STUDY OF MEAN PLATELET VOLUME AND RED CELL DISTRIBUTION WIDTH IN ACUTE KIDNEY INJURY

Introduction:

AKI complicates 5-7% of acute care hospital admissions and up to 30% of admissions to the ICU. AKI is an important risk factor for poor outcomes during admission as well as has a bearing on incident chronic kidney disease (CKD) burden in the long run. 

 Mean platelet volume (MPV) is the average platelet size with a value ranging from 7.2-11.2fL. High platelet turnover secondary to inflammation leads to increased MPV. There is considerable variability in studies on MPV as a predictor of AKI. 

 Red Cell Distribution Width, coefficient of variation (RDW-CV normal range 11-16%) and Red Cell Distribution Width Standard of Deviation (RDW-SD normal range 39-46 FL) measures the variability of red cell size and volume. RDW also increases in inflammatory states and independently predicts mortality in AKI patients admitted in ICU and CCU. 

 Estimation of RDW and MPV, both individually and in combination, might open new avenues in early detection and prediction of AKI as well as its prognostication. 

 As RDW-CV is affected by mean corpuscular volume (MCV), further refinement has come lately in the form of RDW-SD which is a direct measure of RBC volume variability and offers a more precise representation of size changes. 

 Majority of the studies have looked at RDW-CV as a predictor however, we looked at both RDW-CV and RDW-SD. As there is conflicting data in the available literature regarding utility of MPV and RDW we planned this study to correlate MPV and RDW in predicting outcomes of AKI and to check for variability of MPV and RDW in different causes of AKI.  

Methods:

Prospective observational hospital-based study spanning 18 months enrolling 128 adult patients. Detailed history, clinical examination and underlying disease pathology leading to AKI were recorded. Ethical clearance was obtained from institutional ethics committee. 

Exclusion criteria: CKD, smokers, terminal malignancy, chemotherapeutic agents causing myelosuppression, platelet transfusion in last 24 hours, Crohn’s disease and SLE. 

Blood samples were collected on days 0, 1, 3, 5 and 7 and MPV and RDW were analyzed using the XN1000- Hematology Analyzer.  

Results:

• Mean admission RDW-CV values decreased with increasing AKI stages (p=0.38). In non-dialysed group, lowest values of RDW-CV were seen on day 3. Lower RDW-CV did not predict the need for dialysis (p=0.51) 

 • Mean admission MPV values increased with increasing stage of AKI (p=0.05). Higher mean admission values could significantly predict death in our cohort (p=0.03). Lower MPV predicted the need for dialysis (p=0.11) 

 • Changes (from day 0 to day 3) in mean RDW-CV and MPV could not predict dialysis requirement or discharge significantly. 

• The cohort was divided into 6 sub-groups based on above and below the median values of RDW-CV/SD and MPV. In the 2 RDW subgroups, there was no correlation with need for dialysis and mortality. In the subgroup of patients above the median MPV mortality was less. (p=0.08). (Figure 1) 

 • ROC curves were plotted to predict the need for dialysis and prediction of death, however no definite value of the parameters could be found which would accurately predict the 2 outcomes. (Figure 2) 

Conclusions:

• Like the available literature, in our study, the 3 tested parameters (RDW-SD, RDW-CV, MPV) were not reliable predictors of AKI outcomes, including severity, dialysis needs, and mortality. 

• RDW-SD was used for the first time as a parameter in predicting AKI outcomes, but the results were inconclusive. 

• Further studies incorporating additional parameters like serum albumin, platelet count, and platelet distribution width, along with RDW-SD, RDW-CV and MPV may improve the sensitivity and specificity in predicting AKI outcomes. 

I have no potential conflict of interest to disclose.

I did not use generative AI and AI-assisted technologies in the writing process.