Analysis Of Medical Record Data Research Articles

A Retrospective Observational Study on Telemedicine in Prescribing Low-Dose Pills for Patients with Dysmenorrhea.

In Japan, telemedicine has gradually expanded due to deregulation in response to the COVID-19 pandemic. However, its current status remains unclear, as it is primarily provided by general practitioners. Meanwhile, telemedicine has begun to be utilized for low-dose estrogen-progestin (LEP) prescriptions for dysmenorrhea. We conducted a retrospective analysis of medical record data from two gynecology clinics and performed an exploratory evaluation between a group that combined telemedicine and in-person visits during the initial 6 months of LEP treatment, and another group with only in-person visits. After propensity score matching, 89 and 83 patients were eligible for the telemedicine and in-person groups, respectively, with 53 patients in both. The characteristics of both groups were similar after matching. There were no significant differences in the probability of abnormal uterine bleeding during the first 6 months of treatment (25% and 43% in each group; p = 0.064), side effects, or treatment efficacy between the two groups. The withdrawal rate at 6 months was significantly higher in the telemedicine group than in the in-person group (13% and 0%, p = 0.013). The average copayment for patients who covered 30% of the total cost was also significantly higher in the telemedicine group after 1 and 3 months of LEP prescription. The appropriate combination of telemedicine and in-person visits is currently employed in hospital visits, which does not differ significantly from in-person visits. Given the retrospective nature of this study and the limited number of cases, further investigation is necessary in the future.

Electronic Medical Record Data Analysis and Prediction of Stroke Disease Using Explainable Artificial Intelligence (XAI)

The deficiency of oxygen in the brain will cause the cells to die, and the body parts controlled by the brain cells will become dysfunctional. Damage or rupture of blood vessels in the brain is better known as a stroke. Many factors affect stroke. These factors certainly need to be observed and alerted to prevent the high number of stroke sufferers. Therefore, this study aims to analyze the variables that influence stroke in medical records using statistical analysis (correlation) and stroke prediction using the XAI algorithm. Factors analyzed included gender, age, hypertension, heart disease, marital status, residence type, occupation, glucose level, BMI, and smoking. Based on the study results, we found that women have a higher risk of stroke than men, and even people who do not have hypertension and heart disease (hypertension and heart disease are not detected early) still have a high risk of stroke. Married people also have a higher risk of stroke than unmarried people. In addition, bad habits such as smoking, working with very intense thoughts and activities, and the type of living environment that is not conducive can also trigger a stroke. Increasing age, BMI, and glucose levels certainly affect a person's stroke risk. We have also succeeded in predicting stroke using the EMR data with high accuracy, sensitivity, and precision. Based on the performance matrix, PNN has the highest accuracy, sensitivity, and F-measure levels of 95%, 100%, and 97% compared to other algorithms, such as RF, NB, SVM, and KNN.

Association of an Automated Blood Pressure Measurement Quality Improvement Program With Terminal Digit Preference and Recorded Mean Blood Pressure in 11 Clinics

