Browsing by Author "Topcu, Deniz Ilhan"

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ANALYSIS OF INTRA-PATIENT VARIABILITY OF TACROLIMUS IN TRANSPLANT PATIENTS WITH DATA MINING
(2020) Topcu, Deniz Ilhan; Turgut, Didem; Celebi, Zeynep Kendi; Haberal, Mehmet A.
Detection of COVID-19 by Machine Learning Using Routine Laboratory Tests
(2021) Cubukcu, Hikmet Can; Topcu, Deniz Ilhan; Bayraktar, Nilufer; Gulsen, Murat; Sari, Nuran; Arslan, Ayse Hande; 0000-0002-1219-6368; 0000-0002-7886-3688; 34791032; E-3717-2019; Y-8758-2018
Objectives The present study aimed to develop a clinical decision support tool to assist coronavirus disease 2019 (COVID-19) diagnoses with machine learning (ML) models using routine laboratory test results. Methods We developed ML models using laboratory data (n = 1,391) composed of six clinical chemistry (CC) results, 14 CBC parameter results, and results of a severe acute respiratory syndrome coronavirus 2 real-time reverse transcription-polymerase chain reaction as a gold standard method. Four ML algorithms, including random forest (RF), gradient boosting (XGBoost), support vector machine (SVM), and logistic regression, were used to build eight ML models using CBC and a combination of CC and CBC parameters. Performance evaluation was conducted on the test data set and external validation data set from Brazil. Results The accuracy values of all models ranged from 74% to 91%. The RF model trained from CC and CBC analytes showed the best performance on the present study's data set (accuracy, 85.3%; sensitivity, 79.6%; specificity, 91.2%). The RF model trained from only CBC parameters detected COVID-19 cases with 82.8% accuracy. The best performance on the external validation data set belonged to the SVM model trained from CC and CBC parameters (accuracy, 91.18%; sensitivity, 100%; specificity, 84.21%). Conclusions ML models presented in this study can be used as clinical decision support tools to contribute to physicians' clinical judgment for COVID-19 diagnoses.
Developing Data-Centric Clinical Laboratory Workflow Through the Use of Open-Source Tools
(2023) Topcu, Deniz Ilhan; https://orcid.org/0000-0002-1219-6368; 36610422; E-3717-2019
The effect of jet-lag on serum concentrations of thyroid stimulating hormone and prolactin: A case report
(2020) Gungoren, Merve Sibel; Topcu, Deniz Ilhan; Zungun, Cevdet; 0000-0002-1219-6368; 32063733; E-3717-2019
Introduction: This case report is about the importance of sleeping status for analysis of thyroid hormone stimulating hormone (TSH) and prolactin (PRL) which arose from discordant results of a patient who was referred for serum TSH and PRL testing within 12-hour period after an intercontinental flight. Case description: An adult male patient was admitted to our laboratory for serum TSH and PRL tests and came back questioning the accuracy of his previous results. Further investigations: A new analysis with a new sample was offered. His new results were not consistent with his previous results. What happened: It was revealed that the night before the first sampling, he travelled back to Turkey from The United States of America and came to testing within 12 hours after the arrival. Discussion: Sleeping status is one of the factors that can affect laboratory results. Intercontinental flights causing jet-lag can alter the secretions of TSH and PRL which are predominantly modulated by thyrotropin-releasing hormone (TRH). Main lesson: Travel history and sleeping status are important factors to be evaluated prior sampling for hormone analysis. Patients must be informed about the importance of sampling timing.
Effect of rosuvastatin on spatial learning, memory, and anxiety-like behaviour in ovariectomized rats
(2022) Emre-Aydingoz, Selda; Lux, Karl Michael; Efe, Oguzhan Ekin; Topcu, Deniz Ilhan; Erdem, Saban Remzi; 0000-0001-7823-7620; 0000-0002-3243-7843; 0000-0002-1219-6368; 35993621; ABA-4291-2020; W-7908-2019; E-3717-2019
The effect of rosuvastatin (Ros) on cognitive function and anxiety-like behaviour in ovariectomized rats were evaluated. Eighteen female Wistar rats (218-310g, 6-8 months old) were allocated into sham (n = 6), ovariectomy (Ovx, n = 6) or Ovx + Ros (up to eighth week n = 6, then n = 4) groups. Ros was administered at 20 mg/kg/day by oral gavage for 12 weeks. Behavioural tests were performed at 4, 8 and 12 weeks following Ovx. At 12weeks, Ovx group had significantly longer escape latency than the sham group at the first day of the four-day training period of the Morris Water Maze test (p < .01). In the Elevated Plus Maze test, Ovx group spent significantly more time in the closed arms than the sham group (p < .01), and this anxiety-like behavioural effect of Ovx was prevented by 12-weeks Ros treatment (p < .05). In conclusion, Ros prevents memory deficit and anxiety-like behaviour in the ovariectomized rats, a model for human surgical menopause.
