Summary Improvement in healthcare delivery depends on the ability to measure outcomes that can direct changes in the system. An overview of quality indicators within the field of regional anaesthesia is lacking. This systematic review aims to synthesise available quality indicators, as per the Donabedian framework, and provide a concise overview of evidence‐based quality indicators within regional anaesthesia. A systematic literature search was conducted using the databases MEDLINE, Embase, CINAHL and Cochrane from 2003 to present, and a prespecified search of regional anaesthesia society websites and healthcare quality agencies. The quality indicators relevant to regional anaesthesia were subdivided into peri‐operative structure, process and outcome indicators as per the Donabedian framework. The methodological quality of the indicators was determined as per the Oxford Centre for Evidence‐Based Medicine's framework. Twenty manuscripts met our inclusion criteria and, in total, 68 unique quality indicators were identified. There were 4 (6%) structure, 12 (18%) process and 52 (76%) outcome indicators. Most of the indicators were related to the safety (57%) and effectiveness (19%) of regional anaesthesia and were general in nature (60%). In addition, most indicators (84%) were based on low levels of evidence. Our study is an important first step towards describing quality indicators for the provision of regional anaesthesia. Future research should focus on the development of structure and process quality indicators and improving the methodological quality and usability of these indicators.

Sparse projection pursuit analysis (SPPA), a new approach for the unsupervised exploration of highdimensional chemical data, is proposed as an alternative to traditional exploratory methods such as principal components analysis (PCA) and hierarchical cluster analysis (HCA). Where traditional methods use variance and distance metrics for data compression and visualization, the proposed method incorporates the fourth statistical moment (kurtosis) to access interesting subspaces that can clarify relationships within complex data sets. The quasi-power algorithm used for projection pursuit is coupled with a genetic algorithm for variable selection to efficiently generate sparse projection vectors that improve the chemical interpretability of the results while at the same time mitigating the problem of overmodeling. Several multivariate chemical data sets are employed to demonstrate that SPPA can reveal meaningful clusters in the data where other unsupervised methods cannot.

Visual impairment affects many children and can lead to blindness if untreated. The coronavirus disease 2019 (COVID-19) pandemic has led to various restrictions and other challenges accessing in-person medical care, including essential pediatric eye care. The aim of this article was to determine and quantify the effect that pandemics have on access to pediatric eye care. A systematic literature search was conducted using various databases, which yielded 257 articles; nine were included in the final review. All included studies reported a decrease in the number of children accessing eye care during COVID-19. Most studies described virtual triage systems, which restricted in-person care to emergent cases. The average decrease in daily pediatric visits was 67.32% and reached statistical significance in the meta-analysis ( P < .01). However, out of all patients with ocular complaints, the proportion of pediatric visits was unchanged, suggesting that the decrease in access to eye care was not specific to pediatric patients. [ Pediatr Ann . 2023;52(2):e68–e75.]

ObjectiveCongestive acute kidney injury (c-AKI) refers to AKI in the presence of right ventricular failure (RVF) and is a highly morbid complication of cardiac surgery. However, treatment has traditionally been reactive rather than proactive due to limited modalities to predict this complication. The objective of this study was to investigate the ability of insulin-like growth-factor binding protein 7 (IGFBP7), to predict c-AKI, AKI and RVF in patients undergoing cardiac surgery, as compared to N-terminal prohormone B-type natriuretic peptide (NT-pro-BNP) and pulmonary artery pulsatility index (PAPi).MethodsThis prospective nested case–control study consisted of 350 adult patients who underwent elective cardiac surgery. The outcomes were c-AKI, AKI and RVF. Unadjusted and adjusted conditional logistic regression models and areas under the receiver operating characteristic curve (AUC) were used to assess the predictive performance of each marker.ResultsFor the prediction of c-AKI, the unadjusted IGPBP7 model had an AUC of 0.81, as compared with 0.51 for NT-pro-BNP and 0.61 for PAPi. The adjusted c-AKI models had AUCs of 0.90 for IGFBP7, 0.87 for NT-pro-BNP and 0.77 for PAPi. For AKI and RVF, the predictive performance of IGFBP7 was moderate and exceeded that of NT-pro-BNP and PAPi in univariable analysis. IGFBP7 remained a robust independent predictor of all outcomes in multivariable analysis, whereas the other markers did not.ConclusionsIGFBP7 is a promising biomarker for prediction of AKI, RVF and c-AKI and could have value for preoperative optimisation and risk stratification of patients undergoing cardiac surgery.