Serum Creatinine Reference Limits in Pediatric Population-A Single Center Electronic Health Record-Based Database in Taiwan.
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ABSTRACT:
SUBMITTER: Chuang GT
PROVIDER: S-EPMC8756578 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Accurate assessment of kidney function in children requires age and gender-specific reference ranges for serum creatinine. Traditional reference values, often derived from adult populations and different ethnic backgrounds, may not be suitable for children. This study aims to establish specific reference ranges for serum creatinine in the Thai pediatric population, addressing the gap in localized and age-appropriate diagnostic criteria. This retrospective study analyzed serum creatinine levels from Thai children aged newborn to 18 years, collected from the Laboratory Information System of the Queen Sirikit National Institute of Child Health from January 2017 to December 2021. The Bhattacharya method was employed to establish reference ranges, considering different age groups and genders. The study compared these newly established reference values with international studies, including those of Schlebusch H., Pottel H., and Chuang GT., to validate their relevance and accuracy. A total of 27,642 data entries (15,396 males and 12,246 females) were analyzed. The study established distinct reference ranges for serum creatinine, which varied significantly across different age groups and between genders. These ranges were found to gradually increase with age from 2 months to 18 years. The study also highlighted notable differences in reference values when compared with other ethnic populations. The study successfully establishes tailored reference ranges for serum creatinine in Thai children, providing a valuable tool for more accurate diagnosis and monitoring of kidney health in this demographic. This initiative marks a significant advancement in pediatric nephrology in Thailand and suggests a need for continuous refinement of these ranges and further research in this area.
| S-EPMC10931469 | biostudies-literature
Project description:BackgroundCurrent definitions of AKI do not take into account serum creatinine's high variability in children.MethodsWe analyzed data from 156,075 hospitalized children with at least two creatinine tests within 30 days. We estimated reference change value (RCV) of creatinine on the basis of age and initial creatinine level in children without kidney disease or known AKI risk, and we used these data to develop a model for detecting pediatric AKI on the basis of RCV of creatinine. We defined pediatric AKI according to pediatric reference change value optimized for AKI in children (pROCK) as creatinine increase beyond RCV of creatinine, which was estimated as the greater of 20 ?mol/L or 30% of the initial creatinine level.ResultsOf 102,817 children with at least two serum creatinine tests within 7 days, 5432 (5.3%) had AKI as defined by pROCK compared with 15,647 (15.2%) and 10,446 (10.2%) as defined by pediatric RIFLE (pRIFLE) and Kidney Disease Improving Global Outcomes (KDIGO), respectively. Children with pROCK-defined AKI had significantly increased risk of death (hazard ratio, 3.56; 95% confidence interval, 3.15 to 4.04) compared with those without AKI. About 66% of patients with pRIFLE-defined AKI and 51% of patients with KDIGO-defined AKI, mostly children with initial creatinine level of <30 ?mol/L, were reclassified as non-AKI by pROCK, and mortality risk in these children was comparable with risk in those without AKI by all definitions.ConclusionspROCK criterion improves detection of "true" AKI in children compared with earlier definitions that may lead to pediatric AKI overdiagnosis.
| S-EPMC6115652 | biostudies-literature
Project description:BackgroundThe effectiveness of weight loss therapies is commonly measured using body mass index and other obesity-related variables. Although these data are often stored in electronic health records (EHRs) and potentially very accessible, few studies on obesity and weight loss have used data derived from EHRs. We developed processes for obtaining data from the EHR in order to construct a database on patients undergoing Roux-en-Y gastric bypass (RYGB) surgery.MethodsClinical data obtained as part of standard of care in a bariatric surgery program at an integrated health delivery system were extracted from the EHR and deposited into a data warehouse. Data files were extracted, cleaned, and stored in research datasets. To illustrate the utility of the data, Kaplan-Meier analysis was used to estimate length of post-operative follow-up.ResultsDemographic, laboratory, medication, co-morbidity, and survey data were obtained from 2028 patients who had undergone RYGB at the same institution since 2004. Pre-and post-operative diagnostic and prescribing information were available on all patients, while survey laboratory data were available on a majority of patients. The number of patients with post-operative laboratory test results varied by test. Based on Kaplan-Meier estimates, over 74% of patients had post-operative weight data available at 4 years.ConclusionA variety of EHR-derived data related to obesity can be efficiently obtained and used to study important outcomes following RYGB.
