Abstract
Background
Reference intervals are important for interpretation of clinical laboratory tests. The platelet (PLT) indices such as the mean platelet volume (MPV) and platelet distribution width (PDW) are newer hematological parameters, which have been recently reported as clinically valuable biomarkers. However, there are not many studies that have estimated the reference intervals for these parameters in healthy Chinese Han adults.
Objective
The objectives of this study were to establish reference values of PLT indices [including PLT count, MPV, PDW, platelet‐large cell ratio (P‐LCR), and plateletcrit (Pct)] for healthy Chinese Han adults. We also aimed to determine the region‐based differences of PLT indices in China.
Methods
A total of 4,642 volunteers with a mean age of 43 were recruited from six regions of China. PLT indices were performed on Sysmex XE‐2100 hematology analyzers, whose traceability was well verified.
Results
There were significant region‐based differences for all PLT indices. Reference people in Chengdu had the lowest mean PLT count and Pct, but the highest MPV, PDW, and P‐LCR among the six regions. Therefore, we derived the reference intervals in Chinese Han population excluding Chengdu reference people for PLT indices as PLT count: (127–341) × 109/l; MPV: (9.20–13.30) fl; PDW: 9.90–19.00%; P‐LCR: 18.10–52.00%; Pct: 16.00–41.00%.
Conclusions
Region‐specific reference intervals are essential as there were statistically significant region‐related differences in the PLT parameters. The reference intervals established in this study differed from the existing reference values. Chengdu region may need proper specific reference ranges, which apply to their people, for all PLT parameters.
Keywords: reference intervals, platelet indices, PLT count, MPV, PDW, P‐LCR, Pct
INTRODUCTION
Reference intervals are crucial decision‐making tools aiding clinicians in diagnosis orientation and treatment decision. The clinical utility of newer hematological parameters such as the analyzer‐derived PLT indices has been explored in the recent years 1. Mean platelet volume (MPV) and platelet distribution width (PDW) have been reported to be correlated with PLT function and may be more sensitive indices than PLT number as a marker of clinical interest in various disorders such as cardiovascular disease 2 and stroke 3. Platelet‐large cell ratio (P‐LCR), when analyzed along with the other PLT parameters, helps in the differential diagnosis of the thrombocytosis‐related disease 4. Recent studies have explored the role of plateletcrit (Pct) as independent risk factors of spontaneous echo contrast in patients with mitral stenosis 5. Considering the role of the PLT indices in clinical practice, it is encouraging to establish the reference values for these newer parameters.
However, PLT parameters are influenced by various factors such as age, gender, ethnicity origin, altitude, and geographic locations 6, 7, 8 and hence it is important to define the specific reference values with regards to age, gender, ethnicity, and the region. According to this context, we aimed to establish reference values of PLT indices in China by studying healthy Chinese Han adults from voluntary blood donors recruited from six regions (Chengdu, Beijing, Guangzhou, Shanghai, Shenyang, and Xi'an represented Southwest, North, South, East, Northeast, and Northwest China, respectively).
MATERIALS AND METHODS
This study was approved by the Ethics Committee of each study center. Written informed consents were obtained from all participants.
Participants
A total of 4,642 blood donor volunteers were included in this study. Among all subjects, there were 644 from Chengdu, 760 from Beijing, 945 from Guangzhou, 736 from Shanghai, 861 from Shenyang, and 696 from Xi'an. Demographic features of all participants were provided in Table 1.
Table 1.
Demographics of the Reference Individuals
| Mean age (age | ||||
|---|---|---|---|---|
| Region | n | Male/female | range, years) | P value |
| Chengdu | 644 | 331/313 | 41.4 (20–75) | >0.05 |
| Beijing | 760 | 340/420 | 43.7 (20–79) | |
| Guangzhou | 945 | 446/499 | 47.8 (20–79) | |
| Shanghai | 736 | 292/444 | 44.0 (20–78) | |
| Shenyang | 861 | 368/493 | 43.9 (20–79) | |
| Xi'an | 696 | 359/337 | 38.4 (20–78) | |
| Total | 4,642 | 2,136/2,506 | 43.2 (20–79) |
Every subject underwent an interview with a physician using a life‐health questionnaire and a physical examination form. Exclusion criteria included body mass index ≥28, high blood pressure (systolic number ≥ 140 mmHg and/or diastolic number ≥ 90 mmHg), alcohol assumption > 30 g per day, tobacco use > 20 cigarettes per day, drugs intake within 2 weeks, surgery within 6 months, blood donation or transfusion within 4 months, pregnancy, less than 1 year after childbirth, hypothyroidism and hyperthyroidism, diabetes, atherosclerosis and vascular disease, cardiopathy, chronic nephropathy, hepatobiliary disease, allergic diseases, hematological disease, myopathy, autoimmune disease, burns and muscle trauma, the presence of acute and chronic infection, plasma fasting glucose > 7.0 mmol/l, serum creatinine > 120 μmol/l, serum creatine kinase > 400 U/l, positive hepatitis B surface antigen, positive antihepatitis C virus antibody, positive anti‐immunodeficiency virus antibody, and positive urinalysis.
