Tag: pubmed

BMC Pregnancy Childbirth. 2023 Nov 22;23(1):811. doi: 10.1186/s12884-023-06098-z.

ABSTRACT

BACKGROUND: The acute respiratory disease caused by the coronavirus (COVID-19) has spread rapidly worldwide yet has not been eliminated. The infection is especially deadly in vulnerable populations. The current studies indicate that pregnant women are at greater risk of getting seriously ill. Even though fetuses protect against disease, the additional finding showed that the COVID-19 pandemic could increase fetal and maternal morbidities. In a situation where COVID-19 and new strains of the virus are still not controlled, scientists predicted that the world might experience another pandemic. Consequently, more research about the effects of COVID-19 infection on pregnancy outcomes is needed. This study aimed to compare the pregnancy outcomes of Iranian pregnant women in the first year of the pandemic with the previous year.

METHODS: This prospective cross-sectional study was performed to compare the pregnancy outcome during the COVID-19 pandemic among Iranian pregnant women who gave birth during the pandemic and one year before the pandemic (2019-2020 and 2020-2021). The sample size was 2,371,332 births registered at hospitals and birth centers platforms. The studied variables include stillbirth, congenital anomaly, birth weight, preeclampsia, gestational diabetes, cesarean section, ICU admission, mean of the gestational age at birth, preterm births, NICU admission, neonatal mortality and the percentage of deliveries with at least one complication such as blood transfusion and postpartum ICU admission. Analyzing data was done by using SPSS version 25 software.

RESULTS: We found statistical differences between pregnancy and birth outcomes during the COVID-19 pandemic compared to one year before. The risk of preeclampsia, gestational diabetes, cesarean section, preterm birth and NICU admission were clinically significant. Also, there was a significant decrease in mean gestational age.

CONCLUSION: The COVID-19 pandemic has affected the pregnancy outcome by increasing morbidities and complications during pregnancy, birth, and postpartum. In addition, extensive quarantine outbreaks disrupted the healthcare system and hindered access to prenatal services. It is necessary to develop preventive and therapeutic care protocols for similar pandemic conditions.

PMID:37993814 | DOI:10.1186/s12884-023-06098-z

BMC Public Health. 2023 Nov 22;23(1):2310. doi: 10.1186/s12889-023-17214-1.

ABSTRACT

BACKGROUND: Racial inequities in life expectancy, driven by structural racism, have been documented at the state and county levels; however, less information is available at the city level where local policy change generally happens. Furthermore, an assessment of life expectancy during the decade preceding COVID-19 provides a point of comparison for life expectancy estimates and trends post COVID-19 as cities recover.

METHODS: Using National Vital Statistics System mortality data and American Community Survey population estimates, we calculated the average annual city-level life expectancies for the non-Hispanic Black (Black), non-Hispanic White (White), and total populations. We then calculated the absolute difference between the Black and White life expectancies for each of the 30 cities and the U.S. We analyzed trends over four time periods (2008-2010, 2011-2013, 2014-2016, and 2017-2019).

RESULTS: In 2017-2019, life expectancies ranged from 72.75 years in Detroit to 83.15 years in San Francisco (compared to 78.29 years for the U.S.). Black life expectancy ranged from 69.94 years in Houston to 79.04 years in New York, while White life expectancy ranged from 75.18 years in Jacksonville to 86.42 years in Washington, DC. Between 2008-2010 and 2017-2019, 17 of the biggest cities experienced a statistically significant improvement in life expectancy, while 9 cities experienced a significant decrease. Black life expectancy increased significantly in 14 cities and the U.S. but decreased significantly in 4 cities. White life expectancy increased significantly in 17 cities and the U.S. but decreased in 8 cities. In 2017-2019, the U.S. and all but one of the big cities had a significantly longer life expectancy for the White population compared to the Black population. There was more than a 13-year difference between Black and White life expectancies in Washington, DC (compared to 4.18 years at the national level). From 2008-2010 to 2017-2019, the racial gap decreased significantly for the U.S. and eight cities, while it increased in seven cities.

