Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 163
Filtrar
1.
Artigo em Inglês | MEDLINE | ID: mdl-34633450

RESUMO

CONTEXT: Antenatal hyperglycemia is associated with increased risk of future adverse health outcomes in both mother and child. Variations in offspring's epigenome can reflect the impact and response to in utero glycemic exposure, and may have different consequences for the child. OBJECTIVE: We examined possible differences in associations of basal glucose status and glucose handling during pregnancy with both clinical covariates and offspring cord tissue DNA methylation. RESEARCH DESIGN AND METHODS: This study included 830 mother-offspring dyads from the GUSTO cohort. The fetal epigenome of umbilical cord tissue was profiled using Illumina HumanMethylation450 arrays. Associations of maternal mid-pregnancy fasting (FPG) and 2h plasma glucose (2hPG) post-75g oral glucose challenge (OGTT) with both maternal clinical phenotypes and offspring epigenome at delivery were investigated separately. RESULTS: Maternal age, pre-pregnancy BMI and blood pressure measures were associated with both FPG and 2hPG; while Chinese ethnicity (p=1.9×10 -4), maternal height (p=1.1×10 -4), pregnancy weight gain (p=2.2×10 -3), pre-pregnancy alcohol consumption (p=4.6×10 -4), and tobacco exposure (p=1.9×10 -3) showed significantly opposite associations between the two glucose measures. Most importantly, we observed a dichotomy in the effects of these glycemic indices on the offspring epigenome. Offspring born to mothers with elevated 2hPG showed global hypomethylation. CpGs most associated with the two glucose measures also reflected differences in gene ontologies and had different associations with offspring birthweight. CONCLUSIONS: Our findings suggest that two traditionally used glycemic indices for diagnosing gestational diabetes may reflect distinctive pathophysiologies in pregnancy, and have differential impacts on the offspring's DNA methylome.

2.
Artigo em Inglês | MEDLINE | ID: mdl-34613399

RESUMO

OBJECTIVE: Social determinants of health (SDoH) are nonclinical dispositions that impact patient health risks and clinical outcomes. Leveraging SDoH in clinical decision-making can potentially improve diagnosis, treatment planning, and patient outcomes. Despite increased interest in capturing SDoH in electronic health records (EHRs), such information is typically locked in unstructured clinical notes. Natural language processing (NLP) is the key technology to extract SDoH information from clinical text and expand its utility in patient care and research. This article presents a systematic review of the state-of-the-art NLP approaches and tools that focus on identifying and extracting SDoH data from unstructured clinical text in EHRs. MATERIALS AND METHODS: A broad literature search was conducted in February 2021 using 3 scholarly databases (ACL Anthology, PubMed, and Scopus) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 6402 publications were initially identified, and after applying the study inclusion criteria, 82 publications were selected for the final review. RESULTS: Smoking status (n = 27), substance use (n = 21), homelessness (n = 20), and alcohol use (n = 15) are the most frequently studied SDoH categories. Homelessness (n = 7) and other less-studied SDoH (eg, education, financial problems, social isolation and support, family problems) are mostly identified using rule-based approaches. In contrast, machine learning approaches are popular for identifying smoking status (n = 13), substance use (n = 9), and alcohol use (n = 9). CONCLUSION: NLP offers significant potential to extract SDoH data from narrative clinical notes, which in turn can aid in the development of screening tools, risk prediction models, and clinical decision support systems.

3.
J Cardiothorac Surg ; 16(1): 307, 2021 Oct 18.
Artigo em Inglês | MEDLINE | ID: mdl-34663408

RESUMO

BACKGROUND: Bronchiolar adenoma (BA) is a recently proposed diagnostic terminology, which is considered as the expansion of the concept of ciliated muconodular papillary tumors. BA is considered to be a benign neoplasm, but a few previous cases have been reported with the possibility of malignant transformation. Therefore, the genetic and histological nature of BA is controversial so far. We describe a rare case of multiple BAs with malignant transformation and CCNE1 (cyclin E1) mutation to increase the understanding of this disease. CASE DESCRIPTION: A 56-year-old woman was admitted to our hospital due to two ground-glass nodules (GGNs) in the left lung detected by chest CT without symptom. The pure GGN located in the upper lingual segment about 6 mm in diameter and another mixed GGN located in the dorsal segment about 7 mm. The two GGNs have been found a year ago without treatment, and the mixed GGN become larger to 8 mm with vacuole sign in the next year health checkup. We performed a wedge resection of the two nodules completely by video-assisted thoracoscopy (VATS). Postoperative pathology indicated that the pure GGN was atypical bronchial adenoma, while the mixed GGN was atypical bronchial adenoma with malignant transformation which was missed in frozen section. Gene mutations analysis by next-generation sequencing (NGS) showed CCNE1 gene mutation in both lesions, and her-2 mutation was identified in the mixed GGN. The programmed cell death 1 ligand 1 (PD-L1) expression analysis of tumor cells showed 0% and less than 1% in the pure GGN and the mixed GGN, respectively. CONCLUSION: BA is generally considered to be a benign tumor. The present study indicated that BA may be carcinogenic in atypical cases with some driver genes mutation and we should be vigilant for its potentiality of malignant transformation in clinical practice.

