Objective: To explore the relationship between sleep quality and executive function among middle school students, so as to provide theoretical support for the promotion of adolescents physical and mental health development. Methods: From September to December 2023, 5 713 junior and senior high school students aged 13 to 18 were selected by stratified cluster random sampling method from Shanghai, Suzhou, Taiyuan, Wuyuan, Xingyi, and Urumqi. Pittsburgh Sleep Quality Index was used to conduct sleep quality survey. And conduct executive function was tested on middle school students, including inhibitory function, refresh function and conversion function tests. Spearman correlation and linear regression were used to analyze the relationship between sleep quality and executive function of middle school students. Results: The total Pittsburgh Sleep Quality Index (PSQI) score of boys was [4.0(2.0,6.0)] and that of girls was [5.0(3.0,6.0)], and the difference was statistically significant ( Z=-10.90, P < 0.01 ). The total PSQI score of boys was positively correlated with both 2-back reaction time and conversion function of executive function ( r =0.04, 0.04); the total PSQI score of girls was negatively correlated with 2-back reaction time ( r =-0.04) ( P <0.05). After controlling for variables such as mental health, physical activity and nutritional status,linear regression analyses showed that PSQI total score of middle school students was positively correlated with the inhibitory function and the conversion function response time [ B (95% CI )=1.28(0.21-2.34), 7.62(2.34-12.90), P <0.05]; the associations of total PSQI scores among middle school students with both 2-back and 1-back response time were not statistically significant [ B (95% CI )=-5.88(-16.14-4.37), 8.05( -3.39 -19.50), P >0.05]. Conclusion Positive correlations are observed on sleep quality with inhibitory and conversion functions of executive function among middle school students.

Pain is one of the five vital signs,and the leading complication of war trauma,so analgesia is critical to combat casualty care.The U.S.Tactical Combat Casualty Care guidelines have defined the battlefield graded analgesic strategies.This paper reviews the assessment of pain grade of war wounds,involving the preliminary evaluation according to categories and conditions of trauma,and the quantitative evaluation according to subjective feeling and objective index monitoring.The analgesic strategies are analyzed,involving such as analgesic drugs local anesthetics,non-steroidal analgesics,opioids,N-methyl-D-aspartate receptor antagonists,and such analgesic techniques as regional nerve block,nerve radiofrequency,nerve ablation and spinal cord electrical stimulation technology.This review is expected to provide a useful reference for improving pain management and war injury treatment in China's army.

Objective:To assess the risk factors affecting development of non-tumor- related anastomotic stenosis after rectal cancer and to construct a nomogram prediction model.Methods:This was a retrospective study of data of patients who had undergone excision with one-stage intestinal anastomosis for rectal cancer between January 2003 and September 2018 in Nanfang Hospital of Southern Medical University. The exclusion criteria were as follows: (1) pathological examination of the operative specimen revealed residual tumor on the incision margin of the anastomosis; (2) pathological examination of postoperative colonoscopy specimens revealed tumor recurrence at the anastomotic stenosis, or postoperative imaging evaluation and tumor marker monitoring indicated tumor recurrence; (3) follow-up time <3 months; and (4) simultaneous multiple primary cancers. Univariate analysis using the χ 2 or Fisher's exact test was performed to assess the study patients' baseline characteristics and variables such as tumor-related factors and surgical approach ( P<0.05). Multivariate analysis using binary logistic regression was then performed to identify independent risk factors for development of non-tumor-related anastomotic stenosis after rectal cancer. Finally, a nomogram model for predicting non-tumor-related anastomotic stenosis after rectal cancer surgery was constructed using R software. The reliability and accuracy of this prediction model was evaluated using internal validation and calculation of the area under the curve of the model's receiver characteristic curve (ROC). Results:The study cohort comprised 1,610 patients, including 1,008 men and 602 women of median age 59 (50, 67) years and median body mass index 22.4 (20.2, 24.5) kg/m2. Non-tumor-related anastomotic stenosis developed in 121 (7.5%) of these patients. The incidence of non-tumor-related anastomotic stenosis in patients who had undergone neoadjuvant