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Year : 2019  |  Volume : 4  |  Issue : 1  |  Page : 58-64

To evaluate hemoglobin thresholds of elective surgical patients and blood typing policy for reducing the erythrocyte transfusion in a hospital setting

Department of Transfusion Medicine and Blood Bank, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India

Date of Web Publication22-Apr-2019

Correspondence Address:
Dr. Sankalp Sharma
Department of Transfusion Medicine and Blood Bank, All India Institute of Medical Sciences, Raipur, Chhattisgarh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/GJTM.GJTM_51_18

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Introduction: The existing methods to quantify blood requirement in elective surgical procedure are the baseline hemoglobin (Hb) and hematocrit of patients. The risk-based scoring systems available are maximum allowable surgical blood loss and maximum surgical blood ordering schedule employ retrospective data evaluation or patient-specific variables, respectively. The aim of the present study was to evaluate a single institutional data for analyzing red blood cell (RBC) requirement among various surgical diagnoses. The study also evaluated RBC threshold for blood transfusions and efficacy of blood typing policy toward reducing unnecessary transfusions in an institution. Study Design and Methods: This study is a retrospective data evaluation from a single institution of blood transfusion patterns among elective surgical patients. Results: The blood transfusions in surgical diagnoses (n = 259) got integrated under 16 categories. The overall crossmatch-to-transfusion ratio was 1.4, average Hb before transfusion was 9.0 g/dl across the surgical categories, and average erythrocyte transfusion per patient for the various clinical diagnoses was 0.4 blood units. The effective Blood usage was 73.2% of requisitions received and blood typing was performed in 46.3% of total requisitions. Blood typing policy showed a statistically significant improvement in the blood transfusion of crossmatched units in the hospital. A per-unit reduction of blood cost in patients was also observed. Conclusions: The blood transfusion across the surgical categories showed similar Hb thresholds before transfusion. Blood typing policy improved EBU and reduced unnecessary crossmatches and transfusion costs among the patients.

Keywords: Blood typing, Blood orders, CT Ratio, MSBOS, Surgical blood loss

How to cite this article:
Sharma S, Prasad D, Lehre S. To evaluate hemoglobin thresholds of elective surgical patients and blood typing policy for reducing the erythrocyte transfusion in a hospital setting. Glob J Transfus Med 2019;4:58-64

How to cite this URL:
Sharma S, Prasad D, Lehre S. To evaluate hemoglobin thresholds of elective surgical patients and blood typing policy for reducing the erythrocyte transfusion in a hospital setting. Glob J Transfus Med [serial online] 2019 [cited 2020 Oct 25];4:58-64. Available from: https://www.gjtmonline.com/text.asp?2019/4/1/58/256766

  Introduction Top

A total blood volume in an individual is determined by age, sex, body mass index, and total plasma osmolality.[1] Erythrocyte requirement in an individual should be corresponding toward maintaining normal oxygen delivery to the peripheral tissues without an increase in the cardiac output [1] (Morgan and Mikhail, 1996).

Surgical procedure-related blood loss and postoperative blood drainage in a patient are useful to estimate maximum tolerable blood loss, after which transfusions are deemed necessary.[1],[2],[3]

The severity of blood loss is dependent on variables such as blood volume, preoperative hemoglobin (Hb), and hematocrit (Hct) levels; blood loss in pediatric patients and co-morbidities such as cardiac decompensation, elderly atherosclerotic patients.[3],[4]

The risk score systems which quantify blood losses and red blood cell (RBC) requirements involve patient-specific parameters; Studies have quantified patient-specific variables in a risk score system to predict the requirement for a blood transfusion support; Mercurialis approach with volume of packed red cell as a reference parameter estimates erythrocyte requirement after the calculation of maximally tolerated loss of RBCs in each surgical procedure from the preoperative period up to 5th postoperative day.[5]

Institutional regimens such as maximum surgical blood ordering schedule (MSBOS) evaluates the blood requirement of elective surgical procedures and segregate crossmatch and blood Typing based upon the crossmatch-to-transfusion ratio (CM/T). Type and Screen only (BTY) pretransfusion protocol is allocated to procedures showing an effective blood usage (EBU) <30%.[4],[5],[6],[7]

The MSBOS calculates blood requirement on the basis of the amount of Hb lost during any surgical procedure as calculated by the surgical blood ordering equation (SBOE).

