bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Core Outcome Measurement Set for Pediatric Critical Care*
Authors: Pinto Neethi P. , Maddux Aline B. , Dervan Leslie A. , Woodruff Alan G. , Jarvis Jessica M. , Nett Sholeen , Killien Elizabeth Y. , Graham Robert J. , Choong Karen , Luckett Peter M. , Heneghan Julia A. , Biagas Katherine , Carlton Erin F. , Hartman Mary E. , Yagiela Lauren , Michelson Kelly N. , Manning Joseph C. , Long Debbie A. , Lee Jan Hau , Slomine Beth S. , Beers Sue R. , Hall Trevor , Morrow Brenda M. , Meert Kathleen , Arias Lopez Maria del Pilar , Knoester Hennie , Houtrow Amy , Olson Lenora , Steele Lisa , Schlapbach Luregn J. , Burd Randall S. , Grosskreuz Ruth , Butt Warwick , Fink Ericka L. , Watson R. Scott ,   for the POST-PICU Investigators of the Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network and the Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatric Critical Care Research Network (CPCCRN)
Published: August 2022

Objectives:
To identify a PICU Core Outcome Measurement Set (PICU COMS), a set of measures that can be used to evaluate the PICU Core Outcome Set (PICU COS) domains in PICU patients and their families.

Design:
A modified Delphi consensus process.

Setting:
Four webinars attended by PICU physicians and nurses, pediatric surgeons, rehabilitation physicians, and scientists with expertise in PICU clinical care or research (n = 35). Attendees were from eight countries and convened from the Pediatric Acute Lung Injury and Sepsis Investigators Pediatric Outcomes STudies after PICU Investigators and the Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatric Critical Care Research Network PICU COS Investigators.

Subjects:
Measures to assess outcome domains of the PICU COS are as follows: cognitive, emotional, overall (including health-related quality of life), physical, and family health. Measures evaluating social health were also considered.

Interventions:
None.

Measurements and Main Results:
Measures were classified as general or additional based on generalizability across PICU populations, feasibility, and relevance to specific COS domains. Measures with high consensus, defined as 80% agreement for inclusion, were selected for the PICU COMS. Among 140 candidate measures, 24 were delineated as general (broadly applicable) and, of these, 10 achieved consensus for inclusion in the COMS (7 patient-oriented and 3 family-oriented). Six of the seven patient measures were applicable to the broadest range of patients, diagnoses, and developmental abilities. All were validated in pediatric populations and have normative pediatric data. Twenty additional measures focusing on specific populations or in-depth evaluation of a COS subdomain also met consensus for inclusion as COMS additional measures.

Conclusions:
The PICU COMS delineates measures to evaluate domains in the PICU COS and facilitates comparability across future research studies to characterize PICU survivorship and enable interventional studies to target long-term outcomes after critical illness.
Association Between Centralization and Outcome for Children Admitted to Intensive Care in Australia and New Zealand: A Population-Based Cohort Study*
Authors: Slater Anthony , Beca John , Croston Elizabeth , McEniery Julie , Millar Johnny , Norton Lynda , Numa Andrew , Schell David , Secombe Paul , Straney Lahn , Young Paul , Yung Michael , Gabbe Belinda , Shann Frank ,   for the Australian and New Zealand Intensive Care Society Pediatric Study Group and Centre for Outcomes and Resource Evaluation
Published: August 2022

Objectives:
To describe regional differences and change over time in the degree of centralization of pediatric intensive care in Australia and New Zealand (ANZ) and to compare the characteristics and ICU mortality of children admitted to specialist PICUs and general ICUs (GICUs).

Design:
A retrospective cohort study using registry data for two epochs of ICU admissions, 2003–2005 and 2016–2018.

Setting:
Population-based study in ANZ.

Patients:
A total of 43,256 admissions of children aged younger than 16 years admitted to an ICU in ANZ were included. Infants aged younger than 28 days without cardiac conditions were excluded.

Interventions:
None.

