Background: Methotrexate (MTX) is a folic acid antagonist, commonly administered for the treatment of a variety of cancers. However, methotrexate toxicity including bone marrow suppression and hepatic and renal toxicity limits its use. Angiotensin AT₁ receptor blockers including Valsartan (Val) possess the ability to ameliorate MTX-induced toxicity through various mechanisms. In this study, we explored the potential reno-protective effects of Val against MTX-induced acute kidney injury in rats. Methods: Twenty-four Wistar rats were randomly segregated into 3 groups. Group 1 served as the control group and received an oral dose of 1mL/kg of normal saline. Group 2 received a single dose of 20 mg/kg of MTX intraperitoneally (IP) for 5 days. Group 3 received a single IP dose of 20 mg/kg of MTX followed by an oral dose of 10 mg/kg of Valsartan for 5 days. At the end of the experiment, the levels of serum kidney biomarkers, inflammatory and oxidative stress markers were accessed. Furthermore, the effect of MTX on kidney tissue histology was examined. Results and discussion: Our results showed that MTX treatment increased the level of serum kidney and inflammatory biomarkers and decreased the level of antioxidants SOD and GSH while increasing the lipid peroxidation contents. Furthermore, MTX treatment caused structural changes to kidney histology. However, the administration of Val significantly prevented these changes. Conclusion: Valsartan possesses nephroprotective potential and might serve as a potential therapeutic strategy against MTX-induced kidney injury.

Background: Assessment of medical information provided by artificial intelligence (AI) chatbots like ChatGPT and Google’s Gemini and comparison with international guidelines is a burgeoning area of research. These AI models are increasingly being considered for their potential to support clinical decision-making and patient education. However, their accuracy and reliability in delivering medical information that aligns with established guidelines remain under scrutiny. Objective: This study aims to assess the accuracy of medical information generated by ChatGPT and Gemini and its alignment with international guidelines for sepsis management. Methods: ChatGPT and Gemini were asked 18 questions about the Surviving Sepsis Campaign guidelines, and the responses were evaluated by 7 independent intensive care physicians. The responses generated were scored as follows: 3=correct, complete, and accurate; 2=correct but incomplete or inaccurate; and 1=incorrect. This scoring system was chosen to provide a clear and straightforward assessment of the accuracy and completeness of the responses. The Fleiss κ test was used to assess the agreement between evaluators, and the Mann-Whitney U test was used to test for the significance of differences between the correct responses generated by ChatGPT and Gemini. Results: ChatGPT provided 5 (28%) perfect responses, 12 (67%) nearly perfect responses, and 1 (5%) low-quality response, with substantial agreement among the evaluators (Fleiss κ=0.656). Gemini, on the other hand, provided 3 (17%) perfect responses, 14 (78%) nearly perfect responses, and 1 (5%) low-quality response, with moderate agreement among the evaluators (Fleiss κ=0.582). The Mann-Whitney U test revealed no statistically significant difference between the two platforms (P=.48). Conclusions: ChatGPT and Gemini both demonstrated potential for generating medical information. Despite their current limitations, both showed promise as complementary tools in patient education and clinical decision-making. The medical information generated by ChatGPT and Gemini still needs ongoing evaluation regarding its accuracy and alignment with international guidelines in different medical domains, particularly in the sepsis field.

Background: Methotrexate (MTX) is a commonly used chemotherapy drug with known nephrotoxic effects, including the potential for acute kidney injury. However, the precise mechanism through which MTX induces nephrotoxicity remains unclear, though oxidative stress and direct toxic effects on renal tubules are believed to play key roles. Recent studies suggest that calcium channel blockers may offer promise in slowing down the progression of chronic kidney diseases. Objective: The purpose of this study was to explore the potential of Amlodipine, a calcium channel blocker, to alleviate acute kidney injury caused by the administration of MTX in rats. Methods: Three groups of twenty-four male Wistar rats were randomly assigned: Group 1—the control group was given normal saline orally. Group II, underwent five days of continuous administration of a single intraperitoneal (IP) dosage of 20 mg/kg MTX. The same dosage of MTX was given to Group III followed by an oral dose of Amlodipine at 5 mg/kg over the same period. Upon completion of the experiment, serum biochemical parameters, renal damage markers, oxidative stress, inflammatory markers, and kidney tissue histology were assessed. Results: The results indicate that MTX administration significantly increased the levels of serum biochemical parameters, renal damage markers, inflammatory markers, oxidative stress markers, and induced alterations in kidney histology. However, the administration of Amlodipine following MTX treatment protected against these changes. Conclusion: Amlodipine exhibits therapeutic potential in mitigating MTX-induced kidney injury in rats and its associated side effects.

