Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning methods on the Surveillance, Epidemiology, and End Results (SEER) database to forecast the risk probability of distant metastasis. Therefore, the information on UM patients from the SEER database (2000-2020) was split into a 7:3 ratio training set and an internal test set based on distant metastasis presence. Univariate and multivariate logistic regression analyses assessed distant metastasis risk factors. Six machine learning methods constructed a predictive model post-feature variable selection. The model evaluation identified the multilayer perceptron (MLP) as optimal. Shapley additive explanations (SHAP) interpreted the chosen model. A web-based calculator personalized risk probabilities for UM patients. The results show that nine feature variables contributed to the machine learning model. The MLP model demonstrated superior predictive accuracy (Precision = 0.788; ROC AUC = 0.876; PR AUC = 0.788). Grade recode, age, primary site, time from diagnosis to treatment initiation, and total number of malignant tumors were identified as distant metastasis risk factors. Diagnostic method, laterality, rural-urban continuum code, and radiation recode emerged as protective factors. The developed web calculator utilizes the MLP model for personalized risk assessments. In conclusion, the MLP machine learning model emerges as the optimal tool for predicting distant metastasis in UM patients. This model facilitates personalized risk assessments, empowering early and tailored treatment strategies.

Drug-Related Keratitis: A Real-World FDA Adverse Event Reporting System Database Study.

Purpose: This study aimed to assess the drug risk of drug-related keratitis and track the epidemiological characteristics of drug-related keratitis. Methods: This study analyzed data from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database from January 2004 to December 2023. A disproportionality analysis was conducted to assess drug-related keratitis with positive signals, and drugs were classified and assessed with regard to their drug-induced timing and risk of drug-related keratitis. Results: A total of 1606 drugs were reported to pose a risk of drug-related keratitis in the FAERS database, and, after disproportionality analysis and screening, 17 drugs were found to significantly increase the risk of drug-related keratitis. Among them, seven were ophthalmic medications, including dorzolamide (reporting odds ratio [ROR] = 3695.82), travoprost (ROR = 2287.27), and brimonidine (ROR = 2118.52), and 10 were non-ophthalmic medications, including tralokinumab (ROR = 2609.12), trazodone (ROR = 2377.07), and belantamab mafodotin (ROR = 680.28). The top three drugs having the highest risk of drug-related keratitis were dorzolamide (Bayesian confidence propagation neural network [BCPNN] = 11.71), trazodone (BCPNN = 11.11), and tralokinumab (BCPNN = 11.08). The drug-induced times for non-ophthalmic medications were significantly shorter than those for ophthalmic medications (mean days, 141.02 vs. 321.96, respectively; P < 0.001). The incidence of drug-related keratitis reached its peak in 2023. Conclusions: Prevention of drug-related keratitis is more important than treatment. Identifying the specific risks and timing of drug-induced keratitis can support the development of preventive measures. Translational Relevance: Identifying the specific drugs related to medication-related keratitis is of significant importance for drug vigilance in the occurrence of drug-related keratitis.

Psychometric validation of the Chinese version of the dry eye-related quality-of-life score questionnaire.

AIM: To psychometrically validate the Chinese version of the dry eye-related quality-of-life score questionnaire (DEQS-CHN) among Chinese patients with dry eye. METHODS: This study involved 231 participants, including 191 with dry eye disease (DED) comprising the dry eye disease group, and 40 healthy participants forming the control group. Participants were required to complete the DEQS-CHN, and Chinese dry eye questionnaire and undergo clinical tests including the fluorescein breakup time (FBUT), corneal fluorescein staining (CFS), and Schirmer I test. To assess the internal consistency and retest reliability, Cronbach's α and the intraclass correlation coefficient (ICC) were employed. Content validity was assessed by item-level content validity index (ICV) and an average scale-level content validity index (S-CVI/Ave). Construct validity was assessed by confirmatory factor analysis. The concurrent validity was assessed by calculating correlations between DEQS-CHN and Chinese dry eye questionnaire. Discriminative validity was evaluated through non-parametric tests, with receiver operating characteristic (ROC) curve serving as conclusive indicators of the questionnaire's distinguishing capability. RESULTS: The Cronbach's α coefficients for frequency and degree of ocular symptoms, impact on daily life, and summary score were 0.736, 0.704, 0.811, 0.818, 0.861, and 0.860, respectively, and the ICC were 0.611, 0.677, 0.715, 0.769, 0.711, and 0.779, respectively. All I-CVI scores ranged from 0.833 to 1.000, with an S-CVI/Ave of 0.956. Confirmatory factor analysis results exhibited a well-fitting model consistent with the original questionnaire [χ 2/df=2.653, incremental fit index (IFI)=0.924, comparative fit index (CFI)=0.924, Tucker-Lewis index (TLI)=0.909, and root mean square error of approximation (RMSEA)=0.065]. There was a moderate positive correlation between the DEQS-CHN and the Chinese dry eye questionnaire (r 2=0.588). The dry eye group demonstrated significantly higher scores compared to the control group, and the area under the curve (AUC) value was 0.8092. CONCLUSION: The DEQS-CHN has been demonstrated as a valid and reliable instrument for assessing the impact of dry eye disease on the quality of life among Chinese individuals with DED.

[Analysis of 12 cases of fetal malformation in forensic medical malpractice].

OBJECTIVE: To explore the main reasons of medical malpractice of fetal abnormalities and to analyze the key points and the ideas in judicial appraisal. METHODS: According to the related laws, regulations and clinical practice guidelines, the medical faults and the contribution degree in 12 medical malpractice cases about fetal abnormalities were analyzed. RESULTS: There were medical faults in five cases. Among them, the doctors did not fulfill the duty of inform in 2 cases, did not analyze the abnormal results comprehensively in 2 cases, did not have qualified medical conditions and normative reports in 1 case. The hospitals needed to take the minor responsibility in 2 cases and slight responsibility in 2 cases. CONCLUSION: The key points in the judicial appraisal are whether the doctors abide by the related laws, regulations and clinical practice guidelines in prenatal examination, screen and diagnosis, and whether the doctors realize the limitations of ultrasonic testing and fulfill the obligation of inform.