Safe Penicillin Allergy Delabeling in Primary Care: A Systematic Review and Meta-Analysis.

BACKGROUND: Ten percent of the population is labeled as allergic to penicillin(s), when in fact 90% of these labels are inappropriate. Recent studies have shown that inpatient delabeling by a direct drug challenge (dDC) is safe in low-risk patients. However, there is a need for outpatient and nonallergist delabeling. OBJECTIVE: To assess the safety of delabeling low-risk adults by means of dDC in primary care. METHODS: We searched the MEDLINE, Embase, and Cochrane Library databases from inception to March 15, 2022 (updated June 5, 2023) for studies performing dDC in adults in primary care or other outpatient settings. Two researchers independently screened studies for eligibility. The data extraction and critical appraisal were performed by 1 reviewer, and we pooled the results in a meta-analysis. RESULTS: Of 2138 results, 12 studies (1070 participants) were eligible for inclusion. Three studies evaluated delabeling in primary care and 9 studies in an outpatient hospital setting. There were no critical adverse events during dDC. No reaction occurred in 97.13% of the 1070 patients, who previously labeled as penicillin-allergic, and were safely delabeled. Ten patients (<1%) developed an immediate reaction: 3 had self-limiting reactions and 7 needed antihistaminics, steroids, epinephrine, and/or salbutamol. CONCLUSIONS: No serious allergic reactions are observed during direct amoxicillin challenge in adults in an outpatient setting. However, with the exception of 1 recent report, these studies are of low to moderate quality. Nonspecialist delabeling is promising, but further research is required on correct risk stratification and safety assessment in large cohort studies evaluating dDC in primary care.

Do doctors and other healthcare professionals know overdiagnosis in screening and how are they dealing with it? A protocol for a mixed methods systematic review.

INTRODUCTION: Overdiagnosis is the diagnosis of a disease that would never have caused any symptom or problem. It is a harmful side effect of screening and may lead to unnecessary treatment, costs and emotional drawbacks. Doctors and other healthcare professionals (HCPs) have the opportunity to mitigate these consequences, not only by informing their patients or the public but also by adjusting screening methods or even by refraining from screening. However, it is unclear to what extent HCPs are fully aware of overdiagnosis and whether it affects their screening decisions. With this systematic review, we aim to synthesise all available research about what HCPs know and think about overdiagnosis, how it affects their position on screening policy and whether they think patients and the public should be informed about it. METHODS AND ANALYSIS: We will systematically search several databases (MEDLINE, Embase, Web of Science, Scopus, CINAHL and PsycArticles) for studies that directly examine HCPs' knowledge and subjective perceptions of overdiagnosis due to health screening, both qualitatively and quantitatively. We will optimise our search by scanning reference and citation lists, contacting experts in the field and hand searching abstracts from the annual conference on 'Preventing Overdiagnosis'. After selection and quality appraisal, we will analyse qualitative and quantitative findings separately in a segregated design for mixed-method reviews. The data will be examined and presented descriptively. If the retrieved studies allow it, we will review them from a constructivist perspective through a critical interpretive synthesis. ETHICS AND DISSEMINATION: For this type of research, no ethical approval is required. Findings from this systematic review will be published in a peer-reviewed journal and presented at the annual congress of 'Preventing Overdiagnosis'. In addition, the results will serve as guidance for further research on this topic. PROSPERO REGISTRATION NUMBER: CRD42021244513.

Downstream activities after laboratory testing in primary care: an exploratory outcome of the ELMO cluster randomised trial (Electronic Laboratory Medicine Ordering with evidence-based order sets in primary care).

