Aims: A nested case-control study of 75 patients with cardiac device infections (CDI) and 75 matched controls was conducted to evaluate time course, risk factors, culture results and frequency of CDI. Methods and results: CDI occurred in 75/3410 (2.2%) device implantation and revision procedures, performed between 2000 and 2007. The time delay between device procedure and infection ranged from 0 to 64 months (mean 14 (SD 16)), 21 patients (28%) had an early infection (,1 month), 26 (35%) a late infection (1-12 months) and 28 (37%) a delayed infection (.12 months). Of interest, 18 (24%) patients presented with an infection .24 months after the device-related procedure. Time delay until infection was significantly shorter when cultures were positive for micro-organisms compared to negative cultures (8 (12) vs 18 (18) months, p = 0.03). Pocket cultures in delayed infections remained more often negative (61% vs 23%, p = 0.01). Independent CDI risk factors were: device revision (odds ratio (OR) 3.67; 95% confidence interval (CI), 1.51 to 8.96), renal dysfunction defined as glomerular filtration rate ,60 ml/min (OR 4.64; CI, 1.48 to 14.62) and oral anticoagulation use (OR 2.83; CI 1.20 to 6.68). Conclusion: CDI occurred in 2.2% of device procedures, with 24% occurring more than two years after the devicerelated procedure. Renal dysfunction, device revisions and oral anticoagulation are potent risk factors for CDI.With expanding evidence-based indications for the implantation of permanent pacemakers, implantable cardioverter defibrillators (ICDs) and cardiac resynchronisation therapy devices (CRTs) the number of device-related procedures have increased rapidly over the past decade. 1 There are indications that the rate of cardiac device infections (CDI) has increased and that this outpaced the increase in implantation rate. 1 Reported CDI rates vary between 0.5% and 5.1%. 2-5 CDI is a serious and potentially life-threatening complication of cardiac device therapy, associated with significant morbidity and mortality usually requiring explantation of the device and lead system. Furthermore device infection results in prolonged hospital stay which is associated with significant costs. The average economic cost of CDI treatment has been estimated at $50 000 (£34 000; J39 400) per patient. 6 7 Although cardiac device therapy improves the outcome in different patient groups, CDI may negatively influence the risk-benefit ratio, especially in primary prevention patients. 1 Risk factors, although under debate, associated with CDI include sex, advanced age, diabetes mellitus, depressed immunity, number of operators, total number and duration of device-related procedures and oral anticoagulation therapy. 8 9 Moreover, CDI can occur shortly after a devicerelated procedure, but may also occur after several months and even after years. 2 Until now little is known about the occurrence and risk factors of CDI late after a device-related procedure. 10 In addition, exact data of infection rates and risk factors in acute and delayed inf...

IntroductionGuidelines recommend that two blood cultures be performed in patients with febrile urinary tract infection (UTI), to detect bacteremia and help diagnose urosepsis. The usefulness and cost-effectiveness of this practice have been criticized. This study aimed to evaluate clinical characteristics and the biomarker procalcitonin (PCT) as an aid in predicting bacteremia.MethodsA prospective observational multicenter cohort study included consecutive adults with febrile UTI in 35 primary care units and 8 emergency departments of 7 regional hospitals. Clinical and microbiological data were collected and PCT and time to positivity (TTP) of blood culture were measured.ResultsOf 581 evaluable patients, 136 (23%) had bacteremia. The median age was 66 years (interquartile range 46 to 78 years) and 219 (38%) were male. We evaluated three different models: a clinical model including seven bed-side characteristics, the clinical model plus PCT, and a PCT only model. The diagnostic abilities of these models as reflected by area under the curve of the receiver operating characteristic were 0.71 (95% confidence interval (CI): 0.66 to 0.76), 0.79 (95% CI: 0.75 to 0.83) and 0.73 (95% CI: 0.68 to 0.77) respectively. Calculating corresponding sensitivity and specificity for the presence of bacteremia after each step of adding a significant predictor in the model yielded that the PCT > 0.25 μg/l only model had the best diagnostic performance (sensitivity 0.95; 95% CI: 0.89 to 0.98, specificity 0.50; 95% CI: 0.46 to 0.55). Using PCT as a single decision tool, this would result in 40% fewer blood cultures being taken, while still identifying 94 to 99% of patients with bacteremia.The TTP of E. coli positive blood cultures was linearly correlated with the PCT log value; the higher the PCT the shorter the TTP (R2 = 0.278, P = 0.007).ConclusionsPCT accurately predicts the presence of bacteremia and bacterial load in patients with febrile UTI. This may be a helpful biomarker to limit use of blood culture resources.

Fosfomycin is a bactericidal, low-molecular weight, broad-spectrum antibiotic, with putative activity against several bacteria, including multidrug-resistant Gram-negative bacteria, by irreversibly inhibiting an early stage in cell wall synthesis. Evidence suggests that fosfomycin has a synergistic effect when used in combination with other antimicrobial agents that act via a different mechanism of action, thereby allowing for reduced dosages and lower toxicity. Fosfomycin does not bind to plasma proteins and is cleared via the kidneys. Due to its extensive tissue penetration, fosfomycin may be indicated for infections of the CNS, soft tissues, bone, lungs, and abscesses. The oral bioavailability of fosfomycin tromethamine is <50%; therefore, oral administration of fosfomycin tromethamine is approved only as a 3-gram one-time dose for treating urinary tract infections. However, based on published PK parameters, PK/PD simulations have been performed for several multiple-dose regimens, which might lead to the future use of fosfomycin for treating complicated infections with multidrug-resistant bacteria. Because essential pharmacological information and knowledge regarding mechanisms of resistance are currently limited and/or controversial, further studies are urgently needed, and fosfomycin monotherapy should be avoided.

