Nevin Manimala

Psychiatr Danub. 2022 Sep;34(Suppl 8):71-74.

ABSTRACT

Dignity Therapy (DT) is a multi-dimensional, brief and individual psychotherapeutic intervention, designed to increase the sense of dignity in patients. The aim of our study was to evaluate the effectiveness of Dignity Therapy in a group of patients suffering from major depressive disorder or bipolar disorder. The results of the study in a small group of patients showed the effectiveness of DT. The PDI (Patient Dignity Inventory Scores) showed a statistically significant difference in the whole group of patients with a reduction in the mean overall score (T0 vs T1 = Mean Difference: 13.700, T-Score: 4.834, Eta squared: 0.709, p: 0.001, statistically significant). However, there is a need to deepen the study to try to offer an opportunity for treatment in this group of patients.

PMID:36170706

JMIR Form Res. 2022 Sep 28;6(9):e41241. doi: 10.2196/41241.

ABSTRACT

BACKGROUND: Abnormal prolongation or shortening of the QT interval is associated with increased risk for ventricular arrhythmias and sudden cardiac death. For continuous monitoring, widespread use, and prevention of cardiac events, advanced wearable technologies are emerging as promising surrogates for conventional 12‑lead electrocardiogram (ECG) QT interval assessment. Previous studies have shown a good agreement between QT and corrected QT (QTc) intervals measured on a smartwatch ECG and a 12-lead ECG, but the clinical accuracy of computerized algorithms for QT and QTc interval measurement from smartwatch ECGs is unclear.

OBJECTIVE: The prospective observational study compared the smartwatch-recorded QT and QTc assessed using AccurKardia’s AccurBeat platform with the conventional 12‑lead ECG annotated manually by a cardiologist.

METHODS: ECGs were collected from healthy participants (without any known cardiovascular disease) aged >22 years. Two consecutive 30-second ECG readings followed by (within 15 minutes) a 10-second standard 12-lead ECG were recorded for each participant. Characteristics of the participants were compared by sex using a 2-sample t test and Wilcoxon rank sum test. Statistical comparisons of heart rate (HR), QT interval, and QTc interval between the platform and the 12-lead ECG, ECG lead I, and ECG lead II were done using the Wilcoxon sign rank test. Linear regression was used to predict QTc and QT intervals from the ECG based on the platform’s QTc/QT intervals with adjustment for age, sex, and difference in HR measurement. The Bland-Altman method was used to check agreement between various QT and QTc interval measurements.

RESULTS: A total of 50 participants (32 female, mean age 46 years, SD 1 year) were included in the study. The result of the regression model using the platform measurements to predict the 12-lead ECG measurements indicated that, in univariate analysis, QT/QTc intervals from the platform significantly predicted QT/QTc intervals from the 12-lead ECG, ECG lead I, and ECG lead II, and this remained significant after adjustment for sex, age, and change in HR. The Bland-Altman plot results found that 96% of the average QTc interval measurements between the platform and QTc intervals from the 12-lead ECG were within the 95% confidence limit of the average difference between the two measurements, with a mean difference of -10.5 (95% limits of agreement -71.43, 50.43). A total of 94% of the average QT interval measurements between the platform and the 12-lead ECG were within the 95% CI of the average difference between the two measurements, with a mean difference of -6.3 (95% limits of agreement -54.54, 41.94).

CONCLUSIONS: QT and QTc intervals obtained by a smartwatch coupled with the platform’s assessment were comparable to those from a 12-lead ECG. Accordingly, with further refinements, remote monitoring using this technology holds promise for the identification of QT interval prolongation.

PMID:36169999 | DOI:10.2196/41241

J Phys Chem A. 2022 Sep 28. doi: 10.1021/acs.jpca.2c05287. Online ahead of print.