OBJECTIVE: To estimate the rate and type of downstream activities (DAs) after laboratory testing in primary care, with a specific focus on check-up laboratory panels, and to explore the effect of a clinical decision support system (CDSS) for laboratory ordering on these DAs. DESIGN: Cluster randomised clinical trial. SETTING: 72 primary care practices in Belgium, with 272 general practitioners (GPs), randomly assigned to the intervention arm or the control arm. PARTICIPANTS: The study included 10 270 lab panels from 9683 primary care patients (women 55.1%, mean age 56.5). All adult patients who consulted one of the participating GPs during the trial period and needed a laboratory exam were eligible for participation. INTERVENTIONS: GPs in the intervention group used a CDSS integrated into their online laboratory ordering system, while GPs in the control arm used their lab ordering system as usual. The trial duration was 6 months, with another 6 months follow-up. MAIN OUTCOME MEASURES: This publication reports on the exploratory outcome of DAs after an initial laboratory exam and the effect of the CDSS on these DAs. RESULTS: 19.7% of all laboratory panels resulted in further diagnostic procedures (95% CI 18.9% to 20.5%) and 19% (95% CI 18.2% to 19.7%) in treatment changes. Check-up laboratory exams showed similar rates of DAs, with 17.5% (95% CI 13.8% to 21.2%) diagnostic DAs and 18.9% (95% CI 13.9% to 23.9%) treatment changes. Using the CDSS resulted in a significant reduction in downstream referrals (-2.4%; 95% CI -4.2% to -0.6%; p=0008), imaging and endoscopies (-0.9%; 95% CI -1.6% to -0.1%; p=0026) and treatment changes (-5.4%; 95% CI -9.5% to -1.2%; p=0.01). CONCLUSION: This is the largest study so far to examine DAs after laboratory testing. It shows that almost one in three laboratory exams leads to further DAs, even in check-up panels. Using a CDSS for laboratory orders may reduce the rate of some DAs. TRIAL REGISTRATION NUMBER: NCT02950142.

Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial.

BACKGROUND: Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care. METHODS: This study was a pragmatic, cluster randomized, open-label, controlled clinical trial. SETTING: Two hundred eighty general practitioners (GPs) from 72 primary care practices in Belgium. PATIENTS: Patients aged ≥ 18 years with a laboratory test order for at least one of 17 indications: cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication. INTERVENTIONS: The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician. MEASUREMENTS: The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume, and cascade activities. RESULTS: CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16-0.26, p < 0.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37-10.93, p = 0.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease-0.05% increase) in possible diagnostic error. CONCLUSIONS: A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02950142 , registered on October 25, 2016.

Short communication: Subtyping of Staphylococcus haemolyticus isolates from milk and corresponding teat apices to verify the potential teat-skin origin of intramammary infections in dairy cows.

Coagulase-negative staphylococci (CNS) are a major cause of intramammary infections (IMI) in dairy cows and they colonize the teat skin. Staphylococcus haemolyticus, one of the more common CNS, has been identified as a highly versatile opportunistic species. The aim of the present study was to gain better insight into the adaptation of S. haemolyticus subtypes to the udder ecosystem with respect to IMI development. During a longitudinal observational study conducted over 13 mo on 6 Flemish dairy herds, S. haemolyticus isolates were recovered from milk and teat apices. A total of 44 S. haemolyticus isolates originating from milk (24 isolates) and teat apices (20 isolates) of 6 selected udder quarters were singled out and analyzed using a combined methodology of (GTG)5-PCR and amplified fragment length polymorphism (AFLP) fingerprinting to determine intraspecies differences. Combining both fingerprinting methods, 4 S. haemolyticus subtypes were obtained (I to IV). Subtypes I, II, and IV were recovered from both milk and teat apex samples and were found to be associated with persisting IMI. Subtype III, not apparently related to IMI, was isolated solely from teat apices and not from milk. In general, S. haemolyticus subtypes found in milk from infected quarters could be recovered from the corresponding teat apices, although the latter could be colonized with up to 3 different subtypes. Comparing subtypes from milk and teat apices indicates that the IMI-causing agent likely originates from the teat skin.

Further evidence for the existence of environmental and host-associated species of coagulase-negative staphylococci in dairy cattle.

