Longterm prediction of failure after treatment of cervical precancer

Non peer reviewe

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier

The ANTENATAL multicentre study to predict postnatal renal outcome in fetuses with posterior urethral valves: objectives and design

Abstract Background Posterior urethral valves (PUV) account for 17% of paediatric end-stage renal disease. A major issue in the management of PUV is prenatal prediction of postnatal renal function. Fetal ultrasound and fetal urine biochemistry are currently employed for this prediction, but clearly lack precision. We previously developed a fetal urine peptide signature that predicted in utero with high precision postnatal renal function in fetuses with PUV. We describe here the objectives and design of the prospective international multicentre ANTENATAL (multicentre validation of a fetal urine peptidome-based classifier to predict postnatal renal function in posterior urethral valves) study, set up to validate this fetal urine peptide signature. Methods Participants will be PUV pregnancies enrolled from 2017 to 2021 and followed up until 2023 in >30 European centres endorsed and supported by European reference networks for rare urological disorders (ERN eUROGEN) and rare kidney diseases (ERN ERKNet). The endpoint will be renal/patient survival at 2 years postnatally. Assuming α = 0.05, 1–β = 0.8 and a mean prevalence of severe renal outcome in PUV individuals of 0.35, 400 patients need to be enrolled to validate the previously reported sensitivity and specificity of the peptide signature. Results In this largest multicentre study of antenatally detected PUV, we anticipate bringing a novel tool to the clinic. Based on urinary peptides and potentially amended in the future with additional omics traits, this tool will be able to precisely quantify postnatal renal survival in PUV pregnancies. The main limitation of the employed approach is the need for specialized equipment. Conclusions Accurate risk assessment in the prenatal period should strongly improve the management of fetuses with PUV

An innovative approach to investigate the dynamics of the cerebrospinal fluid in the prepontine cistern: A feasibility study using spatial saturation-prepared cine PC-MRI

Purposes: Accurate measurements of the cerebrospinal fluid that flows through the prepontine cistern (PPC) are challenging due to artefacts originating from basilar artery blood flow. We aim to accurately quantify cerebrospinal fluid (CSF) flow and stroke volume in the PPC, which is essential before endoscopic third ventriculostomy. Materials and methods: We developed a new PC-MRI sequence prepared with Hadamard saturation bands to accurately quantify CSF flow in the PPC by suppressing the blood signal in the surrounding vessels. In total, 28 adult hydrocephalic patients (age 59 ± 20 years) were scanned using conventional PC-MRI and our developed sequence. CSF was separately extracted from the PPC and the foramen of Magendie, and flow (min and max) and stroke volume were quantified. Results: Our modifications result in a complete deletion of signal from flowing blood, resulting in significantly reduced CSF stroke volume (Conv = 446 ± 113 mm3, Dev = 390 ± 119 mm3, p = 0.006) and flow, both minimum (Conv = −1630 ± 486 mm3/s, Dev = −1430 ± 406 mm3/s, p = 0.005) and maximum (Conv = 2384 ± 657 mm3/s, Dev = 1971 ± 62 mm3/s, p = 0.002) compared with the conventional sequence, whereas no change in the area of interest was noted (Conv = 236 ± 65 mm2, Dev = 249 ± 75 mm2, p = 0.21). Conclusions: Accurate and reproducible CSF flow and stroke volume measurements in the PPC can be achieved with sat-band prepared cine PC-MRI

Impact of anaesthesia mode on evaluation of LEEP specimen dimensions.

&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;To study the influence of anaesthesia (local by cervical block vs. general or spinal anaesthesia) on height and volume of resection specimens in case of conization treatment for cervical intraepithelial neoplasia (CIN).&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Prospective observational study of all patients who underwent a first treatment by loop electrosurgical excision procedure (LEEP) for CIN. Height of fresh resection specimens was first measured by the operator and then by the pathologist after formaldehyde fixation. Volume of fresh specimens was measured in a measuring cylinder by fluid displacement.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;One hundred patients were included and 35% of LEEP were performed under local anaesthesia. There was a significant difference in height of specimens depending on anaesthesia mode: after fixation, the average height was 11.2mm in the general or spinal anaesthesia group vs. 8.8mm in the local anaesthesia group (P=0.002). There was also a difference in terms of volume depending on anaesthesia mode: 1.6mL in local anaesthesia group vs. 2.3mm in general and spinal anaesthesia group (P=0.01).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Anaesthesia mode has an impact on height and volume of LEEP specimens. In our experience, local anaesthesia could reduce LEEP specimen height.&lt;/p&gt;</p