ABSTRACT
BACKGROUND: Carbapenem-resistant Enterobacterales (CRE) bloodstream infections (BSIs) are a major threat to patients. To date, data on risk factors have been limited, with low internal and external validity. In this multicentre study, risk factors for CRE BSI were determined by comparison with two control groups: patients with carbapenem-susceptible Enterobacterales (CSE) BSI, and patients without Enterobacterales infection (uninfected patients). METHODS: A multicentre, case-control-control study was nested in a European prospective cohort study on CRE (EURECA). CRE BSI:CSE BSI matching was 1:1, CRE BSI:Uninfected patients matching was 1:3, based on hospital, ward and length of stay. Conditional logistic regression was applied. RESULTS: From March 2016 to November 2018, 73 CRE BSIs, 73 CSE BSIs and 219 uninfected patients were included from 18 European hospitals. For CRE versus CSE BSI, previous CRE colonization/infection [incidence rate ratio (IRR) 7.32; 95% CI 1.65-32.38) increased the risk. For CRE versus uninfected controls, independent risk factors included: older age (IRR 1.03; 95% CI 1.01-1.06), patient referral (long-term care facility: IRR 7.19; 95% CI 1.51-34.24; acute care hospital: IRR 5.26; 95% CI 1.61-17.11), previous colonization/infection with other MDR organisms (MDROs) (IRR 9.71; 95% CI 2.33-40.56), haemodialysis (IRR 8.59; 95% CI 1.82-40.53), invasive procedures (IRR 5.66; 95% CI 2.11-15.16), and ß-lactam/ß-lactamase inhibitor combinations (IRR 3.92; 95% CI 1.68-9.13) or third/fourth generation cephalosporin (IRR 2.75; 95% CI 1.06-7.11) exposure within 3â months before enrolment. CONCLUSIONS: Evidence of previous CRE colonization/infection was a major risk factor for carbapenem resistance among Enterobacterales BSI. Compared with uninfected patients, evidence of previous MDRO colonization/infection and healthcare exposure were important risk factors for CRE BSI. Targeted screening, infection prevention and antimicrobial stewardship should focus on these high-risk patients.
Subject(s)
Anti-Bacterial Agents , Bacteremia , Carbapenem-Resistant Enterobacteriaceae , Carbapenems , Enterobacteriaceae Infections , Humans , Case-Control Studies , Risk Factors , Male , Enterobacteriaceae Infections/epidemiology , Enterobacteriaceae Infections/microbiology , Female , Aged , Middle Aged , Prospective Studies , Bacteremia/microbiology , Bacteremia/epidemiology , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Carbapenems/pharmacology , Carbapenem-Resistant Enterobacteriaceae/drug effects , Carbapenem-Resistant Enterobacteriaceae/isolation & purification , Europe/epidemiology , Aged, 80 and overABSTRACT
INTRODUCTION: Artificial intelligence or machine learning (AI/ML) based systems can help personalize prescribing decisions for individual patients. The recommendations of these clinical decision support systems must relate to the "label" of the medicines involved. The label of a medicine is an approved guide that indicates how to prescribe the drug in a safe and effective manner. AREAS COVERED: The label for a medicine may evolve as new information on drug safety and effectiveness emerges, leading to the addition or removal of warnings, drug-drug interactions, or to permit new indications. However, the speed at which these updates are made to these AI/ML recommendation systems may be delayed and could influence the safety of prescribing decisions. This article explores the need to keep AI/ML tools 'in sync' with any label changes. Additionally, challenges relating to medicine availability and geographical suitability are discussed. EXPERT OPINION: These considerations highlight the important role that pharmacoepidemiologists and drug safety professionals must play within the monitoring and use of these tools. Furthermore, these issues highlight the guiding role that regulators need to have in planning and oversight of these tools.
Artificial intelligence or machine learning (AI/ML) based systems that guide the prescription of medications have the potential to vastly improve patient care, but these tools should only provide recommendations that are in line with the label of a medicine. With a constantly evolving medication label, this is likely to be a challenge, and this also has implications for the off-label use of medicines.
