Nevin Manimala

BMC Nurs. 2022 Nov 29;21(1):333. doi: 10.1186/s12912-022-01115-6.

ABSTRACT

BACKGROUND: Coronary heart disease (CHD) has become a leading cause of morbidity and premature death worldwide. Cardiac rehabilitation (CR) was proved to have substantial benefits for patients with CHD. The CR was divided into three phases. Phase 2 is the important part of CR which involves hospital-based structured and closely monitored exercises and activities. However, CR utilization is low worldwide. The barriers to hospital-based phase 2 CR in China have not been well identified.

AIMS: To investigate barriers to hospital-based phase 2 cardiac rehabilitation among coronary heart disease patients in China and to explore the reasons.

METHODS: This study employed an explanatory sequential mixed-methods design. The study was conducted in a university hospital in China from July 2021 to December 2021. Quantitative data was collected through the Cardiac Rehabilitation Barrier Scale. Qualitative data was collected through unstructured face-to-face interviews. Data analysis included descriptive statistics and inductive qualitative content analysis.

RESULTS: One hundred and sixty patients completed the Cardiac Rehabilitation Barrier Scale and 17 patients participated in unstructured face-to-face interviews. The main barriers identified were distance (3.29 ± 1.565), transportation (2.99 ± 1.503), cost (2.76 ± 1.425), doing exercise at home (2.69 ± 1.509) and time constraints (2.48 ± 1.496). Six themes were identified; logistical factors, social support, misunderstanding of cardiac rehabilitation, program and health system-level factors, impression of CR team and psychological distress. The first four themes confirmed the quantitative results and provide a deeper explanation for the quantitative results. The last two themes were new information that emerged in the qualitative phase.

CONCLUSION: This study provides a better understanding of the barriers to hospital-based phase 2 cardiac rehabilitation among coronary heart disease patients in the Chinese context during the Covid-19 pandemic. Innovative programs such as home-based CR, mobile health, and hybrid programs might be considered to overcome some of these barriers. In addition, psychosocial intervention should be included in these programs to mitigate some of the barriers associated with the impression of CR team and psychological distress.

PMID:36447215 | DOI:10.1186/s12912-022-01115-6

Hereditas. 2022 Nov 29;159(1):43. doi: 10.1186/s41065-022-00257-6.

ABSTRACT

OBJECTIVE: Gastric cancer is one of the most common and deadly types of cancer. The molecular mechanism of gastric cancer progression remains unclear.

MATERIALS AND METHODS: Four hub genes were identified through GEO and TCGA database screening and analysis. Prognostic analysis revealed that COL5A2 was the most likely to affect the prognosis of gastric cancer among the four hub genes. The relationships between COL5A2 and clinical variables and immune cell infiltration were analyzed. Then, COL5A2 was analyzed for single-gene differences and related functional enrichment. Using the starBase database for prediction and analysis, miRNAs and pseudogenes/lncRNAs that might combine with COL5A2 were identified; thus, the ceRNA network was constructed. Finally, the network was verified by Cox analysis and qPCR, and a nomogram was constructed.

RESULTS: First, we found that COL5A2, COL12A1, BGN and THBS2 were highly expressed in gastric cancer. COL5A2 had statistical significance in overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) analysis. Immune infiltration analysis suggested that COL5A2 might influence the changes in the tumor immune microenvironment. The StarBase database was used to predict that 3 pseudogenes and 7 lncRNAs might inhibit the hsa-miR-200b-3p-COL5A2 axis in gastric cancer. The pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 ceRNA network was identified and verified using Cox regression analysis and PCR. Finally, we constructed a nomogram.

CONCLUSIONS: We elucidated the regulatory role of the pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 network in gastric cancer progression and constructed a nomogram. These studies may provide effective treatments and potential prognostic biomarkers for gastric cancer.

PMID:36447214 | DOI:10.1186/s41065-022-00257-6

BMC Med. 2022 Nov 30;20(1):464. doi: 10.1186/s12916-022-02668-8.

ABSTRACT

BACKGROUND: Bipolar disorder (BD) is a highly heritable psychiatric illness exhibiting substantial correlation with intelligence.