BACKGROUND Assessment of medical information provided by artificial intelligence (AI) chatbots like ChatGPT and Google’s Gemini and comparison with international guidelines is a burgeoning area of research. These AI models are increasingly being considered for their potential to support clinical decision-making and patient education. However, their accuracy and reliability in delivering medical information that aligns with established guidelines remain under scrutiny. OBJECTIVE This study aims to assess the accuracy of medical information generated by ChatGPT and Gemini and its alignment with international guidelines for sepsis management. METHODS ChatGPT and Gemini were asked 18 questions about the Surviving Sepsis Campaign guidelines, and the responses were evaluated by 7 independent intensive care physicians. The responses generated were scored as follows: 3=correct, complete, and accurate; 2=correct but incomplete or inaccurate; and 1=incorrect. This scoring system was chosen to provide a clear and straightforward assessment of the accuracy and completeness of the responses. The Fleiss κ test was used to assess the agreement between evaluators, and the Mann-Whitney U test was used to test for the significance of differences between the correct responses generated by ChatGPT and Gemini. RESULTS ChatGPT provided 5 (28%) perfect responses, 12 (67%) nearly perfect responses, and 1 (5%) low-quality response, with substantial agreement among the evaluators (Fleiss κ=0.656). Gemini, on the other hand, provided 3 (17%) perfect responses, 14 (78%) nearly perfect responses, and 1 (5%) low-quality response, with moderate agreement among the evaluators (Fleiss κ=0.582). The Mann-Whitney U test revealed no statistically significant difference between the two platforms (P=.48). CONCLUSIONS ChatGPT and Gemini both demonstrated potential for generating medical information. Despite their current limitations, both showed promise as complementary tools in patient education and clinical decision-making. The medical information generated by ChatGPT and Gemini still needs ongoing evaluation regarding its accuracy and alignment with international guidelines in different medical domains, particularly in the sepsis field.

Methotrexate (MTX) is a widely used chemotherapeutic agent known for its nephrotoxic effects, which can lead to acute kidney injury in hospitalized patients. However, the mechanism by which MTX induces nephrotoxicity is not entirely clear, but it is believed to involve oxidative stress and direct toxic effects on renal tubules. Valsartan, an angiotensin II receptor blocker, has been shown to exert renoprotective effects in various contexts, including diabetic nephropathy. In this study, the renoprotective potential of Valsartan to mitigate MTX-induced acute kidney in rats was explored. A total of twenty-four Wistar rats were randomly assigned to three groups. The Control Group (GRP 1) was administered an oral dose of 1 ml/kg of normal saline. The second group (GRP 2) received a single Intraperitoneal (IP) dose of 20 mg/kg MTX for a duration of 5 consecutive days. The third Group (GRP 3) was subjected to a single IP dose of 20 mg/kg MTX followed by an oral dose of 30 mg/kg Valsartan (Val) over the same 5-day period. At the end of the experiment, the levels of serum biochemical parameters, renal damage markers, and inflammatory and oxidative stress markers were accessed. Additionally, the impact of MTX on kidney tissue histology was investigated. The results indicate that MTX administration in rats led to a significant increase in serum biochemical parameters, renal damage markers, inflammatory markers, and oxidative stress markers, as well as changes in kidney histology. However, the administration of Val following MTX treatment to rats attenuated these effects. Conclusions: Val shows therapeutic potential in the treatment of MTX-induced kidney injury and its associated consequences.

Background: The medication regimen complexity–intensive care unit (MRC-ICU) score is a validated tool for assessing medication regimen complexity in critically ill patients and has been associated with several clinical outcomes. However, its association with delirium remains poorly characterized. This study aimed to evaluate the association between the day-1 MRC-ICU score and delirium development and to describe associated clinical outcomes. Methods: This prospective multicenter cohort study enrolled 364 adult patients admitted to intensive care units (ICUs) across four tertiary hospitals between January and April 2025. MRC-ICU, sequential organ failure assessment, and acute physiology and chronic health evaluation II (APACHE II) scores were recorded within 24 h of admission. The primary outcome was delirium during the ICU stay. Secondary outcomes were acute kidney injury (AKI), fluid overload (FO), renal replacement therapy (RRT), ICU and hospital mortality, and ICU and hospital length of stay. Logistic regression was used to assess the association between day-1 MRC-ICU score and delirium. Results: Delirium occurred in 12 patients (3.3%). Baseline MRC-ICU scores did not significantly differ between the delirium and no-delirium groups (median, 12 vs. 11; p = 0.364). No statistically significant association was detected per 5-point increase in the day-1 MRC-ICU score in either the unadjusted model (odds ratio [OR] 1.28, 95% confidence interval [CI] 0.73–2.23; p = 0.385) or the APACHE II-adjusted model (OR 1.27, 95% CI 0.73–2.22; p = 0.398). Patients who developed delirium had higher rates of incident AKI (33.3% vs. 4.5%; p = 0.009), FO (83.3% vs. 10.5%), RRT initiation (66.7% vs. 4.3%), ICU mortality (83.3% vs. 12.5%), and hospital mortality (100% vs. 17.0%) (p < 0.001 for the remaining outcomes). Conclusions: No statistically significant association was detected between the day-1 MRC-ICU score and delirium development. Delirium was associated with higher rates of adverse clinical outcomes. However, the small number of delirium events and imprecise estimates preclude definitive conclusions regarding the association between admission medication regimen complexity and delirium risk.