Based on the data of inpatients with hypertension and a cross-sectional study with a large sample size, this study aims to find the early warning value of the left anteroposterior atrial diameter for the possible occurrence of atrial fibrillation in patients with hypertension, and compare the advantages and disadvantages of the above two methods for the early warning of the risk of atrial fibrillation in patients with hypertension, so as to achieve the purpose of early identification of high-risk groups that may develop atrial fibrillation.
Background Left atrial enlargement resulting from hypertension is closely linked to the development and persistence of atrial fibrillation (AF). The newly proposed staging recognizes AF as disease continuum, which makes us aware that AF prevention should focus on the Pre-AF stage, and atrial enlargement is one of the important manifestations in this stage. Previous scoring systems, such as CHA2DS2-VASc and C2HEST, along with the recently highlighted left atrial diameter (LAD), have been significant tools for predicting AF occurrence. However, a comprehensive assessment of their utility is currently lacking. Purpose This study aims to explore the role of left atrial size in identifying atrial fibrillation (AF) among hospitalized hypertensives, and to compare its recognition effectiveness with previous scoring systems. Methods The investigators conducted a cross-sectional analysis within hospitalized hypertensives. The discovery, internal and external validation datasets were established. The eXtreme Gradient Boosting (XGBoost) was employed to identify key variables related to AF occurrence, which were ranked based on their importance scores. To gauge the predictive prowess of LAD regarding AF occurrence, the investigators plotted the receiver operating characteristic curve (ROC) and calculated the area under the curve (AUC). This enabled us to pinpoint the LAD cutoff value corresponding to the maximum Youden index, indicative of susceptibility to AF. Subsequently, Youden index determined the optimal cutoff value from the ROC curve. Delong's test compared the identification abilities of different tools within the same dataset. Logistic regression analysis assessed the correlation between clinical variables and left atrial size.
Study Type
OBSERVATIONAL
Enrollment
58,427
CHA2DS2-VASc Score: Congestive heart failure (HF) \[1 point\], hypertension \[1 point\], age ≥ 75 years \[2 points\], diabetes \[1 point\], prior stroke or transient ischemic attack \[2 points\], vascular disease \[1 point\], age 65-74 years \[1 point\], and female gender\[1 point\]. C2HEST Score: Coronary artery disease or chronic obstructive pulmonary disease \[1 point each, 2 total points\]; hypertension \[1 point\]; elderly \[2 points for age ≥ 75 years\]; systolic HF \[2 points\]; and thyroid disease \[1 point for hyperthyroidism\]\[10\]. LAD: The LAD values of the enrolled patients were extracted by keyword search based on the results of echocardiography in the database.
2ndChongqingMU
Chongqing, Chongqing Municipality, China
left atrial diameter (LAD)
In this study, after the patients completed the cardiac color Doppler ultrasound, the report and results would be uploaded to the electronic medical record system. Then, the investigator would extract the LAD values recorded in the report from this database.
Time frame: Data collection was completed after discharge from the hospital, up to 3 months.
CHA2DS2-VASc score
The patients' discharge material were extracted from the database, including age, gender, and history of congestive heart failure, hypertension, diabetes, stroke or transient ischemic attacks, and vascular disease. CHA2DS2-VASc score was calculated according to the guidelines (CHA2DS2-VASc criteria: Congestive heart failure \[1 point\], hypertension \[1 point\], age ≥ 75 years \[2 points\], diabetes \[1 point\], prior stroke or transient ischemic attack \[2 points\], vascular disease \[1 point\], age 65-74 years \[1 point\], and female gender\[1 point\]), with the highest score being 9 and the lowest score being 0. Then, the CHA2DS2-VASc score was calculated by the investigator based on the above diagnosis. The higher the score, the higher the risk of AF.
Time frame: Data collection was completed after discharge from the hospital, up to 3 months.
C2HEST score
The patients' discharge material were extracted from the database, including age, and history of coronary artery disease, chronic obstructive pulmonary disease, hypertension, systolic heart failure, thyroid disease. C2HEST score was calculated according to the guidelines (C2HEST criteria: Coronary artery disease or chronic obstructive pulmonary disease \[1 point each, 2 total points\]; hypertension \[1 point\]; elderly \[2 points for age ≥ 75 years\]; systolic heart failure \[2 points\]; and thyroid disease \[1 point for hyperthyroidism\]), with the highest score being 8 and the lowest score being 0. Then, the C2HEST score was calculated by the investigator based on the above diagnosis. The higher the score, the higher the risk of AF.
Time frame: Data collection was completed after discharge from the hospital, up to 3 months.
Atrial fibrillation (AF)
Diagnostic criteria for AF: The preferred indicators for confirming the diagnosis of AF were normal ECG and ambulatory ECG. During physical examination, the patient's heart rhythm is absolutely irregular and the first heart sound is uneven in strength. Patients may also present with clinical manifestations such as palpitations, dizziness, dyspnea, and chest tightness during the course of the disease. The above materials of the patients were recorded in the electronic medical record system.
Time frame: Data collection was completed after discharge from the hospital, up to 3 months.
Area under the curve (AUC) of LAD and occurrence of AF
To assess the ability of LAD to predict the occurrence of AF, the investigators used IBM SPSS 26.0 software to create a receiver operating characteristic curve (ROC) and calculate the AUC in the discovery and external datasets, with LAD as the independent variable and the occurrence of AF as the dependent variable.
Time frame: Statistics were completed after data collection, up to 1 months.
AUC of CHA2DS2-VASc score and occurrence of AF
To gauge the predictive prowess of CHA2DS2-VASc scores regarding AF occurrence, a ROC was plotted and the AUC was calculated in the discovery and external datasets, with CHA2DS2-VASc score as the independent variable and the occurrence of AF as the dependent variable.
Time frame: Statistics were completed after data collection, up to 1 months.
AUC of C2HEST score and occurrence of AF
To gauge the predictive prowess of C2HEST scores regarding AF occurrence, a ROC was plotted and the AUC was calculated in the discovery and external datasets, with C2HEST score as the independent variable and the occurrence of AF as the dependent variable.
Time frame: Statistics were completed after data collection, up to 1 months.
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