CONCLUSION: Urban stakeholders and equity advocates need data on mortality inequities that are aligned with city jurisdictions to help guide the allocation of resources and implementation of interventions.

PMID:37993811 | DOI:10.1186/s12889-023-17214-1

BMC Pulm Med. 2023 Nov 22;23(1):464. doi: 10.1186/s12890-023-02775-z.

ABSTRACT

OBJECTIVE: To investigate the prevalence of intensive care unit (ICU) admission and its predictors among hospitalized chronic obstructive pulmonary disease (COPD) patients.

METHODS: An observational retrospective study was conducted. All patients with a confirmed diagnosis of COPD according to the GOLD guidelines between 28 and 2020 and 1 March 2023 at Al-Noor Specialist Hospital were included in this study. Patients were excluded if a preemptive diagnosis of COPD was made clinically without spirometry evidence of fixed airflow limitation. Descriptive results were presented as frequency (percentage) for categorical variables and mean (SD) for continuous variables and to estimate prevalence of ICU admission. Predictors of ICU admission among hospitalized COPD patients were determined using logistic regression analysis. A SPSS (Statistical Package for the Social Sciences) version 25 was used to perform all statistical analysis.

RESULTS: A total of 705 patients with COPD were included in this study. The mean age was 65.4 (25.3) years. Around 12.4% of the hospitalized patients were admitted to the ICD. Logistic regression analysis identified that older age (OR; 1.92, (1.41-2.62)), smoking (OR; 1.60 (1.17-2.19)), and having specific comorbidities (Hypertension (OR; 1.98 (1.45-2.71)), Diabetes mellitus (OR; 1.42 (1.04-1.93)), GERD (OR; 2.81 (1.99-3.96)), Ischemic heart disease (OR; 3.22 (2.19-4.75)), Obstructive sleep apnea syndrome (OR; 2.14 (1.38-3.33)), stroke (OR; 4.51 (2.20-9.26))) were predictors of ICU admissions among patients with COPD.

CONCLUSIONS: Our study found that a step-up approach to inpatient COPD management requires admission to the ICU in 12.4%, for which age, smoking status, cardiovascular, and stroke were important predictors. Further clinical research is needed to provide a validated model that can be incorporated into clinical practice to monitor this patient population during their admission and identify at-risk individuals for early transfer to higher acuity settings and intensive care units.

PMID:37993810 | DOI:10.1186/s12890-023-02775-z

BMC Infect Dis. 2023 Nov 22;23(1):820. doi: 10.1186/s12879-023-08823-7.

ABSTRACT

BACKGROUND: Because of the multidrug resistance features of Acinetobacter baumannii, endurance to diverse conditions, and causing health fatalities in healthcare settings, the global health system is looking for the development of new antimicrobials for such bacteria. As the new antimicrobial drugs pipeline is running dry, it is imperative to look for eco-friendly bio-control strategies. In this regard, phages are one to combat the biofilm producer and MDR A. baumannii. Thus, the study aimed to isolate and examine the role of phages against biofilm producers and MDR A. baumannii from inanimate objects at Jimma Medical Center (JMC), Ethiopia.

METHOD: Institution-based cross-sectional study was conducted from June to November 2019. A total of 309 swab samples were collected from inanimate objects and the environment in JMC. Isolation of A. baumannii, antimicrobial susceptibility testing, and biofilm detection were carried out according to standard protocol. Kirby Bauer disk diffusion and microliter plate were methods for AST and biofilm detection, respectively. Specific phage was isolated and characterized from sewage at JMC compound. The data were analyzed by SPSS version 25.0, and chi-square (X²) cross-tabulation was used to determine the correlation of variables. A P-value of < 0.05 was considered a statistically significant association.