4.
Gut ; 2021 Sep 06.
Artigo em Inglês | MEDLINE | ID: mdl-34489308

RESUMO

OBJECTIVE: The absent in melanoma 2 (AIM2) cytosolic pattern recognition receptor and DNA sensor promotes the pathogenesis of autoimmune and chronic inflammatory diseases via caspase-1-containing inflammasome complexes. However, the role of AIM2 in cancer is ill-defined. DESIGN: The expression of AIM2 and its clinical significance was assessed in human gastric cancer (GC) patient cohorts. Genetic or therapeutic manipulation of AIM2 expression and activity was performed in the genetically engineered gp130 F/F spontaneous GC mouse model, as well as human GC cell line xenografts. The biological role and mechanism of action of AIM2 in gastric tumourigenesis, including its involvement in inflammasome activity and functional interaction with microtubule-associated end-binding protein 1 (EB1), was determined in vitro and in vivo. RESULTS: AIM2 expression is upregulated by interleukin-11 cytokine-mediated activation of the oncogenic latent transcription factor STAT3 in the tumour epithelium of GC mouse models and patients with GC. Genetic and therapeutic targeting of AIM2 in gp130 F/F mice suppressed tumourigenesis. Conversely, AIM2 overexpression augmented the tumour load of human GC cell line xenografts. The protumourigenic function of AIM2 was independent of inflammasome activity and inflammation. Rather, in vivo and in vitro AIM2 physically interacted with EB1 to promote epithelial cell migration and tumourigenesis. Furthermore, upregulated expression of AIM2 and EB1 in the tumour epithelium of patients with GC was independently associated with poor patient survival. CONCLUSION: AIM2 can play a driver role in epithelial carcinogenesis by linking cytokine-STAT3 signalling, innate immunity and epithelial cell migration, independent of inflammasome activation.

5.
Neurochem Int ; 150: 105191, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-34547325

RESUMO

Spinal cord ischemia-reperfusion injury (SCIRI) can cause dramatic neuron loss and lead to paraplegia in patients. In this research, the role of mGluR5, a member of the metabotropic glutamate receptors (mGluRs) family, was investigated both in vitro and in vivo to explore a possible method to treat this complication. In vitro experiment, after activating mGluR5 via pretreating cells with (RS)-2-Chloro-5-hydroxyphenylglycine (CHPG) and 3-cyano-N-(1,3-diphenyl-1H-pyrazol-5-yl) benzamide (CDPPB), excitotoxicity induced by glutamate (Glu) was attenuated in primary spinal cord neurons, evidenced by higher neuron viability, decreased lactate dehydrogenase (LDH) release and less detected TUNEL-positive cells. According to Western Blot (WB) results, Glu treatment resulted in a high level of large-conductance Ca2+- and voltage-activated K+ (BK) channels, with activation relying on the mGluR5-IP3R (inositol triphosphate) pathway. In vivo part, a rat model of SCIRI was built to further investigate the role of mGluR5. After pretreating them with CHPG and CDPPB, the rats showed markedly lower spinal water content, attenuated motor neuron injury in the spinal cord of L4 segments, and better neurological function. This effect could be partially reversed by paxilline, a blocker of BK channels. In addition, activating BK channels alone using specific openers: NS1619 or NS11021 can protect spinal cord neurons from injury induced by either SCIRI or Glu. In conclusion, in this research, we proved that mGluR5 exerts a protective role in SCIRI, and this effect partially works via IP3R-mediated activation of BK channels.