The institutional SOPs (standard operating procedures) were followed for the sample collection and for conducting the tests.
Methods
Blood samples
All samples were collected between 8:00 a.m. and 9:00 a.m. Three milliliter fasting whole blood was collected from the cubital vein with a BD (New York, USA) Vacutainer tube with EDTA‐K2. Complete blood counts were all performed within 2 hr of the blood collection.
Instruments
XE‐2100 hematology automatic analyzers from six laboratories (laboratories of Chengdu, Beijing, Guangzhou, Shanghai, Shenyang, Xi'an) were all purchased from Sysmex, Japan. Dedicated reagents and standard methodologies were used.
Quality control
Three levels of quality controls (e‐CHECK for XE were purchased from Sysmex, Japan) were run every day and the analyzers were all maintained according to the manufacturer's instructions during the entire period of the study.
Performance verification
Data of the six analyzers (Sysmex XE‐2100 from six laboratories of six regions in this study) were compared with the data from reference measurement procedures (established in Hematology Reference Laboratory of National Center for Clinical Laboratory, Beijing, China) by testing five fresh blood samples assigned target values of PLT count, which were performed three times during the entire study period. Biases were calculated using the mean values of twice tested by the three analyzers.
Statistical Analysis
Data were analyzed using SPSS 17.0 software (Chicago, IL). The point estimate of the mean and the median with an interval estimate of 2.5 percentile and 97.5 percentile were provided as the reference values. ANOVA and Student–Newman–Keuls were performed to detect the difference among groups. P values less than 0.05 were considered significant.
RESULTS
Reference Individuals
Among the 4,642 individuals, 2,136 (46.0%) were males and 2,506 (54.0%) were females. All of them were Han people, and the mean age was 43 (age range 20–79). Table 1 shows the demographic characters of the reference individuals, and the age–gender distribution of the reference individuals was shown in Fig. 1. A majority of them (83%) were in the 20–59 years age group.
Figure 1.
The age–gender distribution of the reference individuals.
Performance Verification
The calculated biases of six analyzers (Sysmex XE‐2100 from six laboratories of six regions in this study) in comparison with the data from reference measurement procedures were presented in Table 2. All biases matched the acceptable bias ranges.
Table 2.
Biases of the Six Analyzers Compared With the Reference Measurement Procedures
| Biases for PLT count (%) | ||||
|---|---|---|---|---|
| Region | First time | Second time | Third time | Acceptable bias for PLT counta |
| Blood sample number | 5 | 5 | 5 | |
| Chengdu | −3.8 ∼ 6.9 | −7.5 ∼ 1.2 | −6.8 ∼ 6.6 | <12.5% |
| Beijing | 2.2 ∼ 10.6 | −5.0 ∼ 8.6 | 0.5 ∼ 9.8 | |
| Guangzhou | −2.5 ∼ 8.3 | −7.5 ∼ 2.5 | −3.0 ∼ −4.0 | |
| Shanghai | 2.9 ∼ 4.1 | −4.2 ∼ 1.0 | −3.1 ∼ 4.7 | |
| Shenyang | −0.4 ∼ 6.5 | −7.5 ∼ 1.2 | −4.7 ∼ 5.3 | |
| Xi'an | −2.1 ∼ 4.6 | −8.4 ∼ 1.2 | −8.5 ∼ 4.7 | |
The acceptable bias ranges for PLT count is the 1/2 allowable error as described in CLIA’88 9.
