Nevin Manimala

Vet World. 2023 Feb;16(2):414-420. doi: 10.14202/vetworld.2023.414-420. Epub 2023 Feb 28.

ABSTRACT

BACKGROUND AND AIM: People who used to rear companion animals are healthier than others who do not. Gastrointestinal (GI) helminths are common in cats and serve as reservoirs for zoonotic diseases. However, the prevalence of GI parasites in cats in Myanmar has never been reported. This study aimed to estimate the prevalence of GI parasites in cats in Myanmar and to identify the potential risk factors associated with GI parasites.

MATERIALS AND METHODS: A total of 230 fecal samples were collected from seven veterinary clinics and two shelters within the Yangon region from January to May 2022. Sampled cats were classified according to age, gender, and the deworming and rearing practices. Fecal samples were analyzed by fecal wet mount, ethyl acetate centrifugal sedimentation, and zinc sulfate centrifugal flotation techniques. Descriptive data were described, and Pearson’s χ² test was used to identify associated risk factors, such as age, gender, and the deworming and rearing practices.

RESULTS: The overall prevalence of GI parasites was 79.56%, and 57.82% of cats were infected with a diagnostic stage of more than one parasite species. Seven GI parasites were detected, including Ancylostoma spp. (55.65%), Toxocara spp. (46.08%), Trichuris spp. (20.86%), Platynosomum spp. (11.73%), Dipylidium caninum (7.39%), Taenia spp. (4.34%), and Cystoisospora spp. (32.17%). Based on statistical analysis, the deworming and rearing practices were significantly associated (p < 0.05) with GI parasitic infections.

CONCLUSION: This study is the first to reveal the prevalence of GI parasites that could assist the need for effective control measures for zoonotic hookworm and roundworm infections in cats. Even with simple microscopic examination, the remarkably high prevalence of GI parasitic infections warrants regular deworming practice. Further molecular studies should also be performed to understand their genetic diversity.

PMID:37041997 | PMC:PMC10082719 | DOI:10.14202/vetworld.2023.414-420

ERJ Open Res. 2023 Apr 11;9(2):00481-2022. doi: 10.1183/23120541.00481-2022. eCollection 2023 Mar.

ABSTRACT

BACKGROUND: Accurate prognosis is important either after acute infection or during long-term follow-up of patients infected by severe acute respiratory syndrome coronavirus 2. This study aims to predict coronavirus disease 2019 (COVID-19) severity based on clinical and biological indicators, and to identify biomarkers for prognostic assessment.

METHODS: We included 261 Vietnamese COVID-19 patients, who were classified into moderate and severe groups. Disease severity prediction based on biomarkers and clinical parameters was performed by applying machine learning and statistical methods using the combination of clinical and biological data.

RESULTS: The random forest model could predict with 97% accuracy the likelihood of COVID-19 patients who subsequently worsened to the severe condition. The most important indicators were interleukin (IL)-6, ferritin and D-dimer. The model could still predict with 92% accuracy after removing IL-6 from the analysis to generalise the applicability of the model to hospitals with limited capacity for IL-6 testing. The five most effective indicators were C-reactive protein (CRP), D-dimer, IL-6, ferritin and dyspnoea. Two different sets of biomarkers (D-dimer, IL-6 and ferritin, and CRP, D-dimer and IL-6) are applicable for the assessment of disease severity and prognosis. The two biomarker sets were further tested through machine learning algorithms and relatively validated on two Danish COVID-19 patient groups (n=32 and n=100). The results indicated that various biomarker sets combined with clinical data can be used for detection of the potential to develop the severe condition.

CONCLUSION: This study provided a simple and reliable model using two different sets of biomarkers to assess disease severity and predict clinical outcomes in COVID-19 patients in Vietnam.

PMID:37041987 | PMC:PMC9885243 | DOI:10.1183/23120541.00481-2022

Stoch Environ Res Risk Assess. 2023;37(4):1593-1613. doi: 10.1007/s00477-022-02348-2. Epub 2022 Dec 30.