SBOE (units) = mean blood loss (g)/200 − (preoperative Hb − postoperative Hb) divided by (40/body weight (kg).[8] Blood requirement in SBOS tends to accommodate a local surgical team and is institution specific.[5],[8],[9]


The aim of this study conducted in a tertiary hospital setting was to observe the Hb thresholds for surgical diagnosis requiring an elective procedure for RBC transfusion requirements; a subgroup analysis evaluated the effectiveness of blood typing only (BTY) policy in the surgical management of a patient in terms of reducing the number of crossmatches, EBU, and cost-effectiveness to the patient with the BTY policy.

This study evaluated the blood requisition patterns in various surgical diagnoses with an assumption that in any elective surgical procedure, the transfusion threshold for blood transfusion requirement can be standardized based on the surgical diagnosis and analysis of transfusion patterns.

  Study Design and Methods Top

This study involves a single 250-bedded tertiary hospital. We did a retrospective data compilation from November 2014 to August 2017, respectively, after segregation of presurgical diagnoses into 16 categories to accommodate common anatomical sites and/or surgical procedure undertaken at these sites and compared for outliers for Hb thresholds of transfusion. The outliers were compared also between the surgical diagnoses to evaluate transfusion patterns within an institution. The blood reserve protocol defined here has been approved by the Hospital Transfusion Committee of this multispecialty hospital.

The parameters evaluated includes BTY (Blood Typing) defined as group-specific blood reserved with the blood bank without cross-matching; BTY converted into crossmatches (BTY-CM); Complete Cross-match (CM), number of transfusions upon patients; average Hb at transfusion; average RBC consumption of each surgical diagnoses, which formulated the transfusion data [Table 1].
Table 1: Blood requisition practices at AIIMS, Raipur

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The eligibility criteria included all surgical diagnosis undergoing an elective surgical procedure at our multispecialty hospital under general or spinal anesthesia. All the benign surgical diagnoses at common anatomical sites were allotted a separate category (for example, multinodular goiter/thyroid nodule/colloid goiter). The malignant conditions grouped separately included carcinoma of gingival/alveolar carcinoma [Table 1]. A few diagnoses such as Wilms tumor and salivary gland tumor were allotted separate category due to the small number of cases for these diagnoses [Table 1].

The exclusion criteria were the surgical diagnoses with <5 surgical procedures.

The preoperative Hb threshold was the only parameter under evaluation to minimize the perioperative, postoperative, or re-explorative bias of increase in blood requirement among the surgical patients.

Patient data in this retrospective data compilation were not compromised or divulged at any point during this study.

The aim and objective of this study were evaluated under the paradigm of correlation regression analyses within the subgroups under evaluation. The regression statement also evaluated the relationship between the EBU and the respective Hb levels at blood transfusions. The study of transfusion pattern was dependent on the strength of correlation and variations of one variable by a unit change in the other (linear regression analysis) (Hazra et al., 2016).

The regression analysis was made within total blood requisitions; BTY for the various surgical diagnoses; number of BTY getting converted into CM and subsequently to transfusions [Figure 1] for the regression parameters evaluated]. The NCSS software by NCSS and XLSTAT (trial version only) among other online statistical software were utilized to formulate a statistical statement of the Hb thresholds and BTY and http://www.biomath.info/power/corr.htm for validating the sample size (n = 259) and power of the study (0.8) for a sensitive correlation coefficient (CC) (r = 1.67 or r = −1.67) before observations were presented based on the data evaluation of the present study.
Figure 1: Linear Regression graphs from the top. (a) Number of transfusion patients and crossmatches. (b) Total requisition and type and screen. (c) Total transfused and type screen to cross-matching. (d) Blood typing and hemoglobin at transfusion. X: blood typing; Y:Average hemoglobin/hematocrit at transfusion

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The potential confounders in the present study included a small number of surgical cases in each surgical category; no matching analysis was performed for the surgical procedure which requires blood transfusion against the procedure at similar pretransfusion Hb not requiring blood transfusions. The number of cases exposed to blood transfusion was not compared with the nonexposed group to identify potential individual confounding factors.

The study was carried out to detect the relationship of unit change of one variable with another by a linear regression analysis and CC quotient along with other statistical parameters.