6.
Small ; 17(37): e2101333, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34378317

RESUMO

With the popularity of portable and miniaturized electronic devices in people's live, flexible piezoelectric nanogenerators (PENG) have become a research hotspot for harvesting energy from the living environment to power small-scale electronic equipment and systems because of its stability. For further enhancing output performance of PENG, chemical modification and structural design for piezoelectric fillers are effective ways. Thus, the 3D porous hetero-structure fillers of BCZT@Ag are prepared by freeze-drying method and subsequent chemical seeding reduction. The silicone rubber as matrix is filled into the micro-voids of fillers to prepare specialized composite. The charge transport mechanism and stress transfer efficiency in PENG can be effectively improved through specialized design which is proven by experimental results and multi-physics simulations. The improved PENG exhibit a significantly enhanced output of 38.6 V and 5.85 µA, which is 3.3 and 3.5 times higher than those of PENG without specific design. The prepared PENG can effectively harvest biomechanical energy through walk and joint bending of human body. Moreover, the PENG can be used as a trigger to remotely control wireless collision alarm system, which can acquire rapid response and shows great potential application in Internet of Things.

7.
J Cardiothorac Surg ; 16(1): 192, 2021 Jul 07.
Artigo em Inglês | MEDLINE | ID: mdl-34233697

RESUMO

INTRODUCTION: Chondroblastoma is a rare, benign locally but aggressive bone tumor. It accounts for < 1% of primary bony tumors, and mostly arises from long bones; the rib chondroblastoma is especial rare. Due to its rarity, there are no definitive or standard treatment guidelines. CASE PRESENTATION: A case of a 24-year-old male with a chondroblastoma located on the 6th posterior left rib. Computed tomography (CT) demonstrated a rib tumor that was a well-defined oval lesion of 20 mm × 18 mm, with lytic bone destruction. The imaging first diagnosis was Langerhans cell histiocytosis (LCH), a giant cell tumor, or other type of neoplasm. The whole tumor and a part of partial rib were resected by video-assisted thoracoscopy surgery (VATS). Pathological and immunohistochemical (IHC) examination made a diagnosis of chondroblastoma. Compared with traditional open thoracic surgery, VATS can achieve the same effects and cause less injury to patient. No postoperative adjuvant therapy was given, and had followed up 23 months after surgery, there was no recurrence or metastasis. CONCLUSION: Chondroblastoma has a risk of recurrence and metastasis, surgery plays an important role in the treatment of chondroblastoma, VATS can achieve the same outcome as traditional open thoracic surgery with less pain and lung function. Close follow-up is needed postoperative.


Assuntos
Neoplasias Ósseas/cirurgia , Condroblastoma/cirurgia , Cirurgia Torácica Vídeoassistida , Neoplasias Ósseas/diagnóstico por imagem , Neoplasias Ósseas/patologia , Condroblastoma/diagnóstico por imagem , Condroblastoma/patologia , Humanos , Masculino , Recidiva Local de Neoplasia , Radiografia Torácica , Costelas , Tomografia Computadorizada por Raios X , Adulto Jovem
8.
Medicine (Baltimore) ; 100(26): e26449, 2021 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-34190169

RESUMO

RATIONALE: Anaplastic lymphoma kinase (ALK) inhibitors have been approved for patients with ALK-rearrangement lung cancer. The effect is superior to the standard first-line therapy of pemetrexed plus platinum-based chemotherapy. However, ALK inhibitors are associated with rare and sometimes fatal adverse events. Organizing pneumonitis (OP) is a rare and serious adverse event usually caused by ceritinib, and it is easily misdiagnosed as infectious pneumonia, metastasis, or cancer progression. PATIENT CONCERNS: A 56-year-old female presented with chest tightness and dyspnea for more than 10 days. She was previously healthy with no significant medical history. Workup including chest computed tomography (CT), pathological examination of a biopsy specimen, and next-generation sequencing was consistent with a diagnosis of IVA ALK-rearrangement lung adenocarcinoma. She was treated with pemetrexed plus platinum-based chemotherapy and crizotinib concurrently, followed by maintenance therapy with crizotinib alone and she had an almost complete response. However, about 26 months after beginning treatment she developed multiple brain metastases. Crizotinib was discontinued and she was begun on ceritinib. After about 3 months the brain metastases had almost complete response. After 5 months of ceritinib, however, multiple patchy lesions appeared in the bilateral upper lungs. DIAGNOSES: Treatment with antibiotics had no effect and blood and sputum cultures are negative. A CT-guided biopsy of the upper lung was performed, and pathological hematoxylin-eosin staining and immunohistochemical studies were consistent with OP. INTERVENTIONS: Ceritinib was discontinued, she was begun on prednisone 0.5 mg/kg orally every day, and regular follow-up is necessary. OUTCOMES: CT of the chest 2 and 4 weeks after beginning prednisone showed the lung lesions to be gradually resolving, and she was continued on prednisone for 2 months and gradually reduced the dose of prednisone every 2 weeks. No related adverse events were occurred in patient. LESSONS: OP must be differentiated from infectious pneumonia, metastasis, or cancer progression. The mechanism of OP is still unknown and needs further research. Biopsy plays a role in making a diagnosis of OP. In our patient, discontinuing ceritinib and treating her with prednisone resulted in a good outcome.