ABSTRACT

We report kinetics studies of H₃O⁺(H₂O)_n=0-3 with isoprene (2-methyl-1,3-butadiene, C₅H₈) as a function of temperature (300-500 K) measured using a flowing afterglow-selected ion flow tube. Results are supported by density functional (DFT) calculations at the B3LYP/def2-TZVP level. H₃O⁺ (n = 0) reacts with isoprene near the collision limit exclusively via proton transfer to form C₅H₉⁺. The first hydrate (n = 1) also reacts at the collision limit and only the proton transfer product is observed, although hydrated protonated isoprene may have been produced and dissociated thermally. Addition of a second water (n = 2) lowers the rate constant by about a factor of 10. The proton transfer of H₃O⁺(H₂O)₂ to isoprene is endothermic, but transfer of the water ligands lowers the thermicity and the likely process occurring is H₃O⁺(H₂O)₂ + C₅H₈ → C₅H₉⁺(H₂O)₂ + H₂O, followed by thermal dissociation of C₅H₉⁺(H₂O)₂. Statistical modeling indicates the amount of reactivity is consistent with the process being slightly endothermic, as is indicated by the DFT calculations. This reactivity was obscured in past experiments due to the presence of water in the reaction zone. The third hydrate is observed not to react and helps explain the past results for n = 2, as n = 2 and 3 were in equilibrium in that flow tube experiment. Very little dependence on temperature was found for the three species that did react. Finally, the C₅H₉⁺ proton transfer product further reacted with isoprene to produce mainly C₆H₉⁺ along with a small amount of clustering.

PMID:36169997 | DOI:10.1021/acs.jpca.2c05287

J Med Internet Res. 2022 Sep 28;24(9):e40547. doi: 10.2196/40547.

ABSTRACT

Scholars from the health and medical sciences have recently proposed the term social informatics (SI) as a new scientific subfield of health informatics (HI). However, SI is not a new academic concept; in fact, it has been continuously used in the social sciences and informatics since the 1970s. Although the dominant understanding of SI was established in the 1990s in the United States, a rich international perspective on SI has existed since the 1970s in other regions of the world. When that perspective is considered, the fields of understanding can be structured into 7 SI schools of thought. Against that conceptual background, this paper contributes to the discussion on the relationship between SI and HI, outlining possible perspectives of SI that are associated with health, medical, and clinical aspects. This paper argues against the multiplication and inconsistent appearance of the term SI when newly used in health and medical sciences. A more explicit name for the area that uses health and social data to advance individual and population health might be helpful to overcome this issue; giving an identity to this new field would help it to be understood more precisely and bring greater separation. This labeling could be fruitful for further segmentation of HI, which is rapidly expanding.

PMID:36169995 | DOI:10.2196/40547

JMIR Form Res. 2022 Sep 28;6(9):e36118. doi: 10.2196/36118.

ABSTRACT

BACKGROUND: There are a myriad of language cues that indicate depression in written texts, and natural language processing (NLP) researchers have proven the ability of machine learning and deep learning approaches to detect these cues. However, to date, these approaches bridging NLP and the domain of mental health for Bengali literature are not comprehensive. The Bengali-speaking population can express emotions in their native language in greater detail.

OBJECTIVE: Our goal is to detect the severity of depression using Bengali texts by generating a novel Bengali corpus of depressive posts. We collaborated with mental health experts to generate a clinically sound labeling scheme and an annotated corpus to train machine learning and deep learning models.

METHODS: We conducted a study using Bengali text-based data from blogs and open source platforms. We constructed a procedure for annotated corpus generation and extraction of textual information from Bengali literature for predictive analysis. We developed our own structured data set and designed a clinically sound labeling scheme with the help of mental health professionals, adhering to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) during the process. We used 5 machine learning models for detecting the severity of depression: kernel support vector machine (SVM), random forest, logistic regression K-nearest neighbor (KNN), and complement naive Bayes (NB). For the deep learning approach, we used long short-term memory (LSTM) units and gated recurrent units (GRUs) coupled with convolutional blocks or self-attention layers. Finally, we aimed for enhanced outcomes by using state-of-the-art pretrained language models.

