Belen Ateş

Background: Paracetamol overdose is a common reason for pediatric poisoning consultations and emergency department visits, and. Large language models (LLMs) are increasingly being explored for clinical decision support, but evidence on pediatric poisoning is scarce. We compared the performance and safety of three contemporary LLMs for managing pediatric paracetamol poisoning using guideline-based simulated scenarios. Methods: In this cross-sectional, comparative, scenario-based study, 30 hypothetical pediatric paracetamol poisoning scenarios were presented to ChatGPT 5.5, Claude Sonnet 4.6, and Gemini 3 Flash via their public browser-based interfaces, with a standardized single-turn prompt (90 responses). Blinded to model identity, a three-clinician expert panel scored each response by consensus using a study-specific Artificial Intelligence Evaluation Score for Clinical Poisoning Vignettes (AIES-CPV; range 5–25), an eight-item key-action checklist (0–8), the Global Quality Scale (GQS; 1–5), reference-standard concordance, and the presence of critical safety errors, against a predefined reference algorithm derived primarily from the Australia and New Zealand guidelines. Models were compared using the Friedman test (with Wilcoxon signed-rank tests and a Bonferroni correction for pairwise comparisons) and the Cochran Q test for critical error rates. Results: than ChatGPT 5.5 and Gemini 3 Flash (Friedman p < 0.001 for all); ChatGPT 5.5 and Gemini 3 Flash did not differ significantly. Claude Sonnet 4.6 produced no critical safety errors and was concordant with the reference standard in all responses, whereas one critical error occurred with ChatGPT 5.5 (1/30) and three with Gemini 3 Flash (3/30); the difference in critical-error rates was not statistically significant (Cochran Q = 4.67, p = 0.097). Conclusions: Among three LLMs evaluated on pediatric paracetamol poisoning scenarios, Claude Sonnet 4.6 showed the highest guideline-based accuracy, key-action performance, and overall quality, with no critical safety errors. Contemporary LLMs may serve as adjunctive decision-support tools in pediatric toxicology, but given inter-model safety differences and the risk of confident errors in high-stakes decisions, they should be used only under expert supervision and with clinical verification.

To the Editor,We read with interest the study by Pişkin et al.1, which provides valuable prospective data on viral etiology and clinical risk factors in preschool children presenting with wheezing. The demonstration that rhinovirus and RSV account for the majority of viral detections is consistent with current evidence and has clear clinical relevance. We wish to raise two methodological concerns that, in our view, warrant explicit acknowledgment in the Limitations section, as they directly bear on the strength of the conclusions drawn.First, we wish to raise a concern regarding the epidemiological interpretation of the seasonal RSV data. The authors report a spring predominance for RSV and contextualize this within the framework of regional Mediterranean climatic variability, citing global analyses of shifting RSV seasonality2. While this is a plausible hypothesis, we would argue that it requires more prominent qualification. The study's data collection spanned November 2017 to January 2019, encompassing only a single spring season (Spring 2018). Distinguishing a true geographical shift in RSV seasonality from a year-to-year epidemiological fluctuation requires surveillance across multiple consecutive seasons, as is widely recognized in respiratory virus epidemiology3. The authors do briefly acknowledge the possibility of "year-to-year fluctuations" within the Discussion, but this caveat is presented alongside the climatic hypothesis, risking equal weight being afforded to an inference that single-season data cannot substantiate. Notably, this constraint does not appear in the Limitations section, despite being directly relevant to one of the paper's more novel epidemiological claims.Second, and thematically related, the absence of longitudinal follow-up precludes monitoring of individual wheezing trajectories over time. Although the study is prospective in design, it captures a single clinical episode per child rather than tracking outcomes beyond the index presentation. Given that the study's stated aim explicitly includes "implications for asthma prevention," this represents a meaningful limitation on the paper's central clinical claim. Whether the children who experienced early rhinovirus- or RSV-associated wheezing in this cohort subsequently developed persistent asthma the outcome of greatest preventive interest cannot be determined from the present data4. The authors note in their conclusion that "future multicenter studies with longitudinal follow-up are warranted," which implicitly acknowledges this gap; however, framing it as a future direction rather than a present limitation understates its significance for readers interpreting the current findings.We respectfully suggest that the Limitations section be revised to explicitly acknowledge that (i) the single-season surveillance window precludes definitive conclusions regarding regional RSV seasonality, and (ii) the study design does not permit assessment of long-term wheezing trajectories or asthma progression. Both constraints share a common thread the temporal scope of the study and acknowledging them together would strengthen the paper's methodological transparency without detracting from its substantive clinical contributions.

