Rapid, simple multi-locus variable number tandem repeat analysis: a reliable tool for Klebsiella pneumoniae outbreak screening.

BACKGROUND: Klebsiella pneumoniae causing nosocomial infections is increasingly multi-drug-resistant. Rapid and efficient typing tools are required for monitoring. AIM: To assess a simple, rapid (<5 h) multiplex polymerase chain reaction method based on multi-locus variable number tandem repeat analysis (MLVA) as a screening tool to determine whether or not K. pneumoniae strains are related. METHODS: The global discriminatory power of the method was assessed on 72 unrelated K. pneumoniae isolates, including community carriage isolates, highly virulent strains causing liver abscess, and extended-spectrum beta-lactamase- and carbapenemase-producing strains. Suspected related strains from a suspected outbreak and a relapsed meningitis case were also studied. MLVA results were compared with whole-genome sequencing (WGS) analysis and multi-locus sequence typing (MLST). FINDINGS: MLVA and MLST had similar discriminatory power, each distinguishing 54 profiles among the 72 unrelated isolates (Hunter-Gaston index 0.989). Each strain belonging to one sequence type (ST) or ST complex had its own MLVA type, with few exceptions. Two strains of ST268 and ST1119 shared the same MLVA profile, and two unrelated strains of ST307, ST86, ST45 and ST37 exhibited two different MLVA types each. Moreover, investigation of seven grouped cases of K. pneumoniae neonatal sepsis pointed to strong suspicion of a common source for five isolates, while two isolates with a different MLVA profile were excluded from this cluster. CONCLUSION: The MLVA approach is a useful, rapid and reliable tool for epidemiological investigation requiring only basic molecular biology equipment, and permits identification of sporadic isolates that are not part of an outbreak. However, analysis of strains sharing the same MLVA type by a highly discriminatory technique, such as WGS, remains necessary.

Impact of the healthcare reorganization of the Local Health Authority services in Rieti (Italy) during the SARS-CoV-2 pandemic.

Background: The need to contain the spread of the SARS-CoV-2 pandemic has forced national and local organizations to define and implement targeted emergency response and management measures. As the knowledge about the infection grew, a wider range of organizational measures were deployed. Methods: This study involves the SARS-CoV-2 infected people managed by the Local Health Authority of Rieti (Italy). Diagnostic test waiting times and hospital admission rates in the Province of Rieti are investigated as the pandemic evolved. Trends were analyzed in relation to the tempora spreading of SARS-CoV-2, to the organizational actions taken by the Local Health Authority of Rieti, and to the deployment of actions across the territory. A municipalities classification of the province of Rieti was conducted after a cluster analysis based on the diagnostic test waiting times and the hospital admission rates. Results: Our findings show a declining trend, thus indicating a possible positive effect of the measures taken to contain the pandemic. The cluster analysis of the municipalities of the Province of Rieti makes evident an inhomogeneous geographical distribution of examined parameters (diagnostic test waiting times and the hospital admission rates), demonstrating the capability of Local Health Authority of Rieti to reach even the most disadvantaged areas and implying that the differences are due to the demographical variabilities. Conclusion: Despite some limitations, this study outlines the importance of management measures in response of the pandemic. These measures should adapt to social, cultural and geographical nature of the territory involved. The findings of the present study will contribute to the update of further pandemic preparedness plans of the Local Health Authorities.

Epidemiological investigation of Pseudomonas aeruginosa isolates including multidrug-resistant serogroup O12 isolates, by use of a rapid and simplified multiple-locus variable-number of tandem repeats analysis and whole genome sequencing.

BACKGROUND: Clustered cases of Pseudomonas aeruginosa infection in immunocompromised patients' wards require rapid characterization of a potential epidemic to guide investigations and identify the potential source of contamination. AIM: To design and evaluate a rapid and simple typing method for P. aeruginosa in comparison to whole genome sequencing (WGS). METHODS: A simplified polymerase chain reaction based on multiple-locus variable-number of tandem repeats analysis (MLVA) was designed and used to investigate cases of P. aeruginosa infection and colonization in a paediatric haematology department. The method was compared to WGS by using the Illumina method. FINDINGS: On the 17 isolates recovered from 15 children (eight from blood cultures, three from urinary tract infections, one from sputum and five stool isolates), MLVA distinguished 10 different profiles, and seven isolates from six children shared the same profile. Analysis by WGS revealed that these seven isolates belonged to sequence type ST111 and serotype O12, allowing at least three different genotypes to be distinguished among them. Five environmental strains had three MLVA profiles; one was shared with a clinical isolate but WGS excluded any relationship. CONCLUSION: The simplified and inexpensive MLVA method enabled the exclusion, in less than 5 h, of most of the unrelated isolates and thus to focus investigations on a small number of cases, whereas WGS, taking several days of work, drew definitive conclusions concerning the outbreak and the genetic relationships of the ST111 isolates circulating in the department. We conclude that sequential use of both methods is the optimal strategy to investigate clustered cases of P. aeruginosa infections.

Chronic urticaria and thyroid autoimmunity: a meta-analysis of case-control studies.