RESULTS: The independent recurrent neural network (RNN) models yielded the highest accuracies and weighted F1 scores. GRUs, in particular, produced 81% accuracy. The hybrid architectures could not surpass the RNNs in terms of performance. Kernel SVM with term frequency-inverse document frequency (TF-IDF) embeddings generated 78% accuracy on test data. We used validation and training loss curves to observe and report the performance of our architectures. Overall, the number of available data remained the limitation of our experiment.

CONCLUSIONS: The findings from our experimental setup indicate that machine learning and deep learning models are fairly capable of assessing the severity of mental health issues from texts. For the future, we suggest more research endeavors to increase the volume of Bengali text data, in particular, so that modern architectures reach improved generalization capability.

PMID:36169989 | DOI:10.2196/36118

JAMA Psychiatry. 2022 Sep 28. doi: 10.1001/jamapsychiatry.2022.2983. Online ahead of print.

ABSTRACT

IMPORTANCE: Self-reported trauma exposure has consistently been found to be a risk factor for major depressive disorder (MDD), and several studies have reported interactions with genetic liability. To date, most studies have examined gene-environment interactions with trauma exposure using genome-wide variants (single-nucleotide variations [SNVs]) or polygenic scores, both typically capturing less than 3% of phenotypic risk variance.

OBJECTIVE: To reexamine genome-by-trauma interaction associations using genetic measures using all available genotyped data and thus, maximizing accounted variance.

DESIGN, SETTING, AND PARTICIPANTS: The UK Biobank study was conducted from April 2007 to May 1, 2016 (follow-up mental health questionnaire). The current study used available cross-sectional genomic and trauma exposure data from UK Biobank. Participants who completed the mental health questionnaire and had available genetic, trauma experience, depressive symptoms, and/or neuroticism information were included. Data were analyzed from April 1 to August 30, 2021.

EXPOSURES: Trauma and genome-by-trauma exposure interactions.

MAIN OUTCOMES AND MEASURES: Measures of self-reported depression, neuroticism, and trauma exposure with whole-genome SNV data are available from the UK Biobank study. Here, a mixed-model statistical approach using genetic, trauma exposure, and genome-by-trauma exposure interaction similarity matrices was used to explore sources of variation in depression and neuroticism.

RESULTS: Analyses were conducted on 148 129 participants (mean [SD] age, 56 [7] years) of which 76 995 were female (52.0%). The study approach estimated the heritability (SE) of MDD to be approximately 0.160 (0.016). Subtypes of self-reported trauma exposure (catastrophic, adult, childhood, and full trauma) accounted for a significant proportion of the variance of MDD, with heritability (SE) ranging from 0.056 (0.013) to 0.176 (0.025). The proportion of MDD risk variance accounted for by significant genome-by-trauma interaction revealed estimates (SD) ranging from 0.074 (0.006) to 0.201 (0.009). Results from sex-specific analyses found genome-by-trauma interaction variance estimates approximately 5-fold greater for MDD in male participants (0.441 [0.018]) than in female participants (0.086 [0.009]).

CONCLUSIONS AND RELEVANCE: This cross-sectional study used an approach combining all genome-wide SNV data when exploring genome-by-trauma interactions in individuals with MDD; findings suggest that such interactions were associated with depression manifestation. Genome-by-trauma interaction accounts for greater trait variance in male individuals, which points to potential differences in depression etiology between the sexes. The methodology used in this study can be extrapolated to other environmental factors to identify modifiable risk environments and at-risk groups to target with interventions.

PMID:36169986 | DOI:10.1001/jamapsychiatry.2022.2983

Melanoma Res. 2022 Sep 28. doi: 10.1097/CMR.0000000000000855. Online ahead of print.

