Furthermore, we checked the relationship between the change in hs-CRP and several clinical factors such as the baseline hs-CRP level, use of a moderate-intensity statin, presence of coronary artery disease (CAD) and taking a previous DDP-4 inhibitor.

The levels of the inflammatory markers hs-CRP, WBC, and IL-6 were determined to have not significantly changed from baseline to the final follow-up in each arm; furthermore, the changes in these markers were not significantly different between the two groups. The change in hs-CRP level was not affected by the baseline hs-CRP level, use of a moderate-intensity statin, presence of coronary artery disease, and absence of prior DPP-4 inhibitor use.

In this sub-analysis from the REASON Trial, taking a DPP-4 inhibitor, either ANA or SITA, for 52 weeks did not affect the levels of inflammatory markers.

In this sub-analysis from the REASON Trial, taking a DPP-4 inhibitor, either ANA or SITA, for 52 weeks did not affect the levels of inflammatory markers.

A prognostic prediction model for metabolic syndrome can calculate the probability of risk of experiencing metabolic syndrome within a specific period for individualized treatment decisions. We aimed to provide a systematic review and critical appraisal on prognostic models for metabolic syndrome.

Studies were identified through searching in English databases (PubMed, EMBASE, CINAHL, and Web of Science) and Chinese databases (Sinomed, WANFANG, CNKI, and CQVIP). A checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) and the prediction model risk of bias assessment tool (PROBAST) were used for the data extraction process and critical appraisal.

From the 29,668 retrieved articles, eleven studies meeting the selection criteria were included in this review. Forty-eight predictors were identified from prognostic prediction models. The c-statistic ranged from 0.67 to 0.95. Critical appraisal has shown that all modeling studies were subject to a hig study for clinical practice since all models are prone to optimism and overfitting.

The aim of this study is to assess the impact of type 1 diabetes mellitus on family environment relationships, as well as the management and approach to this disease.

One hundred one children, 52.47% male and 47.52% female, with an average age of 8.55 ± 4.01 years, diagnosis of type 1 diabetes mellitus. Quantitative cross-sectional descriptive study was conducted using the validated questionnaires „Modified Diabetes Quality of Life” and „Questionnaire for the assessment of psychological impact in parents/guardians of diabetic children”.

Most of the children (70.3% versus 29.7%) identified diabetes as unpleasant or not fun. The ≤5-year-olds expressed that they felt concerned about the consequences of being diabetic (8.1% by age group), as opposed to the 10-year-olds who did not feel concerned (85.1% by age group), P <0.001. The family environment was affected in 98.1% (n=99) of the cases.

Self-care of type 1 diabetes mellitus in pediatric patients is a complex process that impacts the family environment and their relationship with their peers, especially for children under the age of 5. Fear, concern and insecurity were prevalent feelings in children suffering type 1 diabetes mellitus.

Self-care of type 1 diabetes mellitus in pediatric patients is a complex process that impacts the family environment and their relationship with their peers, especially for children under the age of 5. Fear, concern and insecurity were prevalent feelings in children suffering type 1 diabetes mellitus.

Community-based health insurance (CBHI) is a prepayment method of financial contributions for healthcare which aims to risk pooling, avoidance of catastrophic and impoverishing health expenditure. However, a high dropout from the scheme remains the biggest challenge to effective and sustainable progress towards universal financial protection in low- and middle-income countries. While large literature had examined initial enrollment and factors associated with it, only a few studies dealt with dropout. So the study aimed to assess the magnitude and determinants of dropout from community-based health insurance among households in Manna district, Jimma zone, Oromia Regional State, Ethiopia.

A community-based cross-sectional study design was employed to collect data from 634 household heads from March 1 to 30, 2020. A multistage sampling technique was carried out and interviewer-administered questionnaires were used to collect data. Descriptive statistics and multivariable logistic regression analyses were pe. We strongly recommend that greater efforts should be made toward the providers’ attitude, promised benefit package, and quality of services.

Dropout from CBHI in this study area was high. Household heads’ age, educational level, family size, perceived quality of service, providers’ attitude, a benefits package, trust in the contracted health facility, and the scheme were the significant predictors of dropout. We strongly recommend that greater efforts should be made toward the providers’ attitude, promised benefit package, and quality of services.

Integrase strand transfer inhibitors (INSTIs) are used as first-line therapy for HIV-1-infected patients. Next-generation sequencing (NGS) can detect low-frequency mutants; however, the clinical value of NGS to detect resistance variants is unknown. This study aimed to evaluate the prevalence of INSTI resistance in southern Taiwan and determine the clinical implications of using NGS to detect integrase region low-level resistant variants.