Gender‐Specific Reference Intervals and Means
The reference intervals were calculated based on the IFCC and the CLSI 10 guidelines. The study reference intervals (2.5th to 97.5th percentile) for the males and females are presented and compared with the existing reference values that are currently used in our laboratory (Table 3). Both the lower and the upper limits showed an increase with the PLT count but a decrease with Pct values in both males and females. While MPV, PDW, and P‐LCR all showed a mild decrease in the lower limits but an increase in the upper limits for both genders.
Table 3.
Study Reference Intervals and Existing Reference Intervals of the PLT Indices
| Study | Existing | ||
|---|---|---|---|
| reference | reference | ||
| Parameter | Gender | intervals | intervals |
| PLT (×109/l) | Males | 111–305 | |
| Females | 122–334 | ||
| Together | 115–323 | 100–300 | |
| MPV (fl) | Males | 9.24–13.22 | |
| Females | 9.29–13.21 | ||
| Together | 9.27–13.22 | 9.4–12.6 | |
| PDW (%) | Males | 9.21–18.37 | |
| Females | 9.09–18.29 | ||
| Together | 9.13–18.33 | 9.8–16.2 | |
| P‐LCR (%) | Males | 18.60–50.59 | |
| Females | 18.50–50.81 | ||
| Together | 18.50–50.72 | 19.1–47.0 | |
| Pct (%) | Males | 12.87–35.27 | |
| Females | 15.43–36.23 | ||
| Together | 14.05–35.95 | 16.0–38.0 |
Gender‐based statistically significant differences in the means were observed for the mean PLT count and Pct values (P < 0.05). As shown in Table 4, the females had a higher mean PLT count, MPV, P‐LCR, and Pct, whereas the males had a higher PDW than their counterparts.
Table 4.
Gender‐Specific Means and Standard Errors for PLT Indices
| Males | Females | ||
|---|---|---|---|
| Parameter | (n = 2,136) | (n = 2,506) | P value |
| PLT (×109/l) | 208 ± 50 | 228 ± 54 | <0.05 |
| MPV (fl) | 11.23 ± 1.02 | 11.25 ± 1.00 | >0.05 |
| PDW (%) | 13.79 ± 2.34 | 13.69 ± 2.35 | >0.05 |
| P‐LCR (%) | 34.60 ± 8.16 | 34.65 ± 8.24 | >0.05 |
| Pct (%) | 24.07 ± 5.72 | 25.83 ± 5.31 | <0.05 |
Data were expressed as mean ± SE.
Region‐Specific Means and Reference Intervals
When analyzing the region‐based differences of the PLT indices, we found an interesting phenomenon. Statistically significant region‐based differences in the means were also observed for all the PLT parameters. As shown in Table 5, reference people in Chengdu had the lowest mean PLT count and Pct but the highest MPV, PDW, and P‐LCR among the six regions. Meanwhile, when compared with total (means of six regions, including Chengdu, Beijing, Guangzhou, Shanghai, Shenyang, Xi'an), the mean PLT count (164 × 109/l vs. 219 × 109/l) and Pct (21.86% vs. 25.00%) in Chengdu people were also lower while MPV (12.36 fl vs. 11.24 fl), PDW (16.26% vs. 13.73%), and P‐LCR (43.55% vs. 34.61%) were higher.
Table 5.
Region‐Specific Means and Standard Errors for PLT Indices
| Region | PLT (×109/l) | MPV (fl) | PDW (%) | P‐LCR (%) | Pct (%) |
|---|---|---|---|---|---|
| Chengdu | 164 ± 53 | 12.36 ± 1.34 | 16.26 ± 3.61 | 43.55 ± 10.67 | 21.86 ± 4.99 |
| Beijing | 244 ± 52* | 10.92 ± 0.85* | 12.81 ± 1.86* | 32.05 ± 7.25* | 26.53 ± 5.15* |
| Guangzhou | 245 ± 54* | 10.30 ± 0.80* | 11.83 ± 1.63* | 26.88 ± 6.62* | 25.13 ± 5.05* |
| Shanghai | 220 ± 53* | 11.05 ± 1.05* | 13.19 ± 2.25* | 32.57 ± 8.16* | Not available |
| Shenyang | 225 ± 50* | 11.19 ± 0.86* | 13.31 ± 1.89* | 34.41 ± 7.28* | 26.48 ± 7.15* |
| Xi'an | 215 ± 56* | 11.63 ± 1.16* | 14.99 ± 2.84* | 38.21 ± 9.33* | Not available |
| Total | 219 ± 53* | 11.24 ± 1.01* | 13.73 ± 2.35* | 34.61 ± 8.22* | 25.00 ± 5.59* |
Data were expressed as mean ± SE.