ABSTRACT

This study was designed to screen for preliminary evidence of predictive markers of melanoma response to PD-1 blockade. We hypothesized that the following immune markers would be positive predictors of response: increased densities of CD103+CD8+ T cells or Th1 lineage T-bet+ T cells, high expression of CXCL9-11 and presence of tertiary lymphoid structures. Conversely, we hypothesized that the high expression of barrier molecules would be a negative predictor of response. Patients with advanced melanoma treated with pembrolizumab were identified, and clinical response as well as overall survival data were collected. Tumor samples were evaluated by multiplex immunofluorescence histology. All statistical analyses were performed in R Studio and Microsoft Excel using the Mann-Whitney U test, chi-square test, Spearman’s rank correlation and Kaplan-Meier survival curves. Sixty-five advanced melanoma patients were identified, of whom 46 met inclusion criteria and were included in this study. Increased densities (P = 0.04) and proportions (P = 0.02) of CD8+ T cells expressing CD103+ were associated with complete response (CR) to pembrolizumab. Improved survival was associated with increased proportions of CD8+ cells expressing CD103 (P = 0.0085) as well as decreased density of periplakin+ cells (P = 0.012) and periplakin+SOX10+ cells (P = 0.0012). The density and proportion of CD8+ T cells expressing CD103+ positively correlated with PD-L1 expression, though PD-L1 expression was not significantly correlated with outcomes. This screening study found that increased density and proportion of CD8+ T cells expressing CD103 and decreased density of periplakin were associated with positive outcomes in patients with melanoma metastases treated with pembrolizumab and may warrant further study.

PMID:36169985 | DOI:10.1097/CMR.0000000000000855

JAMA Psychiatry. 2022 Sep 28. doi: 10.1001/jamapsychiatry.2022.2990. Online ahead of print.

ABSTRACT

IMPORTANCE: Suicide is a leading cause of death in the United States, having increased more than 30% from 2000 to 2018. An inexpensive, safe, widely available treatment for preventing suicidal behavior could reverse this trend.

OBJECTIVE: To confirm a previous signal for decreased risk of suicide attempt following prescription fills for folic acid in a national pharmacoepidemiologic study of patients treated with folic acid.

DESIGN, SETTING, AND PARTICIPANTS: A within-person exposure-only cohort design was used to study the dynamic association between folic acid (vitamin B9) prescription fills over a 24-month period and suicide attempts and intentional self-harm. Data were collected from a pharmacoepidemiologic database of US medical claims (MarketScan) for patients with private health insurance who filled a folic acid prescription between 2012 and 2017. The same analysis was repeated with a control supplement (cyanocobalamin, vitamin B12). Data were analyzed from August 2021 to June 2022.

EXPOSURE: Folic acid prescription fills.

MAIN OUTCOME AND MEASURE: Suicide attempt or intentional self-harm resulting in an outpatient visit or inpatient admission as identified by codes from the International Statistical Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification.

RESULTS: Data on 866 586 patients were collected; 704 514 (81.30%) were female, and 90 296 (10.42%) were 60 years and older. Overall, there were 261 suicidal events during months covered by a folic acid prescription (5 521 597 person-months) for a rate of 4.73 per 100 000 person-months, compared with 895 suicidal events during months without folic acid (8 432 340) for a rate of 10.61 per 100 000 person-months. Adjusting for age and sex, diagnoses related to suicidal behavior, diagnoses related to folic acid deficiency, folate-reducing medications, history of folate-reducing medications, and history of suicidal events, the hazard ratio (HR) for folic acid for suicide events was 0.56 (95% CI, 0.48-0.65), with similar results for the modal dosage of 1 mg of folic acid per day (HR, 0.57; 95% CI, 0.48-0.69) and women of childbearing age (HR, 0.60; 95% CI, 0.50-0.73). A duration-response analysis (1-mg dosage) revealed a 5% decrease in suicidal events per month of additional treatment (HR, 0.95; 95% CI, 0.93-0.97). The same analysis for the negative control, cyanocobalamin, found no association with suicide attempt (HR, 1.01; 95% CI, 0.80-1.27).

CONCLUSIONS AND RELEVANCE: This large-scale pharmacoepidemiologic study of folic acid found a beneficial association in terms of lower rates of suicide attempts. The results warrant the conduct of a randomized clinical trial with suicidal ideation and behavior as outcomes of interest. If confirmed, folic acid may be a safe, inexpensive, and widely available treatment for suicidal ideation and behavior.

PMID:36169979 | DOI:10.1001/jamapsychiatry.2022.2990

Environ Health Perspect. 2022 Sep;130(9):97008. doi: 10.1289/EHP10889. Epub 2022 Sep 28.

