Dataset Information

CKD and the risk of acute, community-acquired infections among older people with diabetes mellitus: a retrospective cohort study using electronic health records.

ABSTRACT:

Background

Hospital admissions for community-acquired infection are increasing rapidly in the United Kingdom, particularly among older individuals, possibly reflecting an increasing prevalence of comorbid conditions such as chronic kidney disease (CKD). This study describes associations between CKD (excluding patients treated by dialysis or transplantation) and community-acquired infection incidence among older people with diabetes mellitus.

Study design

Retrospective cohort study using primary care records from the Clinical Practice Research Datalink linked to Hospital Episode Statistics admissions data.

Setting & participants

191,709 patients 65 years or older with diabetes mellitus and no history of renal replacement therapy, United Kingdom, 1997 to 2011.

Predictor

Estimated glomerular filtration rate (eGFR) and history of proteinuria.

Outcomes

Incidence of community-acquired lower respiratory tract infections (LRTIs, with pneumonia as a subset) and sepsis, diagnosed in primary or secondary care, excluding hospital admissions from time at risk.

Measurements

Poisson regression was used to calculate incidence rate ratios (IRRs) adjusted for age, sex, smoking status, comorbid conditions, and characteristics of diabetes. Estimates for associations of eGFR with infection were adjusted for proteinuria, and vice versa.

Results

Strong graded associations between lower eGFRs and infection were observed. Compared with patients with eGFRs?60mL/min/1.73m(2), fully adjusted IRRs for pneumonia among those with eGFRs<15, 15 to 29, 30 to 44, and 45 to 59mL/min/1.73m(2) were 3.04 (95% CI, 2.42-3.83), 1.73 (95% CI, 1.57-1.92), 1.19 (95% CI, 1.11-1.28), and 0.95 (95% CI, 0.89-1.01), respectively. Associations between lower eGFRs and sepsis were stronger, with fully adjusted IRRs up to 5.56 (95% CI, 3.90-7.94). Those associations with LRTI were weaker but still clinically relevant at up to 1.47 (95% CI, 1.34-1.62). In fully adjusted models, a history of proteinuria remained an independent marker of increased infection risk for LRTI, pneumonia, and sepsis (IRRs of 1.07 [95% CI, 1.05-1.09], 1.26 [95% CI, 1.19-1.33], and 1.33 [95% CI, 1.20-1.47]).

Limitations

Patients without creatinine results were excluded.

Conclusions

Strategies to prevent infection among people with CKD are needed.

SUBMITTER: McDonald HI

PROVIDER: S-EPMC4510204 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Publications

CKD and the risk of acute, community-acquired infections among older people with diabetes mellitus: a retrospective cohort study using electronic health records.

McDonald Helen I HI Thomas Sara L SL Millett Elizabeth R C ER Nitsch Dorothea D

American journal of kidney diseases : the official journal of the National Kidney Foundation 20150130 1

<h4>Background</h4>Hospital admissions for community-acquired infection are increasing rapidly in the United Kingdom, particularly among older individuals, possibly reflecting an increasing prevalence of comorbid conditions such as chronic kidney disease (CKD). This study describes associations between CKD (excluding patients treated by dialysis or transplantation) and community-acquired infection incidence among older people with diabetes mellitus.<h4>Study design</h4>Retrospective cohort study ...[more]

PMID: 25641062

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Project description:BACKGROUND:Community-acquired acute kidney injury (CA-AKI)-associated hospitalizations impose significant health care needs and contribute to in-hospital mortality. However, most risk prediction models developed to date have focused on AKI in a specific group of patients during hospitalization, and there is limited knowledge on the baseline risk in the general population for preventing CA-AKI-associated hospitalization. OBJECTIVE:To gain further insight into risk exploration, the aim of this study was to develop, validate, and establish a scoring system to facilitate health professionals in enabling early recognition and intervention of CA-AKI to prevent permanent kidney damage using different machine-learning techniques. METHODS:A nested case-control study design was employed using electronic health records derived from a group of Chang Gung Memorial Hospitals in Taiwan from 2010 to 2017 to identify 234,867 adults with at least two measures of serum creatinine at hospital admission. Patients were classified into a derivation cohort (2010-2016) and a temporal validation cohort (2017). Patients with the first episode of CA-AKI at hospital admission were classified into the case group and those without CA-AKI were classified in the control group. A total of 47 potential candidate variables, including age, gender, prior use of nephrotoxic medications, Charlson comorbid conditions, commonly measured laboratory results, and recent use of health services, were tested to develop a CA-AKI hospitalization risk model. Permutation-based selection with both the extreme gradient boost (XGBoost) and least absolute shrinkage and selection operator (LASSO) algorithms was performed to determine the top 10 important features for scoring function development. RESULTS:The discriminative ability of the risk model was assessed by the area under the receiver operating characteristic curve (AUC), and the predictive CA-AKI risk model derived by the logistic regression algorithm achieved an AUC of 0.767 (95% CI 0.764-0.770) on derivation and 0.761 on validation for any stage of AKI, with positive and negative predictive values of 19.2% and 96.1%, respectively. The risk model for prediction of CA-AKI stages 2 and 3 had an AUC value of 0.818 for the validation cohort with positive and negative predictive values of 13.3% and 98.4%, respectively. These metrics were evaluated at a cut-off value of 7.993, which was determined as the threshold to discriminate the risk of AKI. CONCLUSIONS:A machine learning-generated risk score model can identify patients at risk of developing CA-AKI-related hospitalization through a routine care data-driven approach. The validated multivariate risk assessment tool could help clinicians to stratify patients in primary care, and to provide monitoring and early intervention for preventing AKI while improving the quality of AKI care in the general population.

Dataset Information

CKD and the risk of acute, community-acquired infections among older people with diabetes mellitus: a retrospective cohort study using electronic health records.

Background

Study design

Setting & participants

Predictor

Outcomes

Measurements

Results

Limitations

Conclusions

Publications

CKD and the risk of acute, community-acquired infections among older people with diabetes mellitus: a retrospective cohort study using electronic health records.

Similar Datasets

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