Investigation of the contribution of an underlying platelet defect in women with unexplained heavy menstrual bleeding

Figures & data

Table I. The streamlined panel of agonists used for lumi-aggregometry in diagnosing platelet function defects in 175 women with HMB. ATP secretion from dense granules was measured with ADP 30 µM, adrenaline 10 µM, arachidonic acid 1 mM, PAR1 – specific peptide 100 µM and collagen 3 µg/ml.

Agonist	Concentration	Comments/further guidance
ADP	10 µM	Maximal, sustained aggregation expected at this concentration. If reversible aggregation seen use 30 µM.
Adrenaline	10 µM	Biphasic aggregation expected. If aggregation absent or reduced use 30 µM.
Arachidonic acid	1 mM	Maximal, sustained aggregation expected. If aggregation reduced or reversible use U46619 3 µM.
PAR-1 receptor specific peptide (SFLLRN)	100 µM	Maximal, sustained aggregation expected. If aggregation reduced use PAR-4 receptor specific peptide (AYPGKF; 500 µM).
Collagen	1 µg/ml	If aggregation reduced use 3 µg/ml. If this concentration shows reduced aggregation, use collagen related peptide (CRP) 3 µg/ml.
Ristocetin	1.5 mg/ml	Maximal, sustained agglutination (often biphasic) expected. If reduced consider vWF profile and GPIb levels by flow cytometry.

Table II. Typical lumi-aggregometry findings in the commonly encountered platelet defects within the HMB cohort.

Platelet defect	Aggregation results	Secretion results
Secretion defects	Absence of secondary wave aggregation to most agonists used in low concentrations, and epinephrine at all concentrations	Significantly reduced levels of ATP secretion (when normalized for platelet count)
Thromboxane pathway defects	Absence/severe reduction of aggregation in response to arachidonic acid while response to thromboxane mimetics is preserved (for cyclooxygenase defects) or absence of aggregation response to both arachidonic acid and thromboxane mimetics (for thromboxane receptor defects) Commonly, absence of secondary wave aggregation to most agonists used in low concentrations, and epinephrine at all concentrations	Normal
Gi-coupled receptor defects	Reduced aggregation to ADP with notable deaggregation even at high concentrations of agonist Reduced primary wave response to epinephrine and absence of secondary wave	Normal

Figure 1. Spread of ages for all recruited patients.

A scatter dot plot showing the spread of ages of all recruited patients in this study. The patients age was available for 22 healthy controls and 154 HMB patients. Horizontal bars indicate median and interquartile range. Statistical analysis was performed using parametric unpaired t-test, statistically significant difference is denoted by **** P < 0.0001.

Table III. Phenotypic symptoms of 175 patients recruited to the UK-GAPP study with HMB of unknown aetiology. Types of bleeding symptoms were assessed using the ISTH-BAT and the percentage of patients suffering from a platelet defect or no platelet defect using lumiaggregometry are listed. Statistical analysis was performed using ordinary two-way ANOVA with Sidak’s multiple comparisons test. P-values are listed, no statistical significance was noted (P ≥ 0.05).

Type of bleeding	Patients with platelet defect (n = 82)	Patients with no platelet defect (n = 93)	Percentage of total patients with bleeding tendencies	P-value
Heavy menstrual bleeding	82	93	100	0.9898
Cutaneous bleeding	73	77	85.7	>0.9999
Oral cavity bleeding	66	69	77.1	>0.9999
Bleeding from minor wounds	55	57	64.0	>0.9999
Bleeding after tooth/teeth extraction	55	48	58.9	>0.9999
Epistaxis	48	45	53.1	>0.9999
Post-partum hemorrhage	38	45	47.4	0.9998
Bleeding after surgery/major Trauma	44	33	44	0.9898
Gastrointestinal bleeding	25	28	30.3	>0.9999
Hematuria	18	25	24.6	0.9998
Muscle hematomas or hemarthrosis (spontaneous)	14	10	13.7	>0.9999
Other bleeding^1	66	38	59.4	0.2343

¹other bleeding episodes includes: venipuncture and ovulation bleeding, conjunctival hemorrhage or excessive bleeding following or venipuncture. Overall some patients had > 1 other bleeding complaint

Figure 2. The relationship between presence of a platelet function defect detected by lumiaggregometry and the ISTH-BAT score.