This retrospective cohort study included antiretroviral therapy-naïve HIV-1-infected individuals at Kaohsiung Veterans General Hospital, Taiwan, from 2013 to 2017. Drug-resistance mutations were determined, and an in-house polymerase chain reaction was used for genotyping INSTI resistance. NGS was used to assess INSTI resistance (≧1%), and the results were compared with those from population sequencing. Drug resistance-associated mutations were defined according to the 2019 IAS-USA HIV drug resistance-associated mutations list, and accessory mutations by a Stanford HIVdbents. NGS detected more INSTI resistance-associated mutations at a low frequency. Low-level drug resistance-associated mutations to INSTIs identified by NGS did not have an impact on the treatment response to INSTI-based first-line therapy.

Our findings showed a low rate of HIV drug resistance to INSTIs (0.9%) in treatment-naïve patients. NGS detected more INSTI resistance-associated mutations at a low frequency. Low-level drug resistance-associated mutations to INSTIs identified by NGS did not have an impact on the treatment response to INSTI-based first-line therapy.

The frequent identification of resistant bacteria in hospitals constantly presents antimicrobial therapy with a challenge. Imipenem, once considered an extremely powerful antibiotic against multidrug-resistant bacterial infections, is losing its effectiveness. Its use in empirical therapy with inadequate or nonexistent antimicrobial stewardship programs has further triggered bacterial resistance in low-income countries. Therefore, this study aimed at identifying imipenem-resistant Gram-negative bacteria from patients who were referred to health centers in North Gondar, Ethiopia.

A total of 153 sputum samples were used to isolate Gram-negative bacteria. The isolates, which were resistant to imipenem, were identified by standard biochemical tests and 16S rRNA sequencing. The Kirby-Bauer disk diffusion method was used to determine the sensitivity or resistance of the isolate to diverse antimicrobial agents.

The study identified 79 imipenem-resistant bacterial isolates from eight genera with clinically relevant microorganisms, including

(20.77%),

(19.48%),

(16.88%), and

(14.28%). Overall, imipenem-resistant bacterial isolates were detected in 31 samples (20.26%). Additionally, a remarkably high level of resistance to most antibiotics was observed among isolates of

. Gentamycin is the most active antibiotic against many of the isolates, while β-lactams appear to be less effective.

The study indicated that many Gram-negative bacteria were resistant to imipenem with parallel resistances to other antimicrobials. Hence, the prescription of imipenem within the region should be according to the antibiotic resistance profiles of the multi-drug resistant bacteria.

The study indicated that many Gram-negative bacteria were resistant to imipenem with parallel resistances to other antimicrobials. Hence, the prescription of imipenem within the region should be according to the antibiotic resistance profiles of the multi-drug resistant bacteria.

The aim of the present study was to assess the diagnostic performance of an LFA compared with an ELISA test in a cohort of HWs operating in a COVID-19 unit of a teaching hospital in southern Italy.

We performed an observational, prospective, interventional study including 65 COVID-19 unit personnel. On a total of 196 serum samples (at least 2 serum samples for each HW), LFA and ELISA tests for SARS-COV-2 IgG and IgM were performed. Also, 32 serum samples of SARS-CoV-2 RNA positive patients at least 21 days before sampling, and 30 serum samples of patients obtained up to November 2019, before COVID-19 outbreak in China, were used as positive and negative controls, respectively.

Of the 65 HWs enrolled, 6 were positive in LFA; overall, of the 196 serum samples, 20 were positive in LFA. All ELISA tests performed on serum samples collected from HWs were negative. The specificity of LFAs was 90.77% considering the 65 HWs and 89.80% considering all the 196 health workers serum samples analyzed. Considering the data on HWs, ELISA test for SARS-COV-2 antibodies showed a specificity of 100%, including all the 196 serum samples collected, and 100% including the 65 HWs. The ELISA and LFAs performed after 21 days last COVID-19 patient was discharged were all negative.

LFAs compared to ELISA tests result in less specificity, considering COVID-19 negative personnel and patients. Thus, LFAs seem to be not adequate in the active surveillance of HWs.

LFAs compared to ELISA tests result in less specificity, considering COVID-19 negative personnel and patients. Thus, LFAs seem to be not adequate in the active surveillance of HWs.

This retrospective pilot study aimed to investigate the antibiotic regimens used to treat

infections at a secondary hospital in southern Thailand. Additionally, the clinical outcomes and mortality of each regimen are described.

The medical charts of all patients admitted to Phang-Nga Hospital, Thailand, between 1 January 2019 and 31 May 2020 due to

infection were reviewed. Data were collected on the antibiotics that patients received before and after sensitivity testing, along with the clinical cure, mortality rates, and nephrotoxicity.

Of the 32 inpatients recruited in the study, the most prescribed antibiotic regimen for empirical therapy was beta-lactam/beta-lactamase inhibitor monotherapy (22%), and for definitive therapy was meropenem monotherapy (28%). Combination therapy with two, three, or four antibiotics was prescribed less than 50% of cases for both empirical and definitive therapy. Moreover, the results indicated that patients receiving combination therapy had a lower clinical response and higher mortality than those receiving monotherapy.