The Impact of Serum 25-Hydroxyvitamin D3 Levels on Allergic Rhinitis
(2019) Coban, Kubra; Oz, Isilay; Topcu, Deniz Ilhan; Aydin, Erdinc; 0000-0002-1219-6368; 31569970; E-3717-2019
We aimed to clarify the relation between allergic rhinitis and the serum levels of 25-hydroxivitamin D in the adult population. The study group consisted of 86 patients with allergic rhinitis who were diagnosed with the help of history of allergy, positive signs for allergy, blood samples, and positive skin prick tests; while the control group included 43 age- and sex-matched healthy volunteers with negative skin prick tests. The demographic data, medical history, findings in the physical examinations, serum levels of total immunoglobulin E (IgE) and 25-hydroxyvitamin D, and skin prick test results of the groups were noted. A total of 129 patients fulfilling the necessary criteria were enrolled. The median serum 25-hydroxyvitamin D levels in the study group were significantly lower compared to the control group (P= .014). In the study group, median serum vitamin D levels were significantly higher in men, compared to women (P= .03). There was a significant negative correlation between IgE and vitamin D levels in the allergic rhinitis group (P= .028,r= -0.246). This study showed that patients with allergic rhinitis might be more vulnerable to have lower serum levels of vitamin D. Thus, vitamin D supplementation as an adjunctive therapy may be considered in those patients.
INTRA-PATIENT TACROLIMUS LEVEL VARIABILITY IN BK VIRUS ASSOCIATED NEPHROPATHY
(2020) Turgut, Didem; Topcu, Deniz Ilhan; Erdogmus, Siyar; Ozdemir, F. Nurhan; Kirnap, Mahir; Haberal, Mehmet A.
A Model to Establish Autoverification in the Clinical Laboratory
(2021) Topcu, Deniz Ilhan; Gulbahar, Ozlem; 0000-0002-1219-6368; 33831387; E-3717-2019
Objectives: Autoverification is the process of evaluating and validating laboratory results using predefined computer-based algorithms without human interaction. By using autoverification, all reports are validated according to the standard evaluation criteria with predefined rules, and the number of reports per laboratory specialist is reduced. However, creating and validating these rules are the most demanding steps for setting up an autoverification system. In this study, we aimed to develop a model for helping users establish autoverification rules and evaluate their validity and performance. Design & methods: The proposed model was established by analyzing white papers, previous study results, and national/international guidelines. An autoverification software (myODS) was developed to create rules according to the model and to evaluate the rules and autoverification rates. The simulation results that were produced by the software were used to demonstrate that the determined framework works as expected. Both autoverification rates and step-based evaluations were performed using actual patient results. Two algorithms defined according to delta check usage (Algorithm A and B) and three review limits were used for the evaluation. Results: Six hundred seventeen rules were created according to the proposed model. 1,976 simulation results were created for validation. Our results showed that manual review limits are the most critical step in determining the autoverification rate, and delta check evaluation is especially important for evaluating inpatients. Algorithm B, which includes consecutive delta check evaluation, had higher AV rates. Conclusions: Systemic rule formation is a critical factor for successful AV. Our proposed model can help laboratories establish and evaluate autoverification systems. Rules created according to this model could be used as a starting point for different test groups.
Optimization Of Patient-Based Real-Time Quality Control Based On The Youden Index
(2022) Topcu, Deniz Ilhan; Cubukcu, Hikmet Can; 35810801
Aim: This study sets out to investigate the utility of exponentially weighted moving average (EWMA) as patient-based real-time quality control (PBRTQC) by conducting a simulation study and subsequent real-patient data implementation to determine optimal EWMA features (weighting factors, control limits, and truncation methods) based on the Youden index. Methods: A simulation experiment was conducted in the first stage to investigate optimal EWMA features for the tests, including aspartate aminotransferase, blood urea nitrogen, and glucose, calcium, creatinine, potassium, sodium, triglycerides, thyroid - stimulating hormone (TSH), and vitamin B12 tests. In the second stage of the study, EWMA was applied to real patient data to elucidate practical utility and achieve final optimal EWMA features. Different degrees of systematic errors (SE) including total allowable error (TEa) as a maximum error level were added to both simulation and patient results, and then the EWMA performance was assessed for different EWMA features. We calculated Youden's index for each combination of EWMA features to find their optimal features to achieve minimum false positive rate (FPR) and maximum error detection rate at the SE level corresponding to TEa. Results: EWMA implementation on real patient data revealed optimal EWMA features for each test. FPR values of creatinine and glucose were 18.48% and 10.17%, respectively, which exceeded the acceptable criteria for FPR (10%). The remaining six analytes showed acceptable FPR. Conclusions: We showed the implementation of EWMA as PBRTQC, and optimization of its features based on the Youden index by conducting extensive performance evaluations and simulations in this study.
