| Chapter 1:The Meta Analysis of the OSAHS Prevalence in ChinaObjective:to conduct systematic evaluation and comprehensive analysis about OSAHS prevalence among adults in Mainland China;to facilitate the understanding on epidemiology of OSAHS in Mainland China and to provide reference on the nation-wide epidemiologic survey for policy makersMethods:Wanfang Data,chinaqking.com,cqvip.com and pubmed were chosen as the four databases for data retrieving.The key words are:prevalence OR epidemiology AND sleep apnoea.Result:11 journals were shortlisted,which collected data from 53,965 persons.All researchers sampled and conducted polysomnography examination on the suspicious groups after questionnaire survey.Assuming there is no patient in the asymptomatic population;the patients in the high-risk groups are taken as molecular and the entire population are taken as the denominator,then the calculated OSAHS prevalence in Mainland China is 4%(3%,6%).Conclusion:high-standard epidemiology studies are very few at the moment.There is a lack of OSAHS epidemiological data in most of the provinces and areas,especially in rural area.With consideration of economic and social burden caused by OSAHS,it is necessary to standardize the methodology and diagnostic criteria and to conduct nation-wide OSAHS epidemiologic survey.Chapter 2:The Quantity Analysis of OSAHS Literatures Based on SCIObjective:to analyze the OSAHS research and the foremost progress with Science Citation Index(SCI)and Essential Science Indicators(ESI),in order to provide reference for researchers in China.Methods:adopt the SCI Expanded of Institute of Scientific Information and ESI as the retrieval object to search for all literatures with the subject of Sleep Apnoea.Analyze the data-using the built-in analytical functions of the database and HistCite8.12.16.Result:there are an increasing number of literatures about sleep apnoea,most of which come from the US.Such papers were published on 1,127 journals,covering ENT,cardiovascular,pediatric,neurology,psychology and etc.in addition to sleep and respiratory.The institution which published the most papers is Stanford University,and in Mainland China is Nanjing Medical University.The journal which published the most papers is“Sleep"' The author who published the largest number of papers is Guilleminault C.The research frontiers are cardiovascular disease,inflammation,oxidative stress,cognitive defects,and vascular endothelial.Conclusion:sleep apnoea is drawing more and more attention and has become a research hotspot.US is taking the extreme advantage in this research field.OSAHS is an important disease which impacts multi-systems in the body and involves several clinical fields.However,there are still a number of questions remained unanswered.Chapter 3:Survey of Chinese Undergraduates about OSAHS and Other Sleep KnowledgeObjective:the current medical education status of OSAHS and other sleep disorders determines the diagnosis level of future doctors.Conducting a survey on Chinese medical undergraduates about their knowledge,altitudes and practice about OSAHS and other sleep disorders can provide references for regulators and policy makers.Methods:questionnaires on OSAHS and other sleep dysfunctions were designed to survey 324 undergraduates from Nanfang Medical University.Students were requested to fill the self evaluation questionnaire before and after the three-hour OSAHS course.The main content of the course was OSAHS,followed by other sleep medical knowledge.The survey was conducted anonymously.Result:all 324 questionnaires were collected back.93.6%of the students knew that insomnia is a sleep disorder,but only 64.9%of the students considered snoring as a sleep disorder;such figure rose to 92.7%after the completion of the course.Only 27%of the students knew that diabetes and dyslipidemia are related to OSAHS and 23.2%believed that concentration deficit and hyperactivity syndrome are related to OSAHS.After the completion of the three-hour courses,the proportion of the students who knew that hypertension is related to OSAHS rose from 64.9%to 92.7%;the proportion for diabetes also rose from 64.9%to 92.7%.Similarly,the proportion for arrhythmia rose from 48.0%to 60.3%and the proportion for gastroesophageal reflux rose from 33.5%to 59.9%(P<0.001).Most of the students were aware that OSAHS and other sleep disorders are