Terminal digit preference has been shown to be associated with inaccurate blood pressure (BP) recording. To evaluate whether converting from manual BP measurement with aneroid sphygmomanometers to automated BP measurement was associated with terminal digit preference, mean levels of recorded BP, and the rate at which hypertension was diagnosed. This quality improvement study was conducted from May 9, 2021, to March 24, 2022, using interrupted time series analysis of medical record data from 11 primary care clinics in a single health care system from April 2008 to April 2015. The study population was patients aged 18 to 75 years who had their BP measured and recorded at least once during the study period. Manual BP measurement before April 2012 vs automated BP measurement with the Omron HEM-907XL monitor from May 2012 to April 2015. The main outcome was the distribution of terminal digits and mean systolic BP (SBP) values obtained during 4 years of manual measurement vs 3 years of automated measurement, assessed using a generalized linear mixed regression model with a random intercept for clinic and adjusted for seasonal fluctuations and patient demographic and clinical characteristics. The study included 1 541 227 BP measurements from 225 504 unique patients during the entire study period, with 849 978 BP measurements from 165 137 patients (mean [SD] age, 47.1 [15.2] years; 58.2% female) during the manual measurement period and 691 249 measurements from 149 080 patients (mean [SD] age, 48.4 [15.3] years; 56.3% female) during the automated measurement period. With manual measurement, 32.8% of SBP terminal digits were 0 (20% was the expected value because nursing staff was instructed to record BP to the nearest even digit). This proportion decreased to 12.4% during the automated measurement period (expected value, 10%) when both even and odd digits were to be recorded. After automated measurement was implemented, the mean SBP estimated with statistical modeling increased by 5.09 mm Hg (95% CI, 4.98-5.19 mm Hg). Fewer BP values recorded during the automated than the manual measurement period were below 140/90 mm Hg (69.9% vs 84.3%; difference, -14.5%; 95% CI, -14.6% to -14.3%) and below 130/80 mm Hg (42.1% vs 60.0%; difference, -17.9%; 95% CI, -18.0% to -17.7%). The proportion of patients with a diagnosis of hypertension was 4.3 percentage points higher (23.4% vs 19.1%) during the automated measurement period. In this quality improvement study, automated BP measurement was associated with decreased terminal digit preference and significantly higher mean BP levels. The method of BP measurement was also associated with the rate at which hypertension was diagnosed. These findings may have implications for pay-for-performance programs, which may create an incentive to record BP levels that meet a particular goal and a disincentive to adopt automated measurement of BP.

Approach for Electronic Medical Record Data Analysis

As the healthcare environment is being digitalized and changed rapidly, research using medical big data is increasing. One of the most applicable data is electronic medical records which can provide a large amount of clinically practical meaning. Electronic medical data include patient’s demographic information, laboratory test results, imaging and biosignal data. In this article, we provide support for a wide variety of researchers in their efforts to use electronic medical record data accurately and usefully in their work. From the basic concept of the research using electronic medical records to challenging aspects like data integration between multiple institutions are described. Also, examples of each type of data are covered; structured such as numeric data and unstructured such as images, biosignals and narrative text. Using these kinds of electronic medical records, analyses are processed by data cleansing, transforming, and reducing in order. Many kinds of variables such as the exposure and outcome of interest, covariate and the research design can be chosen during the preprocessing. As many machine-learning-based studies as well as epidemiologic-based studies have been conducted using electronic medical records, various research frameworks have been proposed. However, data quality management and data standardization for multicenter data analysis are still remaining as challenging tasks.

Approach for Electronic Medical Record Data Analysis

As the healthcare environment is being digitalized and changed rapidly, research using medical big data is increasing. One of the most applicable data is electronic medical records which can provide a large amount of clinically practical meaning. Electronic medical data include patient’s demographic information, laboratory test results, imaging and biosignal data. In this article, we provide support for a wide variety of researchers in their efforts to use electronic medical record data accurately and usefully in their work. From the basic concept of the research using electronic medical records to challenging aspects like data integration between multiple institutions are described. Also, examples of each type of data are covered; structured such as numeric data and unstructured such as images, biosignals and narrative text. Using these kinds of electronic medical records, analyses are processed by data cleansing, transforming, and reducing in order. Many kinds of variables such as the exposure and outcome of interest, covariate and the research design can be chosen during the preprocessing. As many machine-learning-based studies as well as epidemiologic-based studies have been conducted using electronic medical records, various research frameworks have been proposed. However, data quality management and data standardization for multicenter data analysis are still remaining as challenging tasks.

Artificial Intelligence in Hematology

‘Artificial Intelligence’ is a general term to designate computer technologies for solving the problems that require implementation of human intelligence, for example, human voice or image recognition. Most artificial intelligence products with application in healthcare are associated with machine learning, i.e., a field of informatics and statistics dealing with the generation of predictive or descriptive models through data-based learning, rather than programming of strict rules. Machine learning has been widely used in pathomorphology, radiology, genomics, and electronic medical record data analysis. In line with the current trend, artificial intelligence technologies will most likely become increasingly integrated into health research and practice, including hematology. Thus, artificial intelligence and machine learning call for attention and understanding on the part of researchers and clinical physicians. The present review covers important terms and basic concepts of these technologies, as well as offers examples of their actual use in hematological research and practice.

