scholarly journals Diagnosis and Treatment Rules of Chronic Kidney Disease and Nursing Intervention Models of Related Mental Diseases Using Electronic Medical Records and Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yanli Wang ◽  
Yueyao Sun ◽  
Na Lu ◽  
Xuan Feng ◽  
Minglong Gao ◽  
...  
Keyword(s):  
Data Mining ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Nursing Intervention ◽  
Diagnosis And Treatment ◽  
Mining Technology ◽  
Intervention Models ◽  
Target Behaviour

Objective. On the basis of electronic medical records, the data mining technology was adopted to explore the law of chronic kidney disease (CKD) and the intervention mode of mental health of patients. Methods. Based on the electronic medical records, the corresponding data extraction, database establishment, and data cleaning of CKD were performed. After that, the related data analysis, frequency analysis, cluster analysis, and nonparametric analysis were used to explore the laws of CKD diagnosis and treatment and nursing intervention mode of mental illness. The most common causes of CKD were chronic glomerulonephritis (43.76%), aristolochic acid nephritis (16.34%), diabetic nephritis (12.87%), and hypertensive nephritis (11.58%). The major treatment method for end-stage patients was alternative therapies, accounting for 46%. Compared with the depression score before intervention, that of the patients after the mindfulness therapy (50.99 ± 9.77 vs. 47.01 ± 9.33, P = 0.024 < 0.5 ) and target behaviour nursing intervention (52.21 ± 8.12 vs. 48.01 ± 9.33, P = 0.032 < 0.05 ) was obviously decreased. Conclusion. The data mining technology based on electronic records showed a good application prospect in the analysis of the diagnosis and treatment of CKD; and target behaviour nursing and mindfulness intervention were effective psychological intervention models.

scholarly journals Prevalence of APOL1 Risk Variants in Afro-Descendant Patients with Chronic Kidney Disease in a Latin American Country

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Carlos E. Duran ◽  
Alejandro Ramírez ◽  
Juan G. Posada ◽  
Johanna Schweineberg ◽  
Liliana Mesa ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Electronic Medical Records ◽  
Latin American ◽  
Medical Records ◽  
Cross Sectional Study ◽  
University Hospital ◽  
Cross Sectional ◽  
Risk Variants ◽  
Different Levels

Introduction. In Colombia, the genetic background of the populations was shaped by different levels of admixture between Natives, European, and Africans. Approximately 35.363 patients have diagnosed chronic kidney disease and according to population studies, 10.4% of these patients are Afro-descendant. We aim to assess the frequency of APOL1 variants G1 and G2 in Afro-descendant patients with ESRD treated at la Fundacion Valle del Lili University Hospital in Cali, Colombia. Methods. This is an observational cross-sectional study. Afro-descendant patients with ESRD in waitlist or recipients of kidney transplant were evaluated. Clinical data were collected from the electronic medical records. Genotyping was carried out by amplification of the exon 7 of the APOL1 gene. For the identification of risk genotypes, the bioinformatics tool BLAST was used. Results. We enrolled 102 participants. The frequency of APOL1 risk variants was 67.2%, in which 24.5% (n = 25) were G1 heterozygous and 5.8% (n = 6) were G2 heterozygous and 37% of the patients had high-risk status with two alleles in homozygous (G1/G1 = 21 and G2/G2 = 3) or compound heterozygote (G1/G2 = 14) form.

A rare case of primary hyperaldosteronism associated with chronic kidney disease-difficulties in diagnosis and treatment

2019 ◽  
Author(s):  
Letiţia Leuştean ◽  
Ginuţa Marcela Bălineanu ◽  
Cosmina Rimbu ◽  
Anamaria Hrişcă ◽  
Voroneanu Elena Luminiţa ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Rare Case ◽  
Primary Hyperaldosteronism ◽  
Diagnosis And Treatment

scholarly journals Gambaran Pasien yang Menjalani Prosedur Bedah Emergensi di RSUP Prof. Dr. R. D. Kandou Manado Periode Januari - September 2019

e-CliniC ◽  
2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Utrecht Suleman ◽  
Angelica M. J. Wagiu ◽  
Stephanus J. Ch. Tangel
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Surgical Procedures ◽  
Emergency Surgery ◽  
Medical Records ◽  
Health Centers ◽  
Surgical Patients ◽  
Age Group ◽  
Adult Age ◽  
Epidural Hemorrhage