  Results Top

In an observation period from November 2014 to August 2016, surgical diagnoses requiring anesthesia (n = 259) were integrated under 16 surgical categories [Table 1] and [Figure 2].
Figure 2: Effective blood usage

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  1. An overall CM/T was 1.4 with average blood usage after CM 73.2%. BTY got performed on 46.3% of total blood requisitions with BTY-CM in 43.3% of BTY units. Each group of the blood requisition practices had variations, as depicted in [Table 1] and [Figure 3] (variation among the CM, BTY, and transfusion)
  2. Average Hb for blood transfusion (n = 98) was 9.0 g/dl (5.1–12.5 g/dl; standard deviation [SD] = 2.48; standard error [SE] = 0.62]) with average Hb of transfusion for uterine prolapse (mean Hb = 5.12 g/dl) as the only outlier among the various surgical diagnoses where blood was transfused to the patient. An average erythrocyte transfusion per patient for all clinical diagnosis in the hospital was 0.4 units (SD = 0.17; 95% confidence interval = 0.23–0.40)
  3. The surgical patients in a regression analysis, between the number of crossmatches and transfusion patients [X = CM; Y = transfused patients; [Figure 1]a and [Figure 2]; CC of 0.934, the estimated change in transfused patient per unit change in crossmatch (slope) was 0.695 (0.54–0.84); SE: 0.07 (coefficient of determination [R2] : 0.895; T value: 9.83 [slope] [P < 0.05]; F-ratio [slope] 96.67; [P < 0.05]), and constant residual variance 0.014 [P < 0.05]) X; Y share a linear relationship. The expected CM/T in the patients, if all the blood requisitions were converted into crossmatches without the BTY, would have been CM/T of 2.6, with EBU of 41.8%
  4. There was a statistically significant difference between the total requisitions received for blood transfusions, total BTY samples, and total BTY to CM units (ANOVA testing [P ≤ 0.0001] [DF = 2]). The regression analysis (X: BTY; Y: total requisitions) showed a CC of 0.85. The estimated value of total requisitions when BTY is 0 (y-intercept) is 4.42 (2.17–6.66), SE = 1.04, and the estimated change in total requisitions per unit change in BTY (slope) is 1.56 (1.37–1.76), SE = 0.091. The proportion of the variation in total requisitions that can be accounted for by variation in BTY (R2 = 0.77) is 79% [Figure 1]b
  5. BTY-CM also showed a correlation with the total transfused units (CC: 0.46) with regression coefficient (X = BTY to CM, Y = transfused; R2 = 0.33; CC = 0. 580). The estimated change in the transfused patient explained by the explanatory variable (BTY to CM) is only 34% [Figure 1]c
  6. The EBU assessment when made in context to the present study and total number of requisition converted into crossmatch [Table 1]. BTY was responsible for significantly lesser number of CM, and subsequently transfusions than no intervention (P = 0.05 [Risk ratio 1.5(1.2-1.8)]. BTY and BTY only without crossmatch showed CC (Pearson) = 0.47 (0.010–0.77). The interventions hence saved the cost of crossmatching by the institution with improved EBU among patients (54.47% more EBU with the BTY than without BTY; 120 lesser crossmatches and 83 lesser number of transfusion with BTY than without BTY) [Table 1]
  7. The regression coefficient for (X = BTY; Y = Average Hb for blood transfusion; CC = 0.247) [Figure 1]d; the variation of Hb at elective surgery to the BTY before surgery showed a negative correlation with no increased RBC requirement with lower Hb across the clinical diagnoses R2 = 0.61
  8. The study showed a significant difference between single blood unit only transfusion (77.92% of total transfusions); two blood units (16.88% of total transfusions); and three blood units (5.19% of total transfusions) with significant difference of single-unit transfusion and two and three units of blood transfusions (between diagnosis and within diagnosis; F = 22.62; P < 0.00001)
  9. The cost-effectiveness of the study can be estimated by the fact that the total expenditure for the 98 crossmatches (at the rate of Rs. 1050/-blood unit) was Rs. 102,900/-. If the total number of requisitions was converted into crossmatches, the estimated cost of blood transfusions at the same rate of blood usage would have resulted in the expenditure of Rs. 192,150/- (70.5% of n = 259). The institution in addition saved the cost of unnecessary crossmatches
  10. The EBU was <50% (20% and 30%) for ovarian cyst, multinodular goiter, thyroid nodule, and colloid goiter.
Figure 3: Blood utilization patterns in various surgical diagnoses

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  Discussions Top

The estimation of blood requirement in a patient by statistical calculation has drawbacks in the form of lack of individualization with respect to the patient variables (for example, Hb, Hct, and body mass indices).[5],[8]

A study (Frank et al., 2014) implemented an updated MSBOS on 100,789 patients combined with remote electronic blood release system through the so-called “electronically linked blood vending machines” outside the operation theater.[10] This improvised MSBOS resulted in a decrease of preoperative requisitions (P < 0.0004) and reduction in both BTY (P < 0.001) and CM/BTY (2.11–1.54, respectively). The percentage of patient receiving erythrocytes and intraoperative erythrocyte units/patient however increased in the post electronic blood release system period (P < 0.006 and P < 0.03, respectively).[10]

Our study shows that segregation of patients across the surgical diagnosis in elective procedures had transfusion requirements at comparable Hb thresholds within the surgical diagnoses with also a minimal variation in the RBC requirements within each of the surgical procedure categories (P < 0.05; [Table 1] and [Figure 1]a, [Figure 1]b, [Figure 1]c, [Figure 1]d. The EBU across the clinical diagnoses also did not show significant variation across the surgical diagnoses.