Subject(s)
Artificial Intelligence , Decision Support Systems, Clinical , Drug Labeling , Drug-Related Side Effects and Adverse Reactions , Machine Learning , Humans , Drug-Related Side Effects and Adverse Reactions/prevention & control , Drug Interactions , Pharmacoepidemiology/methods , Practice Patterns, Physicians'/standards , Precision MedicineABSTRACT
OBJECTIVES: To assess the mortality attributable to infections caused by carbapenem-resistant Enterobacterales (CRE) and to investigate the effect of clinical management on differences in observed outcomes in a multinational matched cohort study. METHODS: A prospective matched-cohorts study (NCT02709408) was performed in 50 European hospitals from March 2016 to November 2018. The main outcome was 30-day mortality with an active post-discharge follow-up when applied. The CRE cohort included patients with complicated urinary tract infections, complicated intra-abdominal infections, pneumonia, or bacteraemia from other sources because of CRE. Two control cohorts were selected: patients with infection caused by carbapenem-susceptible Enterobacterales (CSE) and patients without infection. Matching criteria included type of infection for the CSE group, hospital ward of CRE detection, and duration of hospital admission up to CRE detection. Multivariable and stratified Cox regression was applied. RESULTS: The cohorts included 235 patients with CRE infection, 235 patients with CSE infection, and 705 non-infected patients. The 30-day mortality (95% CI) was 23.8% (18.8-29.6), 10.6% (7.2-15.2), and 8.4% (6.5-10.6), respectively. The difference in 30-day mortality rates between patients with CRE infection when compared with patients with CSE infection was 13.2% (95% CI, 6.3-20.0), (HR, 2.57; 95% CI, 1.55-4.26; p < 0.001), and 15.4% (95% CI, 10.5-20.2) when compared with non-infected patients (HR, 3.85; 95% CI, 2.57-5.77; p < 0.001). The population attributable fraction for 30-day mortality for CRE vs. CSE was 19.28%, and for CRE vs. non-infected patients was 9.61%. After adjustment for baseline variables, the HRs for mortality were 1.87 (95% CI, 0.99-3.50; p 0.06) and 3.65 (95% CI, 2.29-5.82; p < 0.001), respectively. However, when treatment-related time-dependent variables were added, the HR of CRE vs. CSE reduced to 1.44 (95% CI, 0.78-2.67; p 0.24). DISCUSSION: CRE infections are associated with significant attributable mortality and increased adjusted hazard of mortality when compared with CSE infections or patients without infection. Underlying patient characteristics and a delay in appropriate treatment play an important role in the CRE mortality.
Subject(s)
Aftercare , Gammaproteobacteria , Humans , Cohort Studies , Patient Discharge , Prospective Studies , Carbapenems/pharmacology , Carbapenems/therapeutic use , Case-Control StudiesABSTRACT
The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools can perform actions such as choosing the 'safest' medication, choosing between competing medications, promoting de-prescribing or even predicting non-adherence. These tools can exist in a variety of formats; for example, they may be directly integrated into electronic medical records or they may exist in a stand-alone website accessible by a web browser. One potential impact of these tools is that they could manipulate our understanding of the benefit-risk of medicines in the real world. Currently, the benefit risk of approved medications is assessed according to carefully planned agreements covering spontaneous reporting systems and planned surveillance studies. But AI-based tools may limit or even block prescription to high-risk patients or prevent off-label use. The uptake and temporal availability of these tools may be uneven across healthcare systems and geographies, creating artefacts in data that are difficult to account for. It is also hard to estimate the 'true impact' that a tool had on a prescribing decision. International borders may also be highly porous to these tools, especially in cases where tools are available over the web. These tools already exist, and their use is likely to increase in the coming years. How they can be accounted for in benefit-risk decisions is yet to be seen.