chemotherapy, neoadjuvant radiotherapy, and surgery alone was 11.2% (10/89), 26.4% (47/178), and 4.8% (64/1,343), respectively. Neoadjuvant treatment (neoadjuvant chemotherapy: OR=2.455, 95%CI: 1.148–5.253, P=0.021; neoadjuvant chemoradiotherapy, OR=3.882, 95%CI: 2.425–6.216, P<0.001), anastomotic leakage (OR=7.960, 95%CI: 4.550–13.926, P<0.001), open laparotomy (OR=3.412, 95%CI: 1.772–6.571, P<0.001), and tumor location (distance of tumor from the anal verge 5–10 cm: OR=2.381, 95%CI:1.227–4.691, P<0.001; distance of tumor from the anal verge <5 cm: OR=5.985,95% CI: 3.039–11.787, P<0.001) were identified as independent risk factors for non-tumor-related anastomotic stenosis. Thereafter, a nomogram prediction model incorporating the four identified risk factors for development of anastomotic stenosis after rectal cancer was developed. The area under the curve of the model ROC was 0.815 (0.773–0.857, P<0.001), and the C-index of the predictive model was 0.815, indicating that the model's calibration curve fitted well with the ideal curve. Conclusion:Non-tumor-related anastomotic stenosis after rectal cancer surgery is significantly associated with neoadjuvant treatment, anastomotic leakage, surgical procedure, and tumor location. A nomogram based on these four factors demonstrated good discrimination and calibration, and would therefore be useful for screening individuals at risk of anastomotic stenosis after rectal cancer surgery.

Objective:To assess the risk factors affecting development of non-tumor- related anastomotic stenosis after rectal cancer and to construct a nomogram prediction model.Methods:This was a retrospective study of data of patients who had undergone excision with one-stage intestinal anastomosis for rectal cancer between January 2003 and September 2018 in Nanfang Hospital of Southern Medical University. The exclusion criteria were as follows: (1) pathological examination of the operative specimen revealed residual tumor on the incision margin of the anastomosis; (2) pathological examination of postoperative colonoscopy specimens revealed tumor recurrence at the anastomotic stenosis, or postoperative imaging evaluation and tumor marker monitoring indicated tumor recurrence; (3) follow-up time <3 months; and (4) simultaneous multiple primary cancers. Univariate analysis using the χ 2 or Fisher's exact test was performed to assess the study patients' baseline characteristics and variables such as tumor-related factors and surgical approach ( P<0.05). Multivariate analysis using binary logistic regression was then performed to identify independent risk factors for development of non-tumor-related anastomotic stenosis after rectal cancer. Finally, a nomogram model for predicting non-tumor-related anastomotic stenosis after rectal cancer surgery was constructed using R software. The reliability and accuracy of this prediction model was evaluated using internal validation and calculation of the area under the curve of the model's receiver characteristic curve (ROC). Results:The study cohort comprised 1,610 patients, including 1,008 men and 602 women of median age 59 (50, 67) years and median body mass index 22.4 (20.2, 24.5) kg/m2. Non-tumor-related anastomotic stenosis developed in 121 (7.5%) of these patients. The incidence of non-tumor-related anastomotic stenosis in patients who had undergone neoadjuvant chemotherapy, neoadjuvant radiotherapy, and surgery alone was 11.2% (10/89), 26.4% (47/178), and 4.8% (64/1,343), respectively. Neoadjuvant treatment (neoadjuvant chemotherapy: OR=2.455, 95%CI: 1.148–5.253, P=0.021; neoadjuvant chemoradiotherapy, OR=3.882, 95%CI: 2.425–6.216, P<0.001), anastomotic leakage (OR=7.960, 95%CI: 4.550–13.926, P<0.001), open laparotomy (OR=3.412, 95%CI: 1.772–6.571, P<0.001), and tumor location (distance of tumor from the anal verge 5–10 cm: OR=2.381, 95%CI:1.227–4.691, P<0.001; distance of tumor from the anal verge <5 cm: OR=5.985,95% CI: 3.039–11.787, P<0.001) were identified as independent risk factors for non-tumor-related anastomotic stenosis. Thereafter, a nomogram prediction model incorporating the four identified risk factors for development of anastomotic stenosis after rectal cancer was developed. The area under the curve of the model ROC was 0.815 (0.773–0.857, P<0.001), and the C-index of the predictive model was 0.815, indicating that the model's calibration curve fitted well with the ideal curve. Conclusion:Non-tumor-related anastomotic stenosis after rectal cancer surgery is significantly associated with neoadjuvant treatment, anastomotic leakage, surgical procedure, and tumor location. A nomogram based on these four factors demonstrated good discrimination and calibration, and would therefore be useful for screening individuals at risk of anastomotic stenosis after rectal cancer surgery.