Assuntos
Adenocarcinoma de Pulmão , Quinase do Linfoma Anaplásico , Pneumonia em Organização Criptogênica , Neoplasias Pulmonares , Prednisona/administração & dosagem , Pirimidinas , Sulfonas , Adenocarcinoma de Pulmão/tratamento farmacológico , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/patologia , Adenocarcinoma de Pulmão/fisiopatologia , Quinase do Linfoma Anaplásico/antagonistas & inibidores , Quinase do Linfoma Anaplásico/genética , Antineoplásicos/uso terapêutico , Biópsia/métodos , Neoplasias Encefálicas/tratamento farmacológico , Neoplasias Encefálicas/secundário , Crizotinibe/uso terapêutico , Pneumonia em Organização Criptogênica/induzido quimicamente , Pneumonia em Organização Criptogênica/patologia , Pneumonia em Organização Criptogênica/terapia , Substituição de Medicamentos , Inibidores Enzimáticos/administração & dosagem , Inibidores Enzimáticos/efeitos adversos , Feminino , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Pulmão/diagnóstico por imagem , Pulmão/patologia , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/fisiopatologia , Pessoa de Meia-Idade , Pemetrexede/uso terapêutico , Pirimidinas/administração & dosagem , Pirimidinas/efeitos adversos , Sulfonas/administração & dosagem , Sulfonas/efeitos adversos , Tomografia Computadorizada por Raios X/métodos , Resultado do Tratamento
9.
J Cardiovasc Pharmacol ; 77(3): 408-417, 2021 03 01.
Artigo em Inglês | MEDLINE | ID: mdl-33662981

RESUMO

ABSTRACT: Promoting angiogenesis is a critical treatment strategy for ischemic cardiovascular diseases. Shexiang Baoxin Pill (SBP), a traditional Chinese medicine, has been reported to be capable of relieving angina and improve heart function by promoting angiogenesis. The aim of this study was to determine the role of mitochondrial aldehyde dehydrogenase 2 (ALDH2) in SBP-induced angiogenesis. Left femoral artery ligation was performed in wild-type mice (WT) and ALDH2 knockout mice, which were administrated with SBP (20 mg/kg/d) or equal volume saline per day by gastric gavage for 2 weeks. Perfusion recovery, angiogenesis in chronic hind limb ischemia, was significantly improved in the WT + SBP group than in the WT group. However, these beneficial effects were absent in ALDH2 knockout mice. In vitro, hypoxia impaired the ability of proliferation, migration and tube formation, sprouting angiogenesis, and promoted apoptosis in cardiovascular microvascular endothelial cells, whereas the hypoxia damage was restored by SBP. The protective effect of SBP was remarkably weakened by ALDH2 knockdown. Furthermore, SBP suppressed hypoxia-induced ALDH2/protein kinase B (AKT)/mammalian target of rapamycin pathways. In conclusion, this study demonstrated that SBP protected lower limb from ischemia injury through the ALDH2-dependent pathway. The protective mechanism of SBP in cardiovascular microvascular endothelial cells was partly mediated through ALDH2/AKT/mammalian target of rapamycin pathways.

10.
Saudi J Biol Sci ; 2021 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-33686327

RESUMO

This article mainly explores the psychological state of occupational exposure of medical staff in operation room contaminated with novel coronavirus, and provides targeted suggestions for mental health service of medical staff so as to maintain their physical and mental health. On February 28, 2020, a questionnaire survey was conducted using Internet. Nurses, anesthesiologists and surgeons in the operating room of the First Affiliated Hospital of Harbin Medical University from January 2020 to March 2020 were selected as the research objects. The psychological state of medical staff was investigated by SAS and PSS-14. As on February 29, 2020, 301 valid questionnaires and one invalid questionnaire were received. The survey showed that there was anxiety but no moderate or severe anxiety in the occupational behavior of operating room medical staff, while some medical staff had a certain degree of psychological pressure (P < 0.05). The present survey suggested that medical staff was under anxiety and pressure in different degrees in the operation room because of novel coronavirus contamination during occupational activities, much attention is required to improve mental health of medical professionals and to reduce their negative emotions.