Abstract: Emergency surgery is performed to avoid further complications of the disease or to save the patient's life. Albeit, there are lack of data in various health centers in Indonesia regarding the evaluation of emergency surgical patients, This study was aimed to obtain the profile of patients undergoing emergency surgical procedures in the Emergency Department of Surgery at Prof. Dr. R. D. Kandou Hospital Manado from January to September 2019. This was a retrospective and descriptive study using patients’ medical records. The results showed that there were 540 patients in this study. Most of the patients were adult age group (18-59 years) as many as 343 patients (63.5%), males 366 patients (67.8%), and non-traumatic cases 436 patients (80.4%). The most common cases of trauma was epidural hemorrhage as many as 23 patients (4.3%) meanwhile the most common non-traumatic cases was chronic kidney disease as many as 122 patients (22.6%). According to the type of surgery, CDL insertion and laparotomy were performed on 131 patients each (24.3%). In conclusion, most patients undergoing emergency surgical procedures were 18-59 years old, males, and non-traumatic cases.Keywords: emergency surgery, traumatic cases, non-traumatic cases Abstrak: Bedah emergensi dilakukan dalam keadaan sangat darurat untuk menghindari komplikasi lanjut dari proses penyakit atau untuk menyelamatkan jiwa pasien. Data mengenai pasien bedah emergensi di berbagai pusat kesehatan di Indonesia masih sangat kurang. Penelitian ini bertujuan untuk mendapatkan gambaran pasien yang menjalani prosedur bedah emergensi di IGD Bedah RSUP Prof. Dr. R. D. Kandou Manado periode Januari sampai September 2019. Jenis penelitian ialah deskriptif retrospektif, menggunakan data rekam medik pasien. Hasil penelitian menunjukkan bahwa dari 540 pasien, didapatkan pasien terbanyak dari golongan usia dewasa (18-59 tahun) yaitu 343 pasien (63,5%), jenis kelamin laki-laki 366 pasien (67,8%), dan kasus non-trauma 436 pasien (80,4%). Kasus trauma terbanyak yaitu epidural hemorrhage pada 23 pasien (4,3%) sedangkan kasus non trauma terbanyak chronic kidney disease pada 122 pasien (22,6%). Menurut jenis tindakan operasi yang terbanyak ialah insersi CDL dan laparotomy, masing-masing 131 pasien (24,3%). Simpulan penelitian ini ialah pasien yang menjalani prosedur bedah emergensi terbanyak ialah usia 18-59 tahun, jenis kelamin laki-laki, dan jenis kasus non-trauma.Kata kunci: bedah emergensi, kasus trauma, kasus non-trauma

scholarly journals Gambaran Anemia pada Subjek Penyakit Ginjal Kronik Stadium 4 dan 5 di Poliklinik Ginjal-Hipertensi RSUP Prof. Dr. R. D. Kandou

e-CliniC ◽  
2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Yordhan Tamsil ◽  
Emma Sy. Moeis ◽  
Frans Wantania
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Medical Records ◽  
Iron Status ◽  
Descriptive Study ◽  
Transfusion Therapy ◽  
Female Age ◽  
Stage 4 ◽  
Almost All ◽  
Age Range

Abstract: Anemia is a complication of chronic kidney disease (CKD) that often occurs. Moreover, it can occur earlier than other complications of CKD in almost all patients with late stage kidney disease. This study was aimed to obtain the profile of anemia in subjects with stage 4 and 5 of chronic kidney disease. This was a retrospective and descriptive study using medical records of patients with CKD associated with anemia for two years. The results showed that of 428 CKD patients, 131 suffered from anemia (30.60%). The majority of patients were female (54.19%), age range 60-69 years (44.27%), non-dialysis stage 5 of CKD patients (74.04%), had sufficient iron status (79.38%). However, 15,26% of the 131 patients got blood transfusion therapy. In conclusion, the majority of CKD patients were stage 5 ND, female, age range of 60-69 years, had sufficient iron status, and were not treated with blood transfusion.Keywords: chronic kidney disease, anemia Abstrak: Anemia merupakan komplikasi penyakit ginjal kronik (PGK) yang sering terjadi, bahkan dapat terjadi lebih awal dibandingkan komplikasi PGK lainnya dan hampir pada semua pasien penyakit ginjal tahap akhir. Penelitian ini bertujuan untuk mengetahui gambaran anemia pada subyek penyakit ginjal kronik stadium 4 dan 5 di Poliklinik Ginjal-Hipertensi RSUP Prof. Dr. R. D. Kandou. Jenis penelitian ialah metode deskriptif retroskpektif dengan mengunakan data rekam medik pasien PGK dengan anemia selama dua tahun. Hasil penelitian memperlihatkan dari 428 pasien PGK didapatkan 131 pasien dengan anemia pada PGK (30,60%). Mayoritas pasien ialah jenis kelamin perempuan (54,19%), usia 60-69 tahun (44,27%), dan PGK derajat 5 non-dialisis (74,04%), memiliki status besi cukup (79,38%). Terdapat 15,26% dari pasien yang mendapatkan terapi transfusi darah. Simpulan penelitian ini ialah pasien terbanyak dengan derajat 5 ND, jenis kelamin perempuan, rentang usia 60-69 tahun, dengan status besi cukup, dan tidak mendapat terapi transfusi darah.Kata kunci: penyakit ginjal kronik, anemia

