Category: Nevin Manimala

BMC Health Serv Res. 2022 Nov 29;22(1):1440. doi: 10.1186/s12913-022-08813-6.

ABSTRACT

BACKGROUND: Older adults with serious mental illness (SMI) often have multiple comorbidities and complex medication schedules. Shortages of behavioral health specialists (BHSs), especially in rural areas, frequently make primary care providers (PCPs) the only clinician managing this complex population. The aim of this study was to describe rural/urban psychiatric medication prescribing in older adults with SMI by PCPs and BHSs, and by clinician type.

METHODS: This retrospective descriptive analysis used 2018 Medicare data to identify individuals with a bipolar, major depression, schizophrenia, or psychosis diagnosis and examined medication claims for antianxiety, antidepressants, antipsychotics, hypnotics, and anticonvulsants. Descriptive statistics summarized percentage of medications provided by PCPs and BHSs stratified by rural and urban areas and by drug class. Additional analyses compared psychiatric prescribing patterns by physicians, advanced practice registered nurses (APRNs), and physician assistants (PAs).

RESULTS: In urban areas, PCPs prescribed at least 50% of each psychiatric medication class, except antipsychotics, which was 45.2%. BHSs prescribed 40.7% of antipsychotics and less than 25% of all other classes. In rural areas, percentages of psychiatric medications from PCPs were over 70% for each medication class, except antipsychotics, which was 60.1%. Primary care physicians provided most psychiatric medications, between 36%-57% in urban areas and 47%-65% in rural areas. Primary care APRNs provided up to 13% of prescriptions in rural areas, which was more than the amount prescribed by BHS physicians, expect for antipsychotics. Psychiatric mental health APRNs provided up to 7.5% of antipsychotics in rural areas, but their prescribing contribution among other classes ranged between 1.1%-3.6%. PAs provided 2.5%-3.4% of medications in urban areas and this increased to 3.9%-5.1% in rural areas.

CONCLUSIONS: Results highlight the extensive roles of PCPs, including APRNs, in managing psychiatric medications for older adults with SMI.

PMID:36447260 | DOI:10.1186/s12913-022-08813-6

BMC Pharmacol Toxicol. 2022 Nov 30;23(1):88. doi: 10.1186/s40360-022-00630-1.

ABSTRACT

BACKGROUND: Prescribing medications without potential drug-drug interactions (pDDIs) is one of the components of the rational use of medications. However, taking combined medications has resulted in life-threatening pDDIs, which are causing severe clinical outcomes for patients. This study was aimed at assessing the prevalence of pDDIs and associated factors in admitted patients with psychiatric disorders.

METHODS: An institution-based multicenter cross-sectional study was conducted among patients with psychiatric disorders admitted to a selected hospital in Northwest Ethiopia. Samples were approached through a systematic sampling method. The Statistical Package for the Social Sciences (SPSS) version 26 was used to analyze the data. Logistic regression was applied to determine the association of variables with pDDIs. A p-value of < 0.05 was statistically significant.

RESULTS: Out of 325 study participants, more than half (52.9%) were females, with a median age of 61 years. Overall, more than two-thirds (68.9%) were exposed to at least one clinically significant, either significant or serious level of pDDIs. Nearly one-fourth (23.2%) of participants had at least one serious level of pDDIs. Older patients were found more likely to have pDDIs compared to younger patients (p = 0.043). Similarly, patients with a higher number of prescribed medications (p = 0.035) and patients with longer hospital admissions (p = 0.004) were found more likely to be exposed to pDDIs than their counterparts.

CONCLUSION: In this study, a significant number of admitted patients with psychiatric problems encountered clinically significant pDDIs. As a result, healthcare providers could assess and follow patients with a combination of medications that potentially have a drug-drug interaction outcome.

PMID:36447276 | DOI:10.1186/s40360-022-00630-1

BMC Med. 2022 Nov 30;20(1):465. doi: 10.1186/s12916-022-02664-y.

ABSTRACT

BACKGROUND: To update and internally validate a model to predict children and young people (CYP) most likely to experience long COVID (i.e. at least one impairing symptom) 3 months after SARS-CoV-2 PCR testing and to determine whether the impact of predictors differed by SARS-CoV-2 status.

