Atrial fibrillation is the most common type of arrhythmia. In people aged 60 to 65, the incidence of atrial fibrillation is less than 1%. But, in people over the age of 80, the incidence of atrial fibrillation is 8% to 10% [
Atrial fibrillation will seriously affect the prognosis of patients. Studies have shown that the incidence of stroke in patients with atrial fibrillation will increase fivefold. Persistent atrial fibrillation accounts for 35% of all-cause mortality in patients with atrial fibrillation [
At present, the mechanism of cognitive impairment in patients with atrial fibrillation is not completely clear. The possible mechanisms include the following points [
The main functions of platelets are coagulation and hemostasis, repair of damaged blood vessels, protection of the vascular endothelium, participation in endothelial repair, and prevention of atherosclerosis. At the same time, platelets have the function of mediating immune inflammatory response [
The purpose of this cross-sectional study was to explore the correlation between plasma platelet count and cognitive function in patients with atrial fibrillation. The independent variable of the study was platelet content (continuous variable), and the dependent variable was cognitive function (continuous variable).
A total of 254 patients with atrial fibrillation were conveniently selected from December 1, 2018, to December 1, 2019, in the Department of Cardiology, Affiliated Hospital of Jining Medical College, Jining City, Shandong Province. Inclusion criteria were age more than 18 years; clinically diagnosed with atrial fibrillation; informed consent to this study; and signed informed consent form. Exclusion criteria were patients with deafness; patients with no basic reading and writing ability; patients with severe illness; and could not cooperate. The diagnosis of atrial fibrillation is based on 12-lead electrocardiogram and 24-hour ambulatory electrocardiogram. According to the onset time of atrial fibrillation, the patients were diagnosed as paroxysmal atrial fibrillation, persistent atrial fibrillation, long-term persistent atrial fibrillation, and permanent atrial fibrillation.
General data of patients were collected, including age, sex, marital status, education, living conditions, smoking, drinking, BMI index, and other indicators. At the same time, the clinical examination and examination results of the patients were collected including hemoglobin (Hb), red blood cell (RBC), prothrombin time (PT), International Normalized Ratio (INR), activated partial thromboplastin time (APTT), D-dimer, free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH), creatinine, urea, uric acid (UA), aspartate transaminase (AST), alanine aminotransferase (ALT), lipoprotein, total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein (LDL), and left ventricular ejection fraction (LVEF) (%). The patients’ past history (including hypertension, diabetes, heart failure, coronary heart disease, myocardial infarction, hyperlipidemia, valvular disease, and cerebral infarction) and medication history within 1 month before admission (including aspirin, warfarin, clopidogrel, tegrel, and rivashaban) were collected. This study was approved by the Medical Scientific Research Ethics Committee of the affiliated Hospital of Jining Medical College.
The cognitive function of the patients was evaluated with the Montreal Cognitive function Assessment scale (MoCA), which was sinicized by the Chinese cultural background. It includes the following aspects: (1) short-term memory: learning and memorizing 5 words twice and delayed recall after about 5 minutes (5 points); (2) visual-spatial ability: clock drawing test (3 points) and copying three-dimensional cube graphics (1 point); (3) executive function: modified wiring test B (1 score), language fluency test (1 score), and word similarity test (2 points); (4) attention, computational ability, and working memory: target number recognition (1 score), continuous subtraction test (3 points), and digit span test (2 points); (5) language: common animal naming test (3 points), retelling 2 complex sentences (2 points), and aforementioned language fluency; and (6) orientation: time and place orientation (6 points). If the subjects have less than 12 years of education, we will add 1 point to the total score. The full score of MoCA is 30. The higher the score, the better the cognitive function. The test will take about 10 minutes.
The continuous variables were presented in two forms. The K-S method was used to conduct the normality test. In the first form, continuous variables with normal distribution were expressed as mean ± standard deviation. In the second form, continuous variables with skewed distribution were presented as median (min, max). The categorical variables were expressed as frequency or percentage. The chi-square (categorical variables), one-way analysis of variance (normal distribution), or Kruskal–Wallis H tests (skewed distribution) were used for the differences among different platelet groups (trisection based on platelets data). The data analysis was based on three criteria: (1) the relationship between platelet count and cognitive function (linear or nonlinear), (2) the factors modifying or interfering with the relationship between platelet count and cognitive function, and (3) the interference factors or the true relationship between platelet count and cognitive function after the stratified analysis. Therefore, data analysis was summarized in three steps. Step 1: univariate and multivariate binary logistic regression analyses were employed. Two models were constructed: model 1, a crude model with no covariates adjusted; model 2, adjusted only for sociodemographic data; and model 3, model 2 + other covariates presented in Table
Baseline characteristics of participants.
