A Comparative Study of Platelet Indices, in Cases of Fever, Sepsis Leading To Multiorgan Dysfunction And Control Group, At A Tertiary Care Hospital Using An Automated Hematology Analyzer Sysmex Xn_1000
Journal Title: IOSR Journal of Dental and Medical Sciences (IOSR-JDMS) - Year 2017, Vol 16, Issue 12
Abstract
Introduction: Platelet indices are a group of derived platelet parameters obtained as a part of the automatic complete blood count.Emerging evidence suggests that Platelet indices may have diagnostic and prognostic value in certain diseases.Hence, simultaneous measurement of all platelet indices (MPV, PDW, P-LCR, PCT and PC) will provide a valid instrument for measuring disease. Aims & Objectives: To compare the parameters of platelet indices (MPV, PDW, P-LCR, PCT and PC) A] in patients with fever and B] in patients with sepsis leading to multiorgan dysfunction ,with control cases. Materials & Methods: Platelet indices of 100 consecutive hemograms with a clinical diagnosis of fever, 100 consecutive hemograms with a clinical diagnosis of MODS (Sepsis with Multiorgan dysfunction) were retrieved. The analysis was done on a Sysmex XN-1000 automated blood cell counter. The parameters of PIs were analyzed statistically using IBM SPSS version 22. Results:The difference in mean PDW between controls and MODS was statistically significant (p value=0.004). The difference in mean MPV between controls and MODS was statistically significant (p value=0.021). The difference in mean PLCR between controls and MODS was statistically significant (p value=0.005). The difference in mean PCT between controls and Fever was statistically significant (p value<0.001).The difference in mean PC between None of the groups was statistically not significant. Conclusions: Among the parameters P-LCR has shown highest predictive validity, followed by MPV and PDW.Considering all the AUC values very close to the null value of 0.5, none of the indices analysed were strong predictors of MODS. A prospective study with a larger sample size and follow up, may help in deriving a predictive value.
Authors and Affiliations
Dr. P. Ramana kumari . M. D, Dr. G. Sampoorna. M. D, Dr. C. Padmavathidevi. M. D, DCP Dr. T. D. N. Mounika
Keywords
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