Cerebroplacental ratio in predicting adverse perinatal outcome : a meta-analysis of individual participant data

Acknowledgement We would like thank Dr F. Figueras, Prof. E. Gratacos, Dr F. Crispi and Dr J. Miranda for sharing data for this project. The CPR IPD Study Group: Asma Khalil (Fetal Medi- cine Unit, St George’s Hospital Medical School and St George’s University of London, London, UK; Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of London, Lon- don, UK), Basky Thilaganathan (Fetal Medicine Unit, St George’s Hospital Medical School and St George’s Univer- sity of London, London, UK; Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of London, London, UK), Ozhan M Turan (Departments of Obstetrics, Gynecology and Repro- ductive Sciences, University of Maryland School of Medi- cine, Baltimore, MD, USA), Sarah Crimmins (Departments of Obstetrics, Gynecology and Reproductive Sciences, University of Maryland School of Medicine, Baltimore, MD, USA), Chris Harman (Departments of Obstetrics, Gynecology and Reproductive Sciences, University of Maryland School of Medicine, Baltimore, MD, USA), Alis- son M Shannon (Departments of Obstetrics, Gynecology and Reproductive Sciences, University of Maryland School of Medicine, Baltimore, MD, USA), Sailesh Kumar (School of Medicine, The University of Queensland, Brisbane, QLD, Australia; Mater Research Institute – University of Queensland, South Brisbane, QLD, Australia), Patrick Dicker (Department of Epidemiology and Public Health, Royal College of Surgeons in Ireland), Fergal Malone (Departments of Obstetrics and Gynaecology, Royal College of Surgeons in Ireland), Elizabeth C Tully (Departments of Obstetrics and Gynaecology, Royal College of Surgeons in Ireland), Julia Unterscheider (Department of Maternal Fetal Medicine, The Royal Women’s Hospital, Melbourne, VIC, Australia), Isabella Crippa (Department of Obstetrics and Gynaecology, University of Milano-Bicocca, Monza, Italy), Alessandro Ghidini (Department of Obstetrics and Gynae- cology, University of Milano-Bicocca, Monza, Italy), Nadia Roncaglia (Department of Obstetrics and Gynaecology, University of Milano-Bicocca, Monza, Italy), Patrizia Ver- gani (Department of Obstetrics and Gynaecology, Univer- sity of Milano-Bicocca, Monza, Italy), Amarnath Bhide (Fetal Medicine Unit, St George’s Hospital Medical School and St George’s University of London, London, UK), Fran- cesco D’Antonio (Fetal Medicine Unit, St George’s Hospital Medical School and St George’s University of London, London, UK), Gianluigi Pilu (Policlinico S. Orsola-Mal- pighi, University of Bologna, Bologna, Italy), Alberto Galindo (Fetal Medicine Unit-SAMID, Department of Obstetrics and Gynaecology, University Hospital 12 de Octubre, 12 de Octubre Research Institute (imas12), Com- plutense University of Madrid, Madrid, Spain), Ignacio Herraiz (Fetal Medicine Unit-SAMID, Department of Obstetrics and Gynaecology, University Hospital 12 de Octubre, 12 de Octubre Research Institute (imas12), Com- plutense University of Madrid, Madrid, Spain), Alicia Vazquez-Sarandeses(FetalMedicineUnit-SAMID,Depart- ment of Obstetrics and Gynaecology, University Hospital 12 de Octubre, 12 de Octubre Research Institute (imas12), Complutense University of Madrid, Madrid, Spain), Cath- rine Ebbing (Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway), Synnøve L Johnsen (Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway), Henriette O Karlsen (Research Group for Pregnancy, Fetal Develop- ment and Birth, Department of Clinical Science, University of Bergen, Bergen, Norway).Peer reviewedPublisher PD

Phase transition in Random Circuit Sampling

Quantum computers hold the promise of executing tasks beyond the capability of classical computers. Noise competes with coherent evolution and destroys long-range correlations, making it an outstanding challenge to fully leverage the computation power of near-term quantum processors. We report Random Circuit Sampling (RCS) experiments where we identify distinct phases driven by the interplay between quantum dynamics and noise. Using cross-entropy benchmarking, we observe phase boundaries which can define the computational complexity of noisy quantum evolution. We conclude by presenting an RCS experiment with 70 qubits at 24 cycles. We estimate the computational cost against improved classical methods and demonstrate that our experiment is beyond the capabilities of existing classical supercomputers

Measurement-induced entanglement and teleportation on a noisy quantum processor

Measurement has a special role in quantum theory: by collapsing the wavefunction it can enable phenomena such as teleportation and thereby alter the "arrow of time" that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time that go beyond established paradigms for characterizing phases, either in or out of equilibrium. On present-day NISQ processors, the experimental realization of this physics is challenging due to noise, hardware limitations, and the stochastic nature of quantum measurement. Here we address each of these experimental challenges and investigate measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping, to avoid mid-circuit measurement and access different manifestations of the underlying phases -- from entanglement scaling to measurement-induced teleportation -- in a unified way. We obtain finite-size signatures of a phase transition with a decoding protocol that correlates the experimental measurement record with classical simulation data. The phases display sharply different sensitivity to noise, which we exploit to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realize measurement-induced physics at scales that are at the limits of current NISQ processors

