Objective To analyze the causes of missed diagnosis of sleep apnea hypopnea syndrome ( SAHS) . Methods 42 missed diagnosed cases with SAHS from May 2009 to May 2011 were retrospectively analyzed and related literatures were reviewed. Results The SAHS patients often visited the doctors for complications of SAHS such as hypertension, diabetes mellitus, metabolic syndrome, etc. Clinical misdiagnosis rate was very high. Lack of specific symptoms during the day, complicated morbidities, and insufficient knowledge of SAHS led to the high misdiagnosis rate and the poor treatment effect of patients with SAHS. Conclusion Strengthening the educational propaganda of SAHS, detail medical history collection, and polysomnography monitoring ( PSG) as early as possible can help diagnose SAHS more accurately and reduce missed diagnosis.
Sleep apnea causes cardiac arrest, sleep rhythm disorders, nocturnal hypoxia and abnormal blood pressure fluctuations in patients, which eventually lead to nocturnal target organ damage in hypertensive patients. The incidence of obstructive sleep apnea hypopnea syndrome (OSAHS) is extremely high, which seriously affects the physical and mental health of patients. This study attempts to extract features associated with OSAHS from 24-hour ambulatory blood pressure data and identify OSAHS by machine learning models for the differential diagnosis of this disease. The study data were obtained from ambulatory blood pressure examination data of 339 patients collected in outpatient clinics of the Chinese PLA General Hospital from December 2018 to December 2019, including 115 patients with OSAHS diagnosed by polysomnography (PSG) and 224 patients with non-OSAHS. Based on the characteristics of clinical changes of blood pressure in OSAHS patients, feature extraction rules were defined and algorithms were developed to extract features, while logistic regression and lightGBM models were then used to classify and predict the disease. The results showed that the identification accuracy of the lightGBM model trained in this study was 80.0%, precision was 82.9%, recall was 72.5%, and the area under the working characteristic curve (AUC) of the subjects was 0.906. The defined ambulatory blood pressure features could be effectively used for identifying OSAHS. This study provides a new idea and method for OSAHS screening.
Objective To analyze the current state, evaluate the accuracy, and determine the influencing factors of hypertension-related subscriptions from official health WeChat accounts. Methods The 36 official health WeChat accounts on the WeChat official accounts monthly list │ September 2022 China WeChat Top 500·New Rank certification were searched using the term "hypertension". We identified diabetes-related subscriptions published from April 1, 2022 to September 30, 2022. The accuracy of subscriptions was analyzed according to the consistency with clinical practice guidelines and was independently assessed by two specialists. SPSS 22.0 software was used for data analysis. Results One hundred and one subscriptions from 36 official health WeChat accounts were included. Forty-seven (46.5%) subscriptions were evaluated as consistent, seven (6.9%) subscriptions were evaluated as inconsistent, and forty-seven (46.5%) subscriptions were evaluated as unconfirmed. The differences between the numbers of reads, "wow" and "like" per thousand reads, were statistically significant. Consistency rates were higher for tweets backed by evidence and experts, and for tweets posted by public figures with the accreditation type "government". Conclusion Hypertension tweets have a good audience base, some of the content is inconsistent with current clinical guideline recommendations, and readers have little ability to screen them. There is a need to develop and improve the review mechanism for writing and publishing hypertension tweets on WeChat.
摘要:目的:研究高血压病患者过氧化物酶体增殖物激活受体(PPAR)γ2基因Pro12Ala多态性与血糖水平之间的关系。方法:纳入177名原发性高血压患者,其中空腹血糖(FBG)lt;5.6 mmol/L组65例, FBG≥5.6 mmol/L组112例,收集一般资料;分别测定空腹及餐后2小时血糖、胰岛素;对PPARγ2 基因Pro12Ala多态性与各临床变量的关系进行研究。结果:FBGlt;5.6 mmol/L组和FBG≥5.6 mmol/L组Pro和Ala等位基因频率分别为0.333,0.034及0.602,0.031;PP和PA基因型频率分别为0.299,0.068及0.571,0.062;无AA型纯合子。以体重指数(BMI)分层后,BMIlt;25组内,FBG与PPARγ2基因型相关（P=0.029)。以基因型分组比较,PA组空腹血糖水平和胰岛素抵抗指数都低于PP组(Plt;0.05)。结论:成都地区高血压患者PPARγ2基因Pro12Ala多态性与空腹血糖水平相关,且携带Ala基因者空腹血糖水平较低,胰岛素抵抗较轻,推测该突变可能有减轻高血压病患者胰岛素抵抗,改善糖代谢异常的作用。Abstract: Objective:To study the association between the Pro12Ala polymorphism in peroxisome proliferatorsactivated receptorγ2 ( PPARγ2 ) gene and blood glucose levels in patients with primary hypertension. Methods：The Pro12Ala polymorphism in PPARγ2 was determined by polymerase chain reactionrestriction fragment length polymorphism (PCRRELP) in 177 subjects with primary hypertension of the Han people in Chengdu of China, including 65 subjects with fasting blood glucose (FBG)lt;5.6 mmol/L and 112 subjects with FBG≥5.6 mmol/L; the clinical characteristics including height, weight, OGTT(0h and 2h) of the subjects were detected and the realationship between the Pro12Ala polymorphism and the clinical characteristics were analysed. Results: The allele frequencies in the group with FBGlt;5.6 mmol/L and FBG≥5.6 mmol/L were 0.333, 0.602 for Pro and 0.034, 0.031 for Ala. The genotype frequencies were 0.299, 0.571 for PP and 0.068, 0.062 for PA, and there was no AA. In the group with BMIlt;25, the Pro12Ala polymorphism was associated with FBG （P=0.029). the Ala allele had a negative relationship to the FPG and insulin resistance index (IRI) (Plt;0.05).Conclusion: The data showed that the Pro12Ala polymorphism was associated with FBG., and The allele Ala probably had benefits to glycometabolic disturbance in patients with primary hypertension by declining insulin resistance.
目的:应用应变率探讨不同左心室构型的原发性高血压患者左心室长轴方向应变－应变率成像的变化,及其与EF、FS及二尖瓣血流测量评价左室功能的对照研究。方法:采用M型、二维、多普勒超声及应变率成像技术,测量左室室壁厚度、左室内径、EF、FS,二尖瓣血流频谱E、A及左室平均应变ε,应变率S、e、a。结果:高血压离心性肥厚组EF、FS明显低于对照组,高血压其余各组EF、FS与对照组无统计学差异;收缩期应变率S应变ε在五组间差异均有显著性意义:高血压各组较正常对照组减小(I--Ⅴ呈递减);舒张期应变率e减低、a增高,e/a比值减小,各组间存在统计学差异(Plt;0.05); E/A,e/a结果大体一致。结论:应变率成像为临床提供了一个敏感、简便、可靠的评价原发性高血压患者左室心肌功能的指标。