11.
Transl Psychiatry ; 11(1): 170, 2021 03 15.
Artigo em Inglês | MEDLINE | ID: mdl-33723212

RESUMO

Canonical transforming growth factor-beta (TGF-ß) signaling exerts neuroprotection and influences memory formation and synaptic plasticity. It has been considered as a new target for the prevention and treatment of depression. This study aimed to examine its modulatory role in linking prenatal maternal depressive symptoms and the amygdala volumes from birth to 6 years of age. We included mother-child dyads (birth: n = 161; 4.5 years: n = 131; 6 years: n = 162) and acquired structural brain images of children at these three time points. Perinatal maternal depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS) questionnaire to mothers at 26 weeks of pregnancy and 3 months postpartum. Our findings showed that the genetic variants of TGF-ß type I transmembrane receptor (TGF-ßRI) modulated the association between prenatal maternal depressive symptoms and the amygdala volume consistently from birth to 6 years of age despite a trend of significance at 4.5 years of age. Children with a lower gene expression score (GES) of TGF-ßRI exhibited larger amygdala volumes in relation to greater prenatal maternal depressive symptoms. Moreover, children with a lower GES of the TGF-ß type II transmembrane receptor (TGF-ßRII), Smad4, and Smad7 showed larger amygdala volumes at 6 years of age in relation to greater prenatal maternal depressive symptoms. These findings support the involvement of the canonical TGF-ß signaling pathway in the brain development of children in the context of in utero maternal environment. Such involvement is age-dependent.


Assuntos
Depressão Pós-Parto , Depressão , Tonsila do Cerebelo , Criança , Pré-Escolar , Feminino , Humanos , Mães , Gravidez , Transdução de Sinais , Fator de Crescimento Transformador beta
12.
Neuropsychopharmacology ; 46(2): 470-477, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-32688365

RESUMO

Inflammatory signaling has a role in sensing intrauterine environment, which may be moderators in altering fetal brain development upon maternal environment. This study integrated cytokine transcriptome of post-mortem fetal brains, neonatal brain imaging and genetic variants (n = 161) to examine whether cytokines are candidates for modulating the relationship between prenatal maternal depression and fetal brain development. This study obtained the transcriptome data of 208 cytokine genes in 12 fetal brain regions from the BrainSpan database. We also included 161 mother-child dyads with prenatal maternal depressive symptoms assessed at 26 weeks of gestation, cytokine genotype data extracted from umbilical cord specimens, and neonatal brain images from a longitudinal prospective birth cohort. We revealed that 22 cytokine genes are expressed in specific brain regions in utero, whose variants have roles in modulating the effects of the prenatal environment on the accelerated fetal development of the hippocampus, auditory, parietal, orbitofrontal, and dorsal prefrontal cortex. Neonates high in the genetic expression score (GES) of TNFRSF19 and IL17RB showed a larger right hippocampal volume, high in the GES of BMPR1B showed the thicker thickness of the sensorimotor cortex, and high in the GES of IL1RAP and CXCR4 demonstrated the thicker thickness of the dorsal and orbital prefrontal cortex in relation with greater prenatal maternal depressive symptoms. Our findings suggest that in humans, the cytokine genes are expressed in a brain region-specific manner in utero and may have potential roles in modulating the fetal development of the corresponding brain regions in response to the maternal environment.


Assuntos
Depressão , Efeitos Tardios da Exposição Pré-Natal , Encéfalo/diagnóstico por imagem , Criança , Depressão/genética , Feminino , Desenvolvimento Fetal , Humanos , Recém-Nascido , Imageamento por Ressonância Magnética , Gravidez , Estudos Prospectivos , Receptores do Fator de Necrose Tumoral
13.
JMIR Med Inform ; 8(12): e22982, 2020 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-33320104