METHODS: Data from a nationally matched cohort of SARS-CoV-2 test-positive and test-negative CYP aged 11-17 years was used. The main outcome measure, long COVID, was defined as one or more impairing symptoms 3 months after PCR testing. Potential pre-specified predictors included SARS-CoV-2 status, sex, age, ethnicity, deprivation, quality of life/functioning (five EQ-5D-Y items), physical and mental health and loneliness (prior to testing) and number of symptoms at testing. The model was developed using logistic regression; performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping and the final model was adjusted for overfitting.

RESULTS: A total of 7139 (3246 test-positives, 3893 test-negatives) completing a questionnaire 3 months post-test were included. 25.2% (817/3246) of SARS-CoV-2 PCR-positives and 18.5% (719/3893) of SARS-CoV-2 PCR-negatives had one or more impairing symptoms 3 months post-test. The final model contained SARS-CoV-2 status, number of symptoms at testing, sex, age, ethnicity, physical and mental health, loneliness and four EQ-5D-Y items before testing. Internal validation showed minimal overfitting with excellent calibration and discrimination measures (optimism-adjusted calibration slope: 0.96575; C-statistic: 0.83130).

CONCLUSIONS: We updated a risk prediction equation to identify those most at risk of long COVID 3 months after a SARS-CoV-2 PCR test which could serve as a useful triage and management tool for CYP during the ongoing pandemic. External validation is required before large-scale implementation.

PMID:36447237 | DOI:10.1186/s12916-022-02664-y

BMC Med. 2022 Nov 30;20(1):463. doi: 10.1186/s12916-022-02665-x.

ABSTRACT

BACKGROUND: Compared with patients who require fewer antihypertensive agents, those with apparent treatment-resistant hypertension (aTRH) are at increased risk for cardiovascular and all-cause mortality, independent of blood pressure control. However, the etiopathogenesis of aTRH is still poorly elucidated.

METHODS: We performed a genome-wide association study (GWAS) in first cohort including 586 aTRHs and 871 healthy controls. Next, expression quantitative trait locus (eQTL) analysis was used to identify genes that are regulated by single nucleotide polymorphisms (SNPs) derived from the GWAS. Then, we verified the genes obtained from the eQTL analysis in the validation cohort including 65 aTRHs, 96 hypertensives, and 100 healthy controls through gene expression profiling analysis and real-time quantitative polymerase chain reaction (RT-qPCR) assay.

RESULTS: The GWAS in first cohort revealed four suggestive loci (1p35, 4q13.2-21.1, 5q22-23.2, and 15q11.1-q12) represented by 23 SNPs. The 23 significant SNPs were in or near LAPTM5, SDC3, UGT2A1, FTMT, and NIPA1. eQTL analysis uncovered 14 SNPs in 1p35 locus all had same regulation directions for SDC3 and LAPTM5. The disease susceptible alleles of SNPs in 1p35 locus were associated with lower gene expression for SDC3 and higher gene expression for LAPTM5. The disease susceptible alleles of SNPs in 4q13.2-21.1 were associated with higher gene expression for UGT2B4. GTEx database did not show any statistically significant eQTLs between the SNPs in 5q22-23.2 and 15q11.1-q12 loci and their influenced genes. Then, gene expression profiling analysis in the validation cohort confirmed lower expression of SDC3 in aTRH but no significant differences on LAPTM5 and UGT2B4, when compared with controls and hypertensives, respectively. RT-qPCR assay further verified the lower expression of SDC3 in aTRH.

CONCLUSIONS: Our study identified a novel association of SDC3 with aTRH, which contributes to the elucidation of its etiopathogenesis and provides a promising therapeutic target.

PMID:36447229 | DOI:10.1186/s12916-022-02665-x

BMC Med Educ. 2022 Nov 29;22(1):821. doi: 10.1186/s12909-022-03908-4.

ABSTRACT

BACKGROUND: Students with developed self-regulated learning (SRL) skills demonstrate an ability to set individualized educational goals, select optimal learning strategies for reaching these goals, and reflect on overall progress. The primary aims of this study were to investigate first-year medical students’ perceived utility of a self-regulated learning-informed intervention and to assess the impact of its implementation on students’ intended use of SRL throughout medical school.

