Identifying subtypes of depression in clinician-annotated text: a retrospective cohort study
Ontology highlight
ABSTRACT:
SUBMITTER: Kung B
PROVIDER: S-EPMC8599474 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundGood communication has been shown to affect patient outcomes; however, the effect varies according to patient and clinician characteristics. To date, no research has explored the differences in the content of secure messages based on these characteristics.ObjectiveThis study aims to explore characteristics of patients and clinic staff associated with the content exchanged in secure messages.MethodsWe coded 18,309 messages that were part of threads initiated by 1031 patients with hypertension, diabetes, or both conditions, in communication with 711 staff members. We conducted four sets of analyses to identify associations between patient characteristics and the types of messages they sent, staff characteristics and the types of messages they sent, staff characteristics and the types of messages patients sent to them, and patient characteristics and the types of messages they received from staff. Logistic regression was used to estimate the strength of the associations.ResultsWe found that younger patients had reduced odds of sharing clinical updates (odds ratio [OR] 0.77, 95% CI 0.65-0.91) and requesting prescription refills (OR 0.77, 95% CI 0.65-0.90). Women had reduced odds of self-reporting biometrics (OR 0.78, 95% CI 0.62-0.98) but greater odds of responding to a clinician (OR 1.20, 95% CI 1.02-1.42) and seeking medical guidance (OR 1.19, 95% CI 1.01-1.40). Compared with White patients, Black patients had greater odds of requesting preventive care (OR 2.68, 95% CI 1.30-5.51) but reduced odds of requesting a new or changed prescription (OR 0.72, 95% CI 0.53-0.98) or laboratory or other diagnostic procedures (OR 0.66, 95% CI 0.46-0.95). Staff had lower odds of sharing medical guidance with younger patients (OR 0.83, 95% CI 0.69-1.00) and uninsured patients (OR 0.21, 95% CI 0.06-0.73) but had greater odds of sharing medical guidance with patients with public payers (OR 2.03, 95% CI 1.26-3.25) compared with patients with private payers. Staff had reduced odds of confirming to women that their requests were fulfilled (OR 0.82, 95% CI 0.69-0.98). Compared with physicians, nurse practitioners had greater odds of sharing medical guidance with patients (OR 2.74, 95% CI 1.12-6.68) and receiving prescription refill requests (OR 3.39, 95% CI 1.49-7.71). Registered nurses had greater odds of deferred information sharing (OR 1.61, 95% CI 1.04-2.49) and receiving responses to messages (OR 3.93, 95% CI 2.18-7.11) than physicians.ConclusionsThe differences we found in content use based on patient characteristics could lead to the exacerbation of health disparities when content is associated with health outcomes. Disparities in the content of secure messages could exacerbate disparities in patient outcomes, such as satisfaction, trust in the system, self-care, and health outcomes. Staff and administrators should evaluate how secure messaging is used to ensure that disparities in care are not perpetuated via this communication modality.
| S-EPMC8414300 | biostudies-literature
Project description:Objectives(1) To develop a clinical prediction rule to identify patients with bacteremia, using only information that is readily available in the emergency room (ER) of community hospitals, and (2) to test the validity of that rule with a separate, independent set of data.DesignMulticenter retrospective cohort study.SettingTo derive the clinical prediction rule we used data from 3 community hospitals in Japan (derivation). We tested the rule using data from one other community hospital (validation), which was not among the three "derivation" hospitals.ParticipantsAdults (age ≥ 16 years old) who had undergone blood-culture testing while in the ER between April 2011 and March 2012. For the derivation data, n = 1515 (randomly sampled from 7026 patients), and for the validation data n = 467 (from 823 patients).AnalysisWe analyzed 28 candidate predictors of bacteremia, including demographic data, signs and symptoms, comorbid conditions, and basic laboratory data. Chi-square tests and multiple logistic regression were used to derive an integer risk score (the "ID-BactER" score). Sensitivity, specificity, likelihood ratios, and the area under the receiver operating characteristic curve (i.e., the AUC) were computed.ResultsThere were 241 cases of bacteremia in the derivation data. Eleven candidate predictors were used in the ID-BactER score: age, chills, vomiting, mental status, temperature, systolic blood pressure, abdominal sign, white blood-cell count, platelets, blood urea nitrogen, and C-reactive protein. The AUCs was 0.80 (derivation) and 0.74 (validation). For ID-BactER scores ≥ 2, the sensitivities for derivation and validation data were 98% and 97%, and specificities were 20% and 14%, respectively.ConclusionsThe ID-BactER score can be computed from information that is readily available in the ERs of community hospitals. Future studies should focus on developing a score with a higher specificity while maintaining the desired sensitivity.