RESUMO

BACKGROUND: Patients' family history (FH) is a critical risk factor associated with numerous diseases. However, FH information is not well captured in the structured database but often documented in clinical narratives. Natural language processing (NLP) is the key technology to extract patients' FH from clinical narratives. In 2019, the National NLP Clinical Challenge (n2c2) organized shared tasks to solicit NLP methods for FH information extraction. OBJECTIVE: This study presents our end-to-end FH extraction system developed during the 2019 n2c2 open shared task as well as the new transformer-based models that we developed after the challenge. We seek to develop a machine learning-based solution for FH information extraction without task-specific rules created by hand. METHODS: We developed deep learning-based systems for FH concept extraction and relation identification. We explored deep learning models including long short-term memory-conditional random fields and bidirectional encoder representations from transformers (BERT) as well as developed ensemble models using a majority voting strategy. To further optimize performance, we systematically compared 3 different strategies to use BERT output representations for relation identification. RESULTS: Our system was among the top-ranked systems (3 out of 21) in the challenge. Our best system achieved micro-averaged F1 scores of 0.7944 and 0.6544 for concept extraction and relation identification, respectively. After challenge, we further explored new transformer-based models and improved the performances of both subtasks to 0.8249 and 0.6775, respectively. For relation identification, our system achieved a performance comparable to the best system (0.6810) reported in the challenge. CONCLUSIONS: This study demonstrated the feasibility of utilizing deep learning methods to extract FH information from clinical narratives.

14.
Medicine (Baltimore) ; 99(52): e23818, 2020 Dec 24.
Artigo em Inglês | MEDLINE | ID: mdl-33350768

RESUMO

ABSTRACT: There have been increasing calls for clinicians to document social determinants of health (SDOH) in electronic health records (EHRs). One potential source of SDOH in the EHRs is in the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) Z codes (Z55-Z65). In February 2018, ICD-10-CM Official Guidelines for Coding and Reporting approved that all clinicians, not just the physicians, involved in the care of a patient can document SDOH using these Z codes.To examine the utilization rate of the ICD-10-CM Z codes using data from a large network of EHRs.We conducted a retrospective analysis of EHR data between 2015 to 2018 in the OneFlorida Clinical Research Consortium, 1 of the 13 Clinical Data Research Networks funded by Patient-Centered Outcomes Research Institute. We calculated the Z code utilization rate at both the encounter and patient levels.We found a low rate of utilization for these Z codes (270.61 per 100,000 at the encounter level and 2.03% at the patient level). We also found that the rate of utilization for these Z codes increased (from 255.62 to 292.79 per 100,000) since the official approval of Z code reporting from all clinicians by the American Hospital Association Coding Clinic and ICD-10-CM Official Guidelines for Coding and Reporting became effective in February 2018.The SDOH Z codes are rarely used by clinicians. Providing clear guidelines and incentives for documenting the Z codes can promote their use in EHRs. Improvements in the EHR systems are probably needed to better document SDOH.


Assuntos
Registros Eletrônicos de Saúde , Classificação Internacional de Doenças , Determinantes Sociais da Saúde , Registros Eletrônicos de Saúde/normas , Registros Eletrônicos de Saúde/estatística & dados numéricos , Fidelidade a Diretrizes/organização & administração , Fidelidade a Diretrizes/estatística & dados numéricos , Humanos , Avaliação de Resultados em Cuidados de Saúde/métodos , Avaliação de Resultados em Cuidados de Saúde/normas , Melhoria de Qualidade , Estados Unidos , Revisão da Utilização de Recursos de Saúde
15.
JMIR Med Inform ; 8(11): e19735, 2020 Nov 23.
Artigo em Inglês | MEDLINE | ID: mdl-33226350

RESUMO

BACKGROUND: Semantic textual similarity (STS) is one of the fundamental tasks in natural language processing (NLP). Many shared tasks and corpora for STS have been organized and curated in the general English domain; however, such resources are limited in the biomedical domain. In 2019, the National NLP Clinical Challenges (n2c2) challenge developed a comprehensive clinical STS dataset and organized a community effort to solicit state-of-the-art solutions for clinical STS. OBJECTIVE: This study presents our transformer-based clinical STS models developed during this challenge as well as new models we explored after the challenge. This project is part of the 2019 n2c2/Open Health NLP shared task on clinical STS. METHODS: In this study, we explored 3 transformer-based models for clinical STS: Bidirectional Encoder Representations from Transformers (BERT), XLNet, and Robustly optimized BERT approach (RoBERTa). We examined transformer models pretrained using both general English text and clinical text. We also explored using a general English STS dataset as a supplementary corpus in addition to the clinical training set developed in this challenge. Furthermore, we investigated various ensemble methods to combine different transformer models. RESULTS: Our best submission based on the XLNet model achieved the third-best performance (Pearson correlation of 0.8864) in this challenge. After the challenge, we further explored other transformer models and improved the performance to 0.9065 using a RoBERTa model, which outperformed the best-performing system developed in this challenge (Pearson correlation of 0.9010). CONCLUSIONS: This study demonstrated the efficiency of utilizing transformer-based models to measure semantic similarity for clinical text. Our models can be applied to clinical applications such as clinical text deduplication and summarization.