Transformer + GAN based Traditional Chinese Medicine inpatient prescription recommendation (Preprint)

2021 ◽  
Author(s):  
Hong Zhang
Keyword(s):  
Decision Making ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Electronic Medical Records ◽  
Clinical Diagnosis ◽  
Medical Records ◽  
Training Data ◽  
Diagnosis And Treatment ◽  
Test Results ◽  
Treatment Scheme

BACKGROUND Clinical diagnosis and treatment decision making support is at the core of medical artificial intelligent research, in which Traditional Chinese Medicine (TCM) decision making is an important part. Traditional Chinese Medicine is a traditional medical system originated from China, of which the main clinical model is to conduct individualized diagnosis and treatment by relying on the four-diagnosis information. One of the key tasks of the TCM artificial intelligence research is to develop techniques and methods of clinical prescription decision making which takes all the relevant information of a patient as input, and produces a diagnosis and treatment scheme as output. Given the complexity of TCM clinical diagnosis and treatment schemes, decision making support of clinical diagnosis and treatment schemes remains as a research challenge for lacking of an effective solution. Fortunately, as the volume of the massive clinical data in the form of electronic medical records increases rapidly, it becomes possible for the computer to produce personalized diagnosis and treatment scheme recommendation through machine learning on the basis of the clinical big data. OBJECTIVE The objective of this research is to develop a real-time diagnosis and treatment scheme recommendation model for TCM inpatients. This is accomplished by using historical clinical medical records as training data to train a Transformer network. Furthermore, to alleviate the issue of overfitting, a Generative Adversarial Network is used to generate noise-added samples from the original training data. These noise-added samples along with the original samples form the complete train data set. METHODS valid information, such as the patient’s current sickness situation, medicines taken, nursing care given, vital signs, examinations and test results, is extracted from the patient’s electronic medical records, then the obtained information is sorted chronically, to produce a sequence of data of each patient. These time-sequence data is then used as input to the Transformer network. The output of the network would be the prescription information a physician would give. Overfitting is a common problem in machine learning, and becomes especially server when the network is complex with insufficient training data. In this research, a Generative Adversarial Network, is used to double the number of training samples by producing noise-added samples from the original samples. This, to a great extent, lessens the overfitting problem. RESULTS A total of 21,295 copies of inpatient electronic medical records from Guang’anmen traditional Chinese medicine hospital was used in this research. These records were created between January 2017 and December 2018, covering a total of 6352 kinds of medicines. These medicines were sorted into 829 types of first category medicines based on the class relationships among medicines. As shown by the test results, the performance of a fully trained Transformer model can have an average precision rate of 80.58%，and an average recall rate of 68.49%. CONCLUSIONS As shown by the preliminary test results, the Transformer-based TCM prescription recommendation model outperforms the existing conventional methods. The extra training samples generated by the GAN network helps to overcome the overfitting issue, leading a further improved recall rate and precision rate.

Early Prediction of Chronic Kidney Disease Using Data Mining Techniques

2021 ◽  
pp. 947-957
Author(s):  
Hasin Shahed Shad ◽  
Zeeshan Jamal ◽  
S. M. Foysal Ahmed ◽  
Sifat Momen ◽  
Nafees Mansoor
Keyword(s):  
Data Mining ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Early Prediction ◽  
Data Mining Techniques ◽  
Using Data
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