PURPOSE: Autoimmunity has been implicated in some patients with idiopathic chronic urticaria (CU). Because of the frequency of autoimmune thyroid diseases, their association with CU deserves special attention. We tested both the existence and the extent of an association between thyroid autoimmunity and CU. METHODS: A thorough search of PubMed, Scopus, Web of Science, and Cochrane databases was performed. Studies reporting the positivity rate for anti-thyroperoxidase antibodies (TPOAbs) in people with (cases) and without CU (controls) were included. Quality of the studies was assessed by the Newcastle-Ottawa Scale. Between-study heterogeneity was assessed by Cochrane Q and I2 tests, and the odds ratio (OR) for TPOAbs positivity was combined using random-effects models. RESULTS: Nineteen studies provided information about TPOAbs positivity on 14,351 patients with CU and 12,404 controls. The pooled estimate indicated a more than fivefold increased risk of exhibiting TPOAbs positivity in the group with CU (pooled OR 5.18, 95% CI 3.27, 8.22; P < 0.00001). Correction for publication bias had a negligible effect on the overall estimate (pooled adjusted OR: 4.42, 95% CI 2.84, 6.87, P < 0.0001). Between­study heterogeneity was established (I2 = 62%, Pfor heterogeneity = 0.0002) and when, according to meta­regression models, a sensitivity analysis was restricted to the 16 studies with the highest quality scores, the OR for TPOAbs positivity rose to 6.72 (95% CI 4.56, 9.89; P < 0.00001) with no significant heterogeneity (I2 = 31%, Pfor heterogeneity = 0.11). CONCLUSIONS: Patients with CU have a five-to-nearly sevenfold higher risk of displaying TPOAbs positivity. All patients with CU may well be offered a screening for thyroid autoimmunity.

The impact of COVID-19 pandemic on emergency services.

BACKGROUND: The SARS-Cov-2 pandemic has placed enormous strain on the global healthcare system. The strict containment measures have adversely affected population movements and mobility, daily activities, and the patterns of healthcare-seeking behavior. Although the Emergency and Admission Departments (EADS) activity has never been disrupted, the pandemic had a significant impact on the routine healthcare delivery. This study aims to assess the changes in healthcare delivery, with a focus on the elderly as a vulnerable component of the general population. DESIGN OF THE STUDY: Retrospective study. METHODS: All non-COVID visits to the EAD of the Local Health Unit (ASL1) in Abruzzo (Italy) from 9 March to 3 May 2020 were analyzed. These were compared to the hospital admissions recorded in the same period of the previous year. RESULTS: We found a 60.4% reduction in overall visits during the study period and an increase in the hospitalization rate from 30% to 39%. Emergency department visits have declined markedly for less acute medical conditions, while we have observed a statistically significant increase in the hospitalization rates for all age groups. Moreover, in 2020 we recorded a decrease in the ratio non-urgent/non-deferrable medical conditions for each age group; while the percentage of hospitalizations for each registered red code increased for each group, particularly for the 65-74 age group. CONCLUSIONS: The COVID-19 pandemic has significantly affected the care-seeking behavior of patients. During the COVID-19 epidemic, total hospital admissions have decreased, particularly for less severe illnesses, whereas the percentage of hospitalizations has increased. During 2020, hospital admissions for mild cases decreased, and patients presented to the EAD only in cases of acute medical condition, selecting those in need for more intensive care. However, several patients may have deferred necessary medical care even for potentially urgent conditions. Such reluctance to seek medical care may have caused delays in diagnosis. The impact of deferred care on patients' health is difficult to estimate at this time. This information will serve as a starting point for further research to improve healthcare management not only during emergency but also in non-emergency periods.

Interlaboratory evaluation of Mucorales PCR assays for testing serum specimens: A study by the fungal PCR Initiative and the Modimucor study group.

Interlaboratory evaluations of Mucorales qPCR assays were developed to assess the reproducibility and performance of methods currently used. The participants comprised 12 laboratories from French university hospitals (nine of them participating in the Modimucor study) and 11 laboratories participating in the Fungal PCR Initiative. For panel 1, three sera were each spiked with DNA from three different species (Rhizomucor pusillus, Lichtheimia corymbifera, Rhizopus oryzae). For panel 2, six sera with three concentrations of R. pusillus and L. corymbifera (1, 10, and 100 genomes/ml) were prepared. Each panel included a blind negative-control serum. A form was distributed with each panel to collect results and required technical information, including DNA extraction method, sample volume used, DNA elution volume, qPCR method, qPCR template input volume, qPCR total reaction volume, qPCR platform, and qPCR reagents used. For panel 1, assessing 18 different protocols, qualitative results (positive or negative) were correct in 97% of cases (70/72). A very low interlaboratory variability in Cq values (SD = 1.89 cycles) were observed. For panel 2 assessing 26 different protocols, the detection rates were high (77-100%) for 5/6 of spiked serum. There was a significant association between the qPCR platform and performance. However, certain technical steps and optimal combinations of factors may also impact performance. The good reproducibility and performance demonstrated in this study support the use of Mucorales qPCR as part of the diagnostic strategy for mucormycosis.