Standardization of the baseline Hb at which transfusion is made across the surgical diagnoses is possible rather than keeping variable transfusion thresholds for different clinical diagnoses, provided the baseline parameters such as cardiac functioning and preoperative blood volume are in the normal range.

Clinical trials such as Functional Outcomes in Cardiovascular Patients undergoing Surgical Hip Fracture Repair have defined threshold of transfusion at 7 g/dl with no adverse primary outcome among the participant of the restrictive group (35.2% liberal group and 34.7% restrictive group).[11]

Our study shows “blood typing protocol” when compared across the surgical diagnoses did not show a significant variation terms of blood requirement threshold in the elective surgical patients.

The CM/T in our study was within the normal range and the proportion of blood bank requisitions actually getting converted into crossmatch, and subsequently, transfusion showed a significant reduction in the number of CM performed due to the BTY protocol and was responsible to subsequently reduction in the institutional costs and patient cost.

BTY protocol a largely unexplored concept in the developing world has a prospect of reducing unnecessary crossmatches and facilitating EBU within elective surgical cases.

  Conclusions Top

  1. A segregation of surgical diagnosis for estimating the transfusion requirements showed minimal interindividual variations in blood requisition practices among various surgical diagnoses in terms of baseline Hb and Hct levels
  2. The “blood typing only protocol” increases EBU, reduces CM/T, and provides evidence for using type and reserve policy for rational transfusions upon patients and saves costs of transfusion per patient
  3. The surgical procedure with EBU of 30% or less may be considered for type and screen policy by surgeons performing the surgical procedure for a specific diagnosis; however, the transfusion patterns and the baseline Hb are a few parameters which should determine the transfusion in an elective surgical procedure
  4. This study showed that BTY reduced the number of unnecessary crossmatches with an assumption that elective surgical procedures in the present study in the hospital did not undergo unnecessary transfusions or undertransfusions following a BTY-CM policy. The results reflected in terms of improved CM/T and EBU with reduction in the cost of unnecessary investigations or procedures.


The author would like to acknowledge the data collection by Dr. Kamlesh Janghel and Dr. Bhupendra toward data collection for this study. The authors are also thankful to the parent institute, All India Institute of Medical Sciences Raipur, where this study was carried out.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

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Arya VK. Basics of fluid and blood transfusion therapy in paediatric surgical patients. Indian J Anaesth 2012;56:454-62.  Back to cited text no. 3
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American Society of Anesthesiologists Task Force on Perioperative Blood Management. Practice guidelines for perioperative blood management: An updated report by the American Society of anesthesiologists task force on perioperative blood management*. Anesthesiology 2015;122:241-75.  Back to cited text no. 4
Inghilleri G. Prediction of transfusion requirements in surgical patients: A review. Transfus Altern Transfus Med 2010;11:10-9.  Back to cited text no. 5
Subramanian A, Sagar S, Kumar S, Agrawal D, Albert V, Misra MC. Maximum surgical blood ordering schedule in a tertiary trauma center in Northern India: A proposal. J Emerg Trauma Shock 2012;5:321-7.  Back to cited text no. 6
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Sakurai Y, Okada C. Comparison by simulation of the efficiency of surgical blood order equation (SBOE) with that of maximum surgical blood order schedule (MSBOS). Masui 2001;50:69-75.  Back to cited text no. 8
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Frank SM, Oleyar MJ, Ness PM, Tobian AA. Reducing unnecessary preoperative blood orders and costs by implementing an updated institution-specific maximum surgical blood order schedule and a remote electronic blood release system. Anesthesiology 2014;121:501-9.  Back to cited text no. 10
Carson JL, Terrin ML, Noveck H, Sanders DW, Chaitman BR, Rhoads GG, et al. Liberal or restrictive transfusion in high-risk patients after hip surgery. N Engl J Med 2011;365:2453-62.  Back to cited text no. 11


  [Figure 1], [Figure 2], [Figure 3]

  [Table 1]


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