Suppressing quantum errors by scaling a surface code logical qubit

Practical quantum computing will require error rates that are well below what is achievable with physical qubits. Quantum error correction offers a path to algorithmically-relevant error rates by encoding logical qubits within many physical qubits, where increasing the number of physical qubits enhances protection against physical errors. However, introducing more qubits also increases the number of error sources, so the density of errors must be sufficiently low in order for logical performance to improve with increasing code size. Here, we report the measurement of logical qubit performance scaling across multiple code sizes, and demonstrate that our system of superconducting qubits has sufficient performance to overcome the additional errors from increasing qubit number. We find our distance-5 surface code logical qubit modestly outperforms an ensemble of distance-3 logical qubits on average, both in terms of logical error probability over 25 cycles and logical error per cycle ($2.914\%\pm 0.016\%$ compared to $3.028\%\pm 0.023\%$). To investigate damaging, low-probability error sources, we run a distance-25 repetition code and observe a $1.7\times10^{-6}$ logical error per round floor set by a single high-energy event ($1.6\times10^{-7}$ when excluding this event). We are able to accurately model our experiment, and from this model we can extract error budgets that highlight the biggest challenges for future systems. These results mark the first experimental demonstration where quantum error correction begins to improve performance with increasing qubit number, illuminating the path to reaching the logical error rates required for computation.Comment: Main text: 6 pages, 4 figures. v2: Update author list, references, Fig. S12, Table I

Non-Abelian braiding of graph vertices in a superconducting processor

Indistinguishability of particles is a fundamental principle of quantum mechanics. For all elementary and quasiparticles observed to date - including fermions, bosons, and Abelian anyons - this principle guarantees that the braiding of identical particles leaves the system unchanged. However, in two spatial dimensions, an intriguing possibility exists: braiding of non-Abelian anyons causes rotations in a space of topologically degenerate wavefunctions. Hence, it can change the observables of the system without violating the principle of indistinguishability. Despite the well developed mathematical description of non-Abelian anyons and numerous theoretical proposals, the experimental observation of their exchange statistics has remained elusive for decades. Controllable many-body quantum states generated on quantum processors offer another path for exploring these fundamental phenomena. While efforts on conventional solid-state platforms typically involve Hamiltonian dynamics of quasi-particles, superconducting quantum processors allow for directly manipulating the many-body wavefunction via unitary gates. Building on predictions that stabilizer codes can host projective non-Abelian Ising anyons, we implement a generalized stabilizer code and unitary protocol to create and braid them. This allows us to experimentally verify the fusion rules of the anyons and braid them to realize their statistics. We then study the prospect of employing the anyons for quantum computation and utilize braiding to create an entangled state of anyons encoding three logical qubits. Our work provides new insights about non-Abelian braiding and - through the future inclusion of error correction to achieve topological protection - could open a path toward fault-tolerant quantum computing

The prognostic accuracy of short term variation of fetal heart rate in early-onset fetal growth restriction: A systematic review

Objective: Cardiotocography (CTG) is an important tool for fetal surveillance in severe early-onset fetal growth restriction (FGR). Assessment of the CTG is usually performed visually (vCTG). However, it is suggested that computerized analysis of the CTG (cCTG) including short term variability (STV) could more accurately detect fetal compromise. The objective of this study was to systematically review the literature on the association between cCTG and perinatal outcome and the comparison of cCTG with vCTG. Study design: A systematic search was performed in MEDLINE, EMBASE and Google Scholar. Studies were included that assessed prognostic accuracy of STV or compared STV to vCTG in patients with FGR. Risk of bias and concerns about applicability were assessed with the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2) instrument. Results: Of the 885 records identified in the search, five cohort studies (387 patients) were included. We found no randomized studies comparing STV with visual CTG in patients with FGR. The risk of bias of all studies was generally judged as ‘low’. One small study found an association of low STV with neonatal acidosis. One study observed no association of STV with long-term outcome. Composite analysis of all five studies showed a non-significant relative risk for acidosis after a low STV of 1.4 (95% CI 0.6–3.2, N = 387). Further meta-analysis was hampered due to heterogeneity in outcome reporting and use of different thresholds. Conclusion: The evidence from the included studies did not support an association of STV and short or long term outcome. However, available data are limited and heterogeneous, and influenced by management based on STV. Solid evidence from a randomized controlled trial comparing STV with vCTG including long term infant outcome is needed before STV can be used clinically for timing of delivery in patients with FGR

Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data

Objective To investigate if cerebroplacental ratio (CPR) adds to the predictive value of umbilical artery pulsatility index (UA PI) alone – standard of practice – for adverse perinatal outcome in singleton pregnancies. Design and setting Meta-analysis based on individual participant data (IPD). Population or sample Ten centres provided 17 data sets for 21 661 participants, 18 731 of which could be included. Sample sizes per data set ranged from 207 to 9215 individuals. Patient populations varied from uncomplicated to complicated pregnancies. Methods In a collaborative, pooled analysis, we compared the prognostic value of combining CPR with UA PI, versus UA PI only and CPR only, with a one-stage IPD approach. After multiple imputation of missing values, we used multilevel multivariable logistic regression to develop prediction models. We evaluated the classification performance of all models with receiver operating characteristics analysis. We performed subgroup analyses according to gestational age, birthweight centile and estimated fetal weight centile. Main outcome measures Composite adverse perinatal outcome, defined as perinatal death, caesarean section for fetal distress or neonatal unit admission. Results Adverse outcomes occurred in 3423 (18%) participants. The model with UA PI alone resulted in an area under the curve (AUC) of 0.775 (95% CI 0.709–0.828) and with CPR alone in an AUC of 0.778 (95% CI 0.715–0.831). Addition of CPR to the UA PI model resulted in an increase in the AUC of 0.003 points (0.778, 95% CI 0.714–0.831). These results were consistent across all subgroups. Conclusions Cerebroplacental ratio added no predictive value for adverse perinatal outcome beyond UA PI, when assessing singleton pregnancies, irrespective of gestational age or fetal size

Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data

Objective To investigate if cerebroplacental ratio (CPR) adds to the predictive value of umbilical artery pulsatility index (UA PI) alone – standard of practice – for adverse perinatal outcome in singleton pregnancies. Design and setting Meta-analysis based on individual participant data (IPD). Population or sample Ten centres provided 17 data sets for 21 661 participants, 18 731 of which could be included. Sample sizes per data set ranged from 207 to 9215 individuals. Patient populations varied from uncomplicated to complicated pregnancies. Methods In a collaborative, pooled analysis, we compared the prognostic value of combining CPR with UA PI, versus UA PI only and CPR only, with a one-stage IPD approach. After multiple imputation of missing values, we used multilevel multivariable logistic regression to develop prediction models. We evaluated the classification performance of all models with receiver operating characteristics analysis. We performed subgroup analyses according to gestational age, birthweight centile and estimated fetal weight centile. Main outcome measures Composite adverse perinatal outcome, defined as perinatal death, caesarean section for fetal distress or neonatal unit admission. Results Adverse outcomes occurred in 3423 (18%) participants. The model with UA PI alone resulted in an area under the curve (AUC) of 0.775 (95% CI 0.709–0.828) and with CPR alone in an AUC of 0.778 (95% CI 0.715–0.831). Addition of CPR to the UA PI model resulted in an increase in the AUC of 0.003 points (0.778, 95% CI 0.714–0.831). These results were consistent across all subgroups. Conclusions Cerebroplacental ratio added no predictive value for adverse perinatal outcome beyond UA PI, when assessing singleton pregnancies, irrespective of gestational age or fetal size

Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data

Objective: To investigate if cerebroplacental ratio (CPR) adds to the predictive value of umbilical artery pulsatility index (UA PI) alone \u2013 standard of practice \u2013 for adverse perinatal outcome in singleton pregnancies. Design and setting: Meta-analysis based on individual participant data (IPD). Population or sample: Ten centres provided 17 data sets for 21 661 participants, 18 731 of which could be included. Sample sizes per data set ranged from 207 to 9215 individuals. Patient populations varied from uncomplicated to complicated pregnancies. Methods: In a collaborative, pooled analysis, we compared the prognostic value of combining CPR with UA PI, versus UA PI only and CPR only, with a one-stage IPD approach. After multiple imputation of missing values, we used multilevel multivariable logistic regression to develop prediction models. We evaluated the classification performance of all models with receiver operating characteristics analysis. We performed subgroup analyses according to gestational age, birthweight centile and estimated fetal weight centile. Main outcome measures: Composite adverse perinatal outcome, defined as perinatal death, caesarean section for fetal distress or neonatal unit admission. Results: Adverse outcomes occurred in 3423 (18%) participants. The model with UA PI alone resulted in an area under the curve (AUC) of 0.775 (95% CI 0.709\u20130.828) and with CPR alone in an AUC of 0.778 (95% CI 0.715\u20130.831). Addition of CPR to the UA PI model resulted in an increase in the AUC of 0.003 points (0.778, 95% CI 0.714\u20130.831). These results were consistent across all subgroups. Conclusions: Cerebroplacental ratio added no predictive value for adverse perinatal outcome beyond UA PI, when assessing singleton pregnancies, irrespective of gestational age or fetal size. Tweetable abstract: Doppler measurement of cerebroplacental ratio in clinical practice has limited added predictive value to umbilical artery alone