Eren Demirpolat

Objective: This study primarily aimed to determine meropenem the trough level (Cmin) in intensive care unit (ICU), with an exploratory secondary aim of evaluating factors influencing Cmin and clinical cure.Material and Method: This prospective study included adult ICU patients receiving meropenem for ≥48 hours, and Cmin levels were measured using a ready-to-use ELISA kit.Result and Discussion: The study included 38 patients, 26 of whom were male. Mean meropenem Cmin value was found to be 0.40 ± 0.07 mg/l which is statistically different than the target value of 8 mg/l (p < 0.001). We found no statistically significant difference in mean Cmin between the patient groups whose creatinine clearance was smaller than 50 ml/min and not. Erythrocyte and hemoglobin values decreased after meropenem treatment compared to baseline (p < 0.05). C-Reactive Protein (CRP) decreased, and Sequential Organ Failure Assessment (SOFA) values increased after meropenem treatment (p < 0.001). Logistic regression in patients with Systemic Inflammatory Response Syndrome (SIRS) showed that only SOFA reduced the clinical cure rate (OR 0.534, 95% CI 0.311–0.917). In this study, the target 100% fT > MIC < 4×MIC was not achieved with standard or extended meropenem infusion, potentially limiting clinical cure in ICUs with resistant pathogens, highlighting the need for alternative dosing strategies.

Introduction: Large language models (LLMs) offer potential as clinical decision support systems (CDSS) for detecting drug-related problems (DRPs), yet their real-world performance compared to clinical pharmacists (CPs) remains unclear, especially in complex hematology care. We aimed to evaluate the concordance between a clinical pharmacist and three LLMs in identifying DRPs within a Bone Marrow Transplantation unit. Methods: This prospective observational study evaluated the concordance between a CP and three LLMs (ChatGPT-4o, Grok-3, DeepSeek-v3) in a Bone Marrow Transplantation unit. Eighty-three anonymized patient cases encompassing 210 CP-identified DRPs, classified via the PCNE v9.1 system, were presented using a standardized CDSS-simulating prompt. Performance was assessed based on direct detection, prompted detection after structured follow-up, and the clinical relevance of AI-generated therapeutic recommendations against the CP's gold-standard assessments. Results: Direct detection of intervention-requiring DRPs was limited (51.4%-60.5% across models), with nearly half missed initially. Guided prompting significantly improved overall detection rates to 93.8%-98.1%, with ChatGPT achieving the highest accuracy. All models produced hallucinations. Recommendation concordance with the CP exceeded 70% in most DRP categories. DeepSeek and ChatGPT showed more consistent performance in context-dependent evaluations, whereas Grok demonstrated higher direct detection but lower recommendation alignment. LLMs demonstrate meaningful potential to assist in DRP detection but are not sufficiently reliable as standalone tools. Expert-guided interaction substantially enhanced their performance, underscoring the critical value of hybrid pharmacist-AI workflows. Conclusion: Future research should validate these findings across broader populations with multiple expert evaluators and integrate next-generation AI architectures for safer CDSS implementation.

Background: Oral mucositis (OM) is a debilitating complication of chemotherapy and radiotherapy, characterized by painful ulcerations and inflammation of the oral mucosa. Current treatments provide limited efficacy and often lack regenerative properties. This study aimed to evaluate the therapeutic potential of topically administered probiotics in a rat model of OM. Methods: OM was induced in Sprague–Dawley rats using 5‐fluorouracil (5‐FU) and acetic acid. Rats were randomized into groups receiving topical formulations of Lactobacillus acidophilus , Lactobacillus reuteri , Bacillus clausii , Bacillus coagulans , Lactobacillus plantarum , sucralfate, triamcinolone, and control. Treatments were applied for 5 consecutive days. OM severity was assessed using macroscopic and histopathological scoring, fibrosis grading, and inflammatory markers (TNF‐α, IL‐10, PGE ₂ ). Results: L. acidophilus and L. reuteri significantly reduced macroscopic and histopathological OM scores compared to controls. L. acidophilus also demonstrated a notable reduction in fibrosis and PGE ₂ levels ( p < 0.05), suggesting anti‐inflammatory and antifibrotic activity. B. clausii and B. coagulans showed moderate efficacy, while sucralfate and triamcinolone reduced mucosal inflammation but were less effective in tissue regeneration. No significant changes in IL‐10 were observed across groups. Conclusion: Topically applied probiotics, particularly L. acidophilus , exhibit significant therapeutic potential in attenuating chemotherapy‐induced OM by modulating inflammation and promoting mucosal healing. These findings support further exploration of localized probiotic therapies as a novel, non‐systemic approach to manage OM in clinical settings.