Objective: We previously elucidated that long non-coding RNA Promoter of CDKN1A Antisense DNA damage Activated RNA (PANDAR) as a p53-dependent oncogene to promote cisplatin resistance in ovarian cancer (OC). Intriguingly, high level of p53-independent PANDAR was found in cisplatin-resistant patients with p53 mutation. Here, our study probed the new roles and the underlying mechanisms of PANDAR in p53-mutant OC cisplatin-resistance. Methods: A2780 and A2780-DDP cells were served as OC cisplatin-sensitive and cisplatinresistant cells. HO-8910PM cells were subjected to construct chemotherapy-induced extracellular vesicles (Chemo-EVs). Transmission electron microscopy (TEM) and nanoparticle tracking analysis were employed to evaluate Chemo-EVs. Cell viability was assessed using cell counting kit-8 and colony formation assays. Cell apoptosis was assessed using Annexin V and propidium iodide staining. The relationships between PANDAR, serine and arginine-rich premRNA splicing factor 9 (SRSF9) were verified by RNA immunoprecipitation and fluorescence in situ hybridization. Tumor xenograft experiment was employed to evaluate the effects of PANDAR-Chemo-EVs on OC cisplatin-resistance in vivo. Immunofluorescent staining and immunohistochemistry were performed in tumor tissue. Results: PANDAR level increased in OC patients with p53-mutation. PANDAR efflux enacted via exosomes under cisplatin conditions. Additionally, exosomes from OC cell lines carried PANDAR, which significantly increased cell survival and chemoresistance in vitro and tumor progression and metastasis in vivo. During cisplatin-induced stress, SRSF9 was recruited to nuclear bodies by increased PANDAR and muted apoptosis in response to cisplatin. Besides, SRSF9 significantly increased the ratio of SIRT4/SIRT6 mRNA in OC. Conclusion Cisplatin-induced exosomes transfer PANDAR and lead to a rapid adaptation of OC cell survival through accumulating SRSF9 following cisplatin stress exposure.

Objective: We previously elucidated that long non-coding RNA Promoter of CDKN1A Antisense DNA damage Activated RNA (PANDAR) as a p53-dependent oncogene to promote cisplatin resistance in ovarian cancer (OC). Intriguingly, high level of p53-independent PANDAR was found in cisplatin-resistant patients with p53 mutation. Here, our study probed the new roles and the underlying mechanisms of PANDAR in p53-mutant OC cisplatin-resistance. Methods: A2780 and A2780-DDP cells were served as OC cisplatin-sensitive and cisplatinresistant cells. HO-8910PM cells were subjected to construct chemotherapy-induced extracellular vesicles (Chemo-EVs). Transmission electron microscopy (TEM) and nanoparticle tracking analysis were employed to evaluate Chemo-EVs. Cell viability was assessed using cell counting kit-8 and colony formation assays. Cell apoptosis was assessed using Annexin V and propidium iodide staining. The relationships between PANDAR, serine and arginine-rich premRNA splicing factor 9 (SRSF9) were verified by RNA immunoprecipitation and fluorescence in situ hybridization. Tumor xenograft experiment was employed to evaluate the effects of PANDAR-Chemo-EVs on OC cisplatin-resistance in vivo. Immunofluorescent staining and immunohistochemistry were performed in tumor tissue. Results: PANDAR level increased in OC patients with p53-mutation. PANDAR efflux enacted via exosomes under cisplatin conditions. Additionally, exosomes from OC cell lines carried PANDAR, which significantly increased cell survival and chemoresistance in vitro and tumor progression and metastasis in vivo. During cisplatin-induced stress, SRSF9 was recruited to nuclear bodies by increased PANDAR and muted apoptosis in response to cisplatin. Besides, SRSF9 significantly increased the ratio of SIRT4/SIRT6 mRNA in OC. Conclusion Cisplatin-induced exosomes transfer PANDAR and lead to a rapid adaptation of OC cell survival through accumulating SRSF9 following cisplatin stress exposure.