Objective: This study aimed to assess maternal attitudes toward infant feeding using the Iowa Infant Feeding Attitude Scale (IIFAS) and to examine the associations of these attitudes with maternal sociodemographic characteristics and breastfeeding practices. Materials and Methods: The study included 305 mothers whose healthy term born children had no chronic diseases, and were 6 to 24 months of age. A questionnaire addressing demographic characteristics was administered during face-to-face interviews. The IIFAS was also used to assess maternal attitudes toward infant feeding. Spearman’s correlation and nonparametric group comparisons (Mann–Whitney U and Kruskal–Wallis tests) were used to examine associations between IIFAS scores and maternal sociodemographic characteristics and breastfeeding practices. Results: The mean age of the participants’ children was 14.7±4.7 months, and 54.8% were male. The mean IIFAS score was 71.7±5.6 (range: 48–82), indicating that most mothers had attitudes favoring breastfeeding. Mothers with university-level education or higher had significantly higher IIFAS scores than those with lower levels of education (p<0.001). Employed mothers had significantly lower scores than non-employed mothers (p=0.016). Significant but weak-to-moderate positive correlations were found between IIFAS scores and maternal education level (r=0.28, p<0.001) and the duration of exclusive breastfeeding (r=0.12, p=0.029), whereas the interval between birth and breastfeeding initiation was weakly negatively correlated with IIFAS scores (r=−0.18, p=0.012). Conclusion: Maternal attitudes toward breastfeeding, as measured by the IIFAS, were primarily associated with educational background and employment status, and may also be related to the duration of exclusive breastfeeding. These findings are hypothesis-generating; whether targeted educational initiatives and workplace policies that support lactation improve breastfeeding practices remains to be tested in prospective studies.

Aim: The aim of our study is to evaluate the reasons for using pediatric emergency services, patient volume, and the rates of admission to intensive care units and inpatient wards in the pediatric emergency department observation unit.Material and Methods: Data from 6,846 patients monitored in the pediatric emergency department observation unit at Prof. Dr. Cemil Tascioglu City Hospital were analyzed between January 1, 2023, and December 31, 2023. The data collected included: date and time of application, age, gender, diagnosis, disease group, length of stay in observation, ward admission, intensive care unit admission, referral unit, presence of chronic conditions, medications used, discharge status, treatment refusal, and histories of previous ward and intensive care unit admissions.Results: Of the 6,846 patients, the most common diseases were respiratory (23.2%) and gastrointestinal (23.1%). Significant differences were observed between patients with prior hospitalizations (p=0.004) and those admitted to the intensive care unit (p

Background: Large language models (LLMs) are increasingly used by patients and caregivers to obtain medical information. In pediatric acute bacterial arthritis, non-guideline-concordant information may be clinically important because timely diagnosis and management are essential. This study evaluated the concordance of LLM-generated responses to parent-oriented reformulations of Pediatric Infectious Diseases Society/Infectious Diseases Society of America (PIDS/IDSA) guideline recommendations. Methods: In this exploratory cross-sectional benchmarking study, 27 PIDS/IDSA guideline-derived recommendations and good practice statements were reformulated into standardized parent-oriented prompts. The same prompts were submitted to GPT-5.4 Thinking, Gemini 3 Thinking and Claude 4.6 Sonnet through browser-based interfaces on April 12, 2026. Responses were anonymized and independently assessed by 3 blinded reviewers. Each response was classified as concordant or discordant; final classifications were determined by majority decision. Interrater agreement was assessed using Fleiss’ kappa, and model differences were evaluated using Cochran’s Q test. Results: Overall, 75 of 81 responses (92.6%) were concordant with PIDS/IDSA recommendations. Gemini 3 Thinking achieved concordance in 27/27 responses (100.0%), Claude 4.6 Sonnet in 25/27 (92.6%) and GPT-5.4 Thinking in 23/27 (85.2%). Cochran’s Q test showed no significant difference among models (Q = 4.800, df = 2, P = 0.091). No unsupported or hallucinated content was identified. Interrater agreement was moderate (κ = 0.580; 95% CI, 0.454–0.706; P < 0.001). Conclusions: LLMs showed high guideline concordance, but selected item-level discordance persisted. Because these models may have been trained on guideline-derived content, high concordance should not be equated with independent clinical reasoning. These tools may support caregiver-oriented education but should not replace clinician assessment or guideline-based care.