| S-EPMC3508953 | biostudies-literature
Project description:To characterize patterns of electronic medical record (EMR) use at pediatric primary care acute visits.Direct observational study of 529 acute visits with 27 experienced pediatric clinician users.For each 20 s interval and at each stage of the visit according to the Davis Observation Code, we recorded whether the physician was communicating with the family only, using the computer while communicating, or using the computer without communication. Regression models assessed the impact of clinician, patient and visit characteristics on overall visit length, time spent interacting with families, and time spent using the computer while interacting.The mean overall visit length was 11:30 (min:sec) with 9:06 spent in the exam room. Clinicians used the EMR during 27% of exam room time and at all stages of the visit (interacting, chatting, and building rapport; history taking; formulation of the diagnosis and treatment plan; and discussing prevention) except the physical exam. Communication with the family accompanied 70% of EMR use. In regression models, computer documentation outside the exam room was associated with visits that were 11% longer (p=0.001), and female clinicians spent more time using the computer while communicating (p=0.003).The 12 study practices shared one EMR.Among pediatric clinicians with EMR experience, conversation accompanies most EMR use. Our results suggest that efforts to improve EMR usability and clinician EMR training should focus on use in the context of doctor-patient communication. Further study of the impact of documentation inside versus outside the exam room on productivity is warranted.
| S-EPMC3005866 | biostudies-other
Project description:Electronic health records (EHRs) have given rise to large and complex databases of medical information that have the potential to become powerful tools for clinical research. However, differences in coding systems and the detail and accuracy of the information within EHRs can vary across institutions. This makes it challenging to identify subpopulations of patients and limits the widespread use of multi-institutional databases. In this study, we leveraged machine learning to identify patterns in medication usage among hospitalized pediatric patients receiving renal replacement therapy and created a predictive model that successfully differentiated between intermittent (iHD) and continuous renal replacement therapy (CRRT) hemodialysis patients. We trained six machine learning algorithms (logistical regression, Naïve Bayes, k-nearest neighbor, support vector machine, random forest, and gradient boosted trees) using patient records from a multi-center database (n = 533) and prescribed medication ingredients (n = 228) as features to discriminate between the two hemodialysis types. Predictive skill was assessed using a 5-fold cross-validation, and the algorithms showed a range of performance from 0.7 balanced accuracy (logistical regression) to 0.86 (random forest). The two best performing models were further tested using an independent single-center dataset and achieved 84-87% balanced accuracy. This model overcomes issues inherent within large databases and will allow us to utilize and combine historical records, significantly increasing population size and diversity within both iHD and CRRT populations for future clinical studies. Our work demonstrates the utility of using medications alone to accurately differentiate subpopulations of patients in large datasets, allowing codes to be transferred between different coding systems. This framework has the potential to be used to distinguish other subpopulations of patients where discriminatory ICD codes are not available, permitting more detailed insights and new lines of research.
| S-EPMC9674326 | biostudies-literature
Project description:BackgroundSerum cystatin C (SCysC) and serum creatinine (SCr) are two biomarkers used in common practice to estimate the glomerular filtration rate (GFR). For SCysC and SCr to be used in a given population, normal values need to be determined to better assess patients. This study aimed to determine SCysC and SCr reference intervals (RIs) in a Cameroonian adult population and factors susceptible of influencing them.MethodsWe carried-out a cross-sectional study from November 2016 to May 2017 in Yaoundé, Cameroon. Participants were Cameroonians aged 18 years and above, residing inside the country and found in good health at study inclusion. SCysC and SCr were determined by particle-enhanced turbidimetric immunoassay standardized against the ERM-DA471/IFCC reference material and by the IDMS reference modified Jaffe kinetic method, respectively. RIs were determined using the 2.5th and 97.5th percentiles and their respective 90% confidence intervals (CIs). The quantile regression served to identify potential factors likely influencing SCysC and SCr values.ResultsWe included 381 subjects comprising 49.1% females.. RIs for SCysC varied between 0.57 (90%CI: 0.50-0.60) and 1.03 mg/L (90%CI: 1.00-1.10) for females, and from 0.70 (90%CI: 0.60-0.70) to 1.10 mg/L (90%CI: 1.10-1.20) for males. Concerning SCr, its RIs ranged from 0.58 (90%CI: 0.54-0.61) to 1.08 mg/dL (90%CI: 1.02-1.21) for females, and from 0.74 (90%CI: 0.70-0.80) to 1.36 mg/dL (90%CI: 1.30-1.45) for males. Men had significantly higher SCysC and SCr values than women (p < 0.001). Likewise, subjects aged 50 years and above had higher SCysC values in comparison to younger age groups (p < 0.001), which was not the case for SCr values (p = 0.491). Moreover, there was a positive and significant correlation between SCysC and SCr in women (ρ = 0.55, p < 0.001), in men (ρ = 0.39, p < 0.001) and globally (ρ = 0.58; p < 0.001). Furthermore, the sex influenced both biomarkers' values across all quantile regression models while age and body surface area (BSA) influenced them inconsistently.ConclusionThis study has determined serum cystatin C and serum creatinine reference intervals in an adult Cameroonian population, whose interpretations might take into account the patient's sex and to a certain extent, his/her age and/or BSA.