Subject(s)
Artificial Intelligence , Delivery of Health Care , Humans , Drug Prescriptions , Electronic Health Records , Risk AssessmentABSTRACT
BACKGROUND: It is a matter of debate whether 1 universal standard, such as the International Fetal and Newborn Growth Consortium for the 21st Century standard, can be applied to all populations. OBJECTIVE: The primary objective was to establish a Danish newborn standard based on the criteria of the International Fetal and Newborn Growth Consortium for the 21st Century standard to compare the percentiles of these 2 standards. A secondary objective was to compare the prevalence and risk of fetal and neonatal deaths related to small for gestational age defined by the 2 standards when used in the Danish reference population. STUDY DESIGN: This was a register-based nationwide cohort study. The Danish reference population included 375,318 singletons born at 33 to 42 weeks of gestation in Denmark between January 1, 2008, and December 31, 2015. The Danish standard cohort included 37,811 newborns who fulfilled the criteria of the International Fetal and Newborn Growth Consortium for the 21st Century standard. Birthweight percentiles were estimated using smoothed quantiles for each gestational week. The outcomes included birthweight percentiles, small for gestational age (defined as a birthweight of 3rd percentile), and adverse outcomes (defined as either fetal or neonatal death). RESULTS: At all gestational ages, the Danish standard median birthweights at term were higher than the International Fetal and Newborn Growth Consortium for the 21st Century standard median birthweights: 295g for females and 320 g for males. Therefore, the estimates of the prevalence rate of small for gestational age within the entire population were different: 3.9% (n=14,698) using the Danish standard vs 0.7% (n=2640) using the International Fetal and Newborn Growth Consortium for the 21st Century standard. Accordingly, the relative risk of fetal and neonatal deaths among small-for-gestational-age fetuses differed by SGA status defined by the different standards (4.4 [Danish standard] vs 9.6 [International Fetal and Newborn Growth Consortium for the 21st Century standard]). CONCLUSION: Our finding did not support the hypothesis that 1 universal standard birthweight curve can be applied to all populations.
Subject(s)
Infant, Newborn, Diseases , Perinatal Death , Male , Female , Infant, Newborn , Humans , Birth Weight , Cohort Studies , Fetal Development , Infant, Small for Gestational Age , Gestational Age , Fetal Growth Retardation/epidemiology , Fetus , Denmark/epidemiologyABSTRACT
Background: Data on risk factors for carbapenem-resistant Enterobacterales (CRE) with wider applicability are needed to inform preventive measures and efficient design of randomised trials. Methods: An international matched case-control-control study was performed in 50 hospitals with high CRE incidence from March 2016 to November 2018 to investigate different aspects of infections caused by CRE (NCT02709408). Cases were patients with complicated urinary tract infection (cUTI), complicated intraabdominal (cIAI), pneumonia or bacteraemia from other sources (BSI-OS) due to CRE; control groups were patients with infection caused by carbapenem-susceptible Enterobacterales (CSE), and by non-infected patients, respectively. Matching criteria included type of infection for CSE group, ward and duration of hospital admission. Conditional logistic regression was used to identify risk factors. Findings: Overall, 235 CRE case patients, 235 CSE controls and 705 non-infected controls were included. The CRE infections were cUTI (133, 56.7%), pneumonia (44, 18.7%), cIAI and BSI-OS (29, 12.3% each). Carbapenemase genes were found in 228 isolates: OXA-48/like, 112 (47.6%), KPC, 84 (35.7%), and metallo-ß-lactamases, 44 (18.7%); 13 produced two. The risk factors for CRE infection in both type of controls were (adjusted OR for CSE controls; 95% CI; p value) previous colonisation/infection by CRE (6.94; 2.74-15.53; <0.001), urinary catheter (1.78; 1.03-3.07; 0.038) and exposure to broad spectrum antibiotics, as categorical (2.20; 1.25-3.88; 0.006) and time-dependent (1.04 per day; 1.00-1.07; 0.014); chronic renal failure (2.81; 1.40-5.64; 0.004) and admission from home (0.44; 0.23-0.85; 0.014) were significant only for CSE controls. Subgroup analyses provided similar results. Interpretation: The main risk factors for CRE infections in hospitals with high incidence included previous colonization, urinary catheter and exposure to broad spectrum antibiotics. Funding: The study was funded by the Innovative Medicines Initiative Joint Undertaking (https://www.imi.europa.eu/) under Grant Agreement No. 115620 (COMBACTE-CARE).