| S-EPMC4811592 | biostudies-literature
Project description:The current pathological diagnostic criteria for sporadic inclusion body myositis (IBM) lack sensitivity. Using immunohistochemical techniques abnormal protein aggregates have been identified in IBM, including some associated with neurodegenerative disorders. Our objective was to investigate the diagnostic utility of a number of markers of protein aggregates together with mitochondrial and inflammatory changes in IBM.Retrospective cohort study. The sensitivity of pathological features was evaluated in cases of Griggs definite IBM. The diagnostic potential of the most reliable features was then assessed in clinically typical IBM with rimmed vacuoles (n=15), clinically typical IBM without rimmed vacuoles (n=9) and IBM mimics-protein accumulation myopathies containing rimmed vacuoles (n=7) and steroid-responsive inflammatory myopathies (n=11).Specialist muscle services at the John Radcliffe Hospital, Oxford and the National Hospital for Neurology and Neurosurgery, London.Individual pathological features, in isolation, lacked sensitivity and specificity. However, the morphology and distribution of p62 aggregates in IBM were characteristic and in a myopathy with rimmed vacuoles, the combination of characteristic p62 aggregates and increased sarcolemmal and internal major histocompatibility complex class I expression or endomysial T cells were diagnostic for IBM with a sensitivity of 93% and specificity of 100%. In an inflammatory myopathy lacking rimmed vacuoles, the presence of mitochondrial changes was 100% sensitive and 73% specific for IBM; characteristic p62 aggregates were specific (91%), but lacked sensitivity (44%).We propose an easily applied diagnostic algorithm for the pathological diagnosis of IBM. Additionally our findings support the hypothesis that many of the pathological features considered typical of IBM develop later in the disease, explaining their poor sensitivity at disease presentation and emphasising the need for revised pathological criteria to supplement the clinical criteria in the diagnosis of IBM.
| S-EPMC4010816 | biostudies-other
Project description:Introduction: MicroRNAs (miRNAs) are small, non-coding RNA molecules involved in post-transcriptional gene regulation and have recently been shown to play a role in cancer metastasis. In solid tumors, especially breast cancer, alterations in miRNA expression contribute to cancer pathogenesis, including metastasis. Considering the emerging role of miRNAs in metastasis, the identification of predictive markers is necessary to further understanding of stage-specific breast cancer development. This is a retrospective analysis that aimed to identify molecular biomarkers related to distant breast cancer metastasis development.<br><br>Methods: A retrospective case cohort study was performed in 64 breast cancer patients treated during the period from 1998-2001. The case group (n=29) consisted of patients with a poor prognosis who presented with breast cancer recurrence or metastasis during follow up. The control group (n=35) consisted of a random sample of patients with a good prognosis who did not develop breast cancer recurrence or metastasis. These patient groups were stratified according to TNM clinical stage (CS) I, II and III, and the main clinical features of the patients were homogeneous. miRNA profiling was performed using formalin-fixed, paraffin-embedded tumors. Biomarkers related to metastatic potential were identified independent of clinical stage, and a cutoff point was selected based on the optimal sensitivity and specificity (ROC curve). Finally, a hazard risk analysis of these biomarkers was performed to evaluate their relation to metastatic potential. <br><br>Results: miRNA expression profiling identified several miRNAs that were either specific and shared across all clinical stages (p?0.05). Among these, we identified miRNAs previously associated with cell motility (let-7 family), cell proliferation and invasion (hsa-miR-16 and has-miR-205) and distant metastasis (hsa-miR-21). In addition, hsa-miR-494 and hsa-miR-21 were up-regulated in metastatic cases of CSI and II. Furthermore, the combination of the 3 miRNAs identified for CSII (hsa-miR-494, hsa-miR-183 and hsa-miR-21) was significant and were a more effective risk marker compared to the single miRNAs. <br><br>Conclusions: Women with metastatic breast cancer, especially CSII, presented up-regulated levels of miR-183, miR-494 and miR-21, which were associated with a poor prognosis. These miRNAs therefore represent new risk biomarkers of breast cancer metastasis and may be useful for future targeted therapies.
