ObjectiveThe risk factors of relapse in 133 epileptic children after withdrawal were analyzed retrospectively and provide reference for clinical withdrawal.MethodsFrom January 2017 to March 2019, 133 children with withdrawal epilepsy were selected as the study object. According to whether there was recurrence during the follow-up period, the children with epilepsy were divided into recurrence group (42 cases) and non recurrence group (91 cases). The gender, age of onset, history of trauma, frequency of seizure before treatment, EEG before drug reduction, imaging, type of medication, family history, time of reaching control, course of disease before treatment, comorbidity, multiple attack types, withdrawal speed and EEG before treatment were observed and compared between the two groups. ResultsThere were significant differences in EEG (χ2 =7.621), medication type (χ2=8.760), time to control (χ2=6.618), course before treatment (χ2=6.435), multiple seizure types (χ2=5.443) and epilepsy comorbidity (χ2=42.795) between the two groups (P < 0.05). The results of Logistic multiple regression analysis showed that the recurrence of epileptic children after drug reduction / withdrawal was correlated with abnormal EEG before drug reduction [OR=9.268, 95%CI (2.255, 38.092)], combined drug treatment [OR=3.205, 95%CI (1.159, 8.866)] and course of disease > 1 year before treatment [OR=5.363, 95%CI (1.781, 16.150)] (P < 0.05).ConclusionsIn order to reduce the possibility of recurrence of epileptic children, the treatment time of epileptic children with abnormal EEG, combined medication and long course before treatment should be prolonged properly.
ObjectiveTo explore the morbidity rate and risk factors of proliferative diabetic retinopathy (PDR) in type 2 diabetes.MethodsThe clinical data of patients, with PDR in 2739 consecutive cases of type 2 diabetes diagnosed in this hospital from 1994 to 2001 were analyed retospectively. The diagnosis of diabetic retinopathy (DR) was confirmed by ophthalmoscopy and fundus fluorescein angiography (FFA). Blood pressure, fasting and postprandial blood sugar, glycosylated haemoglobin（HbA1c）, total serum cholesterol, triglyceride, creatinine, and albumin excretion rate were measured.ResultsThe morbidity rate of type 2 DR was 27.8%（761/2739）, and the morbidity rate of PDR was 4.2%（114/2 739） occupying 15% of the patients with DR. The duration, fasting blood sugar, glycosylated haemoglobin, blood pressure and albumin excretion rate were much higher than those in the control（P＜0.01, glycosylated haemoglobin P＜0.05）. The independent risk factors of PDR were duration of the disease （r=0.15, P＜0.01） and albumin excretion rate （r=0.08, P＜0.05）. The risk factors of PDR were albumin excretion rate and fasting blood sugar (r=0.13, P＜0.05) in patients with longer duration(≥5 years). The morbidity rate of PDR was 2.3%, 5.9% and 12.4% in patients with duration less than 5 years, 5 to 10 years and over 10 years groups, respectively. The morbidity of PDR of the patients in normal albuminuria, microalbuminuria and overt albuminuria group was 2.1%、5.3% and 18.8% respectively.ConclusionsType 2 diabetes accompanied with PDR is relative to the duration of the diabetes, albumin excretion rate, fasting blood sugar, blood pressure, and glycosylated haemoglobin, in which the duration of the disease, albuminuria and fasting blood sugar are the risk factors of occurance of PDR. (Chin J Ocul Fundus Dis, 2003,19:338-340)
ObjectiveTo investigate the clinical risk factors of preterm infants and its severity in premature infants with bronchopulmonary dysplasia (BPD) with retinopathy of prematurity (ROP).MethodsRetrospective clinical study was performed. A total of 126 preterm infants with BPD in the Neonatal Department of the Affiliated Hospital of Qingdao University from January 2016 to December 2018 were enrolled in the study. Among them, 69 were males and 57 were females, whose gestational age＜32 weeks and birth weight＜1500 g. BPD grades Ⅰ, Ⅱ, and Ⅲ were 63, 40, and 23 cases respectively. According to the presence or absence of ROP, children were divided into ROP group and non-ROP group, with 48 (38.1%) and 78 (61.9%) cases respectively. The differences of clinical data between the two groups were compared and analyzed. Quantitative data comparison between groups was performed by t test, and count data comparison was performed by χ2 test. The risk factors of ROP in BPD premature infants were analyzed by multi-factor logistics regression. The correlation between BPD severity and ROP severity was tested by Spearman rank correlation test.ResultsCompared with the non-ROP group, the ROP group had a smaller gestational age (t=5.988), lower birth weight (t=7.371), higher the application rate of oxygen concentration＞30% (duration of service＞24 h), high rate (χ2=17.244) and longer noninvasive ventilation time (t=－7.139), the differences were statistically significant (P＜0.05). In the logistic regression model, the noninvasive ventilation time was the risk factor for ROP in preterm infants with BPD (OR≈1.054, P＜0.05), while gestational age and birth weight were importantly protective factors for ROP in preterm infants with BPD (OR≈0.938, 0.996; P＜0.05). The results of the correlation analysis found that the severity of BPD was significantly positively correlated with the severity of ROP. As the severity of BPD increased, the severity of ROP increased, and the difference was statistically significant (rs=0.306, P＜0.035).ConclusionsFetal gestational age, low birth weight, hyperoxia, and long-term non-invasive mechanical ventilation are the main risk factors for ROP in preterm infants with BPD. The severity of BPD is positively correlated with the incidence and severity of ROP.
