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Body surface area: a predictor of response to red blood cell transfusion

View Article: PubMed Central - PubMed

ABSTRACT

A current focus of transfusion medicine is a judicious strategy in transfusion of blood products. Unfortunately, our ability to predict hemoglobin (Hgb) response to transfusion has been limited. The objective of this study was to determine variability of response to red blood cell transfusion and to predict which patients will have an Hgb rise higher or lower than that predicted by the long-standing convention of “one and three”. This was a retrospective chart review in a single hospital. Data for 167 consecutive patient encounters were reviewed. The dataset was randomly divided into derivation and validation subsets with no significant differences in characteristics. DeltaHgb was defined as posttransfusion Hgb minus pre-transfusion Hgb per red blood cell unit. We classified all the patients in both the subsets as “high responders” (DeltaHgb >1 g/dL) or as “low responders” (DeltaHgb ≤1 g/dL). In univariate analysis, age, sex, body weight, estimated blood volume, and body surface area were significantly associated with response category (P<0.05). Different multivariate regression models were tested using the derivation subset. The probability of being a high responder was best calculated using the logarithmic formula eH / (1 + eH), where H is B0 + (B1 × variable 1) + (B2 × variable 2). Bis are coefficients of the models. On validation, the model H=6.5–(3.3 × body surface area), with the cutoff probability of 0.5, was found to correctly classify patients into high and low responders in 69% of cases (sensitivity 84.6%, specificity 43.8%). This model may equip clinicians to make more appropriate transfusion decisions and serve as a springboard for further research in transfusion medicine.

No MeSH data available.


Nomogram to predict the probability of being a “high responder” based on BSA.Note: This sigmoid nomogram was created to allow quick estimation of patients’ probability of being “high responder” based only on their BSA.Abbreviation: BSA, body surface area.
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f3-jbm-7-199: Nomogram to predict the probability of being a “high responder” based on BSA.Note: This sigmoid nomogram was created to allow quick estimation of patients’ probability of being “high responder” based only on their BSA.Abbreviation: BSA, body surface area.

Mentions: To validate the formula, we measured the sensitivity, specificity, and classification accuracy of Model 2 in predicting high vs low response among patients in the validation subset. We first used the sequence depicted in Figure 2 to assign patients to predicted high vs low response groups. Next, we determined sensitivity, specificity, and classification accuracy according to standard definitions. Using this strategy, the model correctly classified patients into high vs low responders in 69% of cases. Sensitivity and specificity were 84.6% and 43.8%, respectively. Finally, having validated the model on the validation subset, we calculated BSA, which corresponded to a high response probability of 0.50. This calculation yielded a cutoff BSA of 1.97 m2. This means that patients with a BSA less than 1.97 m2 have a probability that is greater than 0.50 of achieving a DeltaHgb per RBC unit of >1 g/dL. Conversely, patients with a BSA greater than 1.97 m2 have a probability less than 0.50 of achieving a DeltaHgb per RBC unit >1 g/dL. A nomogram depicting the probability of being a “high responder” based on BSA is shown in Figure 3.


Body surface area: a predictor of response to red blood cell transfusion
Nomogram to predict the probability of being a “high responder” based on BSA.Note: This sigmoid nomogram was created to allow quick estimation of patients’ probability of being “high responder” based only on their BSA.Abbreviation: BSA, body surface area.
© Copyright Policy
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5036545&req=5

f3-jbm-7-199: Nomogram to predict the probability of being a “high responder” based on BSA.Note: This sigmoid nomogram was created to allow quick estimation of patients’ probability of being “high responder” based only on their BSA.Abbreviation: BSA, body surface area.
Mentions: To validate the formula, we measured the sensitivity, specificity, and classification accuracy of Model 2 in predicting high vs low response among patients in the validation subset. We first used the sequence depicted in Figure 2 to assign patients to predicted high vs low response groups. Next, we determined sensitivity, specificity, and classification accuracy according to standard definitions. Using this strategy, the model correctly classified patients into high vs low responders in 69% of cases. Sensitivity and specificity were 84.6% and 43.8%, respectively. Finally, having validated the model on the validation subset, we calculated BSA, which corresponded to a high response probability of 0.50. This calculation yielded a cutoff BSA of 1.97 m2. This means that patients with a BSA less than 1.97 m2 have a probability that is greater than 0.50 of achieving a DeltaHgb per RBC unit of >1 g/dL. Conversely, patients with a BSA greater than 1.97 m2 have a probability less than 0.50 of achieving a DeltaHgb per RBC unit >1 g/dL. A nomogram depicting the probability of being a “high responder” based on BSA is shown in Figure 3.

View Article: PubMed Central - PubMed

ABSTRACT

A current focus of transfusion medicine is a judicious strategy in transfusion of blood products. Unfortunately, our ability to predict hemoglobin (Hgb) response to transfusion has been limited. The objective of this study was to determine variability of response to red blood cell transfusion and to predict which patients will have an Hgb rise higher or lower than that predicted by the long-standing convention of “one and three”. This was a retrospective chart review in a single hospital. Data for 167 consecutive patient encounters were reviewed. The dataset was randomly divided into derivation and validation subsets with no significant differences in characteristics. DeltaHgb was defined as posttransfusion Hgb minus pre-transfusion Hgb per red blood cell unit. We classified all the patients in both the subsets as “high responders” (DeltaHgb >1 g/dL) or as “low responders” (DeltaHgb ≤1 g/dL). In univariate analysis, age, sex, body weight, estimated blood volume, and body surface area were significantly associated with response category (P<0.05). Different multivariate regression models were tested using the derivation subset. The probability of being a high responder was best calculated using the logarithmic formula eH / (1 + eH), where H is B0 + (B1 × variable 1) + (B2 × variable 2). Bis are coefficients of the models. On validation, the model H=6.5–(3.3 × body surface area), with the cutoff probability of 0.5, was found to correctly classify patients into high and low responders in 69% of cases (sensitivity 84.6%, specificity 43.8%). This model may equip clinicians to make more appropriate transfusion decisions and serve as a springboard for further research in transfusion medicine.

No MeSH data available.