OBJECTIVE To analyze the risk factors associated with serum digoxin concentration （SDC） exceeding the warning threshold and to construct a risk prediction model. METHODS Clinical data were retrospectively collected from hospitalized patients who received regular oral digoxin and completed therapeutic drug monitoring at Guangzhou First People’s Hospital and Nansha Branch of Guangzhou First People’s Hospital between September 2020 and March 2025. Patients with SDC＞2.0 ng/mL were classified as exceeding the warning threshold group， while those with SDC≤2.0 ng/mL were classified as the non-exceeding the warning threshold group. Based on univariate factor analysis， multivariate Logistic regression analysis was used to identify independent risk factors for SDC exceeding the warning threshold. A prediction model was developed and a nomogram was plotted accordingly. The discriminative ability of the model was evaluated by receiver operating characteristic （ROC） curve analysis， and the calibration curve were plotted to assess the calibration of the model. The Hosmer-Lemeshow test was employed to evaluate the goodness of fit of the model， and clinical utility was evaluated by decision curve analysis （DCA）. RESULTS A total of 254 patients were included， among whom 49 patients （19.29%） had SDC exceeding the warning threshold. Univariate factor analysis and multivariate Logistic regression analysis showed that increased daily dose per kilogram of body weight， advanced age， concomitant coronary heart disease， elevated serum creatinine levels， concomitant use of amiodarone， and concomitant use of deslanoside wer e independent risk factors for SDC exceeding the warning threshold （ P ＜0.05）. The area under the ROC curve of the model was 0.869 （95% confidence interval： 0.818-0.920）， with a sensitivity of 0.796 and a specificity of 0.842. The Hosmer-Lemeshow test showed good calibration （ P ＝0.570）. The calibration curve was closely aligned with the ideal curve， with a mean absolute error of 0.012. The model provided a higher net benefit across a threshold probability range of 6% to 82%. CONCLUSIONS The increased daily dose per kilogram of body weight， advanced age， concomitant coronary heart disease， elevated serum creatinine levels， concomitant use of amiodarone， and concomitant use of deslanoside are independent risk factors for SDC exceeding the warning threshold. The nomogram prediction model developed based on the aforementioned factors can be used to predict the risk of SDC exceeding the warning threshold.

Since the discovery of circulating hepatitis B virus (HBV) RNA in the peripheral blood of patients with chronic hepatitis B in 1996, a growing number of studies have focused on clarifying the biological characteristics and clinical application value of serum HBV RNA. This consensus mainly summarizes the research progress of serum HBV RNA existing profiles, quantitative detection methods, and current clinical applications. In order to better apply this indicator for the clinical management of patients with chronic HBV infection, recommendations on quantitative detection target regions, detection results, and clinical applications are put forward.

Objective To investigate the features and diagnostic value of MRI in prenatal and postpartum for placenta accreta. Methods 18 cases of placenta accreta confirmed by surgical pathologically and clinical were retrospectively analyzed,including 10 ca-ses of prenatal and postpartum 8 cases,observed the signal feature and diagnostic value of MRI images.Results In the 10 cases of prenatal patients with placenta accreta,MRI manifestations of 9 cases of placenta prevail,totally or partly covering cervical,10 cases of partial placenta and uterine muscle gap disappeared,boundaries are not clear,2 cases of uterine wall bars low signal-image inter-rupted,bulging outward placenta,increased sub placental vascular wag detected in 8 patients;8 cases of postpartum patients with pla-centa accrete,MRI show 4 examples which were mixed signals within the uterine cavity,with the junctional zone boundaries were not clear,the junctional zone was discontinuous interruption in 7 cases,8 cases of muscular layer appear oval,high and low,patchy mixed signals in shadow,4 cases in the palace district,5 cases of invading the shallow layer,3 cases of infection and deep muscle layers. Conclusion MRI technique is of great value for diagnosis of placenta accreta.

OBJECTIVETo analyze the risk factors of nonspecific low back pain in community populations.

METHODSTwo community populations were investigated using questionnaires in this case-control study. The questionnaire was designed to collect data including age, gender, body weight, marriage, education, income, occupation, labor intensity, smoking, alcohol drinking and social mental status. The subjects with low back pain constituted the case group and those without low back pain served as the control group, and the data was analyzed by a Logistic regression model.

RESULTSA total of 1747 community residents participated in this survey, among whom 398 subjects had low back pain and 1126 subjects without low back pain were selected as the control group. Of all the latent risk factors of low back pain in Logistic regression model, gender was the most relevant factor (OR=3.5522) followed by education (OR=1.958), labor intensity (OR=1.956), marital status (OR=1.612), vibration source exposure (OR=1.491), BMI (OR=1.127) and age (OR=1.060).

CONCLUSIONGender, education, labor intensity, marriage, vibration source exposure and BMI are risk factors of nonspecific low back pain in community populations, and exercises and mental status can be protective factors against low back pain.

Case-Control Studies ; Humans ; Logistic Models ; Low Back Pain ; epidemiology ; Risk Factors ; Surveys and Questionnaires

Objective To analyze the risk factors of nonspecific low back pain in community populations. Methods Two community populations were investigated using questionnaires in this case-control study. The questionnaire was designed to collect data including age, gender, body weight, marriage, education, income, occupation, labor intensity, smoking, alcohol drinking and social mental status. The subjects with low back pain constituted the case group and those without low back pain served as the control group, and the data was analyzed by a Logistic regression model. Results A total of 1747 community residents participated in this survey, among whom 398 subjects had low back pain and 1126 subjects without low back pain were selected as the control group. Of all the latent risk factors of low back pain in Logistic regression model, gender was the most relevant factor (OR=3.5522) followed by education (OR=1.958), labor intensity (OR=1.956), marital status (OR=1.612), vibration source exposure (OR=1.491), BMI (OR=1.127) and age (OR=1.060). Conclusion Gender, education, labor intensity, marriage, vibration source exposure and BMI are risk factors of nonspecific low back pain in community populations, and exercises and mental status can be protective factors against low back pain.

Objective To analyze the risk factors of nonspecific low back pain in community populations. Methods Two community populations were investigated using questionnaires in this case-control study. The questionnaire was designed to collect data including age, gender, body weight, marriage, education, income, occupation, labor intensity, smoking, alcohol drinking and social mental status. The subjects with low back pain constituted the case group and those without low back pain served as the control group, and the data was analyzed by a Logistic regression model. Results A total of 1747 community residents participated in this survey, among whom 398 subjects had low back pain and 1126 subjects without low back pain were selected as the control group. Of all the latent risk factors of low back pain in Logistic regression model, gender was the most relevant factor (OR=3.5522) followed by education (OR=1.958), labor intensity (OR=1.956), marital status (OR=1.612), vibration source exposure (OR=1.491), BMI (OR=1.127) and age (OR=1.060). Conclusion Gender, education, labor intensity, marriage, vibration source exposure and BMI are risk factors of nonspecific low back pain in community populations, and exercises and mental status can be protective factors against low back pain.