A scatter dot plot showing the spread of ISTH-BAT scores in the healthy controls (n = 22), no platelet defect (n = 89) and platelet defect (n = 82) groups. Horizontal bars indicate median and interquartile range. Statistical analysis was performed using the non-parametric Kruskal-Wallis test and Dunn’s adjustment for multiple comparisons, the mean rank of each column was compared with the mean rank of every other column. Statistically significant difference is denoted by **** = P < 0.0001. No statistical significance (P = 0.46) was seen between the no platelet defect and platelet defect group.

Figure 3. The relationship between the type of platelet defect identified by lumiaggregometry and the ISTH-BAT score.

A scatter dot plot showing the spread of ISTH-BAT scores between the platelet defects identified on lumiaggregometry, healthy controls (n = 21), No defect (n = 88), defect (n = 75) of which; cyclooxygenase defect (n = 7), G_i receptor signalling defect (Gi defect) (n = 14), Secretion defect (n = 13), thrombocytopenia (n = 25), ADP receptor defect (n = 3) and other (n = 13). Horizontal bars indicate median and interquartile range. Statistical analysis was performed using non-parametric Kruskal-Wallis and Dunn’s multiple comparisons test, the mean rank of each column was compared with the mean rank of every other column. Statistically significant difference is denoted by * = P < 0.05, **** = P < 0.0001, no statistically significant difference (P > 0.05) was observed between the platelet defect subgroups.

Figure 4. The type of platelet defect identified in the HMB group as defined by lumiaggregometry.

Figure 5. Comparison of PLT-F between types of platelet defect groups identified by lumiaggregometry. A scatter dot plot showing the spread of PLT-F results between the recruited patients. Healthy controls (n = 43), all HMB patients (n = 103), No defect (n = 61), and defect (n = 42). Error bars represent mean ± 1 SD. Statistical analysis was performed using parametric ordinary one-way ANOVA with Tukey multiple comparisons test, the mean rank of each column was compared with the mean rank of every other column. Statistically significant difference is denoted by * = P ≤ 0.05, *** = P ≤ 0.001.

Figure 6. Other haematological and platelet function testing findings between the groups of patients in the study. (A) Comparison of haemoglobin between healthy volunteers and recruited patients with and without a platelet defect. A scatter dot plot showing the spread of Hb results between the recruits. Healthy controls (n = 43), all HMB patients (n = 92), no defect (n = 56), and defect (n = 36). Horizontal bars indicate median and interquartile range. Statistical analysis was performed using non-parametric Kruskal-Wallis and Dunn’s multiple comparisons test, the mean rank of each column was compared with the mean rank of every other column. Comparison between pairs of groups was not significant (P >0.05) for all data points. (B) Comparison of MCV parameters between the healthy control and recruited patients with and without a platelet defect. A scatter dot plot showing the spread of MCV results between the recruits. Healthy controls (n = 42), all recruited HMB patients (n = 92), No defect (n =56) and, defect (n = 36). Horizontal bars indicate median and interquartile range. Statistical analysis was performed using non-parametric Kruskal-Wallis and Dunn’s multiple comparisons test, the mean rank of each column was compared with the mean rank of every other column. Comparison between pairs of groups was not significant (P ≥ 0.05) for all data points. (C) Comparison of MPV parameters between types of platelet defects identifiedvia lumiaggregometry. A scatter dot plot showing the spread of MPV results between the recruits. Healthy controls (n = 43), all HMB patients (n = 162), No defect (n = 86), and defect (n = 76). Horizontal bars indicate median and interquartile range. Statistical analysis performed using the non-parametric Kruskal-Wallis test and Dunn’s adjustment for multiple comparisons, the mean rank of each column was compared with the mean rank of every othercolumn. Statistically significant difference is denoted by * = P ≤ 0.05. (D) Comparison of ATP-secretion between types of platelet defects identified by lumiaggregometry. Scatter dot plot showing the spread of ATP secretion results between the recruited patients. Healthy controls (n = 42), all HMB patients (n = 155), no defect (n = 89), and defect (n = 66). Horizontal bars indicate median and interquartile range. Statistical analysis was performed using non-parametric Kruskal-Wallis and Dunn’s multiple comparisons test, the mean rank of each column was compared with the mean rank of every other column. Statistically significant difference is denoted by *** = P ≤ 0.001.