ABSTRACT

With advances in modern worlds technology, huge datasets that show dependencies in space as well as in time occur frequently in practice. As an example, several monitoring stations at different geographical locations track hourly concentration measurements of a number of air pollutants for several years. Such a dataset contains thousands of multivariate observations, thus, proper statistical analysis needs to account for dependencies in space and time between and among the different monitored variables. To simplify the consequent multivariate spatio-temporal statistical analysis it might be of interest to detect linear transformations of the original observations that result in straightforward interpretative, spatio-temporally uncorrelated processes that are also highly likely to have a real physical meaning. Blind source separation (BSS) represents a statistical methodology which has the aim to recover so-called latent processes, that exactly meet the former requirements. BSS was already successfully used in sole temporal and sole spatial applications with great success, but, it was not yet introduced for the spatio-temporal case. In this contribution, a reasonable and innovative generalization of BSS for multivariate space-time random fields (stBSS), under second-order stationarity, is proposed, together with two space-time extensions of the well-known algorithms for multiple unknown signals extraction (stAMUSE) and the second-order blind identification (stSOBI) which solve the formulated problem. Furthermore, symmetry and separability properties of the model are elaborated and connections to the space-time linear model of coregionalization and to the classical principal component analysis are drawn. Finally, the usefulness of the new methods is shown in a thorough simulation study and on a real environmental application.

PMID:37041981 | PMC:PMC10081984 | DOI:10.1007/s00477-022-02348-2

Diabetes Obes Metab. 2023 Apr 11. doi: 10.1111/dom.15084. Online ahead of print.

ABSTRACT

AIM: The lack of longitudinal metabolomics data and the statistical techniques to analyze them has limited the understanding of the metabolite levels related to type 2 diabetes (T2D) onset. Thus, we carried out logistic regression analysis and simultaneously proposed new approaches based on residuals of multiple logistic regression and geometric angle-based clustering for the analysis in T2D onset-specific metabolic changes.

METHODS: We used the 6th, 7th, and 8th follow-up data from 2013, 2015, and 2017 among the Korea Association REsource (KARE) cohort data. Semi-targeted metabolite analysis was performed using ultra performance liquid chromatography/triple quadrupole-mass spectrometry (UPLC/TQ-MS) systems.

RESULTS: Since the results from the multiple logistic regression and a single metabolite in a logistic regression analysis varied dramatically, we recommend using models that consider potential multicollinearity among metabolites. The residual-based approach particularly identified neurotransmitters or related precursors as T2D onset-specific metabolites. By using geometric angle-based pattern clustering studies, ketone bodies and carnitines are observed as disease onset specific metabolites and separated from others.

CONCLUSIONS: To treat patients with early-stage insulin resistance and dyslipidemia when metabolic disorders are still reversible, our findings may contribute to a greater understanding of how metabolomics could be used in disease intervention strategies in the early stages of T2D. This article is protected by copyright. All rights reserved.

PMID:37041660 | DOI:10.1111/dom.15084

Patient Saf Surg. 2023 Apr 11;17(1):7. doi: 10.1186/s13037-023-00358-9.

ABSTRACT

BACKGROUND: The early surge of the novel coronavirus disease 2019 (COVID-19) pandemic introduced a significant clinical challenge due to the high case-fatality rate in absence of evidence-based recommendations. The empirical treatment modalities were relegated to historical expertise from the traditional management of acute respiratory distress syndrome (ARDS) in conjunction with off-label pharmaceutical agents endorsed under the “emergency use authorization” (EUA) paradigm by regulatory agencies. This study was designed to evaluate the insights from the “fail-and-learn” strategy in 2020 before the availability of COVID-19 vaccines and access to reliable insights from high-quality randomized controlled trials.