ABSTRACT
OBJECTIVE: To compare changes in systolic and diastolic blood pressures (SBP, DBP) from baseline to following 8 weeks of treatment with a low dose combination of amlodipine 5 mg plus bisoprolol 5 mg versus up titration to the maximum daily dose of amlodipine 10 mg, in hypertensive patients uncontrolled by amlodipine 5 mg. METHODS: Individual patient data (IPD) from a randomized clinical trial (RCT) comparing the combination versus amlodipine 5 mg (EudraCT Number: 2019-000751-13) and aggregated data (AgD) from a published RCT comparing amlodipine 10 mg versus amlodipine 5 mg were utilized in an anchored simulated treatment comparison (STC). The RCT with IPD was used to create models assessing how patients might respond to the combination if they were more comparable to those patients in the RCT with AgD. A population-adjusted indirect comparison of the treatment strategies was then conducted, using amlodipine 5 mg as an anchor. RESULTS: In the efficacy analyses, a total of 261 patients were included in the amlodipine 10 mg arm of the RCT with AgD; and a total of 178 patients in the low-dose combination arm of the RCT with IPD. Respectively, in the Amlodipine 10 mg arm and in the low-dose combination arm, the mean age was 54.3 years-old (Standard deviation [SD] 10.6), and 57.1 years-old (13.7); 8.7% and 18.8% of patients were diabetics; and the mean baseline SBP/DBP was 149.3 (12.0)/96.5 (4.7) mmHg, and 148.8 (8.2)/90.2 (7.6) mmHg. The final model for SBP and DBP included the following variables: baseline SBP, baseline DBP, duration of hypertension, age, concomitant diabetes, sex, smoking history (final model for SBP only), and body mass index (final model for DBP only). Mean treatment differences (standard error [SE]) at 8 weeks between the combination and uptitration were -1.6 mmHg (1.9) for SBP; and -3.3 mmHg (1.3) for DBP. CONCLUSION: In this indirect comparison, a more important decrease was observed in DBP with the low-dose combination as compared to the alternative therapeutic approach of up-titration from amlodipine 5 mg to amlodipine 10 mg. No meaningful difference was seen for SBP.
Subject(s)
Bisoprolol , Hypertension , Amlodipine , Antihypertensive Agents/therapeutic use , Bisoprolol/therapeutic use , Blood Pressure , Drug Combinations , Humans , Hypertension/drug therapy , Middle Aged , Treatment OutcomeABSTRACT
For large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of general nested case-control designs, we propose three sampling schemes where not all commonly observed outcomes need to be included in the analysis. Rather, inclusion probabilities may be time-dependent and may even depend on the past sampling and exposure history. A bootstrap analysis of a full cohort data set from hospital epidemiology allows us to investigate the practical utility of the proposed sampling schemes in comparison to a full cohort analysis and a too simple application of the nested case-control design, if the outcome is not rare.
Subject(s)
Case-Control Studies , Cohort Studies , Epidemiologic Methods , Binomial Distribution , Computer Simulation , Cross Infection , Environmental Exposure , Humans , Time FactorsABSTRACT
INTRODUCTION: The rapid worldwide spread of carbapenem-resistant Enterobacteriaceae (CRE) constitutes a major challenge. The aim of the EUropean prospective cohort study on Enterobacteriaceae showing REsistance to CArbapenems (EURECA), which is part of the Innovative Medicines Initiative Joint Undertaking (IMI JU) funded COMBACTE-CARE project, is to investigate risk factors for and outcome determinants of CRE infections to inform randomised clinical trial designs and to provide a historical cohort that could eventually be used for future comparisons with new drugs targeting CRE. METHODS: A multicentre (50 sites), multinational (11 European countries), analytical observational project was designed, comprising 3 studies. The aims of study 1 (a prospective cohort study) include characterising the features, clinical management and outcomes of hospitalised patients with intra-abdominal infection, pneumonia, complicated urinary tract infections and bloodstream infections caused by CRE (202 patients in each group). The main outcomes will be 30-day all-cause mortality and clinical response. Study 2 (a nested case-control study) will identify the risk factors for target infections caused by CRE; 248 selected patients from study 1 will be matched with patients with carbapenem-susceptible Enterobacteriaceae (1:1) and with hospitalised patients (1:3) and will provide a historical cohort of patients with CRE infections. Study 3 (a matched cohort study) will follow patients in study 2 in order to assess mortality, length of stay and hospital costs associated with CRE. All patients will be followed for 30â days. Different, up-to-date statistical methods will be applied to come to unbiased estimates for all 3 studies. ETHICS AND DISSEMINATION: Before-study sites will be initiated, approval will be sought from appropriate regulatory agencies and local Ethics Committees of Research or Institutional Review Boards (IRBs) to conduct the study in accordance with regulatory requirements. This is an observational study and therefore no intervention in the diagnosis, management or treatment of the patients will be required on behalf of the investigation. Any formal presentation or publication of data collected from this study will be considered as a joint publication by the participating physician(s) and will follow the recommendations of the International Committee of Medical Journal Editors (ICMJE) for authorship. TRIAL REGISTRATION NUMBER: NCT02709408.