METHODS: To investigate the shared genetic signatures between BD and intelligence, we utilized the summary statistics from genome-wide association studies (GWAS) to conduct the bivariate causal mixture model (MiXeR) and conjunctional false discovery rate (conjFDR) analyses. Subsequent expression quantitative trait loci (eQTL) mapping in human brain and enrichment analyses were also performed.

RESULTS: Analysis with MiXeR suggested that approximately 10.3K variants could influence intelligence, among which 7.6K variants were correlated with the risk of BD (Dice: 0.80), and 47% of these variants predicted BD risk and intelligence in consistent allelic directions. The conjFDR analysis identified 37 distinct genomic loci that were jointly associated with BD and intelligence with a conjFDR < 0.01, and 16 loci (43%) had the same directions of allelic effects in both phenotypes. Brain eQTL analyses found that genes affected by the “concordant loci” were distinct from those modulated by the “discordant loci”. Enrichment analyses suggested that genes related to the “concordant loci” were significantly enriched in pathways/phenotypes related with synapses and sleep quality, whereas genes associated with the “discordant loci” were enriched in pathways related to cell adhesion, calcium ion binding, and abnormal emotional phenotypes.

CONCLUSIONS: We confirmed the polygenic overlap with mixed directions of allelic effects between BD and intelligence and identified multiple genomic loci and risk genes. This study provides hints for the mesoscopic phenotypes of BD and relevant biological mechanisms, promoting the knowledge of the genetic and phenotypic heterogeneity of BD. The essential value of leveraging intelligence in BD investigations is also highlighted.

PMID:36447210 | DOI:10.1186/s12916-022-02668-8

BMC Public Health. 2022 Nov 29;22(1):2215. doi: 10.1186/s12889-022-14628-1.

ABSTRACT

BACKGROUND: Verbal autopsy (VA) has emerged as an increasingly popular technique to assign cause of death in parts of the world where the majority of deaths occur without proper medical certification. The purpose of this study was to examine the key characteristics of studies that have attempted to validate VA cause of death against an established cause of death.

METHODS: A systematic review was conducted by searching the MEDLINE, EMBASE, Cochrane-library, and Scopus electronic databases. Included studies contained 1) a VA component, 2) a validation component, and 3) original analysis or re-analysis. Characteristics of VA studies were extracted. A total of 527 studies were assessed, and 481 studies screened to give 66 studies selected for data extraction.

RESULTS: Sixty-six studies were included from multiple countries. Ten studies used an existing database. Sixteen studies used the World Health Organization VA questionnaire and 5 studies used the Population Health Metrics Research Consortium VA questionnaire. Physician certification was used in 36 studies and computer coded methods were used in 14 studies. Thirty-seven studies used high level comparator data with detailed laboratory investigations.

CONCLUSION: Most studies found VA to be an effective cause of death assignment method and compared VA cause of death to a high-quality established cause of death. Nonetheless, there were inconsistencies in the methodologies of the validation studies, and many used poor quality comparison cause of death data. Future VA validation studies should adhere to consistent methodological criteria so that policymakers can easily interpret the findings to select the most appropriate VA method.

PROSPERO REGISTRATION: CRD42020186886.

PMID:36447199 | DOI:10.1186/s12889-022-14628-1

BMC Complement Med Ther. 2022 Nov 29;22(1):315. doi: 10.1186/s12906-022-03792-x.

ABSTRACT

BACKGROUND: Coronary angiography is the gold standard for the diagnosis of coronary artery disease. This intervention is nevertheless a source of anxiety for the patient both by its discomfort and by the consequences linked to the discovery of potential diseases.

OBJECTIVES: The aim of this study was to determine the effectiveness of hypnosis in reducing anxiety in patients undergoing coronary angiography.

METHODS: One hundred sixty-nine patients with planned coronary angiography and no history of coronary angiography were randomized to a hypnosis or control group. Patients in the hypnosis group underwent a hypnosis session with self-hypnosis posthypnotic suggestions, while those in the control group had a conversational interview with the hypnotherapist. The primary endpoint was pre-exam anxiety level assessed by the Spielberger State-Trait Anxiety Inventory (STAI-Y A).

