Likelihood of inadequate treatment: a novel approach to evaluating drug-resistance patterns

Restricted antimicrobial prescribing in an area of highly prevalent antimicrobial resistance

OBJECTIVE

To assess the predictive value for infection with multidrug-resistant organisms (MDROs) of reasons for empirical prescription of restricted antibiotics (rABX), in a setting with high resistance rates.

METHODS

We prospectively studied all rABX prescriptions in a 550-bed tertiary teaching hospital from April 15 to June 14, 2018 and from September 1 to October 30, 2018. Prescribing physicians had to justify their decision by choosing one or more prespecified reasons.

RESULTS

We reviewed 172 empirical prescriptions of rABX, which accounted for 67.2% of all rABX prescriptions. Stated reasons for empirical prescription of rABX were recent hospitalization (72.7%), escalation due to non-response to previous antimicrobials (47.7%), treatment for severe sepsis/septic shock (45.9%), escalation due to recurrence or deterioration (22.1%), prior MDRO infection (12.8%), and prior MDRO colonization (7.6%). Empirical treatment for septic shock or severe sepsis was the only significant predictor of MDRO isolation (OR=5.26, 95% CI: 1.5-18.4, P=0.009), while recent hospitalization had a high negative predictive value for MDRO (97.4%). Fourteen per cent of microbiologically documented infections were associated with MDROs resistant to the prescribed rABX.

CONCLUSIONS

Empirical treatment for severe sepsis or septic shock was the only independent predictor of MDRO isolation. Recent hospitalization had a high negative predictive value for MDRO infection. The isolation of pathogens resistant to the prescribed rABX suggests that in a setting with widespread antimicrobial resistance, it could be difficult to reduce the empirical use of rABX without risking inadequate treatment.

A decision support system for antibiotic prescription based on local cumulative antibiograms

BACKGROUND

Local cumulative antibiograms are useful tools with which to select appropriate empiric or directed therapies when treating infectious diseases at a hospital. However, data represented in traditional antibiograms are static, incomplete and not well adapted to decision-making.

METHODS

We propose a decision support method for empiric antibiotic therapy based on the Number Needed to Fail (NNF) measure. NNF indicates the number of patients that would need to be treated with a specific antibiotic for one to be inadequately treated. We define two new measures, Accumulated Efficacy and Weighted Accumulated Efficacy in order to determine the efficacy of an antibiotic. We carried out two experiments: the first during which there was a suspicion of infection and the patient had empiric therapy, and the second by considering patients with confirmed infection and directed therapy. The study was performed with 15,799 cultures with 356,404 susceptibility tests carried out over a four-year period.

RESULTS

The most efficient empiric antibiotics are Linezolid and Vancomycin for blood samples and Imipenem and Meropenem for urine samples. In both experiments, the efficacies of recommended antibiotics are all significantly greater than the efficacies of the antibiotics actually administered (P < 0.001). The highest efficacy is obtained when considering 2 years of antibiogram data and 80% of the cumulated prevalence of microorganisms.

CONCLUSION

This extensive study on real empiric therapies shows that the proposed method is a valuable alternative to traditional antibiograms as regards developing clinical decision support systems for antimicrobial stewardship.

Antimicrobial Susceptibilities of Enterobacteriaceae in Community-Acquired Urinary Tract Infections during a 5-year Period: A Single Hospital Study in Korea

Background

Through investigating antimicrobial susceptibility patterns of Enterobacteriaceae in community-acquired urinary tract infection (CA-UTI), we provide basic evidence for the use of empirical antibiotics in CA-UTI.

Materials and Methods

We retrospectively reviewed the medical records of patients over the age of 19 years who visited a hospital in Seoul between January 2012 and December 2016 for a CA-UTI. Urine cultures were used to identify causative organisms. We investigated extended-spectrum β-lactamase (ESBL) production and the antimicrobial susceptibility of Enterobactereiaceae. We evaluated recommended empirical antibiotics numerically by calculating the syndrome-specific likelihood of inadequate therapy (LIT) for the last 2 years (interpretation of the LIT A value: 1 out of A people is likely to receive inadequate empirical antibiotics).

