Cytokines and clinical predictors in distinguishing pulmonary transfusion reactions

Nareg H. Roubinian, Mark R. Looney, Daryl J Kor, Clifford A. Lowell, Ognjen Gajic, Rolf D. Hubmayr, Michael A. Gropper, Monique Koenigsberg, Gregory A. Wilson, Michael A. Matthay, Pearl Toy, Edward L. Murphy

Research output: Contribution to journalArticle

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Abstract

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.

Original languageEnglish (US)
Pages (from-to)1838-1846
Number of pages9
JournalTransfusion
Volume55
Issue number8
DOIs
StatePublished - Aug 1 2015

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Acute Lung Injury
Cytokines
Lung
Biomarkers
Transfusion Reaction
Interleukin-8
Interleukin-10
Interleukin-6
Inflammation
San Francisco
Granulocyte-Macrophage Colony-Stimulating Factor
ROC Curve
Blood Transfusion
Case-Control Studies

ASJC Scopus subject areas

  • Hematology
  • Immunology
  • Immunology and Allergy

Cite this

Roubinian, N. H., Looney, M. R., Kor, D. J., Lowell, C. A., Gajic, O., Hubmayr, R. D., ... Murphy, E. L. (2015). Cytokines and clinical predictors in distinguishing pulmonary transfusion reactions. Transfusion, 55(8), 1838-1846. https://doi.org/10.1111/trf.13021

Cytokines and clinical predictors in distinguishing pulmonary transfusion reactions. / Roubinian, Nareg H.; Looney, Mark R.; Kor, Daryl J; Lowell, Clifford A.; Gajic, Ognjen; Hubmayr, Rolf D.; Gropper, Michael A.; Koenigsberg, Monique; Wilson, Gregory A.; Matthay, Michael A.; Toy, Pearl; Murphy, Edward L.

In: Transfusion, Vol. 55, No. 8, 01.08.2015, p. 1838-1846.

Research output: Contribution to journalArticle

Roubinian, NH, Looney, MR, Kor, DJ, Lowell, CA, Gajic, O, Hubmayr, RD, Gropper, MA, Koenigsberg, M, Wilson, GA, Matthay, MA, Toy, P & Murphy, EL 2015, 'Cytokines and clinical predictors in distinguishing pulmonary transfusion reactions', Transfusion, vol. 55, no. 8, pp. 1838-1846. https://doi.org/10.1111/trf.13021
Roubinian, Nareg H. ; Looney, Mark R. ; Kor, Daryl J ; Lowell, Clifford A. ; Gajic, Ognjen ; Hubmayr, Rolf D. ; Gropper, Michael A. ; Koenigsberg, Monique ; Wilson, Gregory A. ; Matthay, Michael A. ; Toy, Pearl ; Murphy, Edward L. / Cytokines and clinical predictors in distinguishing pulmonary transfusion reactions. In: Transfusion. 2015 ; Vol. 55, No. 8. pp. 1838-1846.
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abstract = "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.",
author = "Roubinian, {Nareg H.} and Looney, {Mark R.} and Kor, {Daryl J} and Lowell, {Clifford A.} and Ognjen Gajic and Hubmayr, {Rolf D.} and Gropper, {Michael A.} and Monique Koenigsberg and Wilson, {Gregory A.} and Matthay, {Michael A.} and Pearl Toy and Murphy, {Edward L.}",
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T1 - Cytokines and clinical predictors in distinguishing pulmonary transfusion reactions

AU - Roubinian, Nareg H.

AU - Looney, Mark R.

AU - Kor, Daryl J

AU - Lowell, Clifford A.

AU - Gajic, Ognjen

AU - Hubmayr, Rolf D.

AU - Gropper, Michael A.

AU - Koenigsberg, Monique

AU - Wilson, Gregory A.

AU - Matthay, Michael A.

AU - Toy, Pearl

AU - Murphy, Edward L.

PY - 2015/8/1

Y1 - 2015/8/1

N2 - 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.

AB - 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.

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U2 - 10.1111/trf.13021

DO - 10.1111/trf.13021

M3 - Article

C2 - 25702590

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