RESULTS: Performing a hypnosis session did not result in a significant decrease in anxiety before the intervention. Age, high trait anxiety, high state anxiety the day before, and belief that hypnosis works in general were associated with increased anxiety before the procedure. No adverse events were reported after hypnosis. There was no statistically significant difference between the 2 groups for the occurrence of complications of the intervention.

CONCLUSION: In this study, performing a hypnosis session before coronary angiography did not reduce the state of anxiety measured just before the intervention. In all cases, the hypnotic experience appears to be positive for the patient, encouraging further research efforts.

TRIAL REGISTRATION: The research protocol has been registered on the ClinicalTrials.gov registry (NCT02818101; 29/06/2016) and with the ANSM (IDRCB 2016-A00205-46; 02/02/2016).

PMID:36447198 | DOI:10.1186/s12906-022-03792-x

Environ Health. 2022 Nov 29;21(1):119. doi: 10.1186/s12940-022-00937-w.

ABSTRACT

BACKGROUND: Studies showed that PM_2.5 might be associated with various neurogenic diseases such as Alzheimer’s Disease (AD). However, this topic had been little studied in Zhejiang province of China. METHODS: In 2018, we established a cohort of AD high-risk population with 1,742 elderly aged 60 and above. In 2020, the cohort was followed up, a total of 1,545 people participated the 2 surveys. Data collection included questionnaires and basic physical examinations. The average residential exposure to PM_2.5 for each participant, that in a 5-years period prior to the first survey, was estimated using a satellite-based spatial statistical model. We determined the association between PM_2.5 and AD prevalence by cox proportional hazards regression model. RESULTS: This study showed that an increase in the PM_2.5 level was an important associated risk factor that contributed to AD. The average PM_2.5 exposure levels among the study population ranged from 32.69 μg/m³ to 39.67 μg/m³ from 2013 to 2017, which were much higher than 5 μg/m³ that specified in the WHO air quality guidelines. There was an association between PM_2.5 exposure and AD, and the correlations between PM_2.5 and Mini-Mental State Examination, Montreal cognitive assessment scale scores were statistically significant. An increase in the PM_2.5 level by 10 μg/m³ elevated the risk of AD among residents by 2%-5% (HR _{model 2-model 4} = 1.02 to 1.05, CI _{model 2-model 4} = 1.01-1.10). The subgroups of male, with old age, with low education levels, used to work as farmers or blue-collar workers before retirement, overweight and obese were associated with a higher effect of PM_2.5.

CONCLUSIONS: Reducing PM_2.5 exposure might be a good way to prevent AD.

PMID:36447194 | DOI:10.1186/s12940-022-00937-w

BMC Cancer. 2022 Nov 29;22(1):1233. doi: 10.1186/s12885-022-10351-7.

ABSTRACT

BACKGROUND: Lung immune prognostic index (LIPI) is a prognostic marker of extensive-stage small cell lung cancer (ES-SCLC) patients received immunotherapy or chemotherapy. However, its ability in limited-stage SCLC (LS-SCLC) should be evaluated extensively.

METHODS: We retrospectively enrolled 497 patients diagnosed as LS-SCLC between 2015 and 2018, and clinical data included pretreatment lactate dehydrogenase (LDH), white blood cell count, and absolute neutrophil count levels were collected. According to the LIPI scores, the patients were stratified into low-risk (0 points) and high-risk (1-2 points). The correlations between LIPI and overall survival (OS) or progression-free survival (PFS) were analyzed by the Cox regression. Additionally, the propensity score matching (PSM) and inverse probability of treatment weight (IPTW) methods were used to reduce the selection and confounding bias. A nomogram was constructed using on multivariable Cox model.

RESULTS: Two hundred fifty and 247 patients were in the LIPI high-risk group and low-risk group, and their median OS was 14.67 months (95% CI: 12.30-16.85) and 20.53 months (95% CI: 17.67-23.39), respectively. In the statistical analysis, High-risk LIPI was significantly against worse OS (HR = 1.377, 95%CI:1.114-1.702) and poor PFS (HR = 1.338, 95%CI:1.1-1.626), and the result was similar after matching and compensating with the PSM or IPTW method. A novel nomogram based on LIPI has a decent level of predictive power.

CONCLUSION: LIPI stratification was a significant factor against OS or PFS of LS-SCLC patients.

