There is no study that comprehensively evaluates data on the readability and quality of “palliative care” information provided by artificial intelligence (AI) chatbots ChatGPT^®, Bard^®, Gemini^®, Copilot^®, Perplexity^®. Our study is an observational and cross-sectional original research study. In our study, AI chatbots ChatGPT^®, Bard^®, Gemini^®, Copilot^®, and Perplexity^® were asked to present the answers of the 100 questions most frequently asked by patients about palliative care. Responses from each 5 AI chatbots were analyzed separately. This study did not involve any human participants. Study results revealed significant differences between the readability assessments of responses from all 5 AI chatbots (P < .05). According to the results of our study, when different readability indexes were evaluated holistically, the readability of AI chatbot responses was evaluated as Bard^®, Copilot^®, Perplexity^®, ChatGPT^®, Gemini^®, from easy to difficult (P < .05). In our study, the median readability indexes of each of the 5 AI chatbots Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini® responses were compared to the “recommended” 6th grade reading level. According to the results of our study answers of all 5 AI chatbots were compared with the 6th grade reading level, statistically significant differences were observed in the all formulas (P < .001). The answers of all 5 artificial intelligence robots were determined to be at an educational level well above the 6th grade level. The modified DISCERN and Journal of American Medical Association scores was found to be the highest in Perplexity^® (P < .001). Gemini^® responses were found to have the highest Global Quality Scale score (P < .001). It is emphasized that patient education materials should have a readability level of 6th grade level. Of the 5 AI chatbots whose answers about palliative care were evaluated, Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, their current answers were found to be well above the recommended levels in terms of readability of text content. Text content quality assessment scores are also low. Both the quality and readability of texts should be brought to appropriate recommended limits.

Background: Mortality in critically ill patients with coronavirus disease 2019 (COVID‐19) is high, therefore, it is essential to evaluate the independent effect of new‐onset atrial fibrillation (NOAF) on mortality in patients with COVID‐19. We aimed to determine the incidence, risk factors, and outcomes of NOAF in a cohort of critically ill patients with COVID‐19.Methods: We conducted a retrospective study on patients admitted to the intensive care unit (ICU) with a diagnosis of COVID‐19. NOAF was defined as atrial fibrillation that was detected after diagnosis of COVID‐19 without a prior history. The primary outcome of the study was the effect of NOAF on mortality in critically ill COVID‐19 patients.Results: NOAF incidence was 14.9% (n = 37), and 78% of patients (n = 29) were men in NOAF positive group. Median age of the NOAF group was 79.0 (interquartile range, 71.5‐84.0). Hospital mortality was higher in the NOAF group (87% vs 67%, respectively, P = .019). However, in multivariate analysis, NOAF was not an independent risk factor for hospital mortality (OR 1.42, 95% CI 0.40‐5.09, P = .582).Conclusions: The incidence of NOAF was 14.9% in critically ill COVID‐19 patients. Hospital mortality was higher in the NOAF group. However, NOAF was not an independent risk factor for hospital mortality in patients with COVID‐19.

Background: Glycemic variability (GV) is a prevalent and significant condition observed in critically ill patients. This study aimed to investigate the relationship between early glycemic variability parameters and 28-day mortality in critically ill patients. Methods: A multicenter, prospective, and observational study was performed at five tertiary intensive care units (ICUs) in Turkey. All patients who had more than six blood glucose level (BGL) measures per 24 h were included. The parameters of GV including the SD, MGL, MGD (the difference between the maximal and minimal glucose level), and the CV (the percentage of SD to the MGL) in the first 24 h were recorded. Results: A total of 578 eligible patients were enrolled in the study, of whom 43.6% were women. The mean age of the patients was 68.09 ± 16.62 years. Overall mortality was 31.5% (n = 182). The glycemic parameters of the CV, SD, and MGD were significantly higher in the non-survivor group than in the survivor group (p = 0.040, 0.006, and 0.002, respectively). The multivariate logistic regression analysis revealed that the CV (OR 1.023; 95% CI 1.004–1.042; p = 0.017) was an independent factor that increased mortality. Spearman’s rho correlation analysis revealed a strong (r:0.871) and statistically significant correlation (p < 0.001) between the CV and MGD. Conclusions: The CV calculated within the first 24 h of ICU admission is independently associated with 28-day mortality. The MGD is correlated with the CV and is maybe a practical tool to predict increased risk of mortality at the bedside. However, further studies are needed to establish the independent association of the MGD with mortality.