What does a 24-hour child and adolescent psychosocial care center do in the city of Curitiba, Brazil?

The National Policy on Mental Health for Children and Adolescents is still poorly structured in Brazil. In general, it replicates the policy aimed at adults, which creates problems for its articulation with networks. The objective of this study was to analyze and describe the actions carried out at a 24-hour Child and Adolescent Psychosocial Care Center (CAPSi) with beds in the city of Curitiba, Brazil. This is a descriptive study based on the analysis of medical record data and productivity data between 2016-2017, provided by the Department of Informatics at the Unified Health System (DATASUS). Results show that the center performed 29,449 procedures and attended to 112 children and adolescents through its 24-hour service. Medical records indicate extensive use of the service by the network. Primary care accounted for 52% of demand, while the other half could be attributed to a wide range of services. The variety of actions carried out suggests a high degree of flexibility at the clinic, replacing the classic model of the psychiatric hospital with the principles of the expanded clinic. Furthermore, the existence of beds made it easier to manage crises in a manner more closely linked to the community.

Research on diabetes prediction method based on electronic medical record data analysis

The continuous progress of computer science and technology has accelerated the pace of informatization construction of the medical system. Medical technology has developed rapidly in various research directions, and the construction of medical IT systems has been continuously improved. The popular application of electronic medical records has produced massive medical data in the medical process. At the same time, in medical behavior, more and more rely on data to make relevant judgments. The coverage of medical equipment is becoming more and more extensive, and the accuracy of data is constantly improving, and the clinical diagnosis is gradually shifting from qualitative judgment to quantitative analysis. Based on the analysis of electronic medical record data, this article studies and analyzes the risk factors leading to diabetes. By analyzing the characteristic variables, the risk factors significantly related to diabetes are obtained as the input variables of the BP neural network model. For complex problems, machine learning algorithms have higher accuracy and stronger generalization capabilities. Based on the BP artificial neural network model, this paper builds and builds a machine learning simulation to predict diabetes.

Does training in a top-down approach influence recorded goals and treatment plans?

Five stroke rehabilitation teams were supported in the implementation of Cognitive Orientation to daily Occupational Performance (CO-OP) as part of a knowledge translation (KT) project called CO-OP KT. Medical record auditors noted there was occasionally a disconnect between client goals and treatment plans, revealing a need to better understand the characteristics of each and their relationship to each other. This study aimed to examine the characteristics of goals and treatment plans in occupational therapy before and after CO-OP KT. A descriptive secondary analysis of medical record data was employed. Post intervention, there was a change in goal specificity (p = .04) and therapist-client goal alignment (p = .05). Occupation-based goals were often paired with a bottom-up, impairment-based treatment. Top-down treatments, when present, lacked the same detail given to bottom-up plans. CO-OP KT seemed to lead to more specific goals, but matching top-down treatment plans were not found.

Human papillomavirus and oropharyngeal squamous cell carcinoma: a 12-year retrospective review in a New South Wales tertiary referral centre

Background: To compare the epidemiology and survival outcomes of Australian patients with HPV-positive and -negative oropharyngeal squamous cell carcinoma (OPSCC) using a standalone p16 approach. Methods: A retrospective analysis of medical record data was performed for patients presenting with OPSCC to Royal North Shore Hospital in Sydney, Australia from 2005 to 2017. p16 immunohistochemistry (IHC) was used as a biomarker for HPV status. Epidemiological trends and clinicopathological details were compared between the HPV-positive and -negative cohorts. Three-year overall survival rates and the hazard ratio conferred by HPV positivity were calculated. Results: A total of 244 patients were included with 202 (82.8%) having HPV-positive disease. The yearly incidence of HPV-positive OPSCC increased from 2005 to 2016 (P<0.001), driven almost exclusively by HPV-positive disease in me. Those with HPV-positive tumours were more likely to present younger (P=0.005), be male (P=0.008), non-smokers (P<0.001) have a lower T stage (P=0.001) and a higher N stage (P=0.001). HPV-positivity conferred more favourable rates of 3-year overall survival (93.6% vs . 68.9%) and a hazard ratio for death of 0.16 (95% CI, 0.05–0.53, P<0.001). Conclusions: This study corroborates and extends Australian data demonstrating that patients with HPV-positive OPSCC represent a distinct subgroup associated with a significantly better survival.