ObjectiveConstructing a prediction model for seizures after stroke, and exploring the risk factors that lead to seizures after stroke. MethodsA retrospective analysis was conducted on 1 741 patients with stroke admitted to People's Hospital of Zhongjiang from July 2020 to September 2022 who met the inclusion and exclusion criteria. These patients were followed up for one year after the occurrence of stroke to observe whether they experienced seizures. Patient data such as gender, age, diagnosis, National Institute of Health Stroke Scale (NIHSS) score, Activity of daily living (ADL) score, laboratory tests, and imaging examination data were recorded. Taking the occurrence of seizures as the outcome, an analysis was conducted on the above data. The Least absolute shrinkage and selection operator (LASSO) regression analysis was used to screen predictive variables, and multivariate Logistic regression analysis was performed. Subsequently, the data were randomly divided into a training set and a validation set in a 7:3 ratio. Construct prediction model, calculate the C-index, draw nomogram, calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) to evaluate the model's performance and clinical application value. ResultsThrough LASSO regression, nine non-zero coefficient predictive variables were identified: NIHSS score, homocysteine (Hcy), aspartate aminotransferase (AST), platelet count, hyperuricemia, hyponatremia, frontal lobe lesions, temporal lobe lesions, and pons lesions. Multivariate logistic regression analysis revealed that NIHSS score, Hcy, hyperuricemia, hyponatremia, and pons lesions were positively correlated with seizures after stroke, while AST and platelet count were negatively correlated with seizures after stroke. A nomogram for predicting seizures after stroke was established. The C-index of the training set and validation set were 0.854 [95%CI (0.841, 0.947)] and 0.838 [95%CI (0.800, 0.988)], respectively. The areas under the ROC curves were 0.842 [95%CI (0.777, 0.899)] and 0.829 [95%CI (0.694, 0.936)] respectively. Conclusion These nine variables can be used to predict seizures after stroke, and they provide new insights into its risk factors.
ObjectiveTo explore the prevalence and risk factors of hypertension in Anyue County from June 2011 to June 2013.
MethodsUsing stratfied random cluster sampling method, 5 391 people over 15 years of age were selected from 3 residential areas and 3 natural villages to finish a questionnaire and blood pressure measurement.
ResultsThe total prevalence rate of hypertension in Anyue County was 18.77%. The prevalence rates of hypertension in urban areas and rural areas were 21.75% and 16.20%, and the difference was significant (χ2=27.120, P<0.001). In both urban and rural areas, the prevalence rate of hypertension increased with age (χ2=475.634, P<0.001; χ2=394.026, P<0.001). The percentages of awareness, treatment and control in Anyue County were 31.30%, 24.41%, and 9.09%. The percentages of awareness, treatment and control in urban areas were 40.15%, 33.70%, and 11.23% and were 20.68%, 13.65%, and 6.61% in rural areas. There were significant differences in the percentages of awareness, treatment and control between urban and rural areas (χ2=44.475, P<0.001; χ2=54.861, P<0.001; χ2=8.202, P=0.004). The logistic regression analysis showed that age (OR=1.061, P<0.001), diabetes (OR=1.550, P<0.001), hyperlipemia (OR=2.372, P<0.001) and smoking (OR=1.335, P<0.001) were the risk factors for hypertension; and it showed that high level of education was a protective factor for hypertension (OR=0.755, P<0.001).
ConclusionBecause of high prevalence and low percentages of awareness, treatment and control in Anyue County, the prevention and control situation of hypertension are grim. We should focus on the control of smoking, blood lipid and blood glucose.
Objective To evaluate evidence from American medical risk monitoring and precaution system (AMRMPS) which may affect the construction of Chinese medical risk monitoring and precaution system (CMRMPS). Methods We searched relevant databases and Internet resources to identify literature on AMRMPS, medical errors, and patient safety. We used the quality evaluation system for medical risk management literature to extract and evaluate data. Results In 1999, a report from the Institute of Medicine (IOM) not only showed the severity and cause of medical errors in America but also gave the solution of it. In 2000, the Quality Interagency Coordination Task Force (QuIC) was appointed to assess the IOM report and take specific steps to improve AMRMPS. After 5 years, a well-developed medical risk management system was established with the improvement in the public awareness of medical errors, patient safety, performance criteria of medical safety, information technology and error reporting system. There was still some weakness of this system in risk precaution and prevention. Conclusion The experience from AMRMPS can be used to establish the CMRMPS. Firstly, we should disseminate and strengthen the awareness of medical risk and patient safety in public. Secondly, we should establish hospital audit system which includes auditing of medical staff and course of medical risk in continuing and academic education. Thirdly, we should develop regulations and guidelines on health care, medical purchase and drug supply which will benefit in management of regular work. Fourthly, we should develop computer information system for hospital which will regulate the management without the disturbance from human. Lastly, we should emphasize outcome evaluations and strive for perfection during the process.
