Search

Introduction Abdominoperineal resections performed for anorectal tumours leave a large pelvic and perineal defect causing a high rate of morbidity of the perineal wound (40%–60%). Biological meshes offer possibilities for new standards of perineal wound reconstruction. Perineal fillings with biological mesh are expected to increase quality of life by reducing perineal morbidity.Methods and analysis This is a multicentre, randomised and single-blinded study with a blinded endpoint evaluation, the experimental arm of which uses a biological mesh and the control arm of which is defined by the primary closure after abdominoperineal resection for cancer. Patients eligible for inclusion are patients with a proven history of rectal adenocarcinoma and anal canal epidermoid carcinoma for whom abdominoperineal resection was indicated after a multidisciplinary team discussion. All patients must have social security insurance or equivalent social protection. The main objective is to assess the incremental cost–utility ratio (ICUR) of two strategies of perineal closure after an abdominoperineal resection performed for anorectal cancer treatment: perineal filling with biological mesh versus primary perineal closure (70 patient in each arm). The secondary objectives focus on quality of life and morbidity data during a 1-year follow-up. Deterministic and probabilistic sensitivity analyses will be performed in order to estimate the uncertainty surrounding the ICUR. CIs will be constructed using the non-parametric bootstrap approach. A cost-effectiveness acceptability curve will be built so as to estimate the probability of efficiency of the biological meshes given a collective willingness-to-pay threshold.Ethics and dissemination The study was approved by the Regional Ethical Review Board of ‘Nord Ouest 1’ (protocol reference number: 20.05.14.60714; national number: 2020-A01169-30).The results will be disseminated through conventional scientific channels.Trial registration number ClinicalTrials.gov Registry (NCT02841293).

Pediatric neurological injury and disease is a critical public health issue due to increasing rates of survival from primary injuries (e.g., cardiac arrest, traumatic brain injury) and a lack of monitoring technologies and therapeutics for treatment of secondary neurological injury. Translational, preclinical research facilitates the development of solutions to address this growing issue but is hindered by a lack of available data frameworks and standards for the management, processing, and analysis of multimodal datasets. Here, we present a generalizable data framework that was implemented for large animal research at the Children's Hospital of Philadelphia to address this technological gap. The presented framework culminates in a custom, interactive dashboard for exploratory analysis and filtered dataset download. Compared with existing clinical and preclinical data management solutions, the presented framework better enables management of various data types (single measure, repeated measures, time series, and imaging), integration of datasets for comparison across experimental models, cohorts, and groups, and facilitation of predictive modeling from integrated datasets. Further, a predictive model development use case demonstrated utilization and value of the data framework. The general outline of a preclinical data framework presented here can serve as a template for other translational research labs that generate heterogeneous datasets and require a dynamic platform that can easily evolve alongside their research., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Cardiopulmonary bypass (CPB) provides cerebral oxygenation and blood flow (CBF) during neonatal congenital heart surgery, but the impacts of CPB on brain oxygen supply and metabolic demands are generally unknown. To elucidate this physiology, we used diffuse correlation spectroscopy and frequency-domain diffuse optical spectroscopy to continuously measure CBF, oxygen extraction fraction (OEF), and oxygen metabolism (CMRO 2 ) in 27 neonatal swine before, during, and up to 24 h after CPB. Concurrently, we sampled cerebral microdialysis biomarkers of metabolic distress (lactate-pyruvate ratio) and injury (glycerol). We applied a novel theoretical approach to correct for hematocrit variation during optical quantification of CBF in vivo. Without correction, a mean (95% CI) +53% (42, 63) increase in hematocrit resulted in a physiologically improbable +58% (27, 90) increase in CMRO 2 relative to baseline at CPB initiation; following correction, CMRO 2 did not differ from baseline at this timepoint. After CPB initiation, OEF increased but CBF and CMRO 2 decreased with CPB time; these temporal trends persisted for 0-8 h following CPB and coincided with a 48% (7, 90) elevation of glycerol. The temporal trends and glycerol elevation resolved by 8-24 h. The hematocrit correction improved quantification of cerebral physiologic trends that precede and coincide with neurological injury following CPB.