Results

Urine cultures were performed in 1,605 out of 2,208 patients who were diagnosed with CA-UTI, and causative pathogens were identified in 1,134 (70.7%) cases. There were 998 (88.0%) cases of Enterobacteriaceae and Escherichia coli was the most common pathogen, accounting for 80.3% of cases (911 cases). The overall resistance rates to trimethoprim-sulfamethoxazole, fluoroquinolones, and cefotaxime were 31.7%, 23.2%, and 13.5%, respectively. There were 128 (10.8%) cases of ESBL-producing Entererobacteriaceae with an increasing but non-significant trend (P = 0.255). The LIT for CA-UTI in the past two years was highest for ertapenem and imipenem. Fluoroquinolones ranked 11th, with a LIT of 8.2, and cefotaxime ranked higher, at 10.5. In ESBL-producing Enterobacteriaceae, except for carbapenems, amikacin and piperacillin-tazobactam showed the highest susceptibility rates at 99.2% and 94.3%, respectively.

Conclusion

Empiric treatment with fluoroquinolones in CA-UTI should be carefully considered, given the high resistance rate. The proportion of ESBL-producing Entererobacteriaceae in CA-UTI has increased to a high level in Korea. Amikacin and piperacillin-tazobactam could be considered for empiric treatment in patients at risk for ESBL-producing Entererobacteriaceae when considering alternatives to carbapenems.

A multidimensional antimicrobial stewardship intervention targeting aztreonam use in patients with a reported penicillin allergy

BACKGROUND

Local antimicrobial susceptibility patterns should be considered for antimicrobial therapy decisions. Antibiogram data can guide beta-lactam antibiotic use in the presence of a penicillin allergy, particularly when allergic cross-reactivity among antibiotic agents is unlikely.

OBJECTIVE

To evaluate the effect of a multidimensional antimicrobial stewardship intervention to improve antibiogram-driven antibiotic selection for patients with a reported penicillin allergy receiving aztreonam.

METHODS

This historically controlled, quasi-experimental study compared historical aztreonam use with prospective antibiotic selection following a pharmacist-led intervention in patients with a penicillin allergy. The impact of this intervention on aztreonam use, antimicrobial selection, patient allergy profile updates, length of stay, in-hospital mortality, and antibiotic cost savings was assessed.

RESULTS

A significant reduction in median days of aztreonam therapy (4.0 vs. 2.0; p = 0.0001) and median days of therapy per 1000 patient days (14.5 vs. 9.3; p = 0.0001) was found in the intervention group.

CONCLUSION

A pharmacist-led antimicrobial stewardship intervention facilitated antibiogram-driven antibiotic therapy while reducing aztreonam use in patients without an anaphylactic penicillin allergy. Further trials are needed to assess the utility of similar antimicrobial stewardship interventions for patients with penicillin allergy.

Antimicrobial stewardship resources and activities for children in tertiary hospitals in Australasia: a comprehensive survey

OBJECTIVE

To identify current antimicrobial stewardship (AMS) resources and activities for children in hospitals throughout Australasia, to identify gaps in services.

DESIGN, SETTING AND PARTICIPANTS

Tertiary paediatric hospitals (children's hospitals and combined adult and paediatric hospitals that offer tertiary paediatric care) in every state and territory of Australia and the North and South Islands of New Zealand were surveyed in June 2013 regarding AMS resources and activities.

MAIN OUTCOME MEASURE

A description of AMS resources and activities for children in tertiary hospitals.

RESULTS

We surveyed 14 hospitals, with paediatric bed numbers ranging from 40 to 300. Seven had a dedicated paediatric AMS team or AMS team with a paediatric representative and 11 had an AMS pharmacist position, although only four had committed ongoing funding for a permanent paediatric AMS pharmacist and only two had committed funding for a paediatric infectious diseases physician for AMS. All hospitals had empirical antimicrobial prescribing guidelines, and all 10 hospitals with haematology and oncology services had febrile neutropenia guidelines. However, most did not have guidelines for antifungal prophylaxis, surgical prophylaxis, neonatology or paediatric intensive care. All hospitals had restricted drugs but only four had electronic approval systems. Auditing methods differed widely but were mostly ad hoc, with results fed back in an untargeted way. There was a paucity of AMS education: no hospitals provided education for senior medical staff, and four had no education for any staff. The commonest perceived barriers to successful AMS were lack of education (11 hospitals) and lack of dedicated pharmacy (eight) and medical (seven) staff.