Coagulase-negative staphylococci (CNS) are abundantly present in the dairy farm environment and on bovine skin and mucosae. They are also the most prevalent bacteria causing bovine intramammary infections (IMI). Reservoirs and transmission routes of CNS are not yet fully unraveled. The objectives of this study were to explore the distribution of CNS in parlor-related extramammary niches and to compare it to the distributions of CNS causing IMI in those herds. Niches that were targeted in this study were cows' teat apices, milking machine unit liners, and milker's skin or gloves. Each of the three herds had its own CNS microbiota in those niches. The most prevalent species in the parlor-related extramammary niches were Staphylococcus cohnii, S. fleurettii, and S. equorum in the first, second, and third herd, respectively, whereas S. haemolyticus and S. sciuri were found in all herds. S. cohnii and S. fleurettii, as well as S. haemolyticus, which was present in each herd, were also frequently found in milk samples. By contrast, S. chromogenes, S. simulans, and S. xylosus favored the mammary gland, whereas S. equorum was more common in the parlor-associated niches. Within each herd, species distribution was similar between teat apices and milking machine unit liners. In conclusion, some of the extramammary niches related to the milking process might act as infection sources for IMI-causing CNS. This study provides further evidence that the group of CNS species is comprised of environmental, opportunistic and host-adapted species which differ in ecology.

Staphylococcus agnetis sp. nov., a coagulase-variable species from bovine subclinical and mild clinical mastitis.

Thirteen Gram-positive-staining coagulase-variable staphylococci were isolated from subclinical and mild clinical mastitic bovine milk (n=12) and a teat apex (n=1). The results of sequence analysis of the 16S rRNA gene and two housekeeping genes, rpoB and tuf, and DNA fingerprinting with amplified fragment length polymorphism (AFLP) analysis showed that the isolates formed a separate branch within the genus Staphylococcus. The phylogenetically most closely related species were Staphylococcus hyicus and Staphylococcus chromogenes. DNA-DNA hybridization with S. hyicus DSM 20459(T) and S. chromogenes DSM 20674(T) confirmed that the isolates belonged to a separate species. The predominant fatty acids were i-C(15:0), ai-C(15:0), i-C(17:0) and C(20:0) and the peptidoglycan type was A3α L-Lys-Gly(5). Based on the results of genotypic and phenotypic analyses, it is proposed that the thirteen isolates represent a novel species, for which the name Staphylococcus agnetis sp. nov. is proposed. Strain 6-4(T) (=DSM 23656(T)=CCUG 59809(T)) is the type strain.

Validation of amplified fragment length polymorphism genotyping for species identification of bovine associated coagulase-negative staphylococci.

In many countries, coagulase-negative staphylococci (CNS) are currently the most common cause of intramammary infection in lactating cows. In order to elucidate the importance of various CNS species in udder health and milk quality, further research conducted on the species level is required. Phenotypic identification of CNS species appears to be unreliable and more accurate and reproducible genotypic methods are needed. In the current study, use of amplified fragment length polymorphism (AFLP) genotyping was validated for species identification of bovine associated CNS. An initial reference library was generated with AFLP fingerprints of 52 different CNS type and reference strains. Next, 247 bovine CNS field isolates with known species identity were analyzed. These field isolates had been previously identified by gene sequencing and were randomly divided into two subsets, i.e. a training set and a validation set. The training set was identified against the initial reference library containing only type and reference strains, which resulted in a typeability of 80.5%. Accuracy of the AFLP identifications, being the correspondence with gene sequencing results, was 95.0%. Fingerprints of the training set were then added to the initial library and identification of the validation set was done by means of this extended library. By adding bovine CNS to the library, performance of the AFLP identification method improved considerably. Final typeability and accuracy were 98.4% and 99.2%, respectively. Numerical analysis of AFLP fingerprints proves to be an accurate genotypic method for identification of CNS from bovine origin. The constructed AFLP library provides a useful identification tool for field studies on the subject of CNS.