Evaluation of screening algorithms to detect rectal colonization with carbapenemase-producing Enterobacterales in a resource-limited setting.

Objectives: To improve and rationalize the detection of carbapenemase-producing Enterobacterales (CPE) in rectal swabs in a high-prevalence and resource-constrained setting, addressing surveillance challenges typically encountered in laboratories with limited resources. Methods: A point prevalence survey (PPS) was conducted on 15 August 2022, in a provincial children's hospital in northern Vietnam. Rectal swab samples of all admitted children were collected and plated on a selective medium for carbapenem-resistant Enterobacterales (CRE). Species identification and antimicrobial susceptibility testing (AST) were performed by MALDI-TOF, and VITEK2 XL and interpreted according to CLSI breakpoints (2022). Carbapenemases were detected by the carbapenem inactivation method (CIM) and quantitative real-time PCR (qRT-PCR). Results: Rectal swab samples were obtained from 376 patients. Of 178 isolates growing on the CRE screening agar, 140 isolates were confirmed as Enterobacterales of which 118 (84.3%) isolates were resistant to meropenem and/or ertapenem. CIM and PCR showed that 90/118 (76.3%) were carbapenemase producers. Overall, 83/367 (22.6%) were colonized by CPE. Klebsiella pneumoniae, Escherichia coli and Enterobacter cloacae complex were the most common CPE detected, with NDM as the predominant carbapenemase (78/90; 86.7%). Phenotypic resistance to meropenem was the best predictor of CPE production (sensitivity 85.6%, specificity 100%) compared with ertapenem resistance (95.6% sensitivity, 36% specificity). CIM was 100% concordant with PCR in detecting carbapenemases. Conclusions: These findings underscore the effectiveness of meropenem resistance as a robust indicator of the production of carbapenemases and the reliability of the CIM method to detect such carbapenemases in resource-limited settings where the performance of molecular methods is not possible.

Tweedie Compound Poisson Models with Covariate-Dependent Random Effects for Multilevel Semicontinuous Data.

Multilevel semicontinuous data occur frequently in medical, environmental, insurance and financial studies. Such data are often measured with covariates at different levels; however, these data have traditionally been modelled with covariate-independent random effects. Ignoring dependence of cluster-specific random effects and cluster-specific covariates in these traditional approaches may lead to ecological fallacy and result in misleading results. In this paper, we propose Tweedie compound Poisson model with covariate-dependent random effects to analyze multilevel semicontinuous data where covariates at different levels are incorporated at relevant levels. The estimation of our models has been developed based on the orthodox best linear unbiased predictor of random effect. Explicit expressions of random effects predictors facilitate computation and interpretation of our models. Our approach is illustrated through the analysis of the basic symptoms inventory study data where 409 adolescents from 269 families were observed at varying number of times from 1 to 17 times. The performance of the proposed methodology was also examined through the simulation studies.

End-tidal CO2 in the diagnosis of fluid responsiveness - a systematic review.

INTRODUCTION: An indication of the adequacy of the intra-vascular volume is of importance in critically ill patients. The status of the intravascular volume can be determined from a fluid challenge test. Most tests involve invasive monitoring. An exception is the capnographic measurement of changes in end-tidal (ET) CO2 after a fluid challenge. The method is appealing as it rests on solid physiological ground - the Fick principle and the Frank-Starling mechanism. Furthermore, it is non-invasive and convenient. We report the results of a systematic review of the merits of this method. METHODS: After a registration with PROSPERO, we searched MEDLINE, EMBASE, the Cochrane Library database and trial registers for studies on the diagnostic accuracy of changes in ET-CO2 in fluid responsiveness testing. Test sensitivity, specificity and area under the receiver operating charac-teristics curve (AUROC) were the primary outcome meas-ures. RESULTS: Seven papers met the inclusion criteria. The test was found to have a median sensitivity of 0.75 (range: 0.60-0.91) and a median specificity of 0.94 (range: 0.70-1.00). The median AUROC was 0.82 (range: 0.67-0.94); the diagnostic threshold was an increase in ET-CO2 of 2 mmHg/5%. CONCLUSIONS: Monitoring of ET-CO2 during fluid responsiveness testing provides good diagnostic value with few false negative tests and fewer false positive tests. The included studies have important methodological flaws. It must therefore be acknowledged that the diagnostic value of ET-CO2 monitoring found in the review is overrated and overrated to an unknown degree. Therefore, at the present state of affairs, implementation of the test cannot be considered evidence-based.

Taylor's power law and fluctuation scaling explained by a central-limit-like convergence.