PMID:36447193 | DOI:10.1186/s12885-022-10351-7

Cutis. 2022 Sep;110(3):150-154. doi: 10.12788/cutis.0607.

ABSTRACT

Mutations of the BRAF oncogene occur in both melanomas and several other cancers. Our objective was to determine if mutant BRAF V600E expression in a population-based cohort of patients with melanoma was associated with the development of a second primary malignancy of any type. Using the resources of the Rochester Epidemiology Project, we retrospectively identified 380 patients aged 18 to 60 years who were diagnosed with an incident melanoma from 1970 through 2009. We reviewed individual medical records to identify second primary malignancies. We evaluated mutant BRAF V600E expression from available melanoma tissue specimens and assessed its association with the development of a second primary malignancy. BRAF V600E expression in melanomas is associated with an increased risk for basal cell carcinoma (BCC).

PMID:36446115 | DOI:10.12788/cutis.0607

Cutis. 2022 Oct;110(4):215-219. doi: 10.12788/cutis.0626.

ABSTRACT

Approximately 4.5% of adults in the United States identify as members of the lesbian, gay, bisexual, transgender (LGBT) community, and this population has a variety of health care disparities. Dermatologists have the potential to greatly impact the health of this community, but learning experiences in dermatology residency are lacking. In this study, we investigated LGBT education in dermatologic residency from the residents’ perspective and assessed preparedness of dermatology residents to care for this community. An online survey was distributed to current US dermatology residents through program coordinator and program director listserves and postings on dermatology social media groups. Descriptive statistics and a Kruskal-Wallis rank test were used for analysis. There were 114 respondents. This study demonstrated that many dermatology residents are not effectively taught LGBT health topics and feel unprepared to treat this community. Most dermatology residents desired increased training. Further research is needed to determine the best strategies for increasing LGBT learning experiences in dermatology residency programs.

PMID:36446104 | DOI:10.12788/cutis.0626

JMIR Form Res. 2022 Nov 8. doi: 10.2196/40825. Online ahead of print.

ABSTRACT

BACKGROUND: Across each state. the emergence of the COVID-19 pandemic in the United States was marked by policies and rhetoric that often correspond to the political party in power. These diverging responses have sparked broad ongoing discussion about how the political leadership of a state may affect not only the COVID-19 case numbers in a given state, but also the subjective individual experience of the pandemic.

OBJECTIVE: This study leverages state-level data from Google Search Trends and CDC daily case data in order to investigate the temporal relationship between increases in relative search volume for COVID-19 symptoms and corresponding increases in case data. I aimed to identify whether there are state-level differences in patterns of lag time across each of the four spikes in the data (RQ1) and whether the political climate in a given state is associated with these differences (RQ2).

METHODS: Using publicly available data from Google Trends and the Centers for Disease Control and Prevention, linear mixed modeling was utilized to account for random state-level intercepts. Lag time was operationalized as number of days between a peak (a sustained increase before a sustained decline) in symptom search data and a corresponding spike in case data and was calculated manually for each of the four spikes in individual states. Google offers a dataset that tracks the relative search incidence of more than 400 potential COVID-19 symptoms, which is normalized on a 0-100 scale. I used the CDC’s definition of the eleven most common COVID-19 symptoms and created a single construct variable that operationalizes symptom searches. To measure political climate, I considered the proportion of 2020 Trump popular votes in a state as well as a dummy variable for the political party that controls the governorship and a continuous variable measuring proportional party control of federal Congressional representatives.

RESULTS: The strongest overall fit was for a linear mixed model that included proportion of 2020 Trump votes as the predictive variable of interest and included controls for mean daily cases and deaths as well as population. Additional political climate variables were discarded for lack of model fit. Findings indicated evidence that there are statistically-significant differences in lag time by state but that no individual variable measuring political climate was a statistically-significant predictor of these differences.

CONCLUSIONS: Given that there will likely be future pandemics within this political climate, it is important to understand how political leadership affects perceptions of and corresponding responses to public health crises. Although this study did not fully model this relationship, I believe that future research can build on the state-level differences that I identified by approaching the analysis with a different theoretical model, method for calculating lag time, and/or level of geographic modeling.

PMID:36446048 | DOI:10.2196/40825