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Effect of donor parameters and cell separators on yield of apheresis platelet and their impact on corrected count increment in aplastic anemia patients.
BACKGROUND: The new cell separators make it simple to collect single donor platelets (SDP), although the platelet yield may vary depending on the cell separator used and donor-related clinical and laboratory variables.
AIMS: This study aims to study the factors affecting SDP yield and corrected count increment (CCI).
MATERIALS AND METHODS: This retrospective study was carried out at a tertiary care facility in northern India, over 4 years (May 2017-April 2020), data were retrieved and analyzed.
STATISTICAL ANALYSIS: Categorical variables were presented as proportions, while continuous variables were presented as mean with standard deviation, P < 0.05 was considered significant.
RESULTS: We found a positive correlation between predonation platelet count and yield ( r = 0.243, P = 0.000). No such significant correlation was found with Hb concentration ( r = 0.025, P = 0.720), age ( r = 0.016, P = 0.820), sex ( r = -0.038, P = 0.584), and weight ( r = -0.025, P = 0.714). Maximum platelet yield and minimum time were seen with Trima. Only 39.3% (33/84) meet the 24 h CCI. The majority of patients did not meet the desired CCI could be due to the patients' clinical condition. On logistic regression, we found a significant association of 24 h CCI with product yield (odds ratio [OR] = 0.168, P = 0.015) and posttransfusion platelet count (OR = 0.454, P < 0.05).
CONCLUSION: The only donor-related factor that influences yield is predonation platelet count, whereas 24 h CCI may depend on the clinical status of the patient and yield.
AIMS: This study aims to study the factors affecting SDP yield and corrected count increment (CCI).
MATERIALS AND METHODS: This retrospective study was carried out at a tertiary care facility in northern India, over 4 years (May 2017-April 2020), data were retrieved and analyzed.
STATISTICAL ANALYSIS: Categorical variables were presented as proportions, while continuous variables were presented as mean with standard deviation, P < 0.05 was considered significant.
RESULTS: We found a positive correlation between predonation platelet count and yield ( r = 0.243, P = 0.000). No such significant correlation was found with Hb concentration ( r = 0.025, P = 0.720), age ( r = 0.016, P = 0.820), sex ( r = -0.038, P = 0.584), and weight ( r = -0.025, P = 0.714). Maximum platelet yield and minimum time were seen with Trima. Only 39.3% (33/84) meet the 24 h CCI. The majority of patients did not meet the desired CCI could be due to the patients' clinical condition. On logistic regression, we found a significant association of 24 h CCI with product yield (odds ratio [OR] = 0.168, P = 0.015) and posttransfusion platelet count (OR = 0.454, P < 0.05).
CONCLUSION: The only donor-related factor that influences yield is predonation platelet count, whereas 24 h CCI may depend on the clinical status of the patient and yield.
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