Objective: This multicenter retrospective real-world data study aimed to evaluate whether the use of a preparation containing polyphenol, vitamin D3, vitamin C, and zinc in addition to antiviral therapy was associated with symptom duration and severity, time to fever resolution, and functional recovery in children diagnosed with influenza. Materials and Methods: This was a five-center, multicenter, retrospective, comparative real-world data analysis. A total of 128 patients aged 4–10 years with a clinical diagnosis of influenza were classified into a control group receiving antiviral therapy alone (n = 64) and a combined polyphenol group receiving, in addition to antiviral therapy, a preparation containing polyphenol, vitamin D3, vitamin C, and zinc (n = 64). Clinical data were obtained from electronic patient records and parent-reported information. Symptom severity (0–3 ordinal score), recovery time, and functional outcomes were assessed on Days 0, 3, 5, and 7. Continuous variables were compared using the independent-samples t test, categorical variables using the chi-square or Fisher exact test, and changes over time using a repeated-measures general linear model. Statistical significance was accepted as a two-sided p value of p > 0.05). During follow-up, all symptom scores improved more rapidly and markedly in the combined polyphenol group than in the control group. By Day 3, significant differences were observed between groups in fever, cough, rhinorrhea, sore throat, fatigue, general condition, and physical activity scores (p < 0.001 for all parameters). By Day 5, almost complete resolution of symptoms (score 0) was observed in the combined polyphenol group, whereas symptoms persisted to a substantial extent in the control group (p < 0.001). The time to fever resolution was significantly shorter in the combined polyphenol group (1.84 ± 0.72 days vs. 4.5 ± 1.36 days; p < 0.001). Similarly, time to return to school (3.21 ± 0.9 days vs. 5.8 ± 1.91 days; p < 0.001) and time for parents to return to work were significantly shorter in the combined polyphenol group (p < 0.001). The need for additional healthcare visits and antipyretic use was markedly lower in the combined polyphenol group (Day 3: 20.3% vs. 53.1%; Day 5: 0% vs. 15.6%; p < 0.001 for both comparisons). Repeated-measures analyses showed a significant time-by-group interaction, indicating that the reduction in symptom scores occurred more rapidly and prominently in the combined polyphenol group (p < 0.001). Treatment was generally well tolerated in the combined polyphenol group; no serious adverse events were reported, and parent-reported tolerability was high (9.39 ± 0.7). Conclusions: This multicenter retrospective real-world data study suggests that the use of a preparation containing polyphenol, vitamin D3, vitamin C, and zinc in addition to antiviral therapy was associated with shorter symptom duration, lower symptom severity scores, and faster functional recovery in children diagnosed with influenza. These findings suggest that this combination may represent a promising and well-tolerated adjunctive approach in the management of pediatric influenza.