The Acute Phase Serum Zinc Concentration Is a Reliable Biomarker for Predicting the Functional Outcome After Spinal Cord Injury

Background: Spinal cord injury (SCI) is a devastating disorder for which the accurate prediction of the functional prognosis is urgently needed. Due to the lack of reliable prediction methods, the acute evaluation of SCI severity and therapeutic intervention efficacy is extremely difficult, presenting major obstacles to the development of acute SCI treatment. We herein report a novel method for accurately predicting the functional prognosis using the acute-phase serum zinc concentration after SCI. Methods: We produced experimental animal SCI models with different prognoses and examined the relationship among the SCI severity, functional outcome, and acute-phase serum zinc concentration. We also examined whether we could predict the functional prognosis by evaluating the serum zinc concentration within 72 h after SCI in a human prospective study. Findings: In a mouse model, the acute serum zinc concentrations decreased in proportion to SCI severity and the serum zinc concentrations at 12 h after SCI accurately predicted the functional prognosis. We clarified the mechanism underlying this serum zinc proportional decrease, showing that activated monocytes took up zinc from blood-serum and then infiltrated the lesion area in a severity-dependent manner. A non-linear regression analysis of 38 SCI patients showed that the serum zinc concentrations in the acute-phase accurately predicted the long-term functional outcome (R2=0·84) more accurately than any other previously reported acute-phase biomarkers. Interpretation: The acute-phase serum zinc concentration could be a useful biomarker for predicting the functional prognosis. This simple method will allow for more objective clinical trials and the development of patient-tailored treatment for SCI. Funding Statement: This study was supported by JSPS KAKENHI Grant Number JP18K16680 (K.K.); a Grant-in-Aid for Scientific Research (B) (16H05450) (S.O.); Challenging Exploratory Research from the Ministry of Education, Science, and Sports (16K15668) (S.O.); and research foundations from the general insurance association of Japan (K.K.). Declaration of Interests: The authors have declared that no conflict of interest exists. Ethics Approval Statement: All animal studies were approved by the Committee of Ethics on Animal Experimentation of our institute and conducted in accordance with the National Institutes of Health guidelines for the care and use of animals. All human study involving the analysis of medical record data was conducted according to the principles expressed in the Declaration of Helsinki and was approved by the Institutional Review Board. Informed consent was obtained from each subject.

Factors contributing to hospitalization costs for patients with COPD in China: a retrospective analysis of medical record data.

