Role of platelet indices in differentiating hypoproductive and hyperdestructive thrombocytopenia

Parveen, Shabana; Vimal, Mourouguessine

doi:10.21276/apalm.1357

Cited by 12 publications

(39 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the present study group A included infections, neonatal TCPs, cardiac cases, pregnancy induced TCPs, renal, liver, sepsis, burns and immune thrombocytopenias (ITP) accounting to 75.3% of which infections were the majority number of cases similar to other studies. 8,13 In contrast, studies done by Numbenjapon T et al 15 and Khaleel KJ et al 16 found ITP being the majority of cases in group A. In the present study highest MPV and PDW values in group A category were seen in ITP cases similar to the other studies.…”

Section: Discussionsupporting

confidence: 64%

“…Ages of the patients ranged from 1 day (neonatal cases) to 85 years similar to other studies. 8,[13][14][15][16][17][18][19][20] Patients were categorized into three groups according to the predominant mechanism of TCPs. Majority of the cases in the present study were of group A (75.4%), followed by group B (24%) and group C (0.6%) similar to the study done by Reddy 5)…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Paramountcy of platelet parameters in thrombocytopenia- Our hospital experience

Malá¹,

Bhandari²,

Kittur³

2020

IJPO

View full text Add to dashboard Cite

Introduction: Thrombocytopenia defined as platelet count below 1,50,000/ul. This fall in platelet count may be due to decreased production, increased destruction and pooling of platelets. The platelet parameters include platelet count, mean platelet volume (MPV), platelet distribution width (PDW) obtained by automated cell counters. These help in knowing the pathomechanism of myriad cases of TCPs. Hence the present study was undertaken to know the variations and correlations of platelet parameters in various causes of TCPs. Materials and Methods: 700 blood samples of patients with platelet count <1,50,000/ul and 600 control group samples with normal platelet count >1,50,000/ul were studied. Hematological analysis was done by Sysmex KX-21. Platelet parameters of all the cases and control group were noted. The cases were grouped into various categories of A, B or C depending on mechanism of decrease in platelets. Data was analyzed and tested for statistical significance using one-way ANOVA and post hoc testing using Tukey's test. Results: Majority of the cases in the present study were in group A (75.3%), followed by group B (23.9%) and group C (0.6%). A higher value of MPV (10.15±1.30 fl) and PDW (14.44±2.35%) was found in group A compared to other categories. Significant results of MPV and PDW values were seen in group A and group B category. Conclusion: Platelet parameters like MPV and PDW obtained by automated cell counters together with platelet counts help us to know the pathomechanism of various causes of TCPs which inturn provides pivotal information for better management.

show abstract

Section: Discussionsupporting

confidence: 64%

Section: Discussionmentioning

confidence: 99%

Paramountcy of platelet parameters in thrombocytopenia- Our hospital experience

Malá¹,

Bhandari²,

Kittur³

2020

IJPO

View full text Add to dashboard Cite

show abstract

“…However, in studies conducted by Parveen and Vimal [14] and Gulati et al, [10] dengue fever comprised only 30.85% and 25.3% of cases, respectively. Malaria cases were higher in other studies when compared to our study [10,14,15] (Table 10). This difference may be attributed to the demographic variations and endemicity of the infection (Figure 1a and b).…”

Section: Discussionmentioning

confidence: 86%

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

View full text Add to dashboard Cite

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

show abstract

“…The analyzers have the advantage of not only being quick but are also able to throw light on a wide variety of indices and minimize the inter-observer bias. [2,9,10] The analyzers also display a plateletogram along with numerical indices which are often overlooked. [4] Other than the routine platelet counts, which is the most commonly asked parameter, the other platelet indices like MPV [Mean platelet volume], PCT [plateletcrit] and PDW [platelet distribution width] are also available in the analyzer readings.…”

Section: Discussionmentioning

confidence: 99%

“…This approach will narrow differentials, avoid unnecessary investigations and aid in targeted management. [2] Manual methods for determination of hematological parameters in laboratories which are Manual methods for determination of hematological parameters in laboratories which are labor intensive and time consuming are now largely replaced by automated analyzers. These analyzers routinely give platelet histogram in addition to platelet count and indices at no extra cost.…”

Section: Introductionmentioning

confidence: 99%

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

Shetty

Shubha

Vijaya

et al. 2020

APALM

View full text Add to dashboard Cite

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

show abstract

Role of platelet indices in differentiating hypoproductive and hyperdestructive thrombocytopenia

Cited by 12 publications

References 12 publications

Paramountcy of platelet parameters in thrombocytopenia- Our hospital experience

Paramountcy of platelet parameters in thrombocytopenia- Our hospital experience

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

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

Contact Info

Product

Resources

About