Association of SGLT-2 inhibitors with bacterial urinary tract infection in type 2 diabetes

OBJECTIVE

We aimed to investigate the factors associated with UTI in patients with T2D whether being treated with SGLT-2i or not.

METHODS

Adult patients with T2D, whose urine culture results were available, were analyzed retrospectively. Urine culture was obtained from mid-flow urine. Antibacterial treatment was given to the patients with UTI, which was defined by positive urine cultures and/or clinical findings. We grouped the patients as follows: Group A, those treated with SGLT-2i; and Group B, those not treated with SGLT-2i.

RESULTS

A total of 101 patients were included. Median age was 56 (45-67), 56.4% (n = 57) of the patients were female. Urine culture was positive in 54.9% (n = 28) and 16% (n = 8) of Group A (n = 51) and Group B (n = 50), respectively. Of those for whom urine culture was positive, Escherichia coli was isolated in 83.3% (n = 30), and both Escherichia coli and Klebsiella pneumoniae (K.pneumoniae) were isolated in 16.7% (n = 6). Klebsiella pneumoniae was isolated only from Group A. The need for and duration of hospitalization were higher in Group A (p < 0.001). UTI was detected in 60 patients. ROC analysis showed that a HbA1c of > 5.8% was associated with UTI with good accuracy (AUC: 0.835, p < 0.001). In multiple logistic regression analysis, SGLT-2i use and glucosuria were positive predictors for UTI (p = 0.004, Odds Ratio: 1984.013; and p = 0.028, and Odds Ratio: 12.480, respectively).

CONCLUSION

Besides the association of HbA1c and BMI with UTI, SGLT-2i use and glucosuria predicted UTI. Urine culture is important with respect to the choice of antibacterial treatment, especially in those patients under SGLT-2i treatment. The effect of SGLT-2i on the development of UTI is independent of baseline BMI score or HbA1c.

Could ischemia-modified albumin levels predict the severity of disease in SARS-CoV-2 infection?

INTRODUCTION

Ischemia-modified albumin (IMA) level increases in inflammatory conditions. We aimed to investigate the association between IMA levels and the severity of coronavirus disease 2019 (COVID-19) infection in adult patients.

METHODOLOGY

We grouped adult patients with COVID-19 infection: Group A - mild symptoms, but normal computed tomography (CT), Group B - mild/moderate illness, and Group C - severe or critical illness. We measured IMA levels at the time of diagnosis of COVID-19 infection.

RESULTS

Mean age of the total number of patients (n = 90) was 54.43 (± 8.11) year, and 46.7% (n = 42) were female. IMA levels were highest in Group C and lowest in A (p < 0.001). The most important factor predicting COVID-19 disease severity was IMA. Type 2 diabetes was more frequent in Group C (n = 31) than in Group B (n = 30) (p = 0.042). Asthma was less frequent, and coronary artery disease was more frequent in Group C than in Group A (n = 29) and B (p = 0.009). Duration of hospitalization was highest in Group C (p < 0.001).

CONCLUSIONS

We analyzed a sample of patients with COVID-19 infection and found that IMA predicted severe COVID-19 disease. Disease severity grouping was based on patients' clinical and radiological features. IMA level measured when SARS-CoV-2 infection is diagnosed may be a useful marker in predicting likely disease severity or intensive care need.