Platelets ( | T1 <172 | T2 172–225 | T3 >225 | |
---|---|---|---|---|
83 | 85 | 86 | ||
Age (year) | 68.46 ± 11.32 | 67.56 ± 10.08 | 66.10 ± 9.92 | 0.165 |
Sex, | 0.006 | |||
Female | 56 (67.47) | 48 (56.47) | 37 (43.02) | |
Male | 27 (32.53) | 37 (43.53) | 49 (56.98) | |
Degree of education, | 0.240 | |||
Illiterate | 24 (28.92) | 30 (35.29) | 30 (34.88) | |
Primary and junior high school | 43 (51.81) | 36 (42.35) | 40 (46.51) | |
High school | 10 (12.05) | 9 (10.59) | 14 (16.28) | |
Undergraduate and above | 6 (7.23) | 10 (11.76) | 2 (2.33) | |
Smoking or not, | 0.185 | |||
Nonsmoker | 42 (50.60) | 48 (56.47) | 57 (66.28) | |
Current smoker | 19 (22.89) | 22 (25.88) | 17 (19.77) | |
Quit | 22 (26.51) | 15 (17.65) | 12 (13.95) | |
Alcohol consumption, | 0.137 | |||
Nondrinker | 51 (61.45) | 61 (71.76) | 67 (77.91) | |
Current drinker | 20 (24.10) | 16 (18.82) | 15 (17.44) | |
Quit | 12 (14.46) | 8 (9.41) | 4 (4.65) | |
BMI (kg/m2) | 24.64 ± 4.32 | 26.06 ± 4.47 | 25.23 ± 3.98 | 0.132 |
Hb (g/L) | 131.89 ± 21.09 | 138.41 ± 17.84 | 134.20 ± 19.38 | 0.176 |
RBC ( | 4.20 ± 0.67 | 4.51 ± 0.63 | 4.52 ± 0.66 | 0.003 |
PT (s) | 15.70 ± 8.52 | 14.98 ± 10.01 | 13.53 ± 6.75 | 0.008 |
INR | 1.42 ± 0.80 | 1.33 ± 0.88 | 1.20 ± 0.60 | 0.007 |
APTT (s) | 33.02 ± 8.04 | 32.95 ± 8.18 | 31.34 ± 4.45 | 0.209 |
D-dimer (mg/L) | 1.21 ± 2.24 | 0.87 ± 1.53 | 0.81 ± 0.91 | 0.068 |
FT3 (pmol/L) | 4.66 ± 3.82 | 5.00 ± 2.69 | 4.76 ± 3.42 | 0.025 |
FT4 (pmol/L) | 19.38 ± 10.61 | 18.12 ± 6.34 | 19.87 ± 13.79 | 0.554 |
TSH (mIU/L) | 3.59 ± 4.48 | 3.00 ± 3.16 | 2.79 ± 2.14 | 0.597 |
Creatinine (umol/L) | 81.31 ± 28.80 | 71.88 ± 24.03 | 71.99 ± 37.10 | 0.007 |
Urea (mmol/L) | 8.42 ± 4.07 | 6.75 ± 3.37 | 6.87 ± 3.64 | <0.001 |
UA (umol/L) | 371.50 (30.00–745.00) | 344.00 (192.00–1096.00) | 345.00 (163.00–778.00) | 0.044 |
AST (U/L) | 22.00 (6.60–618.00) | 19.00 (6.30–3319.00) | 20.00 (5.20–1847.00) | 0.248 |
ALT (U/L) | 16.90 (5.50–258.70) | 21.00 (7.20–1373.30) | 19.30 (3.70–1095.90) | 0.502 |
Lipoprotein (mg/L) | 172.50 (3.00–1015.00) | 164.50 (3.00–804.00) | 214.00 (3.00–1091.00) | 0.347 |
TC (mmol/L) | 3.46 ± 0.91 | 3.87 ± 0.90 | 3.95 ± 1.01 | 0.002 |
TG (mmol/L) | 0.99 ± 0.59 | 1.33 ± 0.68 | 1.27 ± 0.60 | <0.001 |
HDL (mmol/L) | 1.03 ± 0.26 | 1.08 ± 0.26 | 1.08 ± 0.30 | 0.609 |
LDL (mmol/L) | 2.02 ± 0.70 | 2.28 ± 0.75 | 2.37 ± 0.74 | 0.012 |
LVEF (%) | 46.96 ± 13.86 | 50.27 ± 11.29 | 52.65 ± 10.45 | 0.015 |
