This meta-analysis aims to screen the risk factors for severe illness and death and provide help for early clinical treatment of the new coronavirus (COVID-19). Based on a comprehensive search of PubMed, Embase, and Web of Science databases, we included studies that explored the cause and risk factors for severe illness and death in COVID-19 patients. We evaluated the strength of this relationship using odds ratios (ORs) with 95% confidence intervals (CIs). A total of 17 articles were included; 16 of the 17 articles were from China, and the risk factors associated with severe illness and death were age, sex, and multiple comorbidities. Advanced age (≥65 years, severe illness, OR = 2.62; death, OR = 6.00), male (severe illness, OR = 1.49; death, OR = 1.54), chronic respiratory diseases (severe illness, OR = 5.67; death, OR = 3.72), diabetes (severe illness, OR = 3.27; death, OR = 2.60), hypertension (severe illness, OR = 3.08; death, OR = 3.53), chronic kidney disease (severe illness, OR = 3.59; death, OR = 5.38), and cardiovascular diseases (severe illness, OR = 3.87; death, OR = 4.91) were all risk factors. For COVID-19 patients, advanced age, male, and patients with chronic disease are at higher risk of developing severe illness or even death.

Background: Generative artificial intelligence (AI) systems are increasingly deployed in clinical pharmacy; yet, systematic evaluation of their efficacy, limitations, and risks across diverse practice scenarios remains limited. Objective: This study aims to quantitatively evaluate and compare the performance of 8 mainstream generative AI systems across 4 core clinical pharmacy scenarios—medication consultation, medication education, prescription review, and case analysis with pharmaceutical care—using a multidimensional framework. Methods: Forty-eight clinically validated questions were selected via stratified sampling from real-world sources (eg, hospital consultations, clinical case banks, and national pharmacist training databases). Three researchers simultaneously tested 8 different generative AI systems (ERNIE Bot, Doubao, Kimi, Qwen, GPT-4o, Gemini-1.5-Pro, Claude-3.5-Sonnet, and DeepSeek-R1) using standardized prompts within a single day (February 20, 2025). A double-blind scoring design was used, with 6 experienced clinical pharmacists (≥5 years experience) evaluating the AI responses across 6 dimensions: accuracy, rigor, applicability, logical coherence, conciseness, and universality, scored 0‐10 per predefined criteria (eg, −3 for inaccuracy and −2 for incomplete rigor). Statistical analysis used one-way ANOVA with Tukey Honestly Significant Difference (HSD) post hoc testing and intraclass correlation coefficients (ICC) for interrater reliability (2-way random model). Qualitative thematic analysis identified recurrent errors and limitations. Results: DeepSeek-R1 (DeepSeek) achieved the highest overall performance (mean composite score: medication consultation 9.4, SD 1.0; case analysis 9.3, SD 1.0), significantly outperforming others in complex tasks (P<.05). Critical limitations were observed across models, including high-risk decision errors—75% omitted critical contraindications (eg, ethambutol in optic neuritis) and a lack of localization—90% erroneously recommended macrolides for drug-resistant Mycoplasma pneumoniae (China’s high-resistance setting), while only DeepSeek-R1 aligned with updated American Academy of Pediatrics (AAP) guidelines for pediatric doxycycline. Complex reasoning deficits: only Claude-3.5-Sonnet detected a gender-diagnosis contradiction (prostatic hyperplasia in female); no model identified diazepam’s 7-day prescription limit. Interrater consistency was lowest for conciseness in case analysis (ICC=0.70), reflecting evaluator disagreement on complex outputs. ERNIE Bot (Baidu) consistently underperformed (case analysis: 6.8, SD 1.5; P<.001 vs DeepSeek-R1). Conclusions: While generative AI shows promise as a pharmacist assistance tool, significant limitations—including high-risk errors (eg, contraindication omissions), inadequate localization, and complex reasoning gaps—preclude autonomous clinical decision-making. Performance stratification highlights DeepSeek-R1’s current advantage, but all systems require optimization in dynamic knowledge updating, complex scenario reasoning, and output interpretability. Future deployment must prioritize human oversight (human-AI co-review), ethical safeguards, and continuous evaluation frameworks.