Peri-Implant Crevicular Fluid And Serum Levels Of Soluble ST2 In Peri-Implant Diseases: A Pilot Study
(2023) Ozgur, Engin; Topcu, Deniz Ilhan; Bayraktar, Nilufer; Alptekin, Nilgun Ozlem; https://orcid.org/0000-0002-7911-198X; https://orcid.org/0000-0002-1219-6368; https://orcid.org/0000-0002-7886-3688; https://orcid.org/0000-0003-4104-6462; 36504319; E-3717-2019; Y-8758-2018; G-1816-2014
Background and ObjectiveSoluble ST2 (sST2) is a current biomarker of cardiovascular disease. It is used to predict susceptibility to cardiovascular diseases and to analyze their prognosis. Serum sST2 level increases in inflammatory diseases such as periodontitis. However, the level of sST2 in peri-implant diseases and crevicular fluid has not been investigated yet. Thus, the aim of this cross-sectional study is to analyze the level of sST2 in peri-implant health and diseases. MethodsSixty-nine participants were divided into 3 groups as peri-implant health (PH), peri-implant mucositis (PM), and peri-implantitis (P-I). Peri-implant crevicular fluid (PICF) and serum samples were collected from each participant. The levels of sST2 and IL-6 in PICF and sST2, IL-6, and CRP in serum were compared between the groups. Pocket depth (PD), modified bleeding index (mBI), modified plaque index (mPI), keratinized mucosa index (KTW), and gingival/mucosal recession (REC) were recorded as clinical parameters. Biomarkers in the serum and PICF were analyzed by ELISA kit. ResultsSixty-nine patients were included in the study. The differences in the following parameters were statistically significant between groups: age (p = .009), implant function time (p = .027), PD (p < .001), mBI (p < .001), mPI (p < .001), and KTW (p = .043). The PICF volume of P-I and PM groups were statistically higher than PH (p < .001). The amount of sST2 in P-I and PM groups were higher than PH (p = .043). Serum CRP was higher in the P-I group than in other groups (p = .034). There were no significant differences in serum sST2 (p = .247) and IL-6 (p = .110) levels between groups. ConclusionThe PICF levels of sST2 were significantly higher in PM and P-I groups compared to the healthy group. However, no significant difference was observed between the groups in terms of serum sST2 level.
Peripheral Block Education and Level of Competency: A Survey of Turkish Anesthesiologists
(2020) Selvi, Onur; Tulgar, Serkan; Senturk, Ozgur; Tas, Zafer; Kose, Halil Cihan; Topcu, Deniz Ilhan; Ozer, Zeliha
BACKGROUND/AIMS Presently, in Turkey, there is no work being conducted on the period of regional anesthesia education, and there are no statistics available on the frequency with the administration of basic extremity blocks. The present survey was conducted on anesthesia doctors throughout Turkey to explore the personal knowledge and competency of the participants. Simultaneously, this survey aimed to evaluate the information sources for regional anesthesia training in Turkey. MATERIAL and METHODS The present study surveyed 377 anesthesia doctors in March 2017 through a questionnaire formulated on the Delphi platform. The voluntary participants were recruited from professional organizations, hospital portals, and Turkey's anesthesia departments. Descriptive analyses were conducted for statistical evaluation. RESULTS Of the total participants, 3.2% were professors, 3.2% were associate professor doctors, 7.4% were assistant professors, 64.5% were specialist doctors, and 21.8% were residents. In the segment concerning skill and information level self-evaluation for blocks, the most commonly performed act was infraclavicular block (26.8%). With regard to their "information source," 40% of the participants chose "from my colleagues" for upper extremity blocks. The specialist training was the least popular information source for ultrasound-guided interscalene block, while the digital visual information sources were often consulted for the same. CONCLUSION Various sources have been identified as the source of information as much as the specialty training, more so in some blocks. A significant majority of the participants avoided block applications. In the future, it would be useful to collect data on a more comprehensive national scale to overcome the limitations of the present issue.
