7 research outputs found
Clinical Text Deduplication Practices for Efficient Pretraining and Improved Clinical Tasks
Despite being a unique source of information on patients' status and disease
progression, clinical notes are characterized by high levels of duplication and
information redundancy. In general domain text, it has been shown that
deduplication does not harm language model (LM) pretraining, thus helping
reduce the training cost. Although large LMs have proven to learn medical
knowledge, they still require specialized domain adaptation for improved
downstream clinical tasks. By leveraging large real-world clinical corpora, we
first provided a fine-grained characterization of duplicates stemming from
common writing practices and clinical relevancy. Second, we demonstrated that
deduplicating clinical text can help clinical LMs encode less redundant
information in a more efficient manner and do not harm classification tasks via
prompt-based learning
Extracting Social Support and Social Isolation Information from Clinical Psychiatry Notes: Comparing a Rule-based NLP System and a Large Language Model
Background: Social support (SS) and social isolation (SI) are social
determinants of health (SDOH) associated with psychiatric outcomes. In
electronic health records (EHRs), individual-level SS/SI is typically
documented as narrative clinical notes rather than structured coded data.
Natural language processing (NLP) algorithms can automate the otherwise
labor-intensive process of data extraction.
Data and Methods: Psychiatric encounter notes from Mount Sinai Health System
(MSHS, n=300) and Weill Cornell Medicine (WCM, n=225) were annotated and
established a gold standard corpus. A rule-based system (RBS) involving
lexicons and a large language model (LLM) using FLAN-T5-XL were developed to
identify mentions of SS and SI and their subcategories (e.g., social network,
instrumental support, and loneliness).
Results: For extracting SS/SI, the RBS obtained higher macro-averaged
f-scores than the LLM at both MSHS (0.89 vs. 0.65) and WCM (0.85 vs. 0.82). For
extracting subcategories, the RBS also outperformed the LLM at both MSHS (0.90
vs. 0.62) and WCM (0.82 vs. 0.81).
Discussion and Conclusion: Unexpectedly, the RBS outperformed the LLMs across
all metrics. Intensive review demonstrates that this finding is due to the
divergent approach taken by the RBS and LLM. The RBS were designed and refined
to follow the same specific rules as the gold standard annotations. Conversely,
the LLM were more inclusive with categorization and conformed to common
English-language understanding. Both approaches offer advantages and are made
available open-source for future testing.Comment: 2 figures, 3 table
Auto-antibodies against P/Q- and N-type voltage-dependent calcium channels mimicking frontotemporal dementia
The behavioral variant of frontotemporal dementia is usually a sporadic and progressive neurodegenerative disorder. Here, we report the subacute onset of a frontotemporal dementia phenotype with a treatable etiology. The patient has a history of rheumatoid arthritis, episcleritis, and thyroid eye disease on immunosuppressive therapy. He experienced a rapid personality change, including inappropriate behavior, which suggested frontotemporal dementia. Results of imaging and neuropsychological testing also suggested frontotemporal dementia. Because of his autoimmune diseases and unusually short onset of symptoms, serum paraneoplastic panel and cerebrospinal fluid were analyzed and revealed elevated P/Q- and N-type calcium channel antibodies. Treatment with therapeutic plasma exchange resulted in a rapid improvement of his behavior and cognition. This case suggests that there may be some treatable causes of frontotemporal dementia symptomatology, that is, paraneoplastic antibodies. In the context of atypical features of frontotemporal dementia, practitioners should maintain a high index of suspicion
Social connectedness as a determinant of mental health: A scoping review.
Public health and epidemiologic research have established that social connectedness promotes overall health. Yet there have been no recent reviews of findings from research examining social connectedness as a determinant of mental health. The goal of this review was to evaluate recent longitudinal research probing the effects of social connectedness on depression and anxiety symptoms and diagnoses in the general population. A scoping review was performed of PubMed and PsychInfo databases from January 2015 to December 2021 following PRISMA-ScR guidelines using a defined search strategy. The search yielded 66 unique studies. In research with other than pregnant women, 83% (19 of 23) studies reported that social support benefited symptoms of depression with the remaining 17% (5 of 23) reporting minimal or no evidence that lower levels of social support predict depression at follow-up. In research with pregnant women, 83% (24 of 29 studies) found that low social support increased postpartum depressive symptoms. Among 8 of 9 studies that focused on loneliness, feeling lonely at baseline was related to adverse outcomes at follow-up including higher risks of major depressive disorder, depressive symptom severity, generalized anxiety disorder, and lower levels of physical activity. In 5 of 8 reports, smaller social network size predicted depressive symptoms or disorder at follow-up. In summary, most recent relevant longitudinal studies have demonstrated that social connectedness protects adults in the general population from depressive symptoms and disorders. The results, which were largely consistent across settings, exposure measures, and populations, support efforts to improve clinical detection of high-risk patients, including adults with low social support and elevated loneliness
Molecular states during acute COVID-19 reveal distinct etiologies of long-term sequelae.
Post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are debilitating, clinically heterogeneous and of unknown molecular etiology. A transcriptome-wide investigation was performed in 165 acutely infected hospitalized individuals who were followed clinically into the post-acute period. Distinct gene expression signatures of post-acute sequelae were already present in whole blood during acute infection, with innate and adaptive immune cells implicated in different symptoms. Two clusters of sequelae exhibited divergent plasma-cell-associated gene expression patterns. In one cluster, sequelae associated with higher expression of immunoglobulin-related genes in an anti-spike antibody titer-dependent manner. In the other, sequelae associated independently of these titers with lower expression of immunoglobulin-related genes, indicating lower non-specific antibody production in individuals with these sequelae. This relationship between lower total immunoglobulins and sequelae was validated in an external cohort. Altogether, multiple etiologies of post-acute sequelae were already detectable during SARS-CoV-2 infection, directly linking these sequelae with the acute host response to the virus and providing early insights into their development
Downregulation of exhausted cytotoxic T cells in gene expression networks of multisystem inflammatory syndrome in children.
Multisystem inflammatory syndrome in children (MIS-C) presents with fever, inflammation and pathology of multiple organs in individuals under 21 years of age in the weeks following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Although an autoimmune pathogenesis has been proposed, the genes, pathways and cell types causal to this new disease remain unknown. Here we perform RNA sequencing of blood from patients with MIS-C and controls to find disease-associated genes clustered in a co-expression module annotated to CD56dimCD57+ natural killer (NK) cells and exhausted CD8+ T cells. A similar transcriptome signature is replicated in an independent cohort of Kawasaki disease (KD), the related condition after which MIS-C was initially named. Probing a probabilistic causal network previously constructed from over 1,000 blood transcriptomes both validates the structure of this module and reveals nine key regulators, including TBX21, a central coordinator of exhausted CD8+ T cell differentiation. Together, this unbiased, transcriptome-wide survey implicates downregulation of NK cells and cytotoxic T cell exhaustion in the pathogenesis of MIS-C