RESUMEN
Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviour, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Using data from 6,388 patients, we analysed patterns of self-reported treatment seeking behaviours ('patient pathways') using process mining and single-channel sequence analysis. Among those with microbiologically confirmed UTI (n = 1,946), we used logistic regression to assess the relationship between treatment seeking behaviour, AB use, and the likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathway for UTI-like symptoms in this sample involved attending health facilities, rather than other providers like drug sellers. Patients from sites in Tanzania and Uganda, where over 50% of patients had an MDR UTI, were more likely to report treatment failures, and have repeat visits to providers than those from Kenyan sites, where MDR UTI proportions were lower (33%). There was no strong or consistent relationship between individual AB use and likelihood of MDR UTI, after accounting for country context. The results highlight the hurdles East African patients face in accessing effective UTI care. These challenges are exacerbated by high rates of MDR UTI, suggesting a vicious cycle of failed treatment attempts and sustained selection for drug resistance. Whilst individual AB use may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of variations in ABR.
RESUMEN
Background: In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR. In East Africa, antibiotic susceptibility data are sparse. To fill the gap, this study reports common microorganisms and their susceptibility patterns isolated from patients with UTI-like symptoms in Kenya, Tanzania and Uganda. Within each country, patients were recruited from three sites that were sociodemographically distinct and representative of different populations. Methods: UTI was defined by the presence of >104â cfu/mL of one or two uropathogens in mid-stream urine samples. Identification of microorganisms was done using biochemical methods. Antimicrobial susceptibility testing was performed by the Kirby-Bauer disc diffusion assay. MDR bacteria were defined as isolates resistant to at least one agent in three or more classes of antimicrobial agents. Results: Microbiologically confirmed UTI was observed in 2653 (35.0%) of the 7583 patients studied. The predominant bacteria were Escherichia coli (37.0%), Staphylococcus spp. (26.3%), Klebsiella spp. (5.8%) and Enterococcus spp. (5.5%). E. coli contributed 982 of the isolates, with an MDR proportion of 52.2%. Staphylococcus spp. contributed 697 of the isolates, with an MDR rate of 60.3%. The overall proportion of MDR bacteria (nâ=â1153) was 50.9%. Conclusions: MDR bacteria are common causes of UTI in patients attending healthcare centres in East African countries, which emphasizes the need for investment in laboratory culture capacity and diagnostic algorithms to improve accuracy of diagnosis that will lead to appropriate antibiotic use to prevent and control AMR.
RESUMEN
Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviours, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from 6,827 adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Among 6,388 patients we analysed patterns of self-reported treatment seeking behaviours ('patient pathways') using process mining and single-channel sequence analysis. Of those with microbiologically confirmed UTI (n=1,946), we used logistic regression to assessed the relationship between treatment seeking behaviour, AB use, and likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathways for UTI-like symptoms included attending health facilities, rather than other providers (e.g. drug sellers). Patients from the sites sampled in Tanzania and Uganda, where prevalence of MDR UTI was over 50%, were more likely to report treatment failures, and have repeated visits to clinics/other providers, than those from Kenyan sites, where MDR UTI rates were lower (33%). There was no strong or consistent relationship between individual AB use and risk of MDR UTI, after accounting for country context. The results highlight challenges East African patients face in accessing effective UTI treatment. These challenges increase where rates of MDR UTI are higher, suggesting a reinforcing circle of failed treatment attempts and sustained selection for drug resistance. Whilst individual behaviours may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of ABR.