related to neurology,psychology,oral sciences,otolaryngology and respiratory epidemiology.85.2%agreed that a specialized institution should be set up to deal with diagnosis and treatment of sleep disorders.Almost 80%conceded that they themselves or their friends had sleep problems.44.8%had received respective consultation.More than two-thirds did not receive any sleep medicine education.Clinical knowledge is the most wanted knowledge among medical students(72%),followed by health care on sleep(87.1%),and the mechanisms and pathophysiology(57.5%).A majority of the students wanted to learn through elective courses.71%would like to learn about OSAHS and other sleep medicine knowledge not only because of interest,but also because they believed that the knowledge of sleep medicine was necessary for the future doctors.Conclusion:the Chinese medical undergraduates pay a lot of attention on sleep disorders,but their understanding on sleep medicine is very shallow.A short-term course may have some effects on their understanding and altitude,but the long-term effect remains unknown.More elective modules should be set up to enhance the education on sleep medicine,in order to prepare for OSAHS and other sleep disorders which have high prevalence and big impact.Chapter 4:The Establishment and Analysis of the Chinese OSAHS DatabaseObjective:to collect the data of OSAHS inpatients in Nanfang Hospital and to establish the medical database with the purpose of managing,tracking and analyzing the OSAHS data better,so that the efficiency and quality of the clinical research can be enhanced.Methods:collect and compile the data of inpatients at the Sleep Center of Nanfang Hospital who received polysomnography examination due to symptoms like snoring and daytime sleepiness from July 2009 to July 2011.Apply EpiData software to establish the database structure based on the OSAHS medical records.Key in and verify data after establishing the questionnaire document;then,use SPSS13.0 to analyze the data.Result:a total of 401 cases with complete polysomnography examination data,including 73 non-OSAHS cases(AHI<5)and 328 OSAHS cases were collected.Among the OSAHS cases,there are 67 mild cases(15<AHI>5),82 moderate cases(30<AHI ? 15)and 179 severe cases(AHI>30).Out of the 401 cases,there are 350 male patients(87.3%)and 51 female patients(12.7%).The mean age is 45 ? 12;39 patients are older than 60(9.73%);155 patients had a smoking history or are active smokers(38.7%).In the OSAHS group,the average course of disease is 10 years.The body weight,body weight index,neck circumference,chest circumference,abdomen circumference,night and daytime diastolic pressure of the OSAHS group are all higher than the non-OSAHS group(P<0.01).Out of the 328 OSAHS patients,there are 316 cases with the symptom of snoring(96.3%),36 cases with the symptom of sleep-time over hyperactivity(11%),253 cases with the symptom of breath difficulty(77.1%),145 cases with the symptom of daytime sleepiness(44.2%),216 cases with the symptom of daytime anenergia(65.9%),142 cases with the symptom of dizziness(43.3%),12 cases with the symptom of response lagging(3.7%),4 cases with the symptom of listening decline(1.2%),79 cases with the symptom of morning headache(24.1%),94 cases with the symptom of memory decline(28.1%),48 cases with the symptom of concentration decline(14.6%),5 cases with the symptom of early waking up(1.5%),29 cases with the symptom of chest tightness(8.8%),242 cases with the symptom of mouth dryness(73.8%),40 cases with the symptom of mouth pain(12.2%),2 cases with the symptom of acid regurgitation and belching(0.6%),2 cases with the symptom of drooling(0.6%),23 cases with the symptom of night sweating(7%),115 cases having nocturia>2 times(35.1%),5 cases with the symptom of loss of libido(1.5%)and 17 cases with the symptom of difficult to fall asleep(5.2%).Also out of the 328 OSAHS patients,there are 70 cases with medical history of hypertension(21.3%),4 cases with medical history of coronary heart disease(1.2%),1 case with medical history of arrhythmia(0.3%),17 cases with medical history of diabetes(5.2%),1 case with medical history of hypothyroidism(0.3%),29 cases with medical history of hyperlipidemia(8.8%),2 cases with medical history of asthma(0.6%)and 4 cases with medical history of chronic nasal disease(1.2%).All patients have no medical history of heart