|Year : 2021 | Volume
| Issue : 1 | Page : 30-34
Are donor predonation variables related to the quality of single donor platelets? – A tertiary care center experience
Priti Chatterjee1, Shivali Sehgal2, Swati Bhardwaj3, Reema Bhushan1, Chintamani Pathak4, Manjula Jain5
1 Department of Pathology and Blood Bank, Lady Hardinge Medical College, New Delhi, India
2 Department of Pathology, HIMSR, New Delhi, India
3 Blood Bank, Indian Spinal Injuries Centre, New Delhi, India
4 Department of Pathology, VMMC and Safdarjung Hospital, New Delhi, India
5 Department of Hematology, ESIC Medical College and Hospital, Faridabad, Haryana, India
|Date of Submission||15-Oct-2020|
|Date of Acceptance||17-Jun-2021|
|Date of Web Publication||04-Aug-2021|
B-4/125, Safdarjung Enclave, New Delhi - 110 029
Source of Support: None, Conflict of Interest: None
Introduction: Platelets are the most common product collected by apheresis. The product obtained is called single donor platelets (SDPs). The quality of the SDP is determined by the platelet yield (that is platelet count of the SDP product), which in turn directly influences the patient recovery.
Materials and Methods: In the present study, donor demographic and complete blood count parameters were studied and their influence on the yield of the SDP was analyzed. With such an analysis, a better quality product (with a good platelet yield) can be obtained consequently improving clinical outcome. This would allow prolonging intervals between transfusions.
Results: Parameters such as height, weight, and body mass index did not statistically influence the platelet yield in this study, unlike the results obtained by past studies. The most consistent parameter found to influence the platelet yield was platelet count of the donor. Healthy donors with high platelet counts can yield better platelet yield in SDPs in a shorter time and therefore improve the clinical outcome in patients with thrombocytopenia.
Conclusion: It is important to consider hematological characteristics of the donors on an individual basis so as to ensure a good quality of the plateletpheresis product.
Keywords: Donor, predonation variables, quality, single donor platelets
|How to cite this article:|
Chatterjee P, Sehgal S, Bhardwaj S, Bhushan R, Pathak C, Jain M. Are donor predonation variables related to the quality of single donor platelets? – A tertiary care center experience. J Med Soc 2021;35:30-4
|How to cite this URL:|
Chatterjee P, Sehgal S, Bhardwaj S, Bhushan R, Pathak C, Jain M. Are donor predonation variables related to the quality of single donor platelets? – A tertiary care center experience. J Med Soc [serial online] 2021 [cited 2022 Oct 4];35:30-4. Available from: https://www.jmedsoc.org/text.asp?2021/35/1/30/323156
| Introduction|| |
Platelet transfusions are indicated in patients with thrombocytopenia or platelet dysfunction who are bleeding or at increased risk of bleeding. Platelets for transfusion are provided by platelet concentrates which are harvested from whole blood donation or by apheresis.
Platelets are the most common product collected by apheresis. In plateletpheresis, a portion of the donor's platelet and some plasma is removed with the return of donor's red cells, leukocytes, and remaining plasma. The product obtained is called single donor platelets (SDP). The quality of the SDP is determined by the platelet yield (that is platelet count of the SDP product), which in turn directly influences the patient recovery.
Other donor demographic and hematological parameters might affect the platelet yield. Analysis of the influence of these parameters would help the blood bank personnel to effectively select the appropriate donor for plateletpheresis in less time. Moreover, with this a better quality product (with a good platelet yield) can be obtained consequently improving clinical outcome. This would allow prolonging intervals between transfusions. Furthermore, this would have a significant economic impact on platelet apheresis programs and important clinical consequences for the role of platelet apheresis products in future transfusion strategies. The aim of the study was to study the donor demographics and complete blood count (CBC) parameters in apheresis donors and to analyze their influence on the yield of the SDP.
| Materials and Methods|| |
A prospective observational study was conducted in the Regional Blood Transfusion Center of North India for a period of 1 year. Ethical clearance was taken from the institutional ethical committee.