2013-08-07 | E-MEXP-3947 | biostudies-arrayexpress
Project description:Sindhi Unicode-8 based linguistics data set is multi-class and multi-featured data set. It is developed to solve the natural languages processing (NLP) and linguistics problems of Sindhi language. The data set presents information on grammatical and morphological structure of Sindhi language text as well as sentiment polarity of Sindhi lexicons. Therefore, data set may be used for information retrieving, machine translation, lexicon analysis, language modeling analysis, grammatical and morphological analysis, Semantic and sentiment analysis.
| S-EPMC6139473 | biostudies-literature
Project description:BackgroundHypertensive disorders were proved to be associated with the development of depression. But it is unclear if pregnancy-induced hypertensive diseases, especially preeclampsia (PE), will affect postpartum moods. We aimed to determine the incidence rate of postpartum depression (PPD) in PE patients and comprehensively evaluate the association between PPD and PE, including its severity and complications.Methods425 participants including 130 PE mothers were enrolled in this retrospective cohort study. Each woman was asked to complete a questionnaire integrating the Edinburgh Postnatal Depression Scale (EPDS), the Leakage Index Questionnaire, and a pain scale questionnaire within 6 weeks after delivery. The EPDS cut-off score above 13 was recognized as screening positive for PPD. Data between groups were compared by bivariate analysis.ResultsPE mothers showed a direct tendency to PPD development. The positive screening for PPD in the PE group was significantly higher than that of the control group (30.77% vs. 14.58%). Based on the results of the regression model, women diagnosed with severe PE and fetal growth restriction were more inclined to develop PPD than normal ones (AOR: 2.759, 95% CI: 1.206-6.315 and AOR: 3.450, 95% CI: 1.596-7.458). It is also indicated that postpartum pain exacerbated the odds of PPD in PE patients (AOR: 1.509, 95% CI: 1.078-2.114).ConclusionsPE was an independent risk factor for PPD. Its severity and complications exacerbate the development of PPD. Doctors and society should pay more attention to PE patients after delivery against the development of PPD.
| S-EPMC8087462 | biostudies-literature
Project description:ObjectivesTo identify predictors of recurrent cerebrovascular morbidity in a cohort of patients with depression and a cerebrovascular disease (CBVD) history.MethodsWe used the Maudsley Biomedical Research Centre Case Register to identify patients aged 50 years or older with a diagnosis of depressive disorder between 2008 and 2017 and a previous history of hospitalised CBVD. Using depression diagnosis as the index date we followed patients until first hospitalised CBVD recurrence or death due to CBVD. Sociodemographic data, symptom and functioning scores of Health of the Nation Outcome Scales, medications and comorbidities were extracted and modelled in multivariate survival analyses to identify predictors of CBVD reoccurrence.ResultsOf 1292 patients with depression and CBVD (mean age 75.6 years; 56.6% female), 264 (20.4%) experienced fatal/non-fatal CBVD recurrence during a median follow-up duration of 1.66 years. In multivariate Cox regression models, a higher risk of CBVD recurrence was predicted by older age (HR, 1.02; 95% CI, 1.01 to 1.04) (p=0.002), physical health problems (moderate to severe HR, 2.47; 95% CI, 1.45 to 4.19) (p=0.001), anticoagulant (HR, 1.40; 95% CI, 1.01 to 1.93) (p=0.041) and antipsychotic medication (HR, 0.66; 95% CI 0.44 to 0.99) (p=0.047). Neither depression severity, mental health symptoms, functional status, nor antidepressant prescribing were significantly associated with CBVD recurrence.ConclusionsApproximately one in five patients with depression and CBVD experienced a CBVD recurrence over a median follow-up time of 20 months. Risk of CBVD recurrence was largely dependent on age and physical health rather than on severity of depressive symptoms, co-morbid mental health or functional problems, or psychotropic prescribing.