failure,pulmonary hypertension,deep vein thrombosis,pulmonary embolism,cerebral thrombosis,chronic obstructive pulmonary disease and acromegaly.Comparing the data of the two groups,the difference in total sleep time,phase 2 sleep time,phase 2 sleep time ratio,phase 3 and phase 4 sleep time,phase 3 and phase 4 sleep time ratio,awakening time,total number of obstructive apnea,number of central apnea,total number of apnea and hypopnea,hypopnea index,apnea index,apnea hypopnea index,number of oxygen reduction,oxygen reduction index,oxygen reduction time,mean nighttime oxygen saturation,lowest oxygen saturation and mean heart rate shows a statistical significance(P<0.05).230 patients out of 401 received nasopharyngoscopy,including 191 patients from the OSAHS group.Out of these 191 OSAHS patients,there are 34 cases with nasal septum deviation(17.8%),11 cases with turbinate hypertrophy(5.8%),7 cases with nasal polyps(3.7%),177 cases with nasopharyngeal lymphoid follicular hyperplasia(92.7%),139 cases with soft palate pharyngeal cavity stenosis(72.8%),182 cases with excessive lymphoid follicular hyperplasia at the oropharyngeal glossal root and posterior pharyngeal wall(95.3%),5 cases with epiglottis abnormality(2.6%),185 cases with aryepiglottic wall chronic congestion(96.9%),70 cases with interarytenoid chronic congestion(36.6%),180 cases with ventricle chronic congestion(94.2%),3 cases with laryngeal ventricle abnormality(1.6%),179 cases with vocal cord chronic congestion(93.7%),3 cases with glottis abnormality(1.6%),1 case with sinus piriformis abnormality(0.5%)and 107 cases with 50%or above Muller action airway obstruction(56%).216 patients out of all(53.9%)completed the blood routine examination,the Result indicate that the white blood cell count,the total number of neutrophil,the red blood cell count,the volume ratio between hemoglobin and red blood cell of the OSAHS group are higher(P<0.05)than that of the non-OSAHS group.In the OSAHS group,the fasting blood glucose,1 hour postprandial blood glucose,2 hour postprandial blood glucose,uric acid,alanine aminotransferase,very low-density lipoprotein,apolipoprotein A and B,whole blood viscosity with shear rate 100,plasma viscosity,erythrocyte electrophoresis time,high sensitivity C reactive protein,free T3 are increased.258 patients(64.3%)completed the Epworth Sleepiness Scale and the Result indicate that the scores of the OSAHS group are higher.216 patients(53.9%)completed the Pittsburgh Sleepiness Scale;the scores of the non-OSAHS group are slightly higher,but the difference is not statistically significant(p=0.14).165 patients(41.1%)received the chest plain film examination and chest radiograph abnormality was detected on 68 patients(41.2%).94 patients received the nasopharyngeal lateral film examination and abnormality was detected on 11 patients(11.7%).175 patients(43.6%)received the ECG examination,where 3 patients had myocardial ischemia(1.7%)and 18 patients had arrhythmia(1.3%).182 patients received the urine routine examination;the difference between the two groups is not statistically significant.Part of the patients received the stool routine examination;no abnormality was detected.Conclusion:a preliminary OSAHS database(adult)of Nanfang Hospital was established.It will lay a strong foundation for conducting follow-up investigation,summarizing treatment experience and performing prognosis research.Chapter 5:To Reduce Unnecessary Polysomnography-A Nomogram for Predicting Sleep Apnea SyndromeObjective:to establish a simple and practical OSA disease risk assessment system by integrating the clinical symptoms,the demographic and anthropometric indicators with the best predictive value;to help the patients and doctors make more informed and rational decisions on polysomnography examination and treatment without increasing the current clinical workload.Methods:Conduct a retrospective analysis about the medical data of the inpatients that were suspected to suffer sleep apnea syndrome and received treatment at the Sleep Center of Nanfang Hospital from September 2009 to June 2011.The demographic indicators include sex and age.The subjective indicators include the course of disease,the symptoms of snoring,nighttime hyperactivity,breath difficulty,daytime sleepiness,anenergia,dizziness,slow response,hearing decline,morning headache,memory loss,concentration loss,early