RESULT: A. baumannii from inanimate objects and surfaces of different environments at JMC was detected in 6.5% of the samples. From 20 of the isolates, 85% were biofilm producers, and 60% were MDR. The lytic phage isolated specifically against A. baumannii was found host specific, and thermally stable ranging from 10-50°C. The phage was active against 42% of MDR A. baumannii, 40% of both biofilm-producing and MDR A. baumannii (MDRAB), and 35.3% of the biofilm-producing isolates.

CONCLUSION: The good activity of phages towards MDRAB isolates, its biofilm degradation capability, thermal stability, and host specificity in our study encourages viewing the potential use of phages as a bio-control agent besides the routine cleansing agents. Therefore, we recommend isolation of specific phages in the eradication of MDRAB from health facilities with additional efforts to characterize in detail and assess their efficacy in animal models.

PMID:37993809 | DOI:10.1186/s12879-023-08823-7

BMC Pregnancy Childbirth. 2023 Nov 22;23(1):810. doi: 10.1186/s12884-023-06126-y.

ABSTRACT

BACKGROUND: A nationwide assessment of the link between women’s empowerment and homebirth has not been fully examined in Sierra Leone. Our study examined the association between women’s empowerment and homebirth among childbearing women in Sierra Leone using the 2019 Sierra Leone Demographic Health Survey (2019 SLDHS) data.

METHOD: We used the individual file (IR) of the 2019 SLDHS dataset for our analysis. A total of 7377 women aged 15-49 years who gave birth in the five years preceding the survey were included. Outcome variable was “home birth of their last child among women in the five years preceding the 2019 SLDHS. Women’s empowerment parameters include women’s knowledge level, economic participation, decision-making ability and power to refuse the idea of intimate partner violence. We used the complex sample command on SPSS version 28 to conduct descriptive and multivariate logistic regression analyses.

RESULTS: Three in every 20 women had home childbirth (n = 1177; 15.3%). Women with low [aOR 2.04; 95% CI 1.43-2.92] and medium [aOR 1.44; 95%CI 1.05-1.97] levels of knowledge had higher odds of giving birth at home compared to those with high levels of knowledge. Women who did not have power to refuse the idea of intimate partner violence against women were more likely to had given birth at home [aOR 1.38; 95% CI1.09-1.74]. In addition, women with no [aOR 2.71; 95% CI1.34-5.46) and less than four antenatal care visits [aOR 2.08; 95% CI:1.51-2.88] and for whom distance to a health facility was a major problem [aOR 1.95; 95% CI1.49-2.56] were more likely to have had a homebirth. However, no statistically significant association was observed between a women’s decision-making power and home birth [aOR 1.11; 95% CI 0.86-1.41].

CONCLUSION: Despite improvements in maternal health indicators, homebirth by unskilled birth attendants is still a public health concern in Sierra Leone. Women with low knowledge levels, who did not have power to refuse the idea of intimate partner violence against women, had less than four ANC visits and considered distance to a health facility as a major problem had higher odds of giving birth at home. Our findings reflect the need to empower women by improving their knowledge level through girl child and adult education, increasing media exposure, changing societal norms and unequal power relations that promote gender-based violence against women, and improving roads and transport infrastructure.

PMID:37993807 | DOI:10.1186/s12884-023-06126-y

BMC Pregnancy Childbirth. 2023 Nov 22;23(1):812. doi: 10.1186/s12884-023-06133-z.

ABSTRACT

INTRODUCTION: Determination of the fetal gender in the first trimester is important in twin pregnancy cases of familial X-linked genetic syndromes and helps determine chorionicity. We assessed and compared the accuracy of first-trimester ultrasound scans, and cell-free fetal DNA (CfDNA) in determining fetal gender in the first trimester of twin pregnancies.

METHODS: Women with twin pregnancies were recruited prospectively during the first trimester. Fetal gender was determined using both ultrasound scans and CfDNA screening. Both results were compared to the newborn gender after delivery.

