Prediction Model for Severe Community-acquired Pneumonia Development among Patients with Diabetes Mellitus

Introduction: Diabetes is an independent risk factor for the development of severe community-acquired pneumonia (CAP) and associated with pneumonia-related hospitalization as well as mortality. Here, we assessed several selected biomarkers to determine their predictive value for progression to severe CAP among diabetic patients. Research design and methods: A retrospective cohort study of diabetic patients with CAP was conducted at a tertiary teaching hospital. The prediction model group (N=100) comprised patients registered between January 2015 to December 2016. Multivariate analysis was performed to identify predictive biomarkers from this cohort. The validation group (N=108) comprised the patients between January 2017 to February 2019. Predictive performance was assessed in the validation group. Results: A total of 208 diabetic inpatients with CAP were recruited. Further multivariate analysis showed that C-reactive protein (CRP), absolute lymphocyte count (ALC), immunoglobulin (IgM), and HbA1C at admission were independently associated with progression to severe CAP in diabetic patients during hospitalization. The prediction model =0.0179555*CRP+1.975918* HbA1C-2.879364* ALC -0.026255* IgM -8.220555. The area under ROC (AUROC) curve in the validation group was 0.851 (0.781-0.921) with statistical significance (P<.05). Conclusions: In diabetic patients with CAP, a combination of CRP, ALC, IgM, and HbA1C at admission could be used to predict the progression to severe CAP.

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P6200Effect of LPA gene on CAD risk among diabetic patients

European Heart Journal ◽

10.1093/eurheartj/ehz746.0805 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

S Borges ◽

R Palma Dos Reis ◽

A Pereira ◽

F Mendonca ◽

J Sousa ◽

...

Keyword(s):

Multivariate Analysis ◽

General Population ◽

Independent Predictor ◽

Statistical Significance ◽

Diabetic Patients ◽

Diabetes Status ◽

Chi Squared ◽

Coronary Patients ◽

Diabetic Population ◽

Cad Risk

Abstract Introduction Previous research reported that LPA gene is a strong and independent predictor of CAD in non-diabetic patients but not in patients with type 2 diabetes. These results suggest that LPA gene might contribute less to CAD risk in patients with T2DM than in general population. Objective Investigate, in our population, the association between LPA gene CT variant and CAD risk among diabetic patients. Methods 3050 individuals (1619 coronary patients and 1431 controls) were genotyped for LPA rs3798220 TT/CT. Pearson's chi-squared test was applied to evaluate the association between LPA variants and CAD, firstly, in the general population and, secondly, in the group of patients with T2DM (n=735). Multivariate logistic regression was performed with LPA CT variant and 6 traditional risk factors (TRF) (smoking, dyslipidemia, diabetes, hypertension, family history of CAD and physical inactivity) in both general and diabetic population. Results In total population, LPA CT variant was found to be strongly and significantly associated with CAD with an OR of 2.32 (95% CI: 1.56–3.45; p<0.0001). However, this association was less pronounced in the diabetic population with a CAD risk of 1.38 (95% CI: 0.56–3.43) without statistical significance (p=0.485). In the presence of 6 major TRF, multivariate analysis showed that LPA CT remained a strong and independent predictor of CAD risk (OR= 2.34; 95% CI: 1.52–3.62; p<0.0001). In diabetic population, LPA was no longer an independent predictor for CAD by multivariate analysis. Conclusions Our results show that the effect of LPA gene on CAD risk among diabetic patients might be different from that in the general population. Diabetes status is such a strong risk factor that may attenuate the genetic effects of LPA on CAD risk. This may indicate a complex role of Lp (a) and diabetes interaction in cardiometabolic diseases.

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Evaluation of severity scoring systems in patients with severe community acquired pneumonia

Romanian Journal of Internal Medicine ◽

10.2478/rjim-2021-0025 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Katerina Spasovska ◽

Krsto Grozdanovski ◽

Zvonko Milenkovic ◽

Mile Bosilkovski ◽

Marija Cvetanovska ◽

...

Keyword(s):

Statistical Significance ◽

Scoring Systems ◽

Simplified Acute Physiology Score ◽

Community Acquired Pneumonia ◽

Mortality Prediction ◽

Outcome Variable ◽

Severity Scoring ◽

Increased Risk ◽

Severity Scores ◽

Severe Community Acquired Pneumonia

Abstract Background: The aim of this study was to evaluate the ability of severity scoring systems to predict 30-day mortality in patients with severe community-acquired pneumonia. Methods: The study included 98 patients aged ≥18 years with community acquired pneumonia hospitalized at the Intensive Care Unit of the University Clinic for Infectious Diseases in Skopje, Republic of North Macedonia, during a 3-year period. We recorded demographic, clinical and common biochemical parameters. Five severity scores were calculated at admission: CURB 65 (Confusion, Urea, Respiratory Rate, Blood pressure, Age ≥65 years), SCAP (Severe Community Acquired Pneumonia score), SAPS II (Simplified Acute Physiology Score), SOFA (Sequential Organ Failure Assessment Score) and MPM (Mortality Prediction Model). Primary outcome variable was 30-day in-hospital mortality. Results: The mean age of the patients was 59.08 ± 15.76 years, predominantly males (68%). The overall 30-day mortality was 52%. Charlson Comorbidity index was increased in non-survivors (3.72 ± 2.33) and was associated with the outcome. All severity indexes had higher values in patients who died, that showed statistical significance between the analysed groups. The areas under curve (AUC) values of the five scores for 30-day mortality were 0.670, 0.732, 0,726, 0.785 and 0.777, respectively. Conclusion. Widely used severity scores accurately detected patients with pneumonia that had increased risk for poor outcome, but none of them individually demonstrated any advantage over the others.

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