Restricted ROC curves are useful tools to evaluate the performance of tumour markers.

In Clinical Epidemiology, receiver operating characteristic (ROC) analysis is a standard approach for the evaluation of the performance of diagnostic tests for binary classification based on a tumour marker distribution. The area under a ROC curve is a popular indicator of test accuracy, but its use has been questioned when the curve is asymmetric. This situation often happens when the marker concentrations overlap in the two groups under study in the range of low specificity, corresponding to a subset of values useless for classification purposes (non-informative values). The partial area under the curve at a high specificity threshold has been proposed as an alternative, but a method to identify an optimal cut-off that separates informative from non-informative values is not yet available. In this study, a new statistical approach is proposed to perform this task. Furthermore, a statistical test associated with the area under a ROC curve corresponding to informative values only (restricted ROC curve) is provided and its properties are explored by extensive simulations. Finally, the proposed method is applied to a real data set containing peripheral blood levels of six tumour markers proposed for the diagnosis of neuroblastoma. A new approach to combine couples of markers for classification purposes is also illustrated.

Molecular identification of Mucorales in human tissues: contribution of PCR electrospray-ionization mass spectrometry.

Molecular methods are crucial for mucormycosis diagnosis because cultures are frequently negative, even if microscopy suggests the presence of hyphae in tissues. We assessed PCR/electrospray-ionization mass spectrometry (PCR/ESI-MS) for Mucorales identification in 19 unfixed tissue samples from 13 patients with proven or probable mucormycosis and compared the results with culture, quantitative real-time PCR, 16S-23S rRNA gene internal transcribed spacer region (ITS PCR) and 18S PCR sequencing. Concordance with culture identification to both genus and species levels was higher for PCR/ESI-MS than for the other techniques. Thus, PCR/ESI-MS is suitable for Mucorales identification, within 6 hours, for tissue samples for which microscopy results suggest the presence of hyphae.

Hamming clustering techniques for the identification of prognostic indices in patients with advanced head and neck cancer treated with radiation therapy.

The aim of the study is to demonstrate the usefulness of a new, non-linear classifier method, called Hamming clustering (HC), in selecting prognostic variables affecting overall survival in patients with head and neck cancer. In particular, the aim is to identify whether tumour proliferation parameters can be predictive factors of response in a set of 115 patients that receive either alternating chemo-radiotherapy or accelerated or conventional radiotherapy. HC is able to generate a set of understandable rules underlying the study objective; it can also select a subset of input variables that represent good prognostic factors. HC has been compared with other standard classifiers, providing better results in terms of classification accuracy. In particular, HC obtains the best accuracy of 74.8% (sensitivity of 51.1% and specificity of 91.2%) about survival. The rules found show that, besides the classical, well-known variables concerning the tumour dimension and the involved lymphonodes, some biological parameters, such as DNA ploidy, are also useful as predictive factors.

On convergence properties of pocket algorithm.

The problem of finding optimal weights for a single threshold neuron starting from a general training set is considered. Among the variety of possible learning techniques, the pocket algorithm has a proper convergence theorem which asserts its optimality. However, the original proof ensures the asymptotic achievement of an optimal weight vector only if the inputs in the training set are integer or rational. This limitation is overcome in this paper by introducing a different approach that leads to the general result. Furthermore, a modified version of the learning method considered, called pocket algorithm with ratchet, is shown to obtain an optimal configuration within a finite number of iterations independently of the given training set.

Hamming-Clustering method for signals prediction in 5' and 3' regions of eukaryotic genes.

MOTIVATION: Gene expression is regulated by different kinds of short nucleotide domains. These features can either activate or terminate the transcription process. To predict the signal sites in the 5' and 3' gene regions we applied the Hamming-Clustering network (HC) to the TATA box, to the transcription initiation site and to the poly(A) signal determination in DNA sequences. This approach employs a technique deriving from the synthesis of digital networks in order to generate prototypes, or rules, which can be directly analysed or used for the construction of a final neural network. RESULTS: More than 1000 poly-A signals have been extracted from EMBL database rel. 42 and used to build the training and the test set. A full set of the eukaryotic genes (1252 entry) from the Eukaryotic Promoter Database (EPD rel. 42) have been used for the TATA-box signal and transcription network approach. The results show the applicability of the Hamming-Clustering method to functional signal prediction.

On sequential construction of binary neural networks.

A new technique called sequential window learning (SWL), for the construction of two-layer perceptrons with binary inputs is presented. It generates the number of hidden neurons together with the correct values for the weights, starting from any binary training set. The introduction of a new type of neuron, having a window-shaped activation function, considerably increases the convergence speed and the compactness of resulting networks. Furthermore, a preprocessing technique, called hamming clustering (HC), is proposed for improving the generalization ability of constructive algorithms for binary feedforward neural networks. Its insertion in the sequential window learning is straightforward. Tests on classical benchmarks show the good performances of the proposed techniques, both in terms of network complexity and recognition accuracy.