[Factors associated with dissatisfaction with pharmacological treatment in patients with type 2 diabetes mellitus: A cross-sectional study]

BACKGROUND AND OBJECTIVES

Diabetes is a chronic disease with a high impact on both health and Quality of Life Related to Health (QLRH). To evaluate the satisfaction of treatment in patients with type 2 diabetes mellitus through the Diabetes Treatment Satisfaction Questionnaire (DTSQ) and its relationship with sociodemographic variables, with antidiabetic medication and clinical-analytical variables.

MATERIALS AND METHODS

This cross-sectional study was conducted in General University Hospital of San Juan de Alicante between September 2016 and December 2017. Two hundred thirty-two patients diagnosed with type 2 diabetes mellitus at least 1 year before inclusion, treated with antidiabetic medication were included. The Spanish version of the DTSQ scale was used to measure satisfaction with treatment. Factors associated with low satisfaction were analyzed by applying the Chi-square test for qualitative variables and Student-T for quantitative variables. To estimate magnitudes of association, logistic models were adjusted.

RESULTS

Two hundred thirty-two patients were included in this study. 21.5% of the patients presented low satisfaction with the treatment. Patients who presented low satisfaction with treatment were associated with medications that could cause hypoglycemia (OR: 2.872 [1.195-6.903]), HbA1c levels higher than 7% (OR: 2.260 [1.005-5.083]) and drugs administered by the route oral (OR: 2.749 [1.233-6.131]).

CONCLUSIONS

Patients with type 2 diabetes mellitus who had a lower score on the DTSQ questionnaire were associated with medications that produced hypoglycaemia, and with higher levels of HbA1c higher than 7%, and those who took oral medication.

[Analysis of two health attendance models for the non-hospital emergencies in Gipuzkoa: Retrospective study]

BACKGROUND AND OBJECTIVE

Out-of-hospital medical emergency services are defined as a functional organization that performs a set of sequential human and material activities. The objective of this study was to compare the mortality of patients attended by the out-of-hospital medical emergency services in 2 neighboring Spanish regions with different models of healthcare transport assistance for emergency care.

MATERIAL AND METHOD

Retrospective observational cohort study, done between June 1, 2007 and December 31, 2008 in 2 regions of Gipuzkoa, Alto Deba (AD) and Bajo Deba (BD). The study variables were age, sex and place of exposure (AD/BD), heart rate, blood pressure, initial reason for the call defined by the European Resuscitation Council, unconsciousness and digestive bleeding. 3452 subjects were analyzed.

RESULTS

The risk of in situ mortality in BD was 1.31 times higher than in AD (P=.050), that of hospital mortality in BD was 0.71 times lower than in AD (P=.011) and the risk of mortality at one year between counties and the combined mortality (in situ+hospital) did not contribute significant differences.

CONCLUSIONS

Mortality (in situ+in-hospital, and one year aftercare) of patients treated by the out-of-hospital emergency medical services in AD (non-medicalized healthcare transport model) was similar to that of the BD region (mixed healthcare transport model).

Incubation period of COVID-19: A systematic review and meta-analysis

BACKGROUND AND OBJECTIVE

The incubation period of COVID-19 helps to determine the optimal duration of the quarantine and inform predictive models of incidence curves. Several emerging studies have produced varying results; this systematic review aims to provide a more accurate estimate of the incubation period of COVID-19.

METHODS

For this systematic review, a literature search was conducted using Pubmed, Scopus/EMBASE, and the Cochrane Library databases, covering all observational and experimental studies reporting the incubation period and published from 1 January 2020 to 21 March 2020.We estimated the mean and 95th percentile of the incubation period using meta-analysis, taking into account between-study heterogeneity, and the analysis with moderator variables.

RESULTS

We included seven studies (n = 792) in the meta-analysis. The heterogeneity (I2 83.0%, p < 0.001) was significantly decreased when we included the study quality and the statistical model used as moderator variables (I2 15%). The mean incubation period ranged from 5.6 (95% CI: 5.2 to 6.0) to 6.7 days (95% CI: 6.0 to 7.4) according to the statistical model. The 95th percentile was 12.5 days when the mean age of patients was 60 years, increasing 1 day for every 10 years.

CONCLUSION

Based on the published data reporting the incubation period of COVID-19, the mean time between exposure and onset of clinical symptoms depended on the statistical model used, and the 95th percentile depended on the mean age of the patients. It is advisable to record sex and age when collecting data in order to analyze possible differential patterns.

Incubation period of COVID-19: A systematic review and meta-analysis

Background and objective

The incubation period of COVID-19 helps to determine the optimal duration of the quarantine and inform predictive models of incidence curves. Several emerging studies have produced varying results; this systematic review aims to provide a more accurate estimate of the incubation period of COVID-19.

Methods

For this systematic review, a literature search was conducted using Pubmed, Scopus/EMBASE, and the Cochrane Library databases, covering all observational and experimental studies reporting the incubation period and published from 1 January 2020 to 21 March 2020.We estimated the mean and 95th percentile of the incubation period using meta-analysis, taking into account between-study heterogeneity, and the analysis with moderator variables.

Results

We included seven studies (n = 792) in the meta-analysis. The heterogeneity (I² 83.0%, p < 0.001) was significantly decreased when we included the study quality and the statistical model used as moderator variables (I² 15%). The mean incubation period ranged from 5.6 (95% CI: 5.2–6.0) to 6.7 days (95% CI: 6.0–7.4) according to the statistical model. The 95th percentile was 12.5 days when the mean age of patients was 60 years, increasing 1 day for every 10 years.

Conclusion

Based on the published data reporting the incubation period of COVID-19, the mean time between exposure and onset of clinical symptoms depended on the statistical model used, and the 95th percentile depended on the mean age of the patients. It is advisable to record sex and age when collecting data in order to analyze possible differential patterns.