*P < 0.05 versus Chengdu.
Gender‐Region Based Reference Intervals and Means
As the differences of means for all PLT indices in Chengdu from other regions, we compared the data of Chengdu with those of other five regions (data excluding Chengdu). As shown in Table 6, both the males and females in Chengdu had lower mean PLT count and Pct but higher MPV, PDW, and P‐LCR in comparison with the means of other five regions in the same gender group.
Table 6.
Region‐Gender Specific Means and Standard Errors for PLT Indices
| Males (n = 2,136) | Females (n = 2,506) | |||
|---|---|---|---|---|
| Parameter | Chengdu | Total (except for Chengdu) | Chengdu | Total (except for Chengdu) |
| PLT (×109/l) | 157 ± 48* | 219 ± 51 | 171 ± 57** | 240 ± 55 |
| MPV (fl) | 12.35 ± 1.30* | 10.98 ± 1.04 | 12.37 ± 1.38** | 10.97 ± 1.03 |
| PDW (%) | 16.33 ± 3.53* | 13.22 ± 2.33 | 16.19 ± 3.71** | 13.05 ± 2.31 |
| P‐LCR (%) | 43.47 ± 10.34* | 32.57 ± 8.49 | 43.64 ± 11.02** | 32.39 ± 8.57 |
| Pct (%) | 20.90 ± 4.41* | 25.00 ± 6.36 | 22.90 ± 5.37** | 26.80 ± 5.31 |
Data were expressed as mean ± SE.
*P < 0.05 versus total (except for Chengdu) in males; **P < 0.05 versus total (except for Chengdu) in females.
The region‐gender specific reference intervals in this study for the males and the females are presented and compared with the existing reference values in Table 7. In Chengdu, both the lower and upper limits showed a decrease with the PLT count and Pct values but an increase with the MPV, PDW, and P‐LCR in both genders in comparison with the existing reference intervals. Surveying overall samples excluding that from Chengdu, both the lower and upper limits showed an increase with the PLT count and PDW in both males and females; while both the MPV and P‐LCR showed a mild decrease in the lower limits and an increase in the upper limits, when compared with the existing reference intervals. In addition, an increase in the upper limits of Pct in both genders were observed, whereas the lower limit decreased in males and increased in females. However, when compared with overall regions excluding Chengdu, a decrease in both the lower and upper limits of the PLT count and Pct and an increase in limits of the MPV, PDW, and P‐LCR were observed in both genders in Chengdu.
Table 7.
Region‐Gender Based Reference Intervals for PLT Indices Compared With Existing Reference Intervals
| Study reference intervals | Existing reference | |||
|---|---|---|---|---|
| Parameter | Gender | Chengdu | Total (except for Chengdu) | intervals |
| PLT (×109/l) | Males | 68–254 | 122–322 | |
| Females | 67–304 | 138–354 | ||
| Together | 67–280 | 127–341 | 100–300 | |
| MPV (fl) | Males | 9.94–14.60 | 9.30–13.35 | |
| Females | 9.80–14.90 | 9.20–13.30 | ||
| Together | 9.84–14.70 | 9.20–13.30 | 9.4–12.6 | |
| PDW (%) | Males | 10.60–23.77 | 10.00–19.40 | |
| Females | 10.60–23.50 | 9.80–19.00 | ||
| Together | 10.60–23.56 | 9.90–19.00 | 9.8–16.2 | |
| P‐LCR (%) | Males | 23.50–60.22 | 18.45–51.75 | |
| Females | 22.90–62.09 | 18.00–52.00 | ||
| Together | 23.16–61.02 | 18.10–52.00 | 19.1–47.0 | |
| Pct (%) | Males | 13.00–29.58 | 15.00–45.00 | |
| Females | 13.03–34.98 | 17.00–39.28 | ||
| Together | 13.00–33.58 | 16.00–41.00 | 16.0–38.0 | |
Effect of Age on Region‐Specific Means
To understand the effect of age on the PLT parameters, graphs were plotted between the mean value and age in Chengdu and other five regions (Fig. 2A–E). In all age groups (20–29, 30–39, 40–49, 50–59, 60–69, 70–79 years), reference people in Chengdu had a lower mean value of PLT count and Pct but a higher MPV, PDW, and P‐LCR than their counterparts. Chengdu people showed a gradual rise in the mean PLT count and Pct values with age, and a highest value in (40–49) age group for the mean MPV, PDW, and P‐LCR. Means of all these PLT parameters in other five regions showed a mild decreasing trend. There were no significant differences among all the age groups for these PLT indices in both Chengdu and Total (except for Chengdu). However, statistically significant differences for all PLT parameters between Chengdu and overall regions excluding Chengdu in each age group were observed (P < 0.05).