MoCA score | 18.87 ± 6.58 | 19.58 ± 6.43 | 19.14 ± 7.42 | 0.800 |
Hypertension, | 0.224 | |||
No | 45 (54.22) | 36 (42.35) | 37 (43.02) | |
Yes | 38 (45.78) | 49 (57.65) | 49 (56.98) | |
Diabetes mellitus, | 0.479 | |||
No | 66 (79.52) | 62 (72.94) | 62 (72.09) | |
Yes | 17 (20.48) | 23 (27.06) | 24 (27.91) | |
Heart failure, | 0.009 | |||
No | 25 (30.12) | 44 (51.76) | 42 (48.84) | |
Yes | 58 (69.88) | 41 (48.24) | 44 (51.16) | |
Coronary artery disease, | 0.003 | |||
No | 26 (31.33) | 13 (15.29) | 10 (11.63) | |
Yes | 57 (68.67) | 72 (84.71) | 76 (88.37) | |
Myocardial infarction, | 0.338 | |||
No | 77 (92.77) | 75 (88.24) | 81 (94.19) | |
Yes | 6 (7.23) | 10 (11.76) | 5 (5.81) | |
Hyperlipidemia, | 0.375 | |||
No | 81 (97.59) | 83 (97.65) | 81 (94.19) | |
Yes | 2 (2.41%) | 2 (2.35) | 5 (5.81) | |
Valvular disease, | 0.050 | |||
No | 47 (56.63) | 62 (72.94) | 61 (70.93) | |
Yes | 36 (43.37) | 23 (27.06) | 25 (29.07) | |
Cerebral infarction history, | 0.304 | |||
No | 68 (81.93) | 68 (80.00) | 76 (88.37) | |
Yes | 15 (18.07) | 17 (20.00) | 10 (11.63) | |
Aspirin, | 0.746 | |||
No | 56 (67.47) | 53 (62.35) | 54 (62.79) | |
Yes | 27 (32.53) | 32 (37.65) | 32 (37.21) | |
Warfarin, | 0.295 | |||
No | 70 (84.34) | 73 (85.88) | 79 (91.86) | |
Yes | 13 (15.66) | 12 (14.12) | 7 (8.14) | |
Clopidogrel, | 0.573 | |||
No | 79 (95.18) | 78 (91.76) | 78 (90.70) | |
Yes | 4 (4.82) | 7 (8.24) | 8 (9.30) | |
Rivashaban, | 0.293 | |||
No | 77 (92.77) | 79 (92.94) | 84 (97.67) | |
Yes | 6 (7.23) | 6 (7.06) | 2 (2.33) | |
Type of AF, | 0.269 | |||
Paroxysmal AF | 21 (25.30) | 32 (37.65) | 23 (26.74) | |
Persistent AF | 45 (54.22) | 32 (37.65) | 47 (54.65) | |
Long-term persistent AF | 7 (8.43) | 11 (12.94) | 6 (6.98) | |
Permanent | 10 (12.05) | 10 (11.76) | 10 (11.63) | |
Duration of AF, | 0.323 | |||
≤1 year | 28 (33.73) | 31 (36.47) | 43 (50.00) | |
1–5 years | 29 (34.94) | 24 (28.24) | 23 (26.74) | |
6–10 years | 10 (12.05) | 13 (15.29) | 9 (10.47) | |
>10 years | 16 (19.28) | 17 (20.00) | 11(12.79) |
Hb, hemoglobin; RBC, red blood cell; PT, prothrombin time; INR, International Normalized Ratio; APTT, activated partial thromboplastin time; FT3, free triiodothyronine; FT4, free thyroxine; TSH, thyroid-stimulating hormone; UA, uric acid; AST, aspartate transaminase; ALT, alanine aminotransferase; TC, total cholesterol; TG, triacylglycerol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.