METHODS: A two-part educational intervention focused on SRL skill development was carried out at Harvard Medical School during the start of the 2021 academic year. For the first component of the intervention, 169 first-year medical students engaged in an interactive class session structured around SRL concept videos, a brief lecture, small group discussions and individual reflection. Students completed pre- and post-intervention surveys which inquired about learners’ current and anticipated application of SRL skills. During the second component of the intervention, 15 first-year medical students participated in a set of one-on-one academic SRL coaching sessions. All coaching participants completed follow-up semi-structured interviews.

RESULTS: A statistically significant increase was observed between students’ use of skills in all domains of self-regulated learning prior to the intervention and their anticipated use of these skills following the intervention. Prior to the intervention, 60.1% (n = 92) of students reported utilizing evidence-based learning strategies, compared to 92.8% (n = 142) of students (p < 0.001) who anticipated applying this SRL skills at the completion of the classroom session. Six core themes emerged from qualitative analysis of the post-intervention survey including learning plan development, accountability and progress tracking, goals for growth, engagement through active learning, routine reflection, and adapting to the curriculum.

CONCLUSIONS: Both classroom-based learning sessions and one-on-one academic coaching programs are feasible approaches for encouraging the use of self-regulated learning techniques in the preclinical setting.

PMID:36447223 | DOI:10.1186/s12909-022-03908-4

Malar J. 2022 Nov 29;21(1):358. doi: 10.1186/s12936-022-04381-6.

ABSTRACT

BACKGROUND: Endemic malaria is present in all 15 municipalities of Roraima state, Brazilian Amazonia. Knowledge of epidemiological data of specific populations can guide health policies to formulate effective strategies for integrated control of health-disease care. This study aims to ascertain when, where and who fell ill with malaria in Roraima state from 2010 to 2020.

METHODS: This descriptive study was based on statistical secondary surveillance data through the analysis of relationships underlying numbers of cases, hospitalizations and deaths using the Malaria Epidemiological Surveillance Information System, Mortality Information System and Hospitalization Information System.

RESULTS: From 2010 to 2020, there were 138,504 autochthonous cases, 26,158 Venezuelan imported cases, 3765 hospitalizations, and 77 deaths from malaria reported in Roraima. Annual parasitic incidence and the number of hospitalizations showed impressive changes over the period, but without significantly correlating with number of deaths. The proportion of Plasmodium falciparum infections had significant shifts throughout this study. Malaria prevalence in indigenous and mining areas has been increasing since 2014.

CONCLUSION: The presence of miners in indigenous areas is a reality that has been contributing to the increase of malaria cases in Roraima. The need to implement health policies that also meet this contingent is reinforced.

PMID:36447220 | DOI:10.1186/s12936-022-04381-6

BMC Nurs. 2022 Nov 29;21(1):332. doi: 10.1186/s12912-022-01109-4.

ABSTRACT

BACKGROUND: An accurate and reliable patient classification system (PCS) can help inform decisions regarding adequate assignments for nurse staffing. This study aimed to evaluate the criterion validity of the Asan Patient Classification System (APCS), a new tertiary hospital-specific PCS, by comparing its rating and total scores with those of KPCS-1 and KPCS-GW for measuring patient activity and nursing needs.

METHODS: We performed a retrospective analysis of the medical records of 50,314 inpatients admitted to the general wards of a tertiary teaching hospital in Seoul, South Korea in March, June, September, and December 2019. Spearman’s correlation and Kappa statistics according to quartiles were calculated to examine the criterion validity of the APCS compared with the KPCS-1 and KPCS-GW.

RESULTS: The average patient classification score was 28.3 points for APCS, 25.7 points for KPCS-1, and 21.6 points for KPCS-GW. The kappa value between APCS and KPCS-1 was 0.91 (95% CI:0.9072, 0.9119) and that between APCS and KPCS-GW was 0.88 (95% CI:0.8757, 0.8810). Additionally, Spearman’s correlation coefficients among APCS, KPCS-1, and KPCS-GW showed a very strong correlation. However, 10.8% of the participants’ results were inconsistent, and KPCS-1 tended to classify patients into groups with lower nursing needs compared to APCS.

CONCLUSION: This study showed that electronic health record-generated APCS can provide useful information on patients’ severity and nursing activities to measure workload estimation. Additional research is needed to develop and implement a real-world EHR-based PCS system to accommodate for direct and indirect nursing care while considering diverse population and dynamic healthcare system.

PMID:36447217 | DOI:10.1186/s12912-022-01109-4

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