METHODS: A retrospective, multicenter, propensity-matched, case-control study was performed on a data registry comprising 186 hospitals from a national health care system in the United States, designed to investigate the efficacy of empirical treatment modalities during the early surge of the COVID-19 pandemic in 2020. Reflective of the time-windows of the initial two surges of the pandemic in 2020, patients were stratified into “Early 2020” (March 1-June 30) versus “Late 2020” (July 1-December 31) study cohorts. Logistic regression was applied to determine the efficacy of prevalent medications (remdesivir, azithromycin, hydroxychloroquine, corticosteroids, tocilizumab) and supplemental oxygen delivery modalities (invasive vs. non-invasive ventilation) on patient outcomes. The primary outcome measure was in-hospital mortality. Group comparisons were adjusted for covariates related to age, gender, ethnicity, body weight, comorbidities, and treatment modalities pertinent to organ failure replacement.

RESULTS: From a total of 87,788 patients in the multicenter data registry screened in this study, 9,638 patients were included who received 19,763 COVID-19 medications during the first two waves of the 2020 pandemic. The results showed a minimal, yet statistically significant, association with hydroxychloroquine in “Early 2020” and remdesivir in “Late 2020” with reduced odds of mortality (odds ratios 0.72 and 0.76, respectively; P = 0.01). Azithromycin was the only medication associated with decreased odds of mortality during both study time-windows (odds ratios 0.79 and 0.68, respectively; P < 0.01). In contrast, the necessity for oxygen supply showed significantly increased odds of mortality beyond the effect of all investigated medications. Of all the covariates associated with increased mortality, invasive mechanical ventilation had the highest odds ratios of 8.34 in the first surge and 9.46 in in the second surge of the pandemic (P < 0.01).

CONCLUSION: This retrospective multicenter observational cohort study on 9,638 hospitalized patients with severe COVID-19 during revealed that the necessity for invasive ventilation had the highest odds of mortality, beyond the variable effects observed by administration of the prevalent EUA-approved investigational drugs during the first two surges of the early 2020 pandemic in the United States.

PMID:37041643 | DOI:10.1186/s13037-023-00358-9

BMC Womens Health. 2023 Apr 11;23(1):176. doi: 10.1186/s12905-023-02322-2.

ABSTRACT

BACKGROUND AND PURPOSE: Sexual health means coordination and adaptation of physical, emotional, intellectual and social aspects of human beings. One of the variables that affect sexual function and sexual satisfaction is health literacy. The aim of this study was to investigate the relationship between health literacy level and sexual function in married women in Qazvin health centers.

METHODS: In the cross-sectional study, 340 married women were selected from four health centers in Qazvin, Iran, in 2020. These selected centers were chosen randomly from 26 health centers. Participants were included in the study by using the proportional selection method based on the sample size of the all health centers. Data collection tools include three questionnaires: demographic information, The Health Literacy Questionnaire (HELIA), and Female Sexual Function Index (FSFI). Data were analyzed using SPSS 24 software. A significance level of P < 0.05 was considered for statistical analyses.

RESULTS: The highest and lowest scores of dimension’s sexual function are satisfaction, pain, and lubricant, respectively. The level of women’s health literacy in Qazvin was inadequate and borderline (56.4%). Each of the sexual function dimensions had significant positive correlations with health literacy (P < 0.001). There was a significant relationship between health literacy level with age, education, and occupation (P < 0.05). According to linear regression analysis, with the increase in years of marriage, sexual function is decreased (P < 0.02).

CONCLUSION: Health literacy was inadequate in more than half of the study sample and health literacy was significantly associated with sexual function. Educational programs were necessary in order to promote women’s health literacy in health centers.

PMID:37041642 | DOI:10.1186/s12905-023-02322-2

Cost Eff Resour Alloc. 2023 Apr 11;21(1):25. doi: 10.1186/s12962-023-00434-y.

ABSTRACT

BACKGROUND: Understanding related risk factors of health-related quality of life (HRQoL) could avoid treatment failure and provide an insight of personalized treatment approach among people living with HIV/AIDS (PLWH). The objective of this study was to identify factors associated with self-reported treatment qualities and domains of health-related quality of life (HRQoL) among PLWH in Uganda.