RESULTS: A total of 113 women with twin pregnancies were enrolled. There was 100% sensitivity and specificity in Y chromosome detection using CfDNA. Gender assignment using ultrasound in any first-trimester scans was 79.7%. Accuracy level increased from 54.2% in CRL 45-54 mm to 87.7% in CRL 55-67 mm and 91.5% in CRL 67-87 mm. Male fetuses had significantly higher chances of a gender assignment error compared to female fetuses, odds ratio = 23.574 (CI 7.346 – 75.656).

CONCLUSIONS: CfDNA is highly sensitive and specific in determining the presence of the Y chromosome in twin pregnancies in the first trimester. Between CRL 55-87 mm, ultrasound scanning offers a highly accurate determination of fetal gender in twin pregnancies.

PMID:37993805 | DOI:10.1186/s12884-023-06133-z

BMC Geriatr. 2023 Nov 22;23(1):767. doi: 10.1186/s12877-023-04457-1.

ABSTRACT

BACKGROUND: Delirium is a prevalent neuropsychiatric medical phenomenon that causes serious emergency outcomes, including mortality and morbidity. It also increases the suffering and the economic burden for families and carers. Unfortunately, the pathophysiology of delirium is still unknown, which is a major obstacle to therapeutic development. The modern network-based system biology and multi-omics analysis approach has been widely used to recover the key drug target biomolecules and signaling pathways associated with disease pathophysiology. This study aimed to identify the major drug target hub-proteins associated with delirium, their regulatory molecules with functional pathways, and repurposable drug candidates for delirium treatment.

METHODS: We used a comprehensive proteomic seed dataset derived from a systematic literature review and the Comparative Toxicogenomics Database (CTD). An integrated multi-omics network-based bioinformatics approach was utilized in this study. The STRING database was used to construct the protein-protein interaction (PPI) network. The gene set enrichment and signaling pathways analysis, the regulatory transcription factors and microRNAs were conducted using delirium-associated genes. Finally, hub-proteins associated repurposable drugs were retrieved from CMap database.

RESULTS: We have distinguished 11 drug targeted hub-proteins (MAPK1, MAPK3, TP53, JUN, STAT3, SRC, RELA, AKT1, MAPK14, HSP90AA1 and DLG4), 5 transcription factors (FOXC1, GATA2, YY1, TFAP2A and SREBF1) and 6 microRNA (miR-375, miR-17-5, miR-17-5p, miR-106a-5p, miR-125b-5p, and miR-125a-5p) associated with delirium. The functional enrichment and pathway analysis revealed the cytokines, inflammation, postoperative pain, oxidative stress-associated pathways, developmental biology, shigellosis and cellular senescence which are closely connected with delirium development and the hallmarks of aging. The hub-proteins associated computationally identified repurposable drugs were retrieved from database. The predicted drug molecules including aspirin, irbesartan, ephedrine-(racemic), nedocromil, and guanidine were characterized as anti-inflammatory, stimulating the central nervous system, neuroprotective medication based on the existing literatures. The drug molecules may play an important role for therapeutic development against delirium if they are investigated more extensively through clinical trials and various wet lab experiments.

CONCLUSION: This study could possibly help future research on investigating the delirium-associated therapeutic target biomarker hub-proteins and repurposed drug compounds. These results will also aid understanding of the molecular mechanisms that underlie the pathophysiology of delirium onset and molecular function.

PMID:37993790 | DOI:10.1186/s12877-023-04457-1

BMC Geriatr. 2023 Nov 22;23(1):764. doi: 10.1186/s12877-023-04412-0.

ABSTRACT

BACKGROUND: Aesthetics of everyday life are associated with the physical, mental, and social health of older adults, leading them to experience a successful old age. This study aimed to examine the aesthetics of everyday life and its related factors among older adults in Kashan from 2021 to 2022.