| S-EPMC6955506 | biostudies-literature
Project description:BackgroundTo assess the interaction of sleep duration and depression on the risk of cardiovascular disease (CVD).MethodsA total of 13,488 eligible participants were enrolled in this retrospective cohort study eventually. Baseline characteristics were extracted from the China Health and Retirement Longitudinal Study (CHARLS) database, including age, sex, diabetes, high-density lipoprotein (HDL), blood glucose (GLU), glycosylated hemoglobin (GHB) etc. Univariate and multivariate negative binomial regression models were carried out to assess the statistical correlation of sleep duration and depression on CVD separately. Additionally, multivariate negative binomial regression model was used to estimate the interaction of sleep duration and depression on CVD risk.ResultsAfter adjusting for age, sex, educational background, hypertension, diabetes, dyslipidemia, the use of hypnotics, disability, nap, drinking, deposit, sleep disturbance, HDL, triglyceride, total cholesterol, GLU and GHB, the risk of CVD in participants with the short sleep duration was increased in comparison with the normal sleep duration [relative risk (RR)=1.02, 95% confidence interval (CI):1.01-1.03]; compared to the participants with non-depression, participants suffered from depression had an increased risk of CVD (RR=1.05, 95%CI:1.04-1.06). Additionally, the result also suggested that the interaction between short sleep duration and depression on the risk of CVD was statistically significant in these patients with diabetes and was a multiplicative interaction.ConclusionAn interaction between short sleep duration and depression in relation to an increased risk of CVD among Chinese middle-aged and elderly individuals was noticed, which may provide a reference that people with diabetes should focus on their sleep duration and the occurrence of depression, and coexisting short sleep duration and depression may expose them to a higher risk of CVD.
| S-EPMC9479441 | biostudies-literature
Project description:Analyses of search engine and social media feeds have been attempted for infectious disease outbreaks, but have been found to be susceptible to artefactual distortions from health scares or keyword spamming in social media or the public internet. We describe an approach using real-time aggregation of keywords and phrases of freetext from real-time clinician-generated documentation in electronic health records to produce a customisable real-time viral pneumonia signal providing up to 4 days warning for secondary care capacity planning. This low-cost approach is open-source, is locally customisable, is not dependent on any specific electronic health record system and can provide an ensemble of signals if deployed at multiple organisational scales.
| S-EPMC7904856 | biostudies-literature
Project description:Depression is a significant public health problem but symptom remission is difficult to predict. This may be due to substantial heterogeneity underlying the disorder. Latent class analysis (LCA) is often used to elucidate clinically relevant depression subtypes but whether or not consistent subtypes emerge is unclear. We sought to critically examine the implementation and reporting of LCA in this context by performing a systematic review to identify articles detailing the use of LCA to explore subtypes of depression among samples of adults endorsing depression symptoms. PubMed, PsycINFO, CINAHL, Scopus, and Google Scholar were searched to identify eligible articles indexed prior to January 2016. Twenty-four articles reporting 28 LCA models were eligible for inclusion. Sample characteristics varied widely. The majority of articles used depression symptoms as the observed indicators of the latent depression subtypes. Details regarding model fit and selection were often lacking. No consistent set of depression subtypes was identified across studies. Differences in how models were constructed might partially explain the conflicting results. Standards for using, interpreting, and reporting LCA models could improve our understanding of the LCA results. Incorporating dimensions of depression other than symptoms, such as functioning, may be helpful in determining depression subtypes.
| S-EPMC6345275 | biostudies-literature