CONCLUSIONS

Australasian paediatric hospitals have implemented some AMS activities, but most lack resources. There was consensus among the staff who completed our survey that barriers to successful AMS include lack of education and lack of personnel.

Constructing unit-specific empiric treatment guidelines for catheter-related and primary bacteremia by determining the likelihood of inadequate therapy

This study aimed to determine the feasibility of using likelihood of inadequate therapy (LIT), a parameter calculated by using pathogen frequency and in vitro susceptibility for determination of appropriate empiric antibiotic therapy for primary bloodstream infections. Our study demonstrates that LIT may reveal differences in traditional antibiograms.

Informed switching strongly decreases the prevalence of antibiotic resistance in hospital wards

Antibiotic resistant nosocomial infections are an important cause of mortality and morbidity in hospitals. Antibiotic cycling has been proposed to contain this spread by a coordinated use of different antibiotics. Theoretical work, however, suggests that often the random deployment of drugs ("mixing") might be the better strategy. We use an epidemiological model for a single hospital ward in order to assess the performance of cycling strategies which take into account the frequency of antibiotic resistance in the hospital ward. We assume that information on resistance frequencies stems from microbiological tests, which are performed in order to optimize individual therapy. Thus the strategy proposed here represents an optimization at population-level, which comes as a free byproduct of optimizing treatment at the individual level. We find that in most cases such an informed switching strategy outperforms both periodic cycling and mixing, despite the fact that information on the frequency of resistance is derived only from a small sub-population of patients. Furthermore we show that the success of this strategy is essentially a stochastic phenomenon taking advantage of the small population sizes in hospital wards. We find that the performance of an informed switching strategy can be improved substantially if information on resistance tests is integrated over a period of one to two weeks. Finally we argue that our findings are robust against a (moderate) preexistence of doubly resistant strains and against transmission via environmental reservoirs. Overall, our results suggest that switching between different antibiotics might be a valuable strategy in small patient populations, if the switching strategies take the frequencies of resistance alleles into account.

[Quantitative Bayesian diagnosis developed for lower respiratory tract infections due to methicillin-resistant Staphylococcus aureus]

Using quantitative Bayesian analysis as a clinical epidemiological approach, we developed a diagnosis for lower respiratory tract infection (LRTI) due to Methicillin-resistant Staphylococcus aureus (MRSA). We retrospectively reviewed the charts of 181 subjects--a derivation cohort-with MRSA retrieved from lower respiratory specimens June 2006 to March 2008. Dividing them into infection or colonization (no infection) groups, we compared them for the presence or absence of clinical parameters, including fever > 38 degrees C, MRSA >106 CFU (colony-forming units)/mL, phagocytosis on Gram staining, serum albumin < 3.0 g/dL, and peripheral WBC count > 15,000/mL. We them determined positive and negative likelihood ratios (LR +, LR -) for these parameters to quantify MRSA-LRTI diagnostic probability based on combined likelihood ratios (Bayesian analysis). We then determined Bayesian MRSA-LRTI diagnostic probabilities (BDPs) in 40 subjects with respiratory MRSA--a validation cohort-from May 2008 to October 2008 clinically judged with either infection (n = 14) or colonization (n = 26) by infection control personnel (ICP) blinded to the test (parameter LR+ and LR -). BDPs (mean +/- SD) quantified by combining the four parameters-fever, MRSA CFU, phagocytosis, and serum albumin-were 62.3 +/- 25.4% for 14 judged with infection, and 40.2% +/- 20.4% for 26 patients judged with colonization (p = 0.005). Using a diagnostic probability of 51% as the cut off, we compared positive and negative predictive Bayesian diagnoses ICP judgment, i.c., 77% vs. 85%. The Bayesian approach proved useful in quantitatively diagnosing infectious disease such as MRSA-LRTI that lack established diagnostic, and may aid physicians in deciding the need for specific antimicrobial therapy.