ABSTRACT

BACKGROUND: Based on human and animal experimental studies, exposure to ambient carbon monoxide (CO) may be associated with cardiovascular disease outcomes, but epidemiological evidence of this link is limited. The number and distribution of ground-level regulatory agency monitors are insufficient to characterize fine-scale variations in CO concentrations.

OBJECTIVES: To develop a daily, high-resolution ambient CO exposure prediction model at the city scale.

METHODS: We developed a CO prediction model in Baltimore, Maryland, based on a spatiotemporal statistical algorithm with regulatory agency monitoring data and measurements from calibrated low-cost gas monitors. We also evaluated the contribution of three novel parameters to model performance: high-resolution meteorological data, satellite remote sensing data, and copollutant (PM2.5, NO2, and NOx) concentrations.

RESULTS: The CO model had spatial cross-validation (CV) R2 and root-mean-square error (RMSE) of 0.70 and 0.02 parts per million (ppm), respectively; the model had temporal CV R2 and RMSE of 0.61 and 0.04 ppm, respectively. The predictions revealed spatially resolved CO hot spots associated with population, traffic, and other nonroad emission sources (e.g., railroads and airport), as well as sharp concentration decreases within short distances from primary roads.

DISCUSSION: The three novel parameters did not substantially improve model performance, suggesting that, on its own, our spatiotemporal modeling framework based on geographic features was reliable and robust. As low-cost air monitors become increasingly available, this approach to CO concentration modeling can be generalized to resource-restricted environments to facilitate comprehensive epidemiological research. https://doi.org/10.1289/EHP10889.

PMID:36169978 | DOI:10.1289/EHP10889

J Magn Reson Imaging. 2022 Sep 28. doi: 10.1002/jmri.28435. Online ahead of print.

ABSTRACT

BACKGROUND: Metastatic lymph nodal number (LNN) is associated with the survival of nasopharyngeal carcinoma (NPC); however, counting multiple nodes is cumbersome.

PURPOSE: To explore LNN threshold and evaluate its use in risk stratification and induction chemotherapy (IC) indication.

STUDY TYPE: Retrospective.

POPULATION: A total of 792 radiotherapy-treated NPC patients (N classification: N0 182, N1 438, N2 113, N3 59; training group: 396, validation group: 396; receiving IC: 390).

FIELD STRENGTH/SEQUENCE: T1-, T2- and postcontrast T1-weighted fast spin echo MRI at 1.5 or 3.0 T.

ASSESSMENT: Nomogram with (model B) or without (model A) LNN was constructed to evaluate the 5-year overall (OS), distant metastasis-free (DMFS), and progression-free survival (PFS) for the group as a whole and N1 stage subgroup. High- and low-risk groups were divided (above vs below LNN- or model B-threshold); their response to IC was evaluated among advanced patients in stage III/IV.

STATISTICAL TESTS: Maximally selected rank, univariate and multivariable Cox analysis identified the optimal LNN threshold and other variables. Harrell’s concordance index (C-index) and 2-fold cross-validation evaluated discriminative ability of models. Matched-pair analysis compared survival outcomes of adding IC or not. A P value < 0.05 was considered statistically significant.

RESULTS: Median follow-up duration was 62.1 months. LNN ≥ 4 was independently associated with decreased 5-year DMFS, OS, and PFS in entire patients or N1 subgroup. Compared to model A, model B (adding LNN, LNN ≥ 4 vs <4) presented superior C-indexes in the training (0.755 vs 0.727) and validation groups (0.676 vs 0.642) for discriminating DMFS. High-risk patients benefited from IC with improved post-IC response and OS, but low-risk patients did not (P = 0.785 and 0.690, respectively).

CONCLUSIONS: LNN ≥ 4 is an independent risk stratification factor of worse survival in entire or N1 staging NPC patients. LNN ≥ 4 or the associated nomogram has potential to identify high-risk patients requiring IC.

EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: 4.

PMID:36169976 | DOI:10.1002/jmri.28435