16.
J Am Med Inform Assoc ; 27(12): 1999-2010, 2020 12 09.
Artigo em Inglês | MEDLINE | ID: mdl-33166397

RESUMO

OBJECTIVE: To synthesize data quality (DQ) dimensions and assessment methods of real-world data, especially electronic health records, through a systematic scoping review and to assess the practice of DQ assessment in the national Patient-centered Clinical Research Network (PCORnet). MATERIALS AND METHODS: We started with 3 widely cited DQ literature-2 reviews from Chan et al (2010) and Weiskopf et al (2013a) and 1 DQ framework from Kahn et al (2016)-and expanded our review systematically to cover relevant articles published up to February 2020. We extracted DQ dimensions and assessment methods from these studies, mapped their relationships, and organized a synthesized summarization of existing DQ dimensions and assessment methods. We reviewed the data checks employed by the PCORnet and mapped them to the synthesized DQ dimensions and methods. RESULTS: We analyzed a total of 3 reviews, 20 DQ frameworks, and 226 DQ studies and extracted 14 DQ dimensions and 10 assessment methods. We found that completeness, concordance, and correctness/accuracy were commonly assessed. Element presence, validity check, and conformance were commonly used DQ assessment methods and were the main focuses of the PCORnet data checks. DISCUSSION: Definitions of DQ dimensions and methods were not consistent in the literature, and the DQ assessment practice was not evenly distributed (eg, usability and ease-of-use were rarely discussed). Challenges in DQ assessments, given the complex and heterogeneous nature of real-world data, exist. CONCLUSION: The practice of DQ assessment is still limited in scope. Future work is warranted to generate understandable, executable, and reusable DQ measures.


Assuntos
Pesquisa Biomédica , Confiabilidade dos Dados , Registros Eletrônicos de Saúde/normas , Humanos , Sistemas de Informação
17.
medRxiv ; 2020 Nov 05.
Artigo em Inglês | MEDLINE | ID: mdl-33173920

RESUMO

This study presents a natural language processing (NLP) tool to extract quantitative smoking information (e.g., Pack-Year, Quit Year, Smoking Year, and Pack per Day) from clinical notes and standardized them into Pack-Year unit. We annotated a corpus of 200 clinical notes from patients who had low-dose CT imaging procedures for lung cancer screening and developed an NLP system using a two-layer rule-engine structure. We divided the 200 notes into a training set and a test set and developed the NLP system only using the training set. The experimental results on the test set showed that our NLP system achieved the best F1 scores of 0.963 and 0.946 for lenient and strict evaluation, respectively. Note: Accepted as a presentation at the 2020 IEEE International Conference on Healthcare Informatics (ICHI) Workshop on Health Natural Language Processing (HealthNLP 2020). https://ohnlp.github.io/HealthNLP2020/healthnlp2020# .

18.
J Am Med Inform Assoc ; 27(12): 1935-1942, 2020 12 09.
Artigo em Inglês | MEDLINE | ID: mdl-33120431

RESUMO

OBJECTIVE: The goal of this study is to explore transformer-based models (eg, Bidirectional Encoder Representations from Transformers [BERT]) for clinical concept extraction and develop an open-source package with pretrained clinical models to facilitate concept extraction and other downstream natural language processing (NLP) tasks in the medical domain. METHODS: We systematically explored 4 widely used transformer-based architectures, including BERT, RoBERTa, ALBERT, and ELECTRA, for extracting various types of clinical concepts using 3 public datasets from the 2010 and 2012 i2b2 challenges and the 2018 n2c2 challenge. We examined general transformer models pretrained using general English corpora as well as clinical transformer models pretrained using a clinical corpus and compared them with a long short-term memory conditional random fields (LSTM-CRFs) mode as a baseline. Furthermore, we integrated the 4 clinical transformer-based models into an open-source package. RESULTS AND CONCLUSION: The RoBERTa-MIMIC model achieved state-of-the-art performance on 3 public clinical concept extraction datasets with F1-scores of 0.8994, 0.8053, and 0.8907, respectively. Compared to the baseline LSTM-CRFs model, RoBERTa-MIMIC remarkably improved the F1-score by approximately 4% and 6% on the 2010 and 2012 i2b2 datasets. This study demonstrated the efficiency of transformer-based models for clinical concept extraction. Our methods and systems can be applied to other clinical tasks. The clinical transformer package with 4 pretrained clinical models is publicly available at https://github.com/uf-hobi-informatics-lab/ClinicalTransformerNER. We believe this package will improve current practice on clinical concept extraction and other tasks in the medical domain.