| S-EPMC6423796 | biostudies-literature
Project description:Usability testing is increasingly being recognized as a way to increase the usability and safety of health information technology (HIT). Medical simulation centers can serve as testing environments for HIT usability studies. We integrated the quality assurance version of our emergency department (ED) electronic health record (EHR) into our medical simulation center and piloted a clinical care scenario in which emergency medicine resident physicians evaluated a simulated ED patient and documented electronically using the ED EHR. Meticulous planning and close collaboration with expert simulation staff was important for designing test scenarios, pilot testing, and running the sessions. Similarly, working with information systems teams was important for integration of the EHR. Electronic tools are needed to facilitate entry of fictitious clinical results while the simulation scenario is unfolding. EHRs can be successfully integrated into existing simulation centers, which may provide realistic environments for usability testing, training, and evaluation of human-computer interactions.
| S-EPMC3994869 | biostudies-other
Project description:Excess thyroid hormones have complex metabolic effects, particularly hyperthyroidism, and are associated with various cardiovascular risk factors. Previous candidate gene studies have indicated that genetic variants may contribute to this variable response. Electronic medical record (EMR) biobanks containing clinical and genomic data on large numbers of individuals have great potential to inform the disease comorbidity development. In this study, we combined electronic medical record (EMR) -derived phenotypes and genotype information to conduct a genome-wide analysis of hyperthyroidism in a 35,009-patient cohort in Taiwan. Diagnostic codes were used to identify 2,767 patients with hyperthyroidism. Our genome-wide association study (GWAS) identified 44 novel genomic risk markers in 10 loci on chromosomes 2, 6, and 14 (P < 5 × 10-14), including CTLA4, HCP5, HLA-B, POU5F1, CCHCR1, HLA-DRA, HLA-DRB9, TSHR, RPL17P3, and CEP128. We further conducted a comorbidity analysis of our results, and the data revealed a strong correlation between hyperthyroidism patients with thyroid storm and stroke. In this study, we demonstrated application of the PheWAS using large EMR biobanks to inform the comorbidity development in hyperthyroidism patients. Our data suggest significant common genetic risk factors in patients with hyperthyroidism. Additionally, our results show that sex, body mass index (BMI), and thyroid storm are associated with an increased risk of stroke in subjects with hyperthyroidism.
| S-EPMC9390483 | biostudies-literature
Project description:TK6 cells were exposed to various perturbations and then the transcriptome profiles were collected at 4 hours to assemble a reference database to generate a Genotoxic / Nongenotoxic classifier using the nearest shrunken centroids method.
2015-05-01 | GSE58431 | GEO
Project description:Electronic health records (EHRs) can provide insights into diagnoses, treatment patterns, and clinical outcomes. Acquired hemophilia (AH) is an ultrarare bleeding disorder characterized by factor VIII inhibiting autoantibodies.To identify patients with AH using an EHR database.Records were accessed from a large EHR database (Humedica) between January 1, 2007 and July 31, 2013. Broad selection criteria were applied using the International Classification of Diseases, Ninth Revision, clinical modification (ICD-9-CM) code for intrinsic circulating anticoagulants (286.5 and all subcodes) and confirmation of records 6 months before and 12 months after the first diagnosis. Additional selection criteria included mention of "bleeding" within physician notes identified via natural language processing output and a normal prothrombin time and prolonged activated partial thromboplastin time.Of 6,348 patients with a diagnosis code of 286.5 or any subcodes, 16 males and 15 females met the selection criteria. The most common bleeding locations reported was gastrointestinal (23%), vaginal (16%), and endocrine (13%). A wide range of comorbidities was reported. Natural language processing identified chart note mention of "hemophilia" in 3 patients (10%), "bruise" in 15 patients (48%), and "pain" in all 31 patients. No patients received a prescription for approved/recommended AH treatments. Four patient cases were reviewed to validate whether the identified cohort had AH; each patient had bleeding symptoms and a normal prothrombin time and prolonged activated partial thromboplastin time, although none received hemostatic treatments.In ultrarare disorders, ICD-9-CM coding alone may be insufficient to identify patient cohorts; multimodal analysis combined with in-depth reviews of physician notes may be more effective.
| S-EPMC5529096 | biostudies-other