In this retrospective cohort study, we aimed to evaluate the incidence, risk factors and outcomes of amikacin-induced acute kidney injury (AKI) in critically ill patients with sepsis. A total of 311 patients were included in the study. Of them, 83 (26.7%) had amikacin-induced AKI. In model 1, the multivariable analysis demonstrated concurrent use of colistin (OR 25.51, 95%CI 6.99-93.05, p< 0.001), presence of septic shock during amikacin treatment (OR 4.22, 95%CI 1.76-10.11, p=0.001), and Charlson Comorbidity Index (OR 1.14, 95%CI 1.02-1.28, p=0.025) as factors independently associated with an increased risk of amikacin-induced AKI. In model 2, the multivariable analysis demonstrated concurrent use of at least one nephrotoxic agent (OR 1.95, 95%CI 1.10-3.45; p=0.022), presence of septic shock during amikacin treatment (OR 3.48, 95%CI 1.61-7.53; p=0.002), and Charlson Comorbidity Index (OR 1.12, 95%CI 1.01-1.26; p=0.037) as factors independently associated with an increased risk of amikacin-induced AKI. In conclusion, before amikacin administration, the risk of AKI should be considered, especially in patients with multiple complicated comorbid diseases, septic shock, and those receiving colistin therapy.

Background: The prediction of high-flow nasal oxygen (HFNO) failure in patients with coronavirus disease-2019 (COVID-19) having acute respiratory failure (ARF) may prevent delayed intubation and decrease mortality. Aims: To define the related risk factors to HFNO failure and hospital mortality Study Design: Retrospective cohort study. Methods: To this study. 85 critically ill patients (>= 18 years) with COVID- I 9 related acute kidney injury who were treated with HFNO were enrolled. Treatment success was defined as the de-escalation of the oxygenation support to the conventional oxygen therapies. HFNO therapy failure was determined as the need for invasive mechanical ventilation or death. The patients were divided into HFNO-failure (HFNO-F) and HFNO-success (HFNO-S) groups. Electronic medical records and laboratory data were screened for all patients. Respiratory rate oxygenation (ROX) index on the first hour and chest computed tomography (CT) severity score were calculated. Factors related to HFNO therapy failure and mortality were defined. Results: This study assessed 85 patients (median age 67 years, 69.4% male) who were divided into two groups as HFNO success (n = 33) and HFNO failure (n = 52). The respiratory rate oxygenation (ROX) was measured at I hour and the computed tomography (CT) score indicated HFNO failure and intubation, with an area under the receiver operating characteristic of 0.695 for the ROX index and 0.628 for the CT score. A ROX index of 15 in the first hour of therapy were the predictors of HFNO failure and intubation. Age. Acute Physiology and Chronic Health Evaluation II score, arterial blood gas findings "(i.e., partial pressure of oxygen [PaO2]. PaO2 [fraction of inspired oxygenYSO(2) [oxygen saturation] ratio)", and D-dimer levels were also associated with HFNO failure; however. based on logistic regression analysis, a calculated ROX on the first hour of therapy of 15 (OR = 2.83, 95% CI = 1.01-7.88, P = 0.001) were the only independent risk factors. In logistic regression analysis, a ROX calculated on the first hour of therapy of 15 (OR 2.83. 95% CI = 1.01-7.88, P = <0.001) were the independent risk factors for the HFNO failure. The intensive care unit and hospital mortality rates were 80.2% and 82.7%, respectively. in the HFNO failure group. Conclusion: The early prediction of HFNO therapy failure is essential considering the high mortality rate in patients with HFNO therapy failure. Using the ROX index and the chest CT severity score combined with the other clinical parameters may reduce mortality. Additionally multi-centre observational studies are needed to define the predictive value of ROX and chest CT score not only for COVID-19 but also other causes of ARF.

To date, the coronavirus disease 2019 (COVID-19) caused more than 2.6 million deaths all around the world. Risk factors for mortality remain unclear. The primary aim was to determine the independent risk factors for 28-day mortality. In this retrospective cohort study, critically ill patients (≥ 18 years) who were admitted to the intensive care unit due to COVID-19 were included. Patient characteristics, laboratory data, radiologic findings, treatments, and complications were analyzed in the study. A total of 249 patients (median age 71, 69.1% male) were included in the study. 28-day mortality was 67.9% (n = 169). The median age of deceased patients was 75 (66–81). Of them, 68.6% were male. Cerebrovascular disease, dementia, chronic kidney disease, and malignancy were significantly higher in the deceased group. In the multivariate analysis, sepsis/septic shock (OR, 15.16, 95% CI, 3.96–58.11, p < 0.001), acute kidney injury (OR, 4.73, 95% CI, 1.55–14.46,p = 0.006), acute cardiac injury (OR, 9.76, 95% CI, 1.84–51.83, p = 0.007), and chest CT score higher than 15 (OR, 4.49, 95% CI, 1.51-13.38, p = 0.007) were independent risk factors for 28-day mortality. Early detection of the risk factors and the use of chest CT score might improve the outcomes in patients with COVID-19.