Monitoring physiological waveforms, specifically hemodynamic variables (e.g., blood pressure waveforms) and end-tidal CO 2 (EtCO 2 ), during pediatric cardiopulmonary resuscitation (CPR) has been demonstrated to improve survival rates and outcomes when compared to standard depth-guided CPR. However, waveform guidance has largely been based on thresholds for single parameters and therefore does not leverage all the information contained in multimodal data. We hypothesize that the combination of multimodal physiological features improves the prediction of the return of spontaneous circulation (ROSC), the clinical indicator of short-term CPR success. We used machine learning algorithms to evaluate features extracted from eight low-resolution (4 samples per minute) physiological waveforms to predict ROSC. The waveforms were acquired from the 2nd to 10th minute of CPR in pediatric swine models of cardiac arrest (N = 89, 8-12 kg). The waveforms were divided into segments with increasing length (both forward and backward) for feature extraction, and machine learning algorithms were trained for ROSC prediction. For the full CPR period (2nd to 10th minute), the area under the receiver operating characteristics curve (AUC) was 0.93 (95% CI: 0.87-0.99) for the multivariate model, 0.70 (0.55-0.85) for EtCO 2 and 0.80 (0.67-0.93) for coronary perfusion pressure. The best prediction performances were achieved when the period from the 6th to the 10th minute was included. Poor predictions were observed for some individual waveforms, e.g., right atrial pressure. In conclusion, multimodal waveform features carry relevant information for ROSC prediction. Using multimodal waveform features in CPR guidance has the potential to improve resuscitation success and reduce mortality.

Objectives: Recent research suggests that increased cerebral oxygen use during surgical intervention for neonates with congenital heart disease may play a role in the development of postoperative white matter injury. The objective of this study is to determine whether increased cerebral electrical activity correlates with greater decrease of cerebral oxygen saturation during deep hypothermic circulatory arrest., Methods: Neonates with critical congenital heart disease requiring surgical intervention during the first week of life were studied. All subjects had continuous neuromonitoring with electroencephalography and an optical probe (to quantify cerebral oxygen saturation) during cardiac surgical repair that involved the use of cardiopulmonary bypass and deep hypothermic circulatory arrest. A simple linear regression was used to investigate the association between electroencephalography metrics before the deep hypothermic circulatory arrest period and the change in cerebral oxygen saturation during the deep hypothermic circulatory arrest period., Results: Sixteen neonates had both neuromonitoring modalities attached during surgical repair. Cerebral oxygen saturation data from 5 subjects were excluded due to poor data quality, yielding a total sample of 11 neonates. A simple linear regression model found that the presence of electroencephalography activity at the end of cooling is positively associated with the decrease in cerebral oxygen saturation that occurs during deep hypothermic circulatory arrest ( P  < .05)., Conclusions: Electroencephalography characteristics within 5 minutes before the initiation of deep hypothermic circulatory arrest may be useful in predicting the decrease in cerebral oxygen saturation that occurs during deep hypothermic circulatory arrest. Electroencephalography may be an important tool for guiding cooling and the initiation of circulatory arrest to potentially decrease the prevalence of new white matter injury in neonates with critical congenital heart disease., (© 2023 The Author(s).)

The resistance of some penicillins to beta-lactamase enzymes was previously attributed to the nature of their C(6) side chain. In order to find explicitly the influence of the conformation of this side chain in the enzymatic mechanism, we have analyzed by experimental and theoretical methods (X-ray diffraction, NMR, IR, PCILO) the molecular structure of six resistant penicillins and derivatives: oxacillin, cloxacillin, dicloxacillin, flucloxacillin, methicillin, nafcillin, cloxacillin sulfoxide, and oxacillinpenicilloic acid. X-ray crystallography of flucloxacillin and nafcillin is fully described. We observe that the side chains of these penicillins have no influence on the electronic properties of the penam nucleus but are much more rigid than in the sensitive ones. The molecular conformations are mostly governed by the nonbonded Van der Waals interactions and, in the oxacillins, partly by the conjugation between exocyclic groups. The lack of flexibility could result in a distorting effect on the structure of the active site of the beta-lactamase, leading to the deactivation of the enzyme.