Searching For The Urine Osmolality Surrogate: An Automated Machine Learning Approach
(2022) Topcu, Deniz Ilhan; Bayraktar, Nilufer; https://orcid.org/0000-0002-1219-6368; https://orcid.org/0000-0002-7886-3688; 000819864400001; E-3717-2019; Y-8758-2018
Objectives Automated machine learning (AutoML) tools can help clinical laboratory professionals to develop machine learning models. The objective of this study was to develop a novel formula for the estimation of urine osmolality using an AutoML tool and to determine the efficiency of AutoML tools in a clinical laboratory setting. Methods Three hundred routine urinalysis samples were used for reference osmolality and urine clinical chemistry analysis. The H2O AutoML engine completed the machine learning development steps with minimum human intervention. Four feature groups were created, which include different urinalysis measurements according to the Boruta feature selection algorithm. Method comparison statistics including Spearman correlation, Passing-Bablok regression analysis were performed, and Bland Altman plots were created to compare model predictions with the reference method. The minimum allowable bias (24.17%) from biological variation data was used as the limit of agreement. Results The AutoML engine developed a total of 183 ML models. Conductivity and specific gravity had the highest variable importance. Models that include conductivity, specific gravity, and other urinalysis parameters had the highest R-2 (0.70-0.83), and 70-84% of results were within the limit of agreement. Conclusions Combining urinary conductivity with other urinalysis parameters using validated machine learning models can yield a promising surrogate. Additionally, AutoML tools facilitate the machine learning development cycle and should be considered for developing ML models in clinical laboratories.
Serum growth differentiation factor-15 analysis as a malnutrition marker in hemodialysis patients
(2021) Turgut, Didem; Topcu, Deniz Ilhan; Alperen, Cemile Cansu; Baskin, Esra; 0000-0002-1219-6368; 0000-0001-7474-5927; 34247467; E-3717-2019
Background/aim: Growth differentiation factor (GDF)-15 is related to inflammation and mortality in many conditions. We aimed to determine if an elevated serum GDF-15 level is related to nutritional status of patients on hemodialysis (HD) and mortality. Materials and methods: Routine HD patients (n = 158) were included in the study and followed for 18 months. Some malnutrition/ inflammation scoring indexes (malnutrition/inflammation score (MIS), controlling nutritional status (CONUT) score, and prognostic nutritional index (PNI)), biochemical parameters, and GDF-15 were used to build Cox regression multivariate models to study the association with mortality. Results: Among the patients, 90 (57 %) had a high MIS ( _8), which associates with worse status. The serum GDF-15 level was higher in the same group (p = 0.003). The serum GDF-15 level differentiated malnutrition/inflammation according to the MIS (p = 0.031). Age, GDF15, and C-reactive protein (CRP) were significantly associated with higher all-cause mortality risk. Patients with both age and GDF-15 above the mean had a hazard ratio of 2.76 (p = 0.006) when compared with those both < mean. Conclusion: In HD patients, the GDF-15 level is increased in worse nutritional status. Beyond the MIS, age, GDF-15 and CRP would be used together to estimate the worse clinical outcome in these patients.
User Verification of Abbott Alinity HQ Hematology Analyzer
(2023) Bayraktar, Nilufer; Topcu, Deniz Ilhan; 0000-0002-1219-6368; 0000-0002-7886-3688; E-3717-2019; Y-8758-2018
Objectives This study aims to evaluate the performance characteristics of the Alinity HQ hematology analyzer in a routine laboratory setting.Methods In the study, precision (short-term and long-term precision), accuracy (method comparison with Abbott Cell Dyn Ruby and estimation of bias), confirmation of a background (Limit of Blank, LoB), and carry-over were used to evaluate the performance of Alinity HQ as recommended by ICSH, CLSI guidelines EP15-A3, EP09, EP17A2, and H26-A2. Acceptance criteria were based on manufacturer technical specifications and the EFLM Biological Variation Database.Results According to the short-term precision results, except for mean corpuscular volume (MCV) and mean corpuscular hemoglobin concentration (MCHC), all measurements exhibited coefficient variations (CV) lower than their verification limits. Basophil, eosinophil, and monocyte counts, as well as mean corpuscular hemoglobin (MCH), MCHC, and red cell distribution width standard deviation (RDW-SD), did not meet the allowable imprecision criteria for the long-term precision study. The estimated bias for all analytes was within verification limits. However, the method comparison study showed concentration-dependent variations for MCHC, MCH, and mean platelet volume (MPV) parameters. Furthermore, the correlation of parameters between Alinity HQ and Cell Dyn Ruby ranged from 0.46 to 1.00. The LoB and carry-over studies demonstrated satisfactory performance for the Alinity HQ analyzer.Conclusions Although some parameters had higher CVs than expected and concentration-dependent bias, the overall analytical performance of Alinity HQ was found to be satisfactory. Alinity HQ is an accurate, highly precise analyzer with good analytical performance, suitable for high-volume laboratories.