A power function relationship observed between the variance and the mean of many types of biological and physical systems has generated much debate as to its origins. This Taylor's law (or fluctuation scaling) has been recently hypothesized to result from the second law of thermodynamics and the behavior of the density of states. This hypothesis is predicated on physical quantities like free energy and an external field; the correspondence of these quantities with biological systems, though, remains unproven. Questions can be posed as to the applicability of this hypothesis to the diversity of observed phenomena as well as the range of spatial and temporal scales observed with Taylor's law. We note that the cumulant generating functions derived from this thermodynamic model correspond to those derived over a quarter century earlier for a class of probabilistic models known as the Tweedie exponential dispersion models. These latter models are characterized by variance-to-mean power functions; their phenomenological basis rests with a central-limit-theorem-like property that causes many statistical systems to converge mathematically toward a Tweedie form. We review evaluations of the Tweedie Poisson-gamma model for Taylor's law and provide three further cases to test: the clustering of single nucleotide polymorphisms (SNPs) within the horse chromosome 1, the clustering of genes within human chromosome 8, and the Mertens function. This latter case is a number theoretic function for which a thermodynamic model cannot explain Taylor's law, but where Tweedie convergence remains applicable. The Tweedie models are applicable to diverse biological, physical, and mathematical phenomena that express power variance functions over a wide range of measurement scales; they provide a probabilistic description for Taylor's law that allows mechanistic insight into complex systems without the assumption of a thermodynamic mechanism.

Tweedie convergence: a mathematical basis for Taylor's power law, 1/f noise, and multifractality.

Plants and animals of a given species tend to cluster within their habitats in accordance with a power function between their mean density and the variance. This relationship, Taylor's power law, has been variously explained by ecologists in terms of animal behavior, interspecies interactions, demographic effects, etc., all without consensus. Taylor's law also manifests within a wide range of other biological and physical processes, sometimes being referred to as fluctuation scaling and attributed to effects of the second law of thermodynamics. 1/f noise refers to power spectra that have an approximately inverse dependence on frequency. Like Taylor's law these spectra manifest from a wide range of biological and physical processes, without general agreement as to cause. One contemporary paradigm for 1/f noise has been based on the physics of self-organized criticality. We show here that Taylor's law (when derived from sequential data using the method of expanding bins) implies 1/f noise, and that both phenomena can be explained by a central limit-like effect that establishes the class of Tweedie exponential dispersion models as foci for this convergence. These Tweedie models are probabilistic models characterized by closure under additive and reproductive convolution as well as under scale transformation, and consequently manifest a variance to mean power function. We provide examples of Taylor's law, 1/f noise, and multifractality within the eigenvalue deviations of the Gaussian unitary and orthogonal ensembles, and show that these deviations conform to the Tweedie compound Poisson distribution. The Tweedie convergence theorem provides a unified mathematical explanation for the origin of Taylor's law and 1/f noise applicable to a wide range of biological, physical, and mathematical processes, as well as to multifractality.

Analysis of functional abilities for elderly Danish twins using GEE models.

In this work we present a new method for genetic analysis of twin data which is based on generalized estimating equations and allows for analysis of various response types (e.g., continuous, binary, counts) combined with estimation of residual correlations. The new approach allows for control of covariates of any kind (e.g., continuous, counts) by modeling the dependence of mean and variance on background variables. The proposed method was applied to identify the covariates that have a significant influence on elderly people's functional abilities, and find the estimates for the correlation coefficients of residuals for MZ and DZ twins in a sample of 2401 Danish twin 75 years of age or older. The bootstrap method was used to obtain standard errors for correlation coefficients. It was shown, that the chosen covariates have similar effects on MZ and DZ twins, and that the residual correlation in MZ twins is significantly higher than in DZ twins, which indicates that genetic factors play an etiological role in the determination of physical status of elderly people, controlled for 10 background variables.

A longitudinal study of mortality and air pollution for São Paulo, Brazil.

We study the effects of various air-pollution variables on the daily death counts for people over 65 years in São Paulo, Brazil, from 1991 to 1993, controlling for meteorological variables. We use a state space model where the air-pollution variables enter via the latent process, and the meteorological variables via the observation equation. The latent process represents the potential mortality due to air pollution, and is estimated by Kalman filter techniques. The effect of air pollution on mortality is found to be a function of the variation in the sulphur dioxide level for the previous 3 days, whereas the other air-pollution variables (total suspended particulates, nitrogen dioxide, carbon monoxide, ozone) are not significant when sulphur dioxide is in the equation. There are significant effects of humidity and up to lag 3 of temperature, and a significant seasonal variation.

Regular interval preventive pain relief compared with on demand treatment after hysterectomy.

Eighty otherwise healthy women, aged 22-64 years, admitted for elective hysterectomy were studied in a prospective randomized trial. The aim was to compare two different postoperative pain relief schedules--one with the analgesic given at regular intervals and the other with the analgesic given on demand. All the patients had a neuroleptanaesthesia with fentanyl. Forty patients received an initial dose of buprenorphine 0.3 mg intravenously before termination of anaesthesia and continued with sublingual buprenorphine 0.4 mg 6 hourly postoperatively (regular interval (RI) group). Forty patients received the standard postoperative medication, meperidine 1 mg/kg on demand in the recovery room, followed by ketobemidone 5 mg subcutaneously on demand in the surgical ward (on demand (OD) group). There was no difference between groups concerning pain relief following a single dose of analgesic (P greater than 0.05, type II error 1-5%). In the recovery room 17.5% of the patients in the RI group received an analgesic compared to 87.5% in the OD group (P less than 0.05). Among patients in the RI group who had previously got injections for postoperative pain relief on demand 95% preferred regular interval sublingual buprenorphine for future treatment. The nurses found that 90% of the patients in the RI group were treated adequately compared to 62.5% of the patients in the OD group (P less than 0.05). It is concluded, that regular interval preventive pain relief is superior to conventional on demand analgesic therapy in postoperative pain.