Using transfer learning-based causality extraction to mine latent factors for Sjögren's syndrome from biomedical literature

Secondary Sjögren's syndrome in a rheumatoid arthritis patient: A case report and review of literature

Secondary Sjogren's syndrome (sSS) is a medical condition that occurs in individuals with autoimmune diseases such as systemic lupus erythematosus (SLE) and rheumatoid arthritis. It predominantly affects females rather than males. We present a case of a 32-year-old female with a 3-year history of rheumatoid arthritis (RA) who presented to the internal medicine and rheumatology clinic with several complaints, including swelling and tenderness in her left jaw, dry mouth (xerostomia), irritated eyes (xerophthalmia), severe joint pain, and a decreased in saliva production. The blood tests demonstrate the presence of anti-SSA and anti-SSB autoantibodies and elevation of total leukocyte count (TLC), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) levels, indicating inflammation. A high-frequency ultrasound confirmed the diagnosis of Secondary Sjogren's syndrome grade II, specifically affecting the left parotid gland (PG).

Advancing rheumatology with natural language processing: insights and prospects from a systematic review

Objectives

Natural language processing (NLP) and large language models (LLMs) have emerged as powerful tools in healthcare, offering advanced methods for analysing unstructured clinical texts. This systematic review aims to evaluate the current applications of NLP and LLMs in rheumatology, focusing on their potential to improve disease detection, diagnosis and patient management.

Methods

We screened seven databases. We included original research articles that evaluated the performance of NLP models in rheumatology. Data extraction and risk of bias assessment were performed independently by two reviewers, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used to evaluate the risk of bias.

Results

Of 1491 articles initially identified, 35 studies met the inclusion criteria. These studies utilized various data types, including electronic medical records and clinical notes, and employed models like Bidirectional Encoder Representations from Transformers and Generative Pre-trained Transformers. High accuracy was observed in detecting conditions such as RA, SpAs and gout. The use of NLP also showed promise in managing diseases and predicting flares.

Conclusion

NLP showed significant potential in enhancing rheumatology by improving diagnostic accuracy and personalizing patient care. While applications in detecting diseases like RA and gout are well developed, further research is needed to extend these technologies to rarer and more complex clinical conditions. Overcoming current limitations through targeted research is essential for fully realizing NLP's potential in clinical practice.

Survival analysis of posterior composite restorations in National Dental PBRN general dentistry practices

OBJECTIVE

Quantify the survival of posterior composite restorations (PCR) placed during the study period in permanent teeth in United States (US) general dental community practices and factors predictive of that survival.

METHODS

A retrospective cohort study was conducted utilizing de-identified electronic dental record (EDR) data of patients who received a PCR in 99 general dentistry practices in the National Dental Practice-Based Research Network (Network). The final analyzed data set included 700,885 PCRs from 200,988 patients. Descriptive statistics and Kaplan Meier (product limit) estimator were performed to estimate the survival rate (defined as the PCR not receiving any subsequent treatment) after the first PCR was observed in the EDR during the study time. The Cox proportional hazards model was done to account for patient- and tooth-specific covariates.

RESULTS

The overall median survival time was 13.3 years. The annual failure rates were 4.5-5.8 % for years 1-5; 5.3-5.7 %, 4.9-5.5 %, and 3.3-5.2 % for years 6-10, 11-15, and 16-20, respectively. The failure descriptions recorded for < 7 % failures were mostly caries (54 %) and broken or fractured tooth/restorations (23 %). The following variables significantly predicted PCR survival: number of surfaces that comprised the PCR; having at least one interproximal surface; tooth type; type of prior treatment received on the tooth; Network region; patient age and sex. Based on the magnitude of the multivariable estimates, no single factor predominated.

CONCLUSIONS

This study of Network practices geographically distributed across the US observed PCR survival rates and predictive factors comparable to studies done in academic settings and outside the US.

CLINICAL SIGNIFICANCE

Specific baseline factors significantly predict the survival of PCRs done in US community dental practices.