We divided the study population into three groups according to platelet count (T1: <172
Univariate linear regression analysis was performed to determine the relationships between clinical parameters and cognitive function. As shown in Table
Univariate analysis for cognitive function of atrial fibrillation patients.
Covariate | Statistics | ||
---|---|---|---|
Age (year) | 59.71 ± 11.14 | 1.03 (1.02–1.04) | <0.001 |
Sex, | |||
Male | 141 (55.51%) | Reference | <0.001 |
Female | 113 (44.49%) | −4.91 (−6.46, −3.36) | |
Degree of education, | |||
Illiterate | 84 (33.07%) | Reference | |
Primary and junior high school | 119 (46.85%) | 6.82 (5.32, 8.31) | <0.001 |
High school | 33 (12.99%) | 10.79 (8.62, 12.96) | <0.001 |
Undergraduate and above | 18 (7.09%) | 11.81 (9.19, 14.44) | <0.001 |
Smoking or not, | |||
Nonsmoker | 147 (57.87%) | Reference | |
Current smoker | 58 (22.83%) | 3.89 (1.91, 5.87) | <0.001 |
Quit | 49 (19.29%) | 3.67 (1.57, 5.77) | <0.001 |
Alcohol consumption, | |||
Nondrinker | 179 (70.47%) | Reference | |
Current drinker | 51 (20.08%) | 4.96 (2.98, 6.95) | <0.001 |
Quit | 24 (9.45%) | 2.82 (0.06, 5.58) | 0.047 |
PLT | 208.1 ± 68.2 | 0.00 (−0.01, 0.01) | 0.575 |
BMI | 25.33 ± 4.27 | 0.35 (0.16, 0.54) | <0.001 |
Hb (g/L) | 134.85 ± 19.58 | 0.08 (0.03, 0.12) | <0.001 |
RBC ( | 4.41 ± 0.67 | 1.44 (0.19, 2.69) | 0.024 |
PT (s) | 12.15 (10.00–66.00) | −0.07 (−0.17, 0.03) | 0.154 |
INR | 1.32 ± 0.77 | −0.87 (−1.94, 0.21) | 0.115 |
APTT (s) | 32.53 ± 7.26 | 0.10 (−0.01, 0.21) | 0.084 |
D-dimer ( | 0.55 (0.04–15.37) | −1.00 (−1.51, −0.50) | <0.001 |
FT3 (pmol/L) | 4.31 (0.94–31.80) | 0.08 (−0.18, 0.35) | 0.546 |
FT4 (pmol/L) | 17.60 (3.72–100.00) | −0.05 (−0.14, 0.03) | 0.196 |
TSH (mIU/L) | 2.40 (0.01–33.30) | 0.01 (−0.25, 0.27) | 0.945 |
Creatinine (umol/L) | 74.92 ± 30.66 | −0.00 (−0.03, 0.02) | 0.778 |
Urea (mmol/L) | 7.31 ± 3.74 | −0.24 (−0.47, −0.02) | 0.034 |
UA (umol/L) | 376.68 ± 129.03 | 0.00 (−0.01, 0.01) | 0.854 |
AST (U/L) | 20.00 (5.20–3319.00) | −0.00 (−0.00, 0.00) | 0.397 |
ALT (U/L) | 19.90 (3.70–1373.30) | −0.00 (−0.01, 0.01) | 0.660 |
Lipoprotein (mg/L) | 188.00 (3.00–1091.00) | 0.00 (−0.00, 0.00) | 0.617 |
TC (mmol/L) | 3.77 ± 0.96 | −0.49 (−1.38, 0.40) | 0.280 |
TG (mmol/L) | 1.20 ± 0.64 | 0.74 (−0.59, 2.08) | 0.275 |
HDL (mmol/L) | 1.07 ± 0.28 | −0.66 (−3.74, 2.43) | 0.678 |
LDL (mmol/L) | 2.23 ± 0.74 | −0.59 (−1.74, 0.56) | 0.312 |
LVEF (%) | 50.09 ± 12.05 | 0.03 (−0.04, 0.10) | 0.354 |
Hypertension, | |||
No | 118 (46.46%) | Reference | |
Yes | 136 (53.54%) | −0.51 (−2.16, 1.14) | 0.545 |
Diabetes mellitus, | |||
No | 190 (74.80%) | Reference | |
Yes | 64 (25.20%) | 0.54 (−1.37, 2.44) | 0.580 |
Heart failure, | |||
No | 111 (43.70%) | Reference | |