waking up,chest tightness,mouth dryness,mouth pain,acid regurgitation,drooling,night sweating,nocturia(>2 times),loss of libido,irritability and difficulty to fall asleep,as well as the smoking history(patients with a history of smoking or who are active smokers).The objective indicators include height,body weight,neck circumference,chest circumference,waist circumference and the blood pressure before and after sleep.A nomogram was established by using the ordinal logistic regression equation.The identification and calibration ability and the clinical significance of this nomogram were evaluated.Result:the finalized variables are:course of disease,anenergia,difficulty to fall asleep,smoking and abdominal circumference.This Nomogram exhibits good identification ability on OSAHS,moderate-to-severe OSAHS and severe OSAHS(the area below the characteristic curve of the tester>0.8).The calibration curve shows that this nomogram has a good calibration performance.According to the net benefit calculated based on the threshold value of 82%,this nomogram can reduce 10%of the unnecessary polysomnography examinations.Conclusion:a nomogram was established to predict the OSAHS risk of the suspected OS A patients who are receiving treatment at the sleep center.This nomogram is constructed based on symptoms,demographic and anthropometric indicators.It is simple and non-invasive,able to reduce 10%of the unnecessary polysomnography examinations without increasing the labor cost.Chapter 6:Is Muller Action Helpful for OSAIHS Risk Assessment?Objective:to evaluate the possible function of Muller action in OSAHS risk classification.It provides a reference on whether Muller action check should be performed prior to polysomnography examination.Methods:230 cases from July 2009 to July 2011 with complete data of electronic nasopharyngoscopy,polysomnography examination,clinical-related demographic indicators,symptomatic indicators and physical examination indicators were included.Logistic regression was adopted to establish the clinical model and the clinical + Muller model.The area below the receiver operating characteristic curve was used to evaluate the identification ability of the two models on OSAHS.Thereafter,the clinical model was applied to conduct risk classification at first,and then the clinical + Muller model was applied to conduct risk reclassification for the patients.Risk is divided into three levels:low risk:<83%(prevalence);moderate risk:<83%<97%;high degree of risk:>97%.The Intergrated Discrimination Index(IDI)and the Net Reclassification Improvement(NRI)were used to evaluate the risk reclassification ability of Muller.Result:out of the 230 cases,there are 191 OSAHS patients;3 variables-age,anenergia and neck circumference-were taken to establish the clinical model.The area below ROC curve of the clinical model is 0.86(95%CI,0.80-0.92)(p = 0.030);after including Muller action,the area below ROC curve is increased to 0.88(95%CI,0.82-0.93)(p = 0.029).The difference between the two models is statistically significant(?2 = 4.77;p = 0.029).Then,the Muller action check was included and 13%(30/230)of the samples were reclassified.21 cases were reclassified into the high-risk group(7+1+13),where the sickness ratio is 95.2%(95%CI,74.1%-99.8%);9 cases were reclassified into the low-risk group,where the sickness ratio is 88.9%(95%CI?50.7%-99.4%).When Muller check was included into the clinical model,a total of 13 cases were reclassified from the low or moderate-risk group to the high-risk group(5.7%).These people are all OSAHS patients(100%).7 cases(3%)were reclassified into the low-risk group,where 6 cases(85.7%)are OSAHS patients.No OSAHS patient of the high-risk group was reclassified into the low-risk group.In the moderate-risk group,13 cases(12.6%)were reclassified into the high-risk group and 7 cases(6.8%)were reclassified into the low-risk group(NRI,0.03;p=0.257).The improvement of risk classification is lower compared to the entire sample.For the 95 OSAHS patients in the moderate-risk group,13(14%)were reclassified into the high-risk group and 6(6%)were reclassified into the low-risk group.The inclusion of Muller reclassified additional 8.1%OSAHS patients into the high-risk group,without increasing the reclassification of non-patient cases.Conclusion:Mmuller action check can slightly improve the OSAHS identification