PurposeHospitalization brings considerable economic pressure on COPD patients in China. A clear understanding of hospitalization costs for patients with COPD is warranted to improve treatment strategies and to control costs. Currently, investigation on factors contributing to hospitalization costs for patients with COPD in China is limited. This study aimed to measure the hospitalization costs of COPD and to determine the contributing factors.Patients and methodsMedical record data from the First Affiliated Hospital of Guangzhou Medical University from January 2016 to December 2016 were used for a retrospective analysis. Patients who were hospitalized with a diagnosis of COPD were included. Patient characteristics, medical treatment, and hospitalization costs were analyzed by descriptive statistics and multivariable regression.ResultsAmong the 1,943 patients included in this study, 87.85% patients were male; the mean (SD) age was 71.15 (9.79) years; 94.49% patients had comorbidities; and 82.30% patients had health insurance. Regarding medical treatment, the mean (SD) length of stay was 9.38 (7.65) days; 11.12% patients underwent surgery; 87.91% used antibiotics; and 4.53% underwent emergency treatment. For hospitalization costs, the mean (SD) of the total costs per COPD patient per admission was 24,372.75 (44,173.87) CNY (3,669.33 [6,650.38] USD), in which Western medicine fee was the biggest contributor (45.53%) followed by diagnosis fee (27.00%) and comprehensive medical fee (12.04%). Regression found that reimbursement (−0.032; 95% CI −0.046 to 0.007), length of stay (0.738; 95% CI 0.832–0.892), comorbidity (0.044; 95% CI 0.029–0.093), surgery (0.145; 95% CI 0.120–0.170), antibiotic use (0.086; 95% CI 0.060–0.107), and emergency treatment (0.121; 95% CI 0.147–0.219) were significantly (P<0.01) associated with total hospitalization costs.ConclusionTo control hospitalization costs for COPD patients in China, the significance of comorbidity, length of stay, antibiotic use, surgery, and emergency treatment suggests the importance of controlling the COPD progression and following clinical guidelines for inpatients. Interventions such as examination of pulmonary function for early detection, quality control of medical treatment, and patient education warrant further investigation.

PDB39 - The Burden of Hypoglycemia in Patients With Insulin-Treated Diabetes Mellitus in China: Analysis of Medical Record Data

PDB39 - The Burden of Hypoglycemia in Patients With Insulin-Treated Diabetes Mellitus in China: Analysis of Medical Record Data

The Relationship Between Patient-Controlled Analgesia and Postcesarean Section Pressure Ulcers: Analysis of Medical Record Data

In this study, we aim to investigate the relationship between patient-controlled analgesia (PCA) and the incidence of pressure ulcer in postcesarean section mothers. A retrospective analysis was performed among consecutive cesarean section mothers in2016. Univariate and multivariate logistic regression was used to analyze the relationship between PCA and postcesarean section pressure ulcers. One thousand nine hundred eighteen cesarean section mothers were included in the study. Forty-five mothers (2.3%; 95% confidence interval [CI], 1.7%-3.1%) developed stage I pressure ulcer. The pressure ulcers were cured in 2 to 5days. Eighty percent (1,535) of mothers received PCA after cesarean section surgery. Pressure ulcer incidence was significantly higher in the PCA group compared with non-PCA groups (2.9% vs 0.0%, Fisher's exact P<.0001). Patient-controlled intravenous analgesia and patient-controlled epidural analgesia showed the same pressure ulcer risk (3.2% vs 2.6%, χ2=0.581, P=.446). After multivariate analysis by logistic regression, the adjusted odds ratio of PCA for pressure ulcer risk was 33.632, with a 95% CI of 25.061 to 45.134. Our results showed PCA was an independent risk factor for pressure ulcer in postcesarean section mothers. Although the pressure ulcers were all rated as stage I and can be cured in 2 to 5days, we still recommended some pressure ulcer prevention strategy should be used for these mothers.

Protocol to describe the analysis of text-based communication in medical records for patients discharged from intensive care to hospital ward

IntroductionEffective communication during hospital transitions of patient care is fundamental to ensuring patient safety and continuity of quality care. This study will describe text-based communication included in patient medical records...

Determining client cognitive status following mild traumatic brain injury

Background People with mild traumatic brain injury (mTBI) commonly experience cognitive impairments. Occupational therapists working in acute general hospitals in Australia routinely access client Glasgow Coma Scale (GCS) scores, and assess cognitive status using standardized tools and by observing basic activity of daily living (ADL) performance. However, limited evidence exists to identify the best assessment(s) to determine client cognitive status. Aim/objectives To determine whether cognitive status assessed by GCS score and the Cognistat are predictive of basic ADL performance among clients with mTBI in an acute general hospital and make inferences concerning the clinical utility of these assessment tools. Material and methods Retrospective analysis of medical record data on demographics, Cognistat, GCS, and modified Barthel Index (MBI) using descriptive statistics, chi-square tests and linear regression. Results Data analysis of 166 participants demonstrated that no associations exist between GCS and Cognistat scores, or Cognistat scores and MBI dependency level. The presence of co-morbid multi-trauma injuries and length of stay were the only variables that significantly predicted MBI dependency level. Conclusion and significance While the MBI scores are of value in identifying clients with difficulty in basic ADLs, Cognistat and GCS scores are of limited use in differentiating client levels of cognitive impairment and the authors caution against the routine administration of the Cognistat following mTBI. Further research is required to identify more suitable assessments for use with a mTBI population.