Yes | 143 (56.30%) | −3.45 (−5.05, −1.84) | <0.001 |
Coronary artery disease, | |||
No | 49 (19.29%) | Reference | |
Yes | 205 (80.71%) | −0.46 (−2.52, 1.61) | 0.665 |
Myocardial infarction, | |||
No | 233 (91.73%) | Reference | 0.253 |
Yes | 21 (8.27%) | −1.76 (−4.78, 1.26) | |
Hyperlipidemia, | |||
No | 245 (96.46%) | Reference | 0.026 |
Yes | 9 (3.54%) | 5.11 (0.64, 9.58) | |
Valvular disease, | |||
No | 170 (66.93%) | Reference | |
Yes | 84 (33.07%) | −2.32 (−4.04, −0.59) | 0.009 |
Cerebral infarction history, | |||
No | 212 (83.46%) | Reference | 0.600 |
Yes | 42 (16.54%) | −0.60 (−2.84, 1.64) | |
Aspirin, | |||
No | 163 (64.17%) | Reference | 0.082 |
Yes | 91 (35.83%) | 1.53 (−0.18, 3.24) | |
Warfarin, | |||
No | 222 (87.40%) | Reference | 0.712 |
Yes | 32 (12.60%) | 0.47 (−2.01, 2.95) | |
Clopidogrel, | |||
No | 235 (92.52%) | Reference | 0.765 |
Yes | 19 (7.48%) | 0.48 (−2.69, 3.65) | |
Rivashaban, | |||
No | 240 (94.49%) | Reference | 0.676 |
Yes | 14 (5.51%) | 0.76 (−2.78, 4.29) | |
Type of AF, | |||
Paroxysmal AF | 76 (29.92%) | Reference | |
Persistent AF | 124 (48.82%) | −1.61 (−3.51, 0.30) | 0.099 |
Long-term persistent AF | 24 (9.45%) | −0.01 (−3.11, 3.08) | 0.993 |
Permanent | 30 (11.81%) | −0.59 (−3.40, 2.22) | 0.680 |
Duration of AF, | |||
≤1 year | 102 (40.16%) | Reference | |
1–5 years | 76 (29.92%) | 0.20 (−1.79, 2.20) | 0.842 |
6–10 years | 32 (12.60%) | 0.67 (−2.04, 3.37) | 0.629 |
>10 years | 44 (17.32%) | −0.51 (−2.92, 1.89) | 0.676 |
Hb, hemoglobin; RBC, red blood cell; PT, prothrombin time; INR, International Normalized Ratio; APTT, activated partial thromboplastin time; FT3, free triiodothyronine; FT4, free thyroxine; TSH, thyroid-stimulating hormone; UA, uric acid; AST, aspartate transaminase; ALT, alanine aminotransferase; TC, total cholesterol; TG, triacylglycerol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; CI, confidence interval.
As shown in Figure
Association between platelets and cognitive function of atrial fibrillation. A threshold and a nonlinear relationship between platelet count and the MoCA score were found in a generalized additive model. The solid red line represents the smooth curve fit between variables. Blue bands represent the 95% confidence interval from the fit. Models were adjusted for age; sex; BMI; educational level; smoking; alcohol consumption; valvular disease; hypertension; diabetes mellitus; heart failure; coronary artery disease; myocardial infarction; hyperlipidemia; cerebral infarction history; aspirin; warfarin; clopidogrel; rivashaban; type of AF; duration of AF; Hb; RBC; PT; INR; APTT; D-dimer; FT3; FT4; TSH; creatinine; urea; UA; AST; ALT; lipoprotein; TC; TG; HDL; LDL; and LVEF.
Relationship between platelet count and cognitive function in different models.