Background: Artificial intelligence (AI) is increasingly integrated into healthcare, including pediatrics, offering new opportunities for diagnosis, management, and decision support. However, the effective implementation of AI depends largely on healthcare professionals’ knowledge, attitudes, and readiness to adopt these technologies. This study aimed to evaluate pediatricians’ general attitudes toward artificial intelligence and their level of readiness for medical AI in Istanbul, Türkiye at tertiary hospital. Distinct from previous research focusing primarily on medical students, this study investigates the AI readiness of practicing pediatricians within a major tertiary hospital in Istanbul, addressing a critical gap in professional clinical workforce assessment. Methods: This descriptive cross-sectional study was conducted between August 1 and November 1, 2025, at Prof. Dr. Cemil Taşcıoğlu City Hospital. A total of 130 pediatricians participated. Data were collected using a sociodemographic questionnaire, the GAAIS (General Attitudes toward Artificial Intelligence Scale), and the MAIRS-MS (Medical Artificial Intelligence Readiness Scale for Medical Students). The validity and reliability of scales in Turkish have been previously investigated in various studies. The internal consistency of the scales was excellent, with a Cronbach’s alpha coefficient of 0.972 in our study. Statistical analyses were performed using SPSS 27. Correlation, t-test, ANOVA, and non-parametric tests were applied where appropriate. Results: The mean age of participants was 37.47 ± 9.31 years, and 58.5% were female. The mean AI positive attitude score was 3.81 ± 0.74, and the negative attitude score was 2.83 ± 0.81. The total MAIRS-MS score was 74.97 ± 13.01, indicating a moderate-to-high level of AI readiness. Age was negatively correlated with AI positive attitude and total MAIRS score ( p < 0.05). Participants with ≥ 21 years of professional experience had significantly lower AI readiness and positive attitude scores than younger participants ( p < 0.05). A strong positive correlation was found between AI positive attitude and total MAIRS-MS score ( r = 0.764, p < 0.01). Multiple regression analysis revealed that “Ability” (β = 0.516, p < 0.001) and “Cognition” (β = 0.323, p < 0.001) factors were the strongest predictors of a positive attitude toward AI (R ² = 0.658). A strong positive correlation was found between AI positive attitude and total MAIRS-MS score ( r = 0.764, p < 0.01). These results suggest that clinical AI implementation must be accompanied by tailored institutional support and age-specific training to bridge the generational digital divide in pediatric care. Conclusion: Pediatricians generally demonstrated positive attitudes and moderate-to-high readiness for artificial intelligence in our study. However, advanced age and longer professional experience were associated with lower readiness levels. These findings highlight the need for a structured AI education and training program, especially targeting senior physicians, to ensure effective and ethical integration of AI into pediatric practice.

Objective: This multicenter retrospective real-world data study aimed to determine whether a preparation containing polyphenol, vitamin D3, vitamin C, and zinc added to antiviral therapy accelerates clinical recovery in children diagnosed with influenza by evaluating its effects on symptom duration and severity, time to fever resolution, and functional recovery. Materials and Methods: This was a five-center, multicenter, retrospective, comparative real-world data analysis. A total of 128 patients aged 4-10 years with a clinical diagnosis of influenza were classified into a control group receiving antiviral therapy alone (n=64) and a combined polyphenol group receiving, in addition to antiviral therapy, a preparation containing polyphenol, vitamin D3, vitamin C, and zinc (n=64). Clinical data were obtained from electronic patient records and parent-reported information. Symptom severity (0-3 ordinal score), recovery time, and functional outcomes were assessed on Days 0, 3, 5, and 7. Continuous variables were compared using the independent-samples t test, categorical variables using the chi-square or Fisher exact test, and changes over time using a repeated-measures general linear model. Statistical significance was accepted as a two-sided p value of < 0.05. Results: In this study including 128 pediatric patients, there were no significant differences between the combined polyphenol and control groups in demographic or baseline clinical characteristics (p>0.05). During follow-up, all symptom scores improved more rapidly and markedly in the combined polyphenol group than in the control group. By Day 3, significant differences were observed between groups in fever, cough, rhinorrhea, sore throat, fatigue, general condition, and physical activity scores (p< 0.001 for all parameters). By Day 5, almost complete resolution of symptoms (score 0) was observed in the combined polyphenol group, whereas symptoms persisted to a substantial extent in the control group (p< 0.001). The time to fever resolution was significantly shorter in the combined polyphenol group (1.84±0.72 days vs 4.5±1.36 days; p< 0.001). Similarly, time to return to school (3.21±0.9 days vs 5.8±1.91 days; p< 0.001) and time for parents to return to work were significantly shorter in the combined polyphenol group (p< 0.001). The need for additional healthcare visits and antipyretic use was markedly lower in the combined polyphenol group (Day 3: 20.3% vs. 53.1%; Day 5: 0% vs. 15.6%; p< 0.001 for both comparisons). Repeated-measures analyses showed a significant time-by-group interaction, indicating that the reduction in symptom scores occurred more rapidly and prominently in the combined polyphenol group (p< 0.001). Treatment was generally well tolerated in the combined polyphenol group; no serious adverse events were reported, and parent-reported tolerability was high (9.39±0.7). Conclusion: This multicenter retrospective real-world data study shows that the preparation containing polyphenol, vitamin D3, vitamin C, and zinc added to antiviral therapy significantly reduces symptom duration and severity, accelerates clinical recovery, and markedly decreases healthcare utilization in children diagnosed with influenza. These findings suggest that this combination may represent an effective and well-tolerated adjuvant treatment option in the management of pediatric influenza.