RESUMEN
BACKGROUND: Availability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based analyses. Among these, Bayesian networks have great potential to tackle complex interdisciplinary problems, because they can easily model inter-relations between variables. They work by encoding conditional independence relationships discovered via advanced inference algorithms. One challenge is dealing with missing data, ubiquitous in survey or biomedical datasets. Missing data is rarely addressed in an advanced way in Bayesian networks; the most common approach is to discard all samples containing missing measurements. This can lead to biased estimates. Here, we examine how Bayesian network structure learning can incorporate missing data. METHODS: We use a simulation approach to compare a commonly used method in frequentist statistics, multiple imputation by chained equations (MICE), with one specific for Bayesian network learning, structural expectation-maximization (SEM). We simulate multiple incomplete categorical (discrete) data sets with different missingness mechanisms, variable numbers, data amount, and missingness proportions. We evaluate performance of MICE and SEM in capturing network structure. We then apply SEM combined with community analysis to a real-world dataset of linked biomedical and social data to investigate associations between socio-demographic factors and multiple chronic conditions in the US elderly population. RESULTS: We find that applying either method (MICE or SEM) provides better structure recovery than doing nothing, and SEM in general outperforms MICE. This finding is robust across missingness mechanisms, variable numbers, data amount and missingness proportions. We also find that imputed data from SEM is more accurate than from MICE. Our real-world application recovers known inter-relationships among socio-demographic factors and common multimorbidities. This network analysis also highlights potential areas of investigation, such as links between cancer and cognitive impairment and disconnect between self-assessed memory decline and standard cognitive impairment measurement. CONCLUSION: Our simulation results suggest taking advantage of the additional information provided by network structure during SEM improves the performance of Bayesian networks; this might be especially useful for social science and other interdisciplinary analyses. Our case study show that comorbidities of different diseases interact with each other and are closely associated with socio-demographic factors.
Asunto(s)
Algoritmos , Modelos Estadísticos , Anciano , Humanos , Teorema de Bayes , Simulación por ComputadorRESUMEN
Tangxun Lake is the largest urban lake in China, which is polluted by multiple wastewaters, and now is severely eutrophic. We detected diversity, abundance, and the coexistence of Candidatus Methylomirabilis oxyfera-like and anammox bacteria in different horizontal and vertical directions of the lake sediments through qPCR and clone library. Phylogenetic tree analysis showed that the Ca. Methylomirabilis oxyfera-like and anammox bacteria exhibited high diversity, and they belonged to group BE and Ca. Brocadia genus, respectively. These two bacteria displayed higher diversity in polluted area than in other areas. Furthermore, they had great spatial variation of abundance both horizontally and vertically. The abundance of anammox bacteria was significantly higher than that of Ca. Methylomirabilis oxyfera-like bacteria. The stronger the human interference were, the higher abundances these two bacteria exhibited horizontally, whereas both their abundances and the ratio of anammox to Ca. Methylomirabilis oxyfera-like bacteria decreased with the increasing depth. Redundancy analysis indicated that nitrate was the most influential environmental factor to the abundance of these two bacteria. Ammonia, nitrite, total nitrogen, and organic matters were in positive correlation with the abundance of these two bacteria. Nitrate was slightly negatively correlated with the abundance of Ca. Methylomirabilis oxyfera-like bacteria, while it was positively correlated with that of anammox bacteria. Our results provided an insight into the effects of environmental factors such as ammonia, nitrite, and nitrate on the diversity and abundances of these two bacteria and theoretical basis for restoration of water.(AU)
Asunto(s)
Humanos , Aguas Residuales/microbiología , Microbiología del Agua , Bacterias , Nitratos , Sedimentos , Microbiología , ChinaRESUMEN
BACKGROUND: The objective of this study was to explore the stigma and related influencing factors in individuals with chronic insomnia disorder (CID). METHODS: A total of 70 CID patients and 70 healthy controls (CON) were enrolled in the study. All subjects completed the assessments of sleep, emotion, and cognition. Their stigma and life quality were measured using the Chronic Stigma Scale and the 36-Item Short-Form Health Survey (SF-36). RESULTS: The ratio of individuals with stigma was significantly different between CID and CON groups (C2 = 35.6, p < 0.001). Compared with the CON group, the CID group had higher scores for total stigma (U = 662.0, p < 0.001), internalized stigma (U = 593.0, p < 0.001), enacted stigma (U = 1568.0, p < 0.001), PSQI (U = 2485.0, p < 0.001) and HAMD-17 (U = 69.5, p < 0.001) as well as lower scores for MoCA-C (U = 3997.5, p < 0.001) and most items of SF-36. Partial correlation analysis showed that different items of the Chronic Stigma Scale were positively correlated with illness duration, PSQI and HAMD-17 scores, while negatively correlated with one or more items of the SF-36. Multivariate regression analysis showed that illness duration and the Mental Health domain of the SF-36 were independent risk factors for one or more items of stigma in CID patients. CONCLUSION: Patients with CID have an increased risk of stigma. Moreover, illness duration and Mental Health may be primary factors related to stigma.