Objective: We previously elucidated that long non-coding RNA Promoter of CDKN1A Antisense DNA damage Activated RNA (PANDAR) as a p53-dependent oncogene to promote cisplatin resistance in ovarian cancer (OC). Intriguingly, high level of p53-independent PANDAR was found in cisplatin-resistant patients with p53 mutation. Here, our study probed the new roles and the underlying mechanisms of PANDAR in p53-mutant OC cisplatin-resistance. Methods: A2780 and A2780-DDP cells were served as OC cisplatin-sensitive and cisplatinresistant cells. HO-8910PM cells were subjected to construct chemotherapy-induced extracellular vesicles (Chemo-EVs). Transmission electron microscopy (TEM) and nanoparticle tracking analysis were employed to evaluate Chemo-EVs. Cell viability was assessed using cell counting kit-8 and colony formation assays. Cell apoptosis was assessed using Annexin V and propidium iodide staining. The relationships between PANDAR, serine and arginine-rich premRNA splicing factor 9 (SRSF9) were verified by RNA immunoprecipitation and fluorescence in situ hybridization. Tumor xenograft experiment was employed to evaluate the effects of PANDAR-Chemo-EVs on OC cisplatin-resistance in vivo. Immunofluorescent staining and immunohistochemistry were performed in tumor tissue. Results: PANDAR level increased in OC patients with p53-mutation. PANDAR efflux enacted via exosomes under cisplatin conditions. Additionally, exosomes from OC cell lines carried PANDAR, which significantly increased cell survival and chemoresistance in vitro and tumor progression and metastasis in vivo. During cisplatin-induced stress, SRSF9 was recruited to nuclear bodies by increased PANDAR and muted apoptosis in response to cisplatin. Besides, SRSF9 significantly increased the ratio of SIRT4/SIRT6 mRNA in OC. Conclusion Cisplatin-induced exosomes transfer PANDAR and lead to a rapid adaptation of OC cell survival through accumulating SRSF9 following cisplatin stress exposure.

Objective:To investigate the risk factor of hepatocellular carcinoma (HCC) with vessels encapsulating tumor clusters (VETC) and the application value of its risk scoring model.Methods:The retrospective cross-sectional study was conducted. The clinicopathological data of 149 patients with HCC who were admitted to two medical centers, including 97 cases in the Jiangnan University Medical Center and 52 cases in the Affiliated Xingtai People′s Hospital of Hebei Medical University, from January 2017 to April 2020 were collected. There were 116 males and 33 females, aged (58±12)years. There were 74 cases with VETC and 75 cases without VETC. Observation indica-tors: (1) clinical characteristics of patients with and without VETC; (2) imaging features of patients with and without VETC; (3) multivariable analysis of HCC patients with VETC; (4) construction of VETC related risk scoring model and its performance evaluation; (5) postoperative early tumor recurrence of patients with and without VETC who were confirmed by risk scoring model and histopathological examination. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Count data were described as absolutes, and comparison between groups was conducted using the chi-square test and continuous correction chi-square test. Variables of clinical and imaging characteristics with statistically signifi-cant were included in the multivariate analysis. Multivariate analysis was conducted using the Logistic regression model of backward stepwise selection. VETC related risk scoring model was constructed based on the results of Logistic regression model. The receiver operating characteristic (ROC) curve was drawn, and the area under curve (AUC), the sensitivity, specificity, accuracy and their 95% confidence interval ( CI) were calculated. The maximizing Youden index was the optimal cutoff value for VETC prediction. The Hosmer Lemeshow goodness of fit test was used to assess the consistency between VETC risk scoring model predicted VTEC status and the true VETC status. The Kaplan-Meier method