Figure 2.
PLT indices with age in Chengdu and total regions excluding Chengdu. (A) The mean PLT count with age; (B) the mean MPV with age; (C) the mean PDW with age; (D) the mean P‐LCR with age; (E) the mean Pct with age.
DISCUSSION
By testing fresh blood samples assigned target values, all six hematology analyzers employed in this study were well verified for their traceability. Therefore, the reference ranges established in this study were analyzer‐independent.
The objective of this study was to establish reference values for PLT indices (including PLT count, MPV, PDW, P‐LCR, Pct), which may serve as standards for interpretation of laboratory results in China. Under strict exclusion criteria, a total of 4,642 reference individuals were recruited from Southwest China (Chengdu), North China (Beijing), South China (Guangzhou), East China (Shanghai), Northeast China (Shenyang), and Northwest China (Xi'an), and all of them were Han adults.
In comparison with the existing reference intervals for all PLT indices (PLT count, MPV, PDW, P‐LCR, and Pct), the study reference values calculated with the data from above six regions showed obvious differences. This suggested that the existing reference intervals for PLT parameters could not apply to our population. And it is necessary and important to develop new reference intervals for PLT indices, especially the newer parameters such as MPV and PDW.
In this study, gender‐based statistically significant differences were found for the mean PLT count. In males, the mean platelet count was 208 × 109/l and in females 228 × 109/l. The same results were observed in African 11, 12 and North American 13 studies. The reasons for these differences according to gender are still unclear. However, considering the clinically practical significance and convenience, the reference ranges regardless of gender were recommended.
Besides, region‐based differences for all PLT parameters were also statistically significant. Among six study centers, we observed a lowest mean PLT count and Pct but a highest MPV, PDW, and P‐LCR of reference people in Chengdu, while the mean values of these parameters in other five regions did not show so obvious differences. This was in agreement with the observations that were made by other Chinese researchers 14. We therefore calculated the reference intervals for all PLT parameters with only five regions excluding Chengdu, with both genders together, both the lower and upper limits showed an increase with the PLT count but a decrease with the Pct; while MPV, PDW, and P‐LCR all showed a mild decrease in the lower limits and an increase in the upper limits, when compared with the existing reference intervals. This highlighted the necessity and importance of deriving new and region‐specific reference ranges for PLT indices.
We also calculated the references values for Chengdu only, and both the limits of these values in both genders showed obvious differences from either the above study reference intervals (calculated without data of Chengdu) or the existing reference intervals. Reference people in Chengdu had lower PLT count and Pct but higher MPV, PDW, and P‐LCR than overall people excluding Chengdu people, which suggested that PLT indices of Chengdu people was characterized by low PLT concentration but high volume. This suggested that the study reference intervals for PLT indices, calculated by data without Chengdu, might not be suitable to apply to the interpretation of laboratory tests sometimes in Chengdu region. Chengdu people may need their own reference ranges for PLT indices. This observation merits further studies and we are focused on it.
CONCLUSIONS
Region‐specific reference intervals are essential as there were region‐related statistically significant differences in the PLT parameters. The study reference intervals for PLT indices in our population excluding Chengdu reference people differed from the existing reference values and are established as PLT count: (127–341) × 109/l; MPV: (9.20–13.30) fl; PDW: 9.90–19.00%; P‐LCR: 18.10–52.00%; Pct: 16.00–41.00%. Chengdu region may need proper reference ranges, which apply to their people, for PLT indices.
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
ACKNOWLEDGMENTS
We thank the volunteers for donation of samples to the study, as well as the hospital staff who made this study possible. This study was supported by the Ministry of Health, China.
Grant sponsor: National Key Technologies R&D Program of China; Grant number: 2012BAI37B01.
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