Incidence of acute allergic reactions to contrast medium following CT examination on the basis of analysis of medical record data – preliminary report

Abstract Introduction. A contrast-enhanced CT examination can have negative health implications. It can spark both allergic and other adverse reactions. Aim. The study aimed at analyzing the incidence of acute allergic reactions to Ultravist 370, used as a contrast medium in a CT examination. Material and methods. The analysis of medical records that comprised 12295 patients who had undergone a CT examination. Women accounted for 50.7% of the study participants. Mean age of the patients was 62 years (min. 15; max. 92, SD=10.123). In the study, 6219 patients were examined without using a contrast medium and 6076 individuals underwent a contrast-enhanced CT examination. In the further analysis, Group 1 comprised of 15 patients from the contrastenhanced CT examination group who confirmed being allergic to a contrast medium after the CT examination and Group 2 comprised 49 persons who had reported being allergic to iodine before the CT examination. Results. 15 patients (8 women and 7 men) developed an allergy to Ultravist 370 (contrast medium). An acute allergic reaction was most likely to happen in two groups of patients: between 31-40 and 51-60 years. Some 12 out of 15 patients had no contraindications for taking an iodine-based contrast medium. The most frequent allergic reactions to Ultravist 370 were rash and urticaria (15 patients). Five patients out of those who experienced adverse reactions reported two symptoms of allergy each while other patients reported one symptom only. Patients with mild symptoms of acute reaction to a contrast medium (15 patients) received pharmacotherapy recommended by a radiologist. Some 13 individuals received Solu-Medrol intravenously and 2 patients received Solu-Medrol intravenously and Fenicort intramuscularly. Conclusions. 1. Using Ultravist 370 in patients is safe, since there is very low risk of adverse side effects caused by the application of this contrast medium. 2. In the present study, age, gender, and risk factors contributed to the development of acute allergic reactions. However, due to the small size of the study group, it is obvious that issues like the incidence of symptoms of discomfort or intolerance of the drug need further research. 3. Owing to the fact that essential biochemical tests had not been performed on a large group of patients, doctors referring patients to a CT examination should take care of their own safety by properly preparing themselves for this procedure. 4. It seems essential to develop and implement regular trainings for CT laboratory staff with reference to the following issues: the incidence and nature of acute adverse reactions to non-ionic contrast medium (Ultravist 370), as well as the procedures for dealing with side effects

关联规则在中医肝病电子病历数据分析中的应用研究

目的：基于关联规则挖掘模型分析中医肝病患者数据，探寻检查指标与中医辩证之间的关联。方法：通过设置最小支持度和最小可信度对中医肝病患者资料进行关联规则分析，根据生成规则的重要性筛选出前后件成正相关的规则，结合提升图评价挖掘结果准确性。结果：分析样本例数317例，共获得30条规则，揭示了检查指标组合与中医辨证结果间的关系。结论：在中医肝病电子病历数据中应用关联规则分析可以揭示不同检查指标对于中医辨证的影响，有利于辅助诊断。 Objective: Based on analysis association rules mining model data for the liver disease of traditional Chinese medicine (TCM), to search for relation between checking index and the Chinese medicine dialectical. Method: By setting the minimum support and minimum confidence, we used association rules to analyze the patients’ data for the liver disease of traditional Chinese medicine. According to the importance of generated rules, we screened out the rules which are positively correlated to the before and after rule, and evaluated the accuracy of the mining results with the lift chart. Result: Through the analysis of 317 samples, 48 rules are received, which reveals the relationship between the check index combination and TCM syndrome differentiation results. Conclusion: Using association rules in electronic medical record data analysis for the liver disease of TCM can reveal the influence of different examination indexes for TCM syndrome differentiation, and is advantageous to the auxiliary diagnosis.