was used to calculate survival rates and draw survival curves. The Log-rank test was used for survival analysis. Results:(1) Clinical characteristics of patients with and without VETC. Cases with postoperative albumin <36 g/L were 57 in patients with VETC, versus 68 in patients without VETC, respectively, showing a significant difference between them ( χ2=5.13, P<0.05). (2) Imaging features of patients with and without VETC. Cases with lesion imaging presence as nonperipheral washout, cases with lesion imaging presence as mosaic architecture, cases with lesion imaging presence as intratumoral hemorrhage, cases with lesion imaging presence as corona enhancement, cases with lesion imaging presence as non-smooth tumor margin, cases with lesion imaging presence as peritumoral enhancement in arterial phase, cases with lesion imaging presence as intratumoral arteries, cases with lesion imaging presence as peritumoral hypointensity in hepatobiliary phase, cases with lesion imaging enhancement type as uniform low enhancement, uniform high enhance-ment, heterogeneous enhancement with septations and heterogeneous enhancement with irregular ring-like structures, cases with intratumoral necrosis or ischemic, cases with tumor diameter >5 cm were 73, 35, 33, 15, 39, 28, 42, 27, 4, 5, 27, 38, 45, 46 in patients with VETC, versus 64, 16, 13, 3, 19, 15, 9, 13, 9, 35, 5, 26, 10, 10 in patients without VETC, respectively, showing significant differences in the above indicators between them ( χ2=8.92, 11.15, 12.97, 9.28, 11.74, 5.77, 33.14, 6.96, 41.79, 36.05, 37.86, P<0.05). (3) Multivariable analysis of patients with VETC. Results of multivariable analysis showed that lesion imaging enhancement as heterogeneous enhancement with septations, lesion imaging enhancement as heterogeneous enhancement with irregular ring-like structures, intratumoral necrosis or ischemia and tumor diameter >5 cm were independent risk factors influen-cing patients with VETC ( odds ratio=4.18, 7.62, 4.23, 4.08, 95% CI as 1.60?11.60, 2.00?31.70, 1.71?10.90, 1.60?10.80), P<0.05). (4) Construction of VETC related risk scoring model and its performance evaluation. The VETC related risk scoring model was constructed as (heterogeneous enhancement with septations, presence: 1.0, absence: 0)+(heterogeneous enhancement with irregular ring-like structures, presence: 1.5, absence: 0)+(intratumoral necrosis or ischemia, presence: 1.0, absence: 0)+(main tumor diameter >5 cm, presence: 1.0, absence: 0). The AUC, sensitivity, specificity, and accuracy of VETC related risk scoring model were 0.86 (95% CI as 0.80?0.92), 79.7% (95% CI as 69.2%?87.3%), 80.0% (95% CI as 69.6%?87.5%) and 79.9% (95% CI as 72.7%?85.5%), respectively. Results of Hosmer-Lemeshow goodness of fit test showed a good consistency between VETC risk scoring model predicted VETC status and true VETC status ( P>0.05). (5) Postoperative early tumor recurrence of patients with and without VETC who were confirmed by risk scoring model and histopathological examination. All 149 patients were followed up for 29(range, 26?35)months. The time to tumor recurrence and 2-year cumulative tumor recurrence rate of 149 patients were 29(range, 24?33)months and 43.0%, respectively. The 2-year tumor cumulative recurrence rate of patients with and without VETC predicted by risk scoring model was 47.8% and 37.9%, respectively, showing a significant difference between ( χ2=3.90, P<0.05). The 2-year cumulative tumor recurrence rate of patients with and without VETC confirmed by postoperative histopathological examination was 47.4% and 38.1%, respectively, showing a significant difference between ( χ2=4.20, P<0.05). Conclusions:Lesion imaging enhancement as heterogeneous enhancement with septations or irregular ring-like structures, intratumoral necrosis or ischemia and tumor diameter >5 cm are independent risk factors influen-cing HCC patients with VETC. The proposed risk scoring model based on those three risk factors achieves an optimal preoperative diagnostic performance.

