Investigation on the dynamic trajectory of platelet count in healthy adults
10.3760/cma.j.cn114452-20250626-00375
- VernacularTitle:基于群组轨迹模型的健康成人血小板计数动态变化轨迹研究
- Author:
Yuewei LING
1
;
Qiang MENG
;
Yiming ZHANG
;
Tiancong ZHANG
;
Kuofu LIU
;
Si CHEN
;
Xinwen YUAN
;
Shuang WANG
;
Zheng YANG
;
Hong JIANG
;
Yang FU
Author Information
1. 四川大学华西医院实验医学科，成都 610041
- Publication Type:Journal Article
- Keywords:
Platelet count;
Reference values;
Healthy adults;
Group based trajectory modeling
- From:
Chinese Journal of Laboratory Medicine
2025;48(9):1222-1226
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the longitudinal patterns and influencing factors of platelet counts among healthy adults in Sichuan Province from 2010 to 2021, and to inform the establishment of region-specific reference intervals for platelet counts.Methods:This study is a retrospective study. A total of 7 808 healthy adults who underwent annual physical examinations at West China Hospital, Sichuan University, between January 2010 and December 2021 were included. All participants were permanent Chengdu residents and completed consecutive complete blood count tests. Group-based trajectory modeling (GBTM) was used to identify distinct trajectories of platelet count over the ten-year period. One-way analyses were then conducted to compare baseline demographic characteristics (sex and age) among the different trajectory groups.Results:Among 7 808 participants, 4 589 (58.8%) were male and 3 219 (41.2%) were female. Four platelet count trajectories were identified by GBTM: steadily increasing group [27.4% (2 139/7 808)], early increase-plateau group [44.1% (3 445/7 808)], early decrease-subsequent increase group [5.4% (422/7 808)], and steadily decreasing group [23.1% (1 802/7 808)], with an average growth rate of 3.3%, 1.6%, 0.7%, and -0.6%, respectively. There were statistically significant differences in both sex and age distributions among the four trajectory groups. Sex-distribution differed significantly across the four trajectory groups ( χ2=73.3, P<0.001). The male proportions in the four trajectory groups were 59.6% (1 275/2 139), 62.8% (2 165/3 445), 48.1% (203/422), and 52.5% (946/1 802), respectively. The baseline ages were 45 (36, 55), 43 (35, 53), 50 (40, 60), and 47 (39, 58) years, respectively (H=121.0, P<0.001). Conclusions:Healthy adults in Sichuan Province exhibit four longitudinal trajectories of platelet counts: steadily increasing, early increase-plateau, early decrease-subsequent increase, and steadily decreasing. The two trajectories characterized by rising platelet counts (steadily increasing group and early increase-plateau group) exhibited higher male predominance and lower median ages, whereas the early decrease-subsequent increase group and the steadily decreasing group exhibited lower male proportions and higher median ages. Therefore, while establishing reference intervals and developing health management strategies for platelet counts, it is essential to account for the sex, age characteristics and the population′s dynamic changes.