All apheresis donors fulfilling the requirements for whole blood donation and additionally satisfying the criteria particular to the selected apheresis were included in the study. Donors <18 years of age and more than 60 years of age or on any medical treatment 7 days before the procedure were excluded in this study. Informed consent was obtained from all the donors. Physical examination, donor history questionnaire, and testing of transfusion transmissible infections were done before each procedure. It was mandatory for the platelet count in peripheral blood of the donors to be more than 150,000/μL.
The antecubital vein was used for access. All procedures were automated and were done on Haemonetics Blood cell separator MCS: Multicomponent collection system + with single needle. Blood flow rate was maintained at 45–90 ml/min with anticoagulant ratio of 1:12.
The target yield was set in the machine. At the end of the procedure, the machine calculated the platelet yield (estimated platelet yield) of the SDP unit (using the hematocrit, platelet count, height, and weight of the donor). The platelet count of the product (“true platelet yield” or “absolute platelet count” or “platelets per bag”) was also calculated manually. Sample from each bag was collected in ethylenediaminetetraacetic acid following stripping of the tube segment. The samples were mixed thoroughly over a mechanized blood mixer for quarter of an hour and then evaluated by Sysmex KX-21 hematology analyzer. The red blood cell (RBC) count and platelet count of the product were noted. The absolute platelet count was then calculated by the formula:
Absolute platelet count/True platelet yield = SDP volume (ml) × Platelet count obtained by Hematology analyzer (platelets/μL) × Conversion factor (1000).
All the data were collected from apheresis records in blood bank. The donor variables included in the study were demographic variables (age, sex, weight, height, blood group) and hematological variables (platelet count, hemoglobin, hematocrit, RBC count, mean corpuscular volume, mean platelet volume (MPV), red cell distribution width (RDW), platelet distribution width (PDW). The SDP parameters such as physical appearance, processing time, number of cycles, volume of blood processed, volume of the SDP product, and the amount of acid citrate dextrose (ACD) anticoagulant used were also noted. The RBC count and leukocyte count of the product were also analyzed.
Statistical analysis was done using IBM SPSS Statistics for Windows, Version 22.0 (Armonk, NY, USA: IBM Corp.). Descriptive statistics including mean, standard deviation, range values were calculated for normally distributed data. Comparison of two groups was done with Student's t-test and of more than two groups was done using analysis of variance test. Relationship between the predonation donor variables and yield of platelets (absolute platelet count) was studied using the Pearson correlation coefficient. The estimated yield was compared with the absolute platelet count. For all statistical tests, a two-sided probability of P < 0.05 was considered as statistically significant.
| Results|| |
Plateletpheresis was done in a total of 96 donors (once in each donor) for a period of 1 year.
[Table 1] describes the demographic parameters of the SDP donors.
|Table 1: Average complete blood count parameters and their correlation with platelet yield|
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All the donors were males. Female donors were deferred mainly because of not meeting the requirement of adequate hemoglobin or because of difficulty in obtaining venous access (lack of prominent veins and increased subcutaneous fat). Maximum number of donors belonged to the age group 29–33 years.
Around 83% of the donors were replacement donors and the rest were voluntary donors. The most common blood group was B positive (in around 40% of the donors).
Maximum donors had weight between 70 and 79 kg and height between 5 feet 6 inches and 5 feet 8 inches. The body mass index (BMI) of the donors varied from 18.85 to 39.56 kg/m2 with a mean of 24.8 kg/m2.