Variable | Crude model | Adjust I | Adjust II |
---|---|---|---|
Platelets | 0.00 (−0.01, 0.01) 0.6716 | 0.00 (−0.01, 0.01) 0.5349 | 0.00 (−0.01, 0.01) 0.7866 |
Platelets | |||
T1 | Reference | Reference | Reference |
T2 | 0.71 (−1.36, 2.77) 0.5014 | 1.00 (−0.82, 2.83) 0.2813 | 1.25 (−0.75, 3.25) 0.2210 |
T3 | 0.27 (−1.79, 2.33) 0.7958 | 0.85 (−1.01, 2.71) 0.3707 | 1.32 (−0.87, 3.51) 0.2397 |
0.13 (−0.90, 1.16) 0.8005 | 0.42 (−0.51, 1.35) 0.3725 | 0.64 (−0.45, 1.73) 0.2532 |
Nonadjusted model adjusted for none. Adjust I model adjusted for age and sex. Adjust II model adjusted for age and Sex; BMI; educational level; smoking; alcohol consumption; valvular disease; hypertension; diabetes mellitus; heart failure; coronary artery disease; myocardial infarction; hyperlipidemia; cerebral infarction history; aspirin; warfarin; clopidogrel; rivashaban; type of AF; duration of AF; Hb; RBC; PT; INR; APTT; D-dimer; FT3; FT4; TSH; creatinine; urea; UA; AST; ALT; lipoprotein; TC; TG; HDL; LDL; LVEF.
Results of platelet count and cognitive function using two-piecewise linear regression.
Inflection point of platelets | Effect size | 95% CI | |
---|---|---|---|
<230 | 0.03 | 0.01–0.05 | 0.011 |
≥230 | −0.03 | −0.05–0.00 | 0.023 |
Effect: cognitive function; cause: platelet count. Adjusted for age and sex; BMI; educational level; smoking; alcohol consumption; valvular disease; hypertension; diabetes mellitus; heart failure; coronary artery disease; myocardial infarction; hyperlipidemia; cerebral infarction history; aspirin; warfarin; clopidogrel; rivashaban; type of AF; duration of AF; Hb; RBC; PT; INR; APTT; D-dimer; FT3; FT4; TSH; creatinine; urea; UA; AST; ALT; lipoprotein; TC; TG; HDL; LDL; LVEF.
In our study, there was a nonlinear relationship between platelet count and cognitive function in patients with atrial fibrillation, and the turning point was 230. When the platelet count was less than 230, the cognitive function score of patients with atrial fibrillation increased significantly with the increase of platelet count. When the platelet count was greater than 230, the cognitive function of patients with atrial fibrillation decreased significantly with the increase of platelet count.
The results of this study revealed the effect of platelet count on cognitive function in patients with atrial fibrillation, which proved the relationship between the platelet and brain from a clinical point of view, and found the threshold point of platelet count. In previous studies [
Platelets have been considered as a marker for the diagnosis of dementia. Studies have shown that platelet APP ratio (representing the percentage of 120–130 kDa to 110 kDa isoforms of the amyloid precursor protein) is reduced in patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD) [
In addition, our study also found that the cognitive function of patients with atrial fibrillation is affected by age, sex, education, smoking, drinking, body mass index, hemoglobin, urea, D-dimer, heart failure, vascular disease, and other factors. This is consistent with some previous studies [
The strengths and innovations of this study include the following: (1) we explored and described the relationship between platelet count and cognitive function in patients with atrial fibrillation from a clinical point of view; (2) we found the turning point of the effect of platelets on cognitive function through a curve fitting model, which can provide a certain reference value for clinical treatment; and (3) the cognitive function of Chinese patients with atrial fibrillation was evaluated, and some risk factors were identified. However, this study still has some limitations: (1) the sample size of this study is small, and only 254 patients with atrial fibrillation are evaluated and collected; (2) this study is a single-center study. Only patients with atrial fibrillation in the Affiliated Hospital of Jining Medical College were studied. (3) This study is a cross-sectional study, and there is no follow-up of the patients. In the future, the sample size can be expanded, data collection can be carried out in more hospitals in multiple regions, and patients with atrial fibrillation can be followed up for a long time to study the effect of platelet count on the long-term outcome of patients with atrial fibrillation. In the future, we can also explore the correlation between platelet count and cognitive function in patients with nonatrial fibrillation.
In conclusion, this study describes the nonlinear relationship between cognitive function and platelet count in patients with atrial fibrillation after adjusting for confounding factors. This finding suggests that, in patients with atrial fibrillation, platelets should be maintained at about 230, and too high or too low will affect cognitive function to a certain extent.
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare that they have no conflicts of interest.
The project was funded by the MiaoPu Project of Affiliated Hospital of Jining Medical University (No. MP-2018-016).