Objectives: The UGT1A1*28 allele in HIV-positive patients receiving atazanavir(ATV) might be associated with the risk of hyperbilirubinemia. Owing to mixed and inconclusive results, a meta-analysis was conducted to systematically summarize and clarify this association. Methods: Based on a comprehensive search of PubMed, Embase and Web of Science databases, studies investigating the association between UGT1A1 alleles and hyperbilirubinemia were retrieved. We evaluated the strength of this relationship using odds ratios (ORs) with 95% confidence intervals (CIs). Sensitivity analysis was performed by removing each study one at a time and calculating the pooled ORs of the remaining studies to test the robustness of the meta-analysis results. The Q statistic and the I² index statistic were used to assess heterogeneity. Publication bias was evaluated using Orwin's fail-safe N test. Results: A total of 6 individual studies were included in this meta-analysis. A significant increased risk of hyperbilirubinemia was observed in HIV-positive patients receiving ATV with the UGT1A1*1/*28 or UGT1A1*28/*28 genotype, and the risk was higher with the UGT1A1*28/*28 genotype than with the UGT1A1*1/*28 genotype. (UGT1A1*28/*28 versus UGT1A1*1/*28: OR = 3.69, 95%CI = 1.82 - 7.49; UGT1A1*1/*28 versus UGT1A1*1/*1: OR = 3.50, 95%CI = 1.35 - 9.08; UGT1A1*28/*28 versus UGT1A1*1/*1: OR = 10.07, 95%CI = 4.39 - 23.10). All of the pooled ORs were not significantly affected by the remaining studies and different modeling methods, indicating robust results. Conclusions: This meta-analysis suggests that the UGT1A1*28 allele represents a biomarker for an increased risk of hyperbilirubinemia in HIV-positive patients receiving ATV.

What is known and objectives The association between inosine triphosphatase (ITPA) rs1127354 polymorphisms in HCV‐infected patients receiving ribavirin (RBV)‐based therapy, and the risk of adverse drug reaction and outcomes is still unclear. A meta‐analysis was conducted to summarize and clarify this association systematically. Methods A comprehensive search was performed in PubMed, Embase and Web of Sciences, and twenty‐two studies were selected from the literature search. Pooled odds ratio (OR) and 95% confidence interval (95% CI) were estimated by either fixed‐ or random‐effects models. Results Four outcomes were evaluated: (a) haemoglobin decline: significant associations with haemoglobin decline were found for rs1127354 CC VS CA + AA (OR = 10.59, 95% CI = 6.39‐17.54); (b) severe anaemia: significant association with severe anaemia was observed for rs1127354 CC VS CA + AA (OR = 16.24, 95% CI = 6.21‐42.43); (c) sustained virological response (SVR): CC genotype carriers had a decrease SVR during treatment (OR = 0.65, 95% CI = 0.52‐0.81); (d) RBV dose reduction or stopping treatment: although statistical evidence of an association was found between the polymorphism and RBV dose reduction during treatment (OR = 1.80, 95% CI = 1.03‐3.13), the sensitivity analysis suggested this result was not robust. What is new and conclusion Patients with ITPA rs1127354 CC polymorphism are more likely to develop haemolytic anaemia, severe anaemia and decreased SVR. Testing for this genetic polymorphism may benefit patients.

Objective: To determine the causative gene mutation in a family with monilethrix and observe the therapeutic effect of 5% topical minoxidil.Method: Clinical data from a family with monilethrix were collected. Peripheral blood samples were taken from the proband, the parents, and 100 unrelated healthy controls. Genomic DNA was extracted. The genetic variation sites were screened with exome sequencing and verified by Sanger sequencing. The proband was treated with 5% topical minoxidil (1 mL twice daily). Hair quality was examined by dermoscopy before and after treatment.Results: The proband and her father have the heterozygous missense variant c.1204G > A (p.E402K) in exon 7 of theKRT86gene. However, the mutation was not found in the mother and healthy controls. The proband was treated with 5% topical minoxidil. Hair density and hair shaft quality improved significantly after 6 months of treatment. No adverse events occurred during treatment.Conclusion: This study shows that p.E402K is a mutation “hot spot” in patients with autosomal dominant monilethrix in China. Treatment with 5% topical minoxidil, is safe and effective.