[Table 2] mentions the average CBC parameters of the donors. The platelet count of the donors ranged from 1.5 lacs/mm3 to 4.4 lacs/mm3. The mean platelet count of the donors was 2.37 lacs/mm3. The mean hemoglobin level was 14.4 g/dl and the mean hematocrit was 44%.
|Table 2: Average complete blood count parameters and their correlation with platelet yield|
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Single donor platelet parameters
The volume of the SDP product ranged from 86 ml to 349 ml (mean = 242 ml). The mean duration of the procedure was 73 min.
None of the products showed any evidence of RBC contamination and appeared clear physically. The target yield was set at an average of 3.09 × 1011 platelets/bag and ranged from 1 to 4.5 × 1011 platelets/bag. The estimated yield varied from 1 to 4.9 × 1011 platelets/bag (average = 3.20). The absolute platelet count (further referred to ask the target yield) calculated manually ranged from 1 to 5.5 × 1011 platelets (average 3.20). A significant correlation was seen between the target yield, the estimated yield, and the absolute platelet count (P < 0.05).
Correlation of demographic variables with platelet yield
No statistical significance was found between the age of the donor and the platelet yield. Furthermore, no correlation was found between the height, weight, or BMI of the donor and the platelet yield. Maximum yield was found in donors of O negative blood group, however, no significant association was found between the blood group of the donor and the platelet yield. No association was found between the yield and replacement versus voluntary donation.
Correlation of hematological parameters with platelet yield
There was direct positive correlation with the predonation platelet count and the platelet yield (P < 0.05). Similar correlation was found between the platelet parameters: MPV and PDW and the platelet yield which was significant statistically (P < 0.05). The hemoglobin, hematocrit, RBC count, and RDW showed a negative correlation with the platelet yield.
Correlation of single donor platelet Parameters with platelet yield
The platelet yield did not vary with the amount of ACD anticoagulant used. The volume of blood processed, number of cycles, and the processing time also did not show any relation with the platelet yield. The leukocyte count and RBC count of the product showed significant negative correlation with the platelet yield.
| Discussion|| |
Platelet transfusion success depends on the rational use of platelet components and on the quality of the component. With the introduction of advanced cell separators, demand of SDPs has increased. SDPs clearly meet the issues of quality and safety in transfusion as compared to random donor platelets (RDPs).
Platelet recovery in a patient is influenced by the transfused dose of platelets which in turn is dependent on the platelet yield. Higher platelet yield has important clinical implications. It reduces the frequency of platelet transfusions and number of donor exposures (therefore reduced risk of exposure of transfusion transmissible infections, alloimmunization, and febrile nonhemolytic transfusion reactions) with important consequent clinical and economic advantages. In addition, leukoreduction is accomplished during collection and no additional processing is needed. The relative cost of apheresis and RDP concentrates has caused renewed debate regarding SDP and RDPs. In an institution which caters to a large number of patients with thrombocytopenia, SDP is a better choice.
Routinely, the number of platelets in a SDP is equivalent to 6–8 RDP concentrates (RDP). SDP is superior to RDP because of it reduces the number of donor exposures. According to the American Association of Blood Banks, 75% of the SDP must contain ≥3 × 1011 platelets per unit while the European guidelines recommend a platelet count ≥2 × 1011 per unit. In the present study, the absolute platelet count met the American/guidelines. The average platelet yield in the past series has ranged from 2.29 ± 0.43 × 1011 per unit to 3.39 ± 0.88 × 1011 per unit.,,, No significant difference was noted between the yield estimated by the machine and that calculated manually at the end of the procedure.
Multiple donor parameters such as age, sex, weight, height, hemoglobin, total leukocyte count, hematocrit, platelet count, platelet indices, and the donor blood volume processed and processing time of the machine were analyzed to assess their influence on the platelet yield. Such an identification of these donor clinical and laboratory parameters would help in better selection of donors in the future resulting in higher platelet yield and consequently lower number of donor exposure to the patients.