METHOD: Data were from “Life on antiretroviral therapy: People’s adaptive coping and adjustment to living with HIV as a chronic condition in Wakiso District, Uganda” in English. The World Health Organization Quality of Life Brief Version (WHOQOL-BREF) questionnaire was used to assess the HRQoL of 263 PLWH in the sample. Considering variance inflation factors, multiple regression analyses were performed to assess the associations between demographic factors, ART obtainment, treatment burden, and self-reported treatment qualities, associations between demographic factors, self-reported treatment qualities, and HRQoL, and association between ART obtainment and HRQoL. Controlling for the confounding effects, several regression anatomies were employed to explore the associations between self-reported treatment qualities and six domains of HRQoL.

RESULTS: In the sample, the geographical distribution were urban (5.70%), semi-urban (37.26%), and rural (57.03%). 67.30% of the participants were females. The mean age of the sample was 39.82 years (standard deviation = 9.76) ranging from 22 to 81 years. Multiple logistic regressions reported statistically significant associations of distance to ART facility with self-reported quality of services, advice, manners, and counseling, statistically significant association between self-reported manners quality and four domains of HRQoL, and statistically significant association between TASO membership and domains of HRQoL. Plots from regression anatomies reported that self-reported treatment qualities had statistically significant associations with six domains of HRQoL.

CONCLUSIONS: Treatment burden, self-reported treatment qualities, ART obtainment, and TASO were possible determinants of individual domains of HRQoL among PLWH in Uganda. PLWH’s HRQoL might be improved by promoting medical quality and optimizing ART obtainment in the healthcare providers’ practice. Findings in this study had important implications for the redesign of clinical guidelines, healthcare delivery, and health care co-ordination among PLWH globally.

PMID:37041641 | DOI:10.1186/s12962-023-00434-y

BMC Health Serv Res. 2023 Apr 11;23(1):356. doi: 10.1186/s12913-023-09337-3.

ABSTRACT

BACKGROUND: Jazan region in the Kingdom of Saudi Arabia (KSA) has been extensively studied regarding access to dental care services, but there is currently no specific study on the distribution of public (primary healthcare centres (PHCs) and hospitals) and private dental healthcare facilities in the area. This study aimed to evaluate the spatial distribution of public and private dental care facilities in the Jazan region in relation to the population distribution in each governorate of the region.

METHODS: The most up-to-date, easily accessible, and anonymous data and information were used for this investigation. The Ministry of Health’s (MOH) Statistical Yearbook 2020 and interactive map were used to identify the locations of healthcare facilities. These locations were plotted on a map using Google Maps, and the data was converted to longitude and latitude with 90% level building accuracy. QGIS’s integrated database was used to develop buffer zones and perform attribute analysis. The data was then exported for analysis in Microsoft Excel, where healthcare facility-to-population ratios were determined.

RESULTS: In Jazan region, consisting of 17 governorates and a population of 1,726,739, there were 275 public and private dental clinics, with a ratio of one dental clinic per 6,279 people in terms of general health services. Only 12.4% of these clinics were located beyond 20 km of the city centre, serving approximately 70% of the region’s population.

CONCLUSION: The uneven distribution of dental clinics in the Jazan region has hampered access to dental treatments and has led to a significant burden on dental health facilities, reducing the quality of care available in the region. Mapping the distribution of MOH, private, and other health facilities, as well as the burden of oral disease in the Jazan region, is necessary for further research.

PMID:37041635 | DOI:10.1186/s12913-023-09337-3

J Exp Clin Cancer Res. 2023 Apr 11;42(1):83. doi: 10.1186/s13046-023-02651-y.

ABSTRACT

BACKGROUND: Validated prognostic biomarkers for anti-angiogenic therapy using the anti-VEGF antibody Bevacizumab in ovarian cancer (OC) patients are still an unmet clinical need. The EGFR can contribute to cancer-associated biological mechanisms in OC cells including angiogenesis, but its targeting gave disappointing results with less than 10% of OC patients treated with anti-EGFR compounds showing a positive response, likely due to a non adequate selection and stratification of EGFR-expressing OC patients.