Effectiveness of Palonosetron Versus Other Serotonin 5-HT3 Receptor Antagonists in Triple Antiemetic Regimens During Multiday Highly Emetogenic Chemotherapy

The second-generation serotonin 5-HT(3) receptor antagonist palonosetron has shown improved efficacy in the prevention of both acute and delayed chemotherapy-induced nausea and vomiting (CINV). However, there have been no randomized controlled trials supporting the preferential use of palonosetron in triple antiemetic regimens for patients receiving multiday highly emetogenic chemotherapy (HEC). To compare the effectiveness of palonosetron-based and first-generation 5-HT(3) receptor antagonist-based triple antiemetic regimens in cancer patients receiving multiday HEC. This was a review and analysis of medical record data. A total of 115 patients who had received multiday HEC were included and grouped into a palonosetron-based antiemetic group (n = 73) or a first-generation 5-HT(3) receptor antagonist-based antiemetic group (n = 42). Data on CINV were collected in 24-hour intervals for 120 hours after the start of chemotherapy. Complete response rates did not differ significantly between the 2 groups during any of the 3 phases: acute (0-24 hours), p = 0.877; overlap (24-120 hours), p = 0.997; and overall (0-120 hours), p = 0.723. The proportion of patients with complete control was similar between the groups during each phase: acute, p = 0.862; overlap, p = 0.838; and overall, p = 0.828. There was also no significant difference in other end points between the 2 groups. Among all patients, females experienced significantly more acute nausea (p = 0.040) and vomiting (p = 0.046) than males. Compared with nondrinkers, patients who consumed alcohol had a lower overall incidence of vomiting (p = 0.020). Within a triple antiemetic regimen, a palonosetron-based antiemetic regimen was not significantly different from regimens based on first-generation 5-HT(3) receptor antagonists in preventing CINV during multiday HEC.

Chronic kidney disease in children: A report from a tertiary care center over 11 years.

Chronic kidney disease (CKD) is an overwhelming illness in children. Considering the importance of CKD in pediatric age group, in addition to the racial and ethnic differences in prevalence and etiology of CKD, epidemiologic studies are recommended. The majority of the results regarding the incidence of CKD have been achieved from studies on hospitalized children. This study evaluates the incidence and etiology of chronic renal failure (CRF) in children in a tertiary care center in Isfahan, the second large province of Iran. A retrospective analysis of medical record data of children less than 19 years old, hospitalized for CKD at St Alzahra hospital, Isfahan, Iran, during the period of November 2001 until December 2011 was made. A total of 268 eligible cases were recruited. Patients were categorized into 5 groups according to glomerular filtration rate (GFR) and KDOQI guideline. Out of 268 patients, 144 patients were male (54%). The mean and median of age was 11.01± 0.39(SD) years and 12.5 years, respectively. Approximately 55% of patients had either systolic and/or diastolic hypertension. The most frequent etiology of CKD was glomerular diseases (34%) followed by reflux nephropathy (16.7%). Most patients (74.8%) had GFR less than 15 ml/min/m², when diagnosed. Anemia was the most prevalent laboratory abnormality (85%). Small-size kidneys were seen in 65.8% of patients. Kidney replacement therapy (either hemo- or peritoneal dialysis) was applied for 72.3% of the patients. The transplantation rate average was 7.2 per million children population. The annual incidences of CKD (mostly advanced stages) were 5.52 per million population (PMP) and 16.8 per million children population, respectively. The all cause of mortality rate was 18.4%. Younger age was the only independent predictor of mortality (p=0.005). We concluded that glomerular diseases are the leading cause of CKD in our patients. In addition, the annual incidence of CKD is considerably high.