Background During the COVID-19 pandemic, the scarcity of resources has necessitated triage of critical care for patients with the disease. In patients aged 65 years and older, triage decisions are regularly based on degree of frailty measured by the Clinical Frailty Scale (CFS). However, the CFS could also be useful in patients younger than 65 years. We aimed to examine the association between CFS score and hospital mortality and between CFS score and admission to intensive care in adult patients of all ages with COVID-19 across Europe. Methods This analysis was part of the COVID Medication (COMET) study, an international, multicentre, retrospective observational cohort study in 63 hospitals in 11 countries in Europe. Eligible patients were aged 18 years and older, had been admitted to hospital, and either tested positive by PCR for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or were judged to have a high clinical likelihood of having SARS-CoV-2 infection by the local COVID-19 expert team. CFS was used to assess level of frailty: fit (CFS 1-3), mildly frail (CFS 4-5), or frail (CFS 6-9). The primary outcome was hospital mortality. The secondary outcome was admission to intensive care. Data were analysed using a multivariable binary logistic regression model adjusted for covariates (age, sex, number of drugs prescribed, and type of drug class as a proxy for comorbidities). Findings Between March 30 and July 15, 2020, 2434 patients (median age 68 years [IQR 55-77]; 1480 [61%] men, 954 [30%] women) had CFS scores available and were included in the analyses. In the total sample and in patients aged 65 years and older, frail patients and mildly frail patients had a significantly higher risk of hospital mortality than fit patients (total sample: CFS 6-9 vs CFS 1-3 odds ratio [OR] 2•71 [95% CI 2•04-3•60], p<0•0001 and CFS 4-5 vs CFS 1-3 OR 1•54 [1•16-2•06], p=0•0030; age ≥65 years: CFS 6-9 vs CFS 1-3 OR 2•90 [2•12-3•97], p<0•0001 and CFS 4-5 vs CFS 1-3 OR 1•64 [1•20-2•25], p=0•0020). In patients younger than 65 years, an increased hospital mortality risk was only observed in frail patients (CFS 6-9 vs CFS 1-3 OR 2•22 [1•08-4•57], p=0•030; CFS 4-5 vs CFS 1-3 OR 1•08 [0•48-2•39], p=0•86). Frail patients had a higher incidence of admission to intensive care than fit patients (CFS 6-9 vs CFS 1-3 OR 1•54 [1•21-1•97], p=0•0010), whereas mildly frail patients had a lower incidence than fit patients (CFS 4-5 vs CFS 1-3 OR 0•71 [0•55-0•92], p=0•0090). Among patients younger than 65 years, frail patients had an increased incidence of admission to intensive care (CFS 6-9 vs CFS 1-3 OR 2•96 [1•98-4•43], p<0•0001), whereas mildly frail patients had no significant difference in incidence compared with fit patients (CFS 4-5 vs CFS 1-3 OR 0•93 [0•63-1•38], p=0•72). Among patients aged 65 years and older, frail patients had no significant difference in the incidence of admission to intensive care compared with fit patients (CFS 6-9 vs CFS 1-3 OR 1•27 [0•92-1•75], p=0•14), whereas mildly frail patients had a lower incide...

Background During the first wave of the COVID-19 pandemic older patients had an increased risk of hospitalisation and death. Reports on the association of frailty with poor outcome have been conflicting. Objective The aim of the present study was to investigate the independent association between frailty and in-hospital mortality in older hospitalised COVID-19 patients in the Netherlands. Methods This was a multi-centre retrospective cohort study in 15 hospitals in the Netherlands, including all patients aged ≥70 years, who were hospitalised with clinically confirmed COVID-19 between February and May 2020. Data were collected on demographics, co-morbidity, disease severity and Clinical Frailty Scale (CFS). Primary outcome was in-hospital mortality. Results A total of 1,376 patients were included (median age 78 years (IQR 74–84), 60% male). In total, 499 (38%) patients died during hospital admission. Parameters indicating presence of frailty (CFS 6–9) were associated with more co-morbidities, shorter symptom duration upon presentation (median 4 vs. 7 days), lower oxygen demand and lower levels of CRP. In multivariable analyses, the CFS was independently associated with in-hospital mortality: compared to patients with CFS 1–3, patients with CFS 4–5 had a two times higher risk (odds ratio (OR) 2.0 (95%CI 1.3–3.0) and patients with CFS 6–9 had a three times higher risk of in-hospital mortality (OR 2.8 (95%CI 1.8–4.3)). Conclusions The in-hospital mortality of older hospitalised COVID-19 patients in the Netherlands was 38%. Frailty was independently associated with higher in-hospital mortality, even though COVID-19 patients with frailty presented earlier to the hospital with less severe symptoms.