) values were 1.2 times lower using the reference versus comparator lot. For CL‐I antibodies the between‐lot standard deviation (SD) was 1.36 (95% confidence interval [CI], 1.19‐1.60), while the between‐day SD was 1.27 (95% CI, 1.08‐1.52). Similarly, for CL‐II antibodies the between‐lot SD was 0.81 (95% CI, 0.70‐0.95), while the between‐day SD was 0.50 (95% CI, 0.43‐0.60).ConclusionsThere is interlot variability in the tested HLA detection assay as well as significant bias between lots. It may be reasonable to develop a new cutoff when a new lot is obtained.

AbstractTransfusion-related acute lung injury (TRALI) is the leading cause of transfusion-related mortality. To determine TRALI incidence by prospective, active surveillance and to identify risk factors by a case-control study, 2 academic medical centers enrolled 89 cases and 164 transfused controls. Recipient risk factors identified by multivariate analysis were higher IL-8 levels, liver surgery, chronic alcohol abuse, shock, higher peak airway pressure while being mechanically ventilated, current smoking, and positive fluid balance. Transfusion risk factors were receipt of plasma or whole blood from female donors (odds ratio = 4.5, 95% confidence interval [CI], 1.85-11.2, P = .001), volume of HLA class II antibody with normalized background ratio more than 27.5 (OR = 1.92/100 mL, 95% CI, 1.08-3.4, P = .03), and volume of anti–human neutrophil antigen positive by granulocyte immunofluoresence test (OR = 1.71/100 mL, 95% CI, 1.18-2.5, P = .004). Little or no risk was associated with older red blood cell units, noncognate or weak cognate class II antibody, or class I antibody. Reduced transfusion of plasma from female donors was concurrent with reduced TRALI incidence: 2.57 (95% CI, 1.72-3.86) in 2006 versus 0.81 (95% CI, 0.44-1.49) in 2009 per 10 000 transfused units (P = .002). The identified risk factors provide potential targets for reducing residual TRALI.