Objective:To study the protective effects of various doses of Glycyrrhizin on hippocampus of young rats with status epilepticus (SE).Methods:Lithium chloride and pilocarpine were injected intraperitoneally into male Sprague-Dawley (SD) rats (with a postnatal age of 18-21 days), so as to induce SE in rats.The rats were divided into 5 groups according to the random number table method: control group, SE group, SE+ low dose Glycyrrhizin group, SE+ medium dose Glycyrrhizin group and SE+ high dose Glycyrrhizin group.Three different doses of Glycyrrhizin (20 mg/kg, 40 mg/kg and 60 mg/kg) were injected intraperitoneally into the rats.The levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6 in serum of SE rats were determined by enzyme linked immunosorbent assay.Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression levels of TNF- α, IL-1β and IL-6 in hippocampus of SE rats.The expression levels of Bax, Bcl-2 and Caspase-3 in hippocampus were detected by Western blot.The damage of neurons was measured by hematoxylin and eosin (HE) staining and Nissl staining.Neurons apoptosis was examined by terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL). The mitochondrial changes were observed under transmission electron microscopy.One-way ANOVA followed by Tukey post-hoc test was used for statistical analysis. Results:Compared to the control group, TNF-α[(369.69±58.07) ng/L vs. (75.46±14.64) ng/L], IL-1β[(242.27±25.23) ng/L vs. (45.29±5.90) ng/L] and IL-6[(288.15±24.60) ng/L vs. (46.59±8.80) ng/L] in the serum of SE rats were significantly up-regulated(all P<0.05). Compared to SE group, low, medium and high doses Glycyrrhizin could effectively reduce the levels of TNF-α[(216.67±8.31) ng/L, (158.81±5.03) ng/L and (113.69±12.54) ng/L vs. (369.69±58.07) ng/L], IL-1β[(131.21±5.50) ng/L, (86.60±7.79) ng/L and (65.06±4.39) ng/L vs. (242.27±25.23) ng/L] and IL-6[(150.24±9.48) ng/L, (101.70±5.85) ng/L and (91.60±2.81) ng/L vs. (288.15±24.60) ng/L] released in serum after SE occurred (all P<0.05). The neuronal damage, loss, apoptosis and mitochondrial damage were found in the hippocampus of SE rats.Glycyrrhizin could ameliorate these symptoms.Compared to the control group, Bax levels(0.57±0.01 vs. 0.14±0.01)and Caspase-3 levels(0.54±0.00 vs. 0.11±0.01)in the hippocampus of SE rats were markedly increased, while Bcl-2 levels(0.27±0.01 vs. 0.57±0.02)were decreased(all P<0.05). Compared to the SE group, low, medium and high doses Glycyrrhizin could effectively reduce the levels of Bax(0.51±0.02, 0.45±0.03 and 0.40±0.02 vs. 0.57±0.01)and Caspase-3(0.47±0.02, 0.42±0.02 and 0.37±0.01 vs. 0.54±0.00), and increase the levels of Bcl-2(0.41±0.02, 0.45±0.02 and 0.51±0.01 vs. 0.27±0.01)(all P<0.05). Conclusions:Glycyrrhizin can effectively protect the hippocampus of young rats with SE.

Objective: This study used cardiac magnetic resonance imaging (MRI) to compare the characteristics of left ventricular remodeling in patients with primary aldosteronism (PA) with those of patients with essential hypertension (EH) and healthy controls (HCs). Materials and Methods: This prospective study enrolled 35 patients with PA, in addition to 35 age- and sex-matched patients with EH, and 35 age- and sex-matched HCs, all of whom underwent comprehensive clinical and cardiac MRI examinations. The analysis of variance was used to detect the differences in the characteristics of left ventricular remodeling among the three groups. Univariable and multivariable linear regression analyses were used to determine the relationships between left ventricular remodeling and the physiological variables. Results: The left ventricular end-diastolic volume index (EDVi) (mean ± standard deviation [SD]: 85.1 ± 13.0 mL/m2 for PA, 75.9 ± 14.3 mL/m2 for EH, and 77.3 ± 12.8 mL/m2 for HC; p = 0.010), left ventricular end-systolic volume index (ESVi) (mean ± SD: 35.2 ± 9.8 mL/m2 for PA, 30.7 ± 8.1 mL/m2 for EH, and 29.5 ± 7.0 mL/m2 for HC; p = 0.013), left ventricular mass index (mean ± SD: 65.8 ± 16.5 g/m2 for PA, 56.9 ± 12.1 g/m2 for EH, and 44.1 ± 8.9 g/m2 for HC; p < 0.001), and native T1 (mean ± SD: 1224 ± 39 ms for PA, 1201 ± 47 ms for EH, and 1200 ± 44 ms for HC; p = 0.041) values were higher in the PA group compared to the EH and HC groups. Multivariable linear regression demonstrated that log (plasma aldosteroneto-renin ratio) was independently correlated with EDVi and ESVi. Plasma aldosterone was independently correlated with native T1. Conclusion Patients with PA showed a greater degree of ventricular hypertrophy and enlargement, as well as myocardial fibrosis, compared to those with EH. Cardiac MRI T1 mapping can detect left ventricular myocardial fibrosis in patients with PA.