Asunto(s)
Trastornos del Inicio y del Mantenimiento del Sueño , Emociones , Humanos , Calidad de Vida/psicología , Estigma Social , Encuestas y CuestionariosRESUMEN
Tangxun Lake is the largest urban lake in China, which is polluted by multiple wastewaters, and now is severely eutrophic. We detected diversity, abundance, and the coexistence of Candidatus Methylomirabilis oxyfera-like and anammox bacteria in different horizontal and vertical directions of the lake sediments through qPCR and clone library. Phylogenetic tree analysis showed that the Ca. Methylomirabilis oxyfera-like and anammox bacteria exhibited high diversity, and they belonged to group B-E and Ca. Brocadia genus, respectively. These two bacteria displayed higher diversity in polluted area than in other areas. Furthermore, they had great spatial variation of abundance both horizontally and vertically. The abundance of anammox bacteria was significantly higher than that of Ca. Methylomirabilis oxyfera-like bacteria. The stronger the human interference were, the higher abundances these two bacteria exhibited horizontally, whereas both their abundances and the ratio of anammox to Ca. Methylomirabilis oxyfera-like bacteria decreased with the increasing depth. Redundancy analysis indicated that nitrate was the most influential environmental factor to the abundance of these two bacteria. Ammonia, nitrite, total nitrogen, and organic matters were in positive correlation with the abundance of these two bacteria. Nitrate was slightly negatively correlated with the abundance of Ca. Methylomirabilis oxyfera-like bacteria, while it was positively correlated with that of anammox bacteria. Our results provided an insight into the effects of environmental factors such as ammonia, nitrite, and nitrate on the diversity and abundances of these two bacteria and theoretical basis for restoration of water.
Asunto(s)
Lagos , Nitritos , Amoníaco , Oxidación Anaeróbica del Amoníaco , Anaerobiosis , Bacterias/genética , Humanos , Metano , Nitratos , Oxidación-Reducción , Filogenia , ARN Ribosómico 16S/genéticaRESUMEN
Baicalein has efficient antitumor properties and has been reported to promote the apoptosis of several human cancer cell lines. Decidual protein induced by progesterone (DEPP), a transcriptional target of Forkhead Box O, was originally identified from the human endometrial stromal cell cDNA library. However, the expression and physiological functions of DEPP in human colon cancer cells remain to be fully elucidated. In the present study, it was reported that baicalein stimulated apoptosis and morphological changes of HCT116, A549 and Panc1 cells in a dose-dependent manner. It also upregulated the mRNA and protein levels of DEPP and growth arrest and DNA damage-inducible 45α (Gadd45a). In addition, the overexpression of DEPP promoted mitogen-activated protein kinase (MAPK) phosphorylation. To further investigate the role of DEPP and Gadd45a in baicalein-induced apoptosis, HCT116 cells were transfected with small interfering RNA against either DEPP or Gadd45a as in vitro models. Through an Annexin V/PI double staining assay, it was observed that baicalein-induced apoptosis was impaired by the inactivation of either DEPP or Gadd45a, which in turn restricted the baicalein-induced activation of caspase3 and caspase9 and phosphorylation of MAPKs. In addition, the inhibition of cJun Nterminal kinase (JNK)/p38 activity with SP600125/SB203580 decreased the expression of Gadd45a, whereas the inactivation of extracellular signal-regulated kinase with SCH772984 had no effect on the expression of Gadd45a. Taken together, these results demonstrated that baicalein induced the upregulation of DEPP and Gadd45a, which promoted the activation of MAPKs with a positive feedback loop between Gadd45a and JNK/p38, resulting in a marked apoptotic response in human colon cancer cells. These results indicated that baicalein is a potential antitumor drug for the treatment of colon cancer.