Purpose Acute kidney injury (AKI) is a prevalent complication in critically care, affecting prognosis and management. Standard formulas for estimating glomerular filtration rate (GFR), such as CKD-EPI and MDRD, are frequently used; accuracy in AKI is limited due to fluctuating creatinine. This study aimed to evaluate the agreement between standard GFR and kinetic-GFR formulas in AKI patients and to assess the impact on antibiotic dosing. Methods In this prospective, observational study conducted at Erciyes University Hospital, 100 patients with AKI were enrolled. GFR was estimated using CKD-EPI, MDRD, and kinetic-GFR formulas, including volume-adjusted kinetic formulas. Agreement between formulas was analyzed using Kappa coefficient. Results Statistically significant but imperfect agreement was observed between kinetic and standard formulas (CKD-EPI: κ = 0.592 ± 0.026, p < 0.001; MDRD: κ = 0.649 ± 0.025, p < 0.001). Approximately 28–30% of follow-up days revealed category mismatches between standard and kinetic formulas. 47% of the mismatches of CKD-EPI vs ki-CKD-EPI, and 31% for MDRD vs ki-MDRD occurred on day 2. Volume-adjusted kinetic formulas increased the mismatch rate, with CKD-EPI increasing from 28.5% to 30.6% (p < 0.001) and MDRD from 24.4% to 27.2% (p < 0.001). Significant dose adjustments were required when kinetic-GFR was used, particularly for nephrotoxic antibiotics. Conclusion The use of kinetic-GFR formulas improves the accuracy of GFR estimation in AKI, especially in the early stages, and may lead to more appropriate antibiotic dosing. However, further studies are needed to fully understand the clinical implications, especially regarding drug levels and patient outcomes.

Voriconazole (VCZ) is the drug of choice for invasive aspergillosis (IA). However, narraow therapeutic range and variable pharmacokinetics can effect the success of the therapy. VCZ serum concentration is influenced by several factor including CYP450 polymorphisms primarily by CY2C19. Therapeutic drug monitoring (TDM) of VCZ is highly recommended to check adequate serum concentrations. Herein, we investigated the usefulness of detecting CYP450 polymorphism. Patients with hematological malignancies were included in the study.CYP450 polymorphisms which are responsible for metabolism of VCZ were investigated using RT-PCR. TDM of VCZ was peformed usingLC/MS/MS.11 patients were included in the study. Frequencies of CYP2C19 genotypes are 27% for intermediate metabolizer; 36% rapid metabolizer, 18% for ultra rapid metabolizer, 18% for normal metabolizer. Two patients experienced dose related side effects and one of these patient’s voriconazole blood concentration was supratherapeuticAlthough VCZ is the drug of choice for thetreatment of IA, the variabality of the pharmacokinetics can influence the success of therapy significantly. Therefore implementing the pharmacogenetic testing and therapeutic drug monitoring to clinical practice might help clinicians to provide improved care to patients and improve treatment outcomes.

Objectives Vancomycin, a glycopeptide antibiotic has antibacterial activity against Gram-positive bacteria and is frequently used in the intensive care unit (ICU). Inappropriate therapeutic drug monitoring (TDM) of vancomycin is a common problem encountered in hospital daily practice. The aim of this study was to evaluate the appropriateness of vancomycin trough-guided TDM in patients treated in the ICU using a clinical pharmacy approach. Methods The study was conducted retrospectively in patients over 18 years old who had at least one vancomycin trough level and who had received intravenous (IV) vancomycin for ≥3 days between 1 November 2020 and 1 April 2022. The study included 137 patients. Patient demographics and relevant vancomycin TDM data were collected from medical records. The appropriateness of TDM was evaluated according to the criteria established based on the monitoring recommendations specified in consensus guidelines for therapeutic drug monitoring of vancomycin published by the American Society of Health-System Pharmacists (ASHP) in 2009 and 2020. Results Of a total of 238 vancomycin trough levels measured in patients, 32.4% were collected at an inappropriate time. When patients were evaluated in terms of TDM appropriateness according to vancomycin level ranges (20 µg/mL), we found the appropriate TDM was significantly higher in the therapeutic range (10–20 µg/mL) (p Conclusion Our study shows that appropriate vancomycin TDM increases the likelihood of achieving target trough concentrations. Involvement of clinical pharmacists in TDM management may prevent the development of adverse reactions by ensuring appropriate sampling time and appropriate interpretation of vancomycin levels.