Objective
To summarize the role and implementation effect of risk management in Ophthalmic Day Surgery Center.
Methods
Since the establishment of Ophthalmic Day Surgery Center on October 8th, 2012, risk management was implemented in the aspects of hardware management, post setting, file management, operating process, service, etc., and the adverse events occurred in the period were analyzed to find out the defectiveness and hidden dangers in the working process, and then refined intervention measures were put forward and carried out. The surgical amount, occurrence of nosocomial infections and nursing adverse events, and patients satisfaction from October 8th, 2012 to June 30th, 2015 were analyzed.
Results
During this period, 52 073 ambulatory operations were completed, with no nosocomial infection and 2 cases of nursing adverse events. The patients satisfaction in 2013, 2014, and 2015 was 98.09%, 98.22%, and 99.85%, respectively.
Conclusion
The implementation of risk management in Ophthalmic Day Surgery Center can effectively reduce the occurrence of adverse events in nursing work, improve work efficiency, help to establish and improve the nursing security environment, improve the nurse-patient relationship, and improve patients satisfaction.
ObjectiveTo understand basic characteristics and clinical features of tuberculosis in Mianyang, Sichuan, and to investigate the risk factors of two case-finding methods for tuberculosis:"passive finding" and "active screening".
MethodsOne-hundred and seventy-five active tuberculosis patients screened by physical examination in 21 villages of Fucheng and Jiangyou from June 2013 to March 2014 were included. Information about basic characteristics and clinical features of tuberculosis was collected using questionnaire, chest X-ray and laboratory examinations. We also applied binary logistic regression to explore the risk factors of finding for tuberculosis.
ResultsIn all 175 tuberculosis patients, 41.71% were over 60 years old and 73.71% were farmers. Productive cough over two weeks was the most common symptom, accountting for 58.29%. 19.63% were sputum smear-positive while 70.87% were PPD-positive. Binary logistic regression analysis demonstrated that tuberculosis history significantly influenced the findings for tuberculosis (OR=15.809,95%CI: 6.708~37.258).
ConclusionsActive tuberculosis patients screened by physical examination in Mianyang, Sichuan were mainly elderly male over 60 years old and farmers, with single pulmonary symptom as the primary clinical feature. The patients with tuberculosis history may be found by "passive finding".
Purpose To analyze the clinical characteristicsand prognostic factors of Status epilepticus (SE) in children. Methods The clinical data of 33 children with SE treated in Jinan Central Hospital Affiliated of Shandong University from January 2014 to June 2021 were collected, and their clinical characteristics were analyzed. Then, according to Glasgow prognosis scale, the children were divided into good prognosis group (n=20) and poor prognosis group (n=13). The age of first attack, duration of attack, type of attack and SE classification, EEG, cranial imaging and etiology were used to analyze the influencing factors of SE prognosis. Results 75.7% were 0 ~ 6 years old in the age of first attack, and 29 cases of convulsive status epilepticus accounted for 87.9% in the classification of seizure types. There were significant differences in age of first attack, duration of attack, EEG, history of mental retardation and etiology between the two groups (P<0.05); Logistic regression analysis showed that the age of first attack, duration of attack, history of mental retardation and EEG were independent factors affecting the prognosis. Conclusion Low age, especially ≤ 6 years old, is the high incidence of SE in children at first attack. Most children are symptomatic and have obvious incentives. Convulsive SE is the main type of SE in children. The age of first onset, duration of epilepsy, history of mental retardation, and EEG can affect the prognosis of SE.
Objective To compare the risk factors between multiple cerebral infarction (MCI) and single cerebral infarction (SCI). This would be beneficial for carrying out corresponding prevention and treatment. Methods We prospectively registered consecutive cases of ischemic stroke in the neurological wards and divided them into two groups: MCI group and SCI group according to their clinical and imaging data. Firstly, the single variable analyses of 24 factors that could be related to the onset of MCI were conducted, and then the multivariate non-condition stepwise logistic regression was performed. Results Significant differences were noted between MCI group and SCI group in terms of age, gender, hpertension, diabetes, heart valvular disease, smoking, cerebral infarction history and first systolic blood pressure after admission. The logistic regression analyses showed that factors of age (OR=1.014, 95%CI 1.003 to 1.026), hypertension (OR=1.566, 95%CI 1.185 to 2.068), smoking (OR=1.473, 95%CI 1.052 to 2.061), cerebral infarction history (OR=1.948, 95%CI 1.326 to 2.864) were independent risk factors for MCI. Conclusion Compared to SCI, age, hypertension, smoking and cerebral infarction history were independent risk factors for MCI patients.