ability,but compared to the basic clinical information,the improvement on the ability of OSAHS risk assessment is limited.It should not be used as a screening examination prior to routine PSG.Chapter 7:Comparison of the 6 Models for Sleep Apnea Hypopnea Syndrome PredictionObjective:to compare the effects of the 6 types of OSAHS prediction models established based on logistic regression,support vector machine,neural networks,C5.0,classification and regression tree and Bayesian,respectively,so as to provide reference for selecting the OSAHS data mining tool in clinical practice.Methods:a total of 401 cases were randomly divided into two groups:30%as training samples and 70%as testing samples.Logistic regression,Bayesian network,artificial neural network,support vector learning machine,C5.0 and classification and regression tree were adopted respectively to establish the prediction model.After conducting training using 284 samples,the 6 models were taken to test the other 117 testing samples.The testing samples were used to calculate the correct rate and error rates of each model.Result:22 variables,the difference of which between the patient group and the non-patient group is statistically significant,were selected as the input variables:male,age,course of disease,snoring,apnea,daytime sleepiness,dry mouth,anenergia,chest tightness,early waking up,nocturia>2,difficulty of falling asleep,smoking,height,weight,neck circumference,chest circumference,abdominal circumference,body mass index,night systolic blood pressure,morning systolic blood pressure,morning diastolic blood pressure.Neck circumference(4/5),abdominal circumference(4/5),age(4/5)and nocturia>2 are considered as the most important variables by the models.Support vector machines,neural networks and C5.0 are superior to the classification and regression tree,Bayesian network and logistic regression models.Conclusion:in terms of OSAHS risk prediction,Support vector machines,neural networks and C5.0 are superior to the classification and regression tree,Bayesian network and logistic regression models.However,such Result were obtained based on the data of a single center,so the Conclusion need to be further validated by other institutions.Chapter 8:Study about the Hypoxia Resistance of Heat AdaptationObjective:high temperature can result in cross adaptation to hypoxia,but whether high temperature can also result in tolerance to hypoxia in mammals is still unclear.The objective of this study is to design a heat adaptation approach to observe whether heat adaptation can enhance the anti-hypoxia ability of mice,and at the same time,to explore its mechanism.Methods:healthy Balb/C male mice 4-6w were divided into two groups.The heat adaptation group was placed in the 51.5 ? constant-temperature box two sessions a day,10 min for each session.The control group was placed in the 26 ?closed box.After 10 consecutive days,observe the survival rate and survival time of mice under the lethal hypoxia condition,as well as the changes of blood brain barrier,lung vascular permeability,brain lung water ratio,pathological morphology of cortex and hippocampal CA1 area and the expression of brain tissues p-IRE,IRE,Bax and Bc12 under the sub-lethal hypoxia condition.Result:the survival time of the heat adaptation group is 13 ± 1min and the survival rate is 70%;the survival time of the control group is 10.7 ± 1.0min and the survival rate is 45%(p=0.009).The difference between the two groups is statistically significant.For the hypoxia group,the pyramidal neurons of the cortex hippocampal CA1 area present a disorderly arrangement and the cells are shrinking.Heat adaptation reduces the pathological changes caused by hypoxia.The difference in brain water,lung water,blood brain barrier,pulmonary vascular permeability,expression of p-IRE,IRE,Bax and Bc12 among the hypoxia control group,the hypoxia heat adaptation group,the normoxic control group and the normoxic heat adaptation group is not statistically significant.Conclusion:the intermittent heat adaptation of 2 sessions a day,10 min for each session,can prolong the survival time and survival rate of mice under the lethal hypoxia condition.Heat adaptation may produce such effect by mitigating the hypoxic brain injury of mice.Its specific mechanism still needs to be further studied. |
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