Assuntos
Mineração de Dados/métodos , Aprendizado Profundo , Processamento de Linguagem Natural , Software , Conjuntos de Dados como Assunto , Registros Eletrônicos de Saúde , Humanos
19.
Toxicol Ind Health ; 36(8): 580-590, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-33064063

RESUMO

Nickel (Ni) is a known human carcinogen that has an adverse effect on various human organs in occupational workers during Ni refinement and smelting. In the present study, we used real-time polymerase chain reactions, Western blot analysis, and a lactate production assay to investigate whether an increase in the NLRP3 inflammasome induced by Ni-refining fumes was associated with the Warburg effect in BEAS-2B cells, a nonmalignant pulmonary epithelial line. Exposure to Ni-refining fumes suppressed cell proliferation and increased lactate production compared with those in an untreated control group in a dose- and time-dependent manner. Ni-refining fumes induced the Warburg effect, which was observed based on increases in the levels of hypoxia-inducible factor-1α, hexokinase 2, pyruvate kinase isozyme type M2, and lactate dehydrogenase A. In addition, Ni-refining fumes promoted increased expression of NLRP3 at both the gene and protein levels. Furthermore, inhibition of the Warburg effect by 2-Deoxy-d-glucose reversed the increased expression of NLRP3 induced by Ni-refining fumes. Collectively, our data demonstrated that the Warburg effect can promote the expression of the NLRP3 inflammasome induced by the Ni-refining fumes in BEAS-2B cells. This indicates a new phenomenon in which alterations in energy production in human cells induced by Ni-refining fumes regulate the inflammatory response.

20.
Int J Med Inform ; 143: 104272, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32980667

RESUMO

BACKGROUND: Inpatient falls, many resulting in injury or death, are a serious problem in hospital settings. Existing falls risk assessment tools, such as the Morse Fall Scale, give a risk score based on a set of factors, but don't necessarily signal which factors are most important for predicting falls. Artificial intelligence (AI) methods provide an opportunity to improve predictive performance while also identifying the most important risk factors associated with hospital-acquired falls. We can glean insight into these risk factors by applying classification tree, bagging, random forest, and adaptive boosting methods applied to Electronic Health Record (EHR) data. OBJECTIVE: The purpose of this study was to use tree-based machine learning methods to determine the most important predictors of inpatient falls, while also validating each via cross-validation. MATERIALS AND METHODS: A case-control study was designed using EHR and electronic administrative data collected between January 1, 2013 to October 31, 2013 in 14 medical surgical units. The data contained 38 predictor variables which comprised of patient characteristics, admission information, assessment information, clinical data, and organizational characteristics. Classification tree, bagging, random forest, and adaptive boosting methods were used to identify the most important factors of inpatient fall-risk through variable importance measures. Sensitivity, specificity, and area under the ROC curve were computed via ten-fold cross validation and compared via pairwise t-tests. These methods were also compared to a univariate logistic regression of the Morse Fall Scale total score. RESULTS: In terms of AUROC, bagging (0.89), random forest (0.90), and boosting (0.89) all outperformed the Morse Fall Scale (0.86) and the classification tree (0.85), but no differences were measured between bagging, random forest, and adaptive boosting, at a p-value of 0.05. History of Falls, Age, Morse Fall Scale total score, quality of gait, unit type, mental status, and number of high fall risk increasing drugs (FRIDs) were considered the most important features for predicting inpatient fall risk. CONCLUSIONS: Machine learning methods have the potential to identify the most relevant and novel factors for the detection of hospitalized patients at risk of falling, which would improve the quality of patient care, and to more fully support healthcare provider and organizational leadership decision-making. Nurses would be able to enhance their judgement to caring for patients at risk for falls. Our study may also serve as a reference for the development of AI-based prediction models of other iatrogenic conditions. To our knowledge, this is the first study to report the importance of patient, clinical, and organizational features based on the use of AI approaches.


Assuntos
Registros Eletrônicos de Saúde , Pacientes Internados , Inteligência Artificial , Estudos de Casos e Controles , Eletrônica , Humanos , Aprendizado de Máquina , Medição de Risco , Fatores de Risco
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...