Antimicrobial drugs are frequently used in the intensive care unit (ICU) and may cause drug-drug interactions (DDIs) which change treatment outcomes. This study aims to determine the frequency of potential DDIs (pDDIs) caused by antimicrobial drugs in the ICU, according to two databases, address the differences between these two databases, discuss the clinical significance of pDDIs and investigate their relationship with clinical outcomes. This study was designed as a 1-year retrospective cross-sectional study. Patients over the age of 18 who used antimicrobials for at least 72 hours were included. pDDIs between other drugs and antimicrobials were checked using the “drug interactions” modules of the Lexicomp and Micromedex databases. Data were collected from the hospital’s records by a clinical pharmacist. A total of 393 drug profiles were evaluated for 100 patients, of which 84.2% were antibacterial drugs. According to at least one database, 88% of patients had pDDIs. Of these, 62.4% were classified as major according to at least one database. Only 27.3% of pDDIs had the same level of interaction in both databases. Common pDDIs posed risks such as additive nephrotoxicity, excessive sedation, respiratory depression and QT interval prolongation. pDDIs should be checked not only by one database but by multiple databases, coupled with the input of an experienced clinical pharmacist.

Introduction: Drug drug interactions can effect the success of stem cell transplantation process. Therefore, analyzing the risk of these interactions would be helpful for practitioners. This study was conducted to identify drug-drug interactions in allogeneic and autologous stem cell transplantation patients before and after transplantation. Methods: Patients who underwent allogeneic stem cell transplantation and autologous stem cell transplantation were included in the study. Patients’ treatment sheets were collected ten days before transplantation day, on the transplantation day, and ten days after transplantation day. Drug-drug interactions were analyzed by using four drug-drug interaction checking databases. Results: 50 patients from both transplantation types were included. The mean ages for allogeneic and autologous transplants were 42.4 and 51.8, respectively. 52% of allogeneic transplants and 28% of autologous transplants were on ≥5 drugs at tenth day before transplantation. The means of interactions in allogeneic and autologous stem cell transplantation patients were 75.42 and 43.62, respectively. The detection of at least one contraindicated interaction in allogeneic and autologous transplant patients were 94% and 92%, respectively. In 48% of allogeneic transplants and 36% of autologous transplants, two or more contraindicated interactions were detected. Conclusion: Allogeneic stem cell transplantation patients experienced almost two times more drug-drug interactions than autologous stem cell transplantation patients. Transplantation type, being in the pre and post-transplantation period and the drug number at the beginning of the transplantation process matter in terms of the number of drug-drug interactions. Identifying interactions in terms of transplantation type and existing medications is very important.

Introduction Acute kidney injury (AKI) is an important and life-threatening complication following allogeneic haematopoietic stem cell transplantation (allo-HSCT). This is therefore an active research area with studies aiming to understand the factors that cause this complication. Materials and methods We conducted a retrospective study to identify the factors that caused AKI in 100 patients who underwent allo-HSCT in the first 100 days after transplantation using logistic regression analysis. Results The mean time of onset of AKI was 45.58 days (range 13–97) and the mean±SD maximum serum creatinine value was 1.53±0.78 mg/dL. In 47 patients, level 1 or higher AKI occurred in the first month of transplantation and 38 of these patients were diagnosed with a higher level of AKI 31–100 days after transplantation. According to multivariate analysis, use of cyclophosphamide (adjusted odds ratio (AOR) 4.01, p=0.012), mean ciclosporin blood levels ≥250 ng/mL (AOR 2.81, p=0.022) and ciclosporin blood levels ≥450 ng/mL in the first month of transplantation (AOR 3.30, p=0.007) were found to be potential factors for early onset AKI. Ciclosporin blood levels exceeded 450 ng/mL in 35% of those using posaconazole and voriconazole during administration route change of ciclosporin. Use of ≥2 nephrotoxic anti-infective drugs (AOR 3, p=0.026) and developing AKI in the first month of transplantation (AOR 4.14, p=0.002) were found to be potential factors in the development of advanced AKI. Conclusion Nephrotoxic drugs, cyclophosphamide use and ciclosporin blood levels are factors to be considered to prevent the development of AKI in patients undergoing allo-HSCT.