METHODS: EGFR membrane expression was evaluated by immunohistochemistry in a cohort of 310 OC patients from the MITO-16A/MANGO-OV2A trial, designed to identify prognostic biomarkers of survival in patients treated with first line standard chemotherapy plus bevacizumab. Statistical analyses assessed the association between EGFR and clinical prognostic factors and survival outcomes. A single sample Gene Set Enrichment-like and Ingenuity Pathway Analyses were applied to the gene expression profile of 195 OC samples from the same cohort. In an OC in vitro model, biological experiments were performed to assess specific EGFR activation.

RESULTS: Based on EGFR-membrane expression, three OC subgroups of patients were identified being the subgroup with strong and homogeneous EGFR membrane localization, indicative of possible EGFR out/in signalling activation, an independent negative prognostic factor for overall survival of patients treated with an anti-angiogenic agent. This OC subgroup resulted statistically enriched of tumors of histotypes different than high grade serous lacking angiogenic molecular characteristics. At molecular level, among the EGFR-related molecular traits identified to be activated only in this patients’ subgroup the crosstalk between EGFR with other RTKs also emerged. In vitro, we also showed a functional cross-talk between EGFR and AXL RTK; upon AXL silencing, the cells resulted more sensitive to EGFR targeting with erlotinib.

CONCLUSIONS: Strong and homogeneous cell membrane localization of EGFR, associated with specific transcriptional traits, can be considered a prognostic biomarker in OC patients and could be useful for a better OC patients’ stratification and the identification of alternative therapeutic target/s in a personalized therapeutic approach.

PMID:37041632 | DOI:10.1186/s13046-023-02651-y

Infect Dis Poverty. 2023 Apr 11;12(1):35. doi: 10.1186/s40249-023-01085-0.

ABSTRACT

BACKGROUND: Cryptosporidiosis is a zoonotic intestinal infectious disease caused by Cryptosporidium spp., and its transmission is highly influenced by climate factors. In the present study, the potential spatial distribution of Cryptosporidium in China was predicted based on ecological niche models for cryptosporidiosis epidemic risk warning and prevention and control.

METHODS: The applicability of existing Cryptosporidium presence points in ENM analysis was investigated based on data from monitoring sites in 2011-2019. Cryptosporidium occurrence data for China and neighboring countries were extracted and used to construct the ENMs, namely Maxent, Bioclim, Domain, and Garp. Models were evaluated based on Receiver Operating Characteristic curve, Kappa, and True Skill Statistic coefficients. The best model was constructed using Cryptosporidium data and climate variables during 1986‒2010, and used to analyze the effects of climate factors on Cryptosporidium distribution. The climate variables for the period 2011‒2100 were projected to the simulation results to predict the ecological adaptability and potential distribution of Cryptosporidium in future in China.

RESULTS: The Maxent model (AUC = 0.95, maximum Kappa = 0.91, maximum TSS = 1.00) fit better than the other three models and was thus considered the best ENM for predicting Cryptosporidium habitat suitability. The major suitable habitats for human-derived Cryptosporidium in China were located in some high-population density areas, especially in the middle and lower reaches of the Yangtze River, the lower reaches of the Yellow River, and the Huai and the Pearl River Basins (cloglog value of habitat suitability > 0.9). Under future climate change, non-suitable habitats for Cryptosporidium will shrink, while highly suitable habitats will expand significantly (χ² = 76.641, P < 0.01; χ² = 86.836, P < 0.01), and the main changes will likely be concentrated in the northeastern, southwestern, and northwestern regions.

CONCLUSIONS: The Maxent model is applicable in prediction of Cryptosporidium habitat suitability and can achieve excellent simulation results. These results suggest a current high risk of transmission and significant pressure for cryptosporidiosis prevention and control in China. Against a future climate change background, Cryptosporidium may gain more suitable habitats within China. Constructing a national surveillance network could facilitate further elucidation of the epidemiological trends and transmission patterns of cryptosporidiosis, and mitigate the associated epidemic and outbreak risks.

PMID:37041630 | DOI:10.1186/s40249-023-01085-0