METHODS: This cross-sectional study consisted of 350 older adults who were referred to Urban Comprehensive Health Service Centers (UCHSC) in Kashan. Sampling was done by a two-stage method (cluster, random). The data collection was performed with a background information questionnaire and the Elderly’s Perception of Everyday Aesthetics scale (EPEA-S). Data were analyzed using an independent t-test, analysis of variance, Pearson’s correlation coefficient, and multiple linear regression tests in the SPSS software.

RESULTS: The mean age of the participants was 69.56 ± 6.63 years. The mean score of aesthetics of everyday life in older adults was 133.02 ± 14.73, with the family and others subscale receiving the highest score. The univariate test indicated a statistically significant correlation between age, employment status, education, income, smoking, social activities, physical activities, interest in artistic works, and the aesthetics of everyday life in older adults (P < 0.01). Multivariate linear analysis showed that age, employment status, smoking, income, social activities, physical activities, and interest in artistic works predicted and explained 28% of the variance of life aesthetics in older adults (R2 = 0.28).

CONCLUSIONS: The aesthetics of everyday life of the Iranian older adults were in a good range. Healthcare providers and families of older adults can use this concept to enhance the elderly’s physical, mental, and social health.

PMID:37993782 | DOI:10.1186/s12877-023-04412-0

BMC Bioinformatics. 2023 Nov 22;24(1):443. doi: 10.1186/s12859-023-05560-1.

ABSTRACT

Messenger RNA (mRNA) has an essential role in the protein production process. Predicting mRNA expression levels accurately is crucial for understanding gene regulation, and various models (statistical and neural network-based) have been developed for this purpose. A few models predict mRNA expression levels from the DNA sequence, exploiting the DNA sequence and gene features (e.g., number of exons/introns, gene length). Other models include information about long-range interaction molecules (i.e., enhancers/silencers) and transcriptional regulators as predictive features, such as transcription factors (TFs) and small RNAs (e.g., microRNAs – miRNAs). Recently, a convolutional neural network (CNN) model, called Xpresso, has been proposed for mRNA expression level prediction leveraging the promoter sequence and mRNAs’ half-life features (gene features). To push forward the mRNA level prediction, we present miREx, a CNN-based tool that includes information about miRNA targets and expression levels in the model. Indeed, each miRNA can target specific genes, and the model exploits this information to guide the learning process. In detail, not all miRNAs are included, only a selected subset with the highest impact on the model. MiREx has been evaluated on four cancer primary sites from the genomics data commons (GDC) database: lung, kidney, breast, and corpus uteri. Results show that mRNA level prediction benefits from selected miRNA targets and expression information. Future model developments could include other transcriptional regulators or be trained with proteomics data to infer protein levels.

PMID:37993778 | DOI:10.1186/s12859-023-05560-1

BMC Bioinformatics. 2023 Nov 22;24(1):442. doi: 10.1186/s12859-023-05572-x.

ABSTRACT

Drug repurposing is an exciting field of research toward recognizing a new FDA-approved drug target for the treatment of a specific disease. It has received extensive attention regarding the tedious, time-consuming, and highly expensive procedure with a high risk of failure of new drug discovery. Data-driven approaches are an important class of methods that have been introduced for identifying a candidate drug against a target disease. In the present study, a model is proposed illustrating the integration of drug-disease association data for drug repurposing using a deep neural network. The model, so-called IDDI-DNN, primarily constructs similarity matrices for drug-related properties (three matrices), disease-related properties (two matrices), and drug-disease associations (one matrix). Then, these matrices are integrated into a unique matrix through a two-step procedure benefiting from the similarity network fusion method. The model uses a constructed matrix for the prediction of novel and unknown drug-disease associations through a convolutional neural network. The proposed model was evaluated comparatively using two different datasets including the gold standard dataset and DNdataset. Comparing the results of evaluations indicates that IDDI-DNN outperforms other state-of-the-art methods concerning prediction accuracy.

PMID:37993777 | DOI:10.1186/s12859-023-05572-x