Mean Platelet Volume (MPV) in Thrombocytopenia

Reddy, Sridhar R; Phansalkar, Manjiri; PVB, Ramalakshmi

doi:10.18049/jcmad/229

Cited by 9 publications

(37 citation statements)

References 7 publications

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“…[13] Hyperdestructive thrombocytopenia category includes idiopathic thrombocytopenias, malaria, Kala-azar, dengue fever, renal diseases, cardiac diseases, sepsis and viral fevers. [12,14] In our study distribution of the etiologies were similar to other studies by Reddy et al [15] , Katti et al [16] and Numbenjapon et al [17] as shown in the results. Dengue cases predominated the hyperdestructive group as the study was done during the early monsoon which is the peak season for this entity.…”

Section: Discussionsupporting

confidence: 91%

A Study of Variation in Adult Thrombocytopenic Histograms A Graph Often Overlooked

Shetty

Shubha

Vijaya

et al. 2020

APALM

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Background: With the advent of automation in hematology, both platelet indices and their histograms are available from the blood cell counters at no extra cost or time. The variations of histograms in various mechanisms of thrombocytopenias are explored in this study.Methods: Adults with thrombocytopenia determined with (name of the analyser)were categorized into four groups based on the mechanism of thrombocytopenia and variations in platelet histograms were studied in all groups. Data was collated and analysed using Microsoft Excel.Results: A total of 224 adults with thrombocytopenia were seen, most of them had hyperdestructive type (73.6%) followed by hypoproductive type (16.08%), abnormal pooling (6.3%) and EDTA induced thrombocytopenia (4.01%). The following variations in histogram were seen; Normal curve(8.03%), Curve not touching/reaching the baseline (43.75%), Broad based curve (10.71%), Bimodal curve (7.14%), Curve with short peak (25.9%) and Saw-tooth appearance of curve (4.47%) and correlated with the above mentioned mechanisms of thrombocytopenias using SPSS software version 20. Conclusion:An awareness regarding the variations in the platelet curve ensures a good correlation with its numerical parameters and also with the etiology of thrombocytopenias. With the era of automation taking over in most of the laboratories, it is imperative to have knowledge about these simple yet, often overlooked platelet histograms

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Section: Discussionsupporting

confidence: 91%

A Study of Variation in Adult Thrombocytopenic Histograms A Graph Often Overlooked

Shetty

Shubha

Vijaya

et al. 2020

APALM

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“…In a similar study done by Yalavarthi et al, [11] MPV and P-LCR were significantly higher in study groups in comparison to healthy controls while there was no significant variation of PDW in nonimmune thrombocytopenia and miscellaneous groups (Table 12). They also found PDW to be significantly lower in ITP cases when compared to healthy controls.…”

Section: Platelet Indicessupporting

confidence: 60%

“…Maximum number of cases belonged to first and third decades with a mean age of 28 years. In the study done by Gulati et al, [10] maximum number of cases belonged to first decade while Reddy et al [11] reported maximum number of cases in third decade. The age of the patients ranged from 2 days to 72 years.…”

Section: Discussionmentioning

confidence: 91%

A Study to Evaluate Use of Platelet Indices in Hyperdestructive Thrombocytopenia: A Two-year Experience from Tertiary Care Rural Hospital

Francis¹,

Shetageri²,

Roopa³

et al. 2021

JMSH

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Background: Thrombocytopenia is one of the most common causes of abnormal bleeding and is defined as platelet counts < 1.5 lakhs/cumm. Three processes can cause thrombocytopenia, namely: Deficient platelet production, accelerated platelet destruction, and abnormal pooling of the platelets within the body. Of these, accelerated platelet destruction is the most common cause for thrombocytopenia and has variety of etiologies. The usefulness of bone marrow analysis in assessing accelerated platelet destruction is still debated. Therefore, a new simple and non-invasive diagnostic approach for thrombocytopenia is needed. Aims and Objectives: The present study was done with an aim to evaluate the use of platelet indices, namely, mean platelet volume (MPV), Platelet Distribution Width (PDW), and Platelet Large Cell Ratio (P-LCR) in differentiating the various causes of hyperdestructive thrombocytopenia. Materials and Methods: This was a prospective study conducted over a period of 2 years and consisted of 206 cases of hyperdestructive thrombocytopenia. After recording relevant clinical details, platelet count along with platelet indices – MPV, PDW, and P-LCR was recorded. Based on the etiopathology identified, cases were categorized into three groups: Group I: Immunologic – cases of Immune thrombocytopenic purpura (ITP), Group II: Non-immune: Cases of sepsis and other non-immune causes of platelet destruction, and Group III: Viral and parasitic infections. Platelet indices were compared between the study groups and the control group which included 100 healthy individuals. Comparison was done among the three study groups as well. Results & Conclusions: Dengue accounted for the highest number of 131 (89.72%) cases in the study. MPV, PDW, and P-LCR were significantly higher (P < 0.0001) when compared to the healthy controls except P-LCR in Group II. A statistically significant increase in MPV was noted among ITP cases when compared to other causes of thrombocytopenia. There wa

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“…The association between Dengue and MPV is variable as shown by studies. Studies by Reddy et al [10] and Khanna et al [11] have shown a raised MPV in dengue cases. However a study by Nehara et al [12] has shown a low MPV in dengue cases.…”

Section: Discussionmentioning

confidence: 94%

Diagnostic Implication of Mean Platelet Volume in Thrombocytopenia

Bhat

Goveas

2020

APALM

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Introduction: The newer haematology analysers measure the platelet indices such as the mean platelet volume (MPV), platelet large cell ratio and platelet distribution width. It has been observed that MPV is increased in conditions associated with thrombocytopenia due to peripheral destruction. This study was carried out to know the utility of MPV and derive cutoff values in categorizing the conditions causing thrombocytopenia into hyperdestructive and hypoproliferative groups. Methods: The thrombocytopenia cases were categorized into two groups as hyperdestructive and hypoproliferative groups based on the bone marrow findings. The MPV on the day of admission was taken into consideration. The data were analysed using the mean, standard deviation and the t-test. ROC curve was plotted to derive the cutoff MPV value. Results: Of the total 89 thrombocytopenia cases, 53 were of hyperdestructive etiology and 36 were of hypoproliferative etiology. The mean MPV for group A was 9.56 with a standard deviation of 1.34 and that for group B was 8.45 with a standard deviation of 1.30. The p value was < 0.001. From the ROC curve, a cut off of 8.5 fl was taken. Conclusion: We conclude that a MPV value of >8.5fl is suggestive of a hyperdestructive etiology. Even though bone marrow remains a gold standard to distinguish between the hyperdestructive and hypoproductive thrombocytopenia groups, platelet indices like MPV can be used to aid in the diagnosis of etiology of thrombocytopenia.

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Mean Platelet Volume (MPV) in Thrombocytopenia

Cited by 9 publications

References 7 publications

A Study of Variation in Adult Thrombocytopenic Histograms A Graph Often Overlooked

A Study of Variation in Adult Thrombocytopenic Histograms A Graph Often Overlooked

A Study to Evaluate Use of Platelet Indices in Hyperdestructive Thrombocytopenia: A Two-year Experience from Tertiary Care Rural Hospital

Diagnostic Implication of Mean Platelet Volume in Thrombocytopenia

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