Correlation of demographic variables with platelet yield
Previous studies have reported a negative correlation between donor age and platelet yield and a positive correlation with the BMI and platelet yield.,
p> Greater the body weight, greater is the blood volume available for processing, higher is the yield. Bahadur et al., however, reported no statistical significance between the height and weight and the platelet yield. Similarly, no correlation was observed between the gender, age, weight of the donor with the yield in another study. The current study also found no correlation with the age, height, weight, and BMI of the donor [Table 1].
Some previous studies have shown direct correlation of female gender with yield.,, Women tend to have higher yields possibly because of higher prevalence of iron deficiency leading to thrombocytosis, in addition, hormonal influence could also play a role. In our study, all the donors were males, therefore, gender correlation could not be carried out.
ABO correlation did not show any correlation with the platelet yield, however, some studies have reported that Rh-negative donors had longer processing time than Rh-positive donors.,
Correlation of hematological parameters with platelet yield
Similar to this study, most of the past studies have reported a direct relationship between the platelet count and yield.,,,,,, Goodnough et al. reported a mean platelet count of 237 ± 49 × 103 and mean yield of 4.24 ± 1.09 × 1011 platelets. Twelve percent of the procedures had yield of <3 × 1011 platelets in their study. Das et al. reported that when the predonation platelet count was ≥2.5 lacs, the yield was = 3 × 1011 in 80% of the procedures. Patel et al. found that platelet yield correlated negatively with the MPV, PDW, and platelet-large cell ratio. Smaller platelets are collected more efficiently by automated cell separators and yield a better quality product.
A donor with higher hemoglobin level was found to have a comparatively lower platelet yield.,, Inverse relationship of the hemoglobin with the platelet yield is probably due to the fact that because of the higher plasma volume processed in donor with low hemoglobin concentration. However, most of the studies have noticed no correlation between the donor hemoglobin concentration and yield., Similarly, no significant correlation between hematocrit and the platelet yield was observed.
Correlation of single donor platelet parameters with platelet yield
Various machine-related parameters also have been found influence the platelet yield in the past series. Mangwana reported that larger yield was obtained when the separation is done in shorter time. According to other studies, platelet yield can be increased by increasing the processing time, the ACD infusion rate, or the volume of the plasma obtained., Studies done previously have reported that platelet yield depends mainly on the donor's blood volume before apheresis and on the volume of the blood processed. Lasky et al. reported that the yield was related to the number of cycles. However, none of the above was found to significantly influence the platelet yield in this study.
The RBC count and leukocyte count of the product were found to have an inverse significant correlation with the platelet yield. Higher leukocyte and RBC counts meant contamination, hence lower the yield. However, the reason of contamination could not be pinpointed to a specific CBC parameter since no significant correlation was found. It was probably related to the technique of the technologist due to subjective variation.
Plateletpheresis is growing in use to support thrombocytopenic patients because products with low cross-contamination and high yield are obtained. Due to advances in technology, the procedure has become highly reproducible, automated, and free of adverse effects. The end product yield is often the interplay of various factors which affect the yield.
Due to an increasing requirement of SDPs, optimization of platelet yield is an emerging issue in transfusion services, and therefore, the demand of eligible and good donors has grown. The limited duration and small number of patients analyzed were the main drawbacks of the current study. A larger and longer prospective study might give a better direction for the future. This is also necessary because the cost of platelet transfusion therapy, a major concern for patients, will be influenced by the apheresis yield and dose and hence, by donor platelet count and other donor variables.
| Conclusion|| |
Parameters such as height, weight, and BMI did not statistically influence the platelet yield in this study, unlike the results obtained by past studies. The most consistent parameter found to influence the platelet yield was platelet count of the donor. Healthy donors with high platelet counts can yield better platelet yield in SDPs in a shorter time and therefore improve the clinical outcome in patients with thrombocytopenia. Also, therefore, it is important to consider these hematological characteristics of the donors on an individual basis so as to ensure a good quality of the product.
The authors acknowledge the work of Dr. Arushi Sehgal who helped in statistical analysis of the data.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2]