Measurements and Main Results:
The primary outcome was risk-adjusted ICU mortality. Logistic regression was used to investigate the association of mortality with the exposure to ICU type, epoch, and their interaction. Compared with children admitted to GICUs, children admitted to PICUs were younger (median 25 vs 47 mo; p < 0.01) and stayed longer in ICU (median 1.6 vs 1.0 d; p < 0.01). For the study overall, 93% of admissions in Australia were to PICUs whereas in New Zealand only 63% of admissions were to PICUs. The adjusted odds of death in epoch 2 relative to epoch 1 decreased (adjusted odds ratio [AOR], 0.50; 95% CI, 0.42–0.59). There was an interaction between unit type and epoch with increased odds of death associated with care in a GICU in epoch 2 (AOR, 1.63; 95% CI, 1.05–2.53 for all admissions; 1.73, CI, 1.002–3.00 for high-risk admissions).

Conclusions:
Risk-adjusted mortality of children admitted to specialist PICUs decreased over a study period of 14 years; however, a similar association between time and outcome was not observed in high-risk children admitted to GICUs. The results support the continued use of a centralized model of delivering intensive care for critically ill children.
Factors Associated With Mechanical Ventilation Duration in Pediatric Burn Patients in a Regional Burn Center in the United States*
Authors: Garren Benjamin N. , Akhondi-Asl Alireza , DePamphilis Matthew A. , Burns Jeffrey P. , Sheridan Robert L. 
Published: August 2022

Objectives:
Among burned children who arrive at a burn center and require invasive mechanical ventilation (IMV), some may have prolonged IMV needs. This has implications for patient-centered outcomes as well as triage and resource allocation decisions. Our objective was to identify factors associated with the duration of mechanical ventilation in pediatric patients with acute burn injury in this setting.

Design:
Single-center, retrospective cohort study.

Setting:
Registry data from a regional, pediatric burn center in the United States.

Patients:
Children less than or equal to 18 years old admitted with acute burn injury who received IMV between January 2005 and December 2020.

Interventions:
None.

Measurements and Main Results:
Ventilator days were defined as any full or partial day having received IMV via an endotracheal tube or tracheostomy, not inclusive of time spent ventilated for procedures. Of 5,766 admissions for acute burn care, 4.3% (n = 249) required IMV with a median duration of 10 days. A multivariable model for freedom from mechanical ventilation showed that the presence of inhalational injury (subhazard ratio [sHR], 0.62; 95% CI, 0.46–0.85) and burns to the head and neck region (sHR, 0.94; 95% CI, 0.90–0.98) were associated with increased risk of remaining mechanically ventilated at any time point. Older (sHR, 1.03; 95% CI, 1.01–1.04) and male children (sHR, 1.39; 95% CI, 1.05–1.84) were more likely to discontinue mechanical ventilation. A majority of children (94.8%) survived to hospital discharge.

Conclusions:
The presence of inhalational injury and burns to the head and neck region were associated with a longer duration of mechanical ventilation. Older age and male gender were associated with a shorter duration of mechanical ventilation. These factors should help clinicians better estimate a burned child’s expected trajectory and resource-intensive needs upon arrival to a burn center.
The Effect of Center Esophagectomy Volume on Outcomes in Clinical Stage I to III Esophageal Cancer
Authors: Rhodin Kristen E. , Raman Vignesh , Jensen Christopher W. , Kang Lillian , Harpole David H. , D’Amico Thomas A. , Tong Betty C. 
Published: August 2022

Objective:
To determine the threshold annualized esophagectomy volume that is associated with improved survival, oncologic resection, and postoperative outcomes.

Background:
Esophagectomy at high-volume centers is associated with improved outcomes; however, the definition of high-volume remains debated.

Methods:
The 2004 to 2016 National Cancer Database was queried for patients with clinical stage I to III esophageal cancer undergoing esophagectomy. Center esophagectomy volume was modeled as a continuous variable using restricted cubic splines. Maximally selected ranks were used to identify an inflection point of center volume and survival. Survival was compared using multivariable Cox proportional hazards methods. Multivariable logistic regression was used to examine secondary outcomes.

Results:
Overall, 13,493 patients met study criteria. Median center esophagectomy volume was 8.2 (interquartile range: 3.2–17.2) cases per year. On restricted cubic splines, inflection points were identified at 9 and 30 cases per year. A multivariable Cox model was constructed modeling annualized center surgical volume as a continuous variable using 3 linear splines and inflection points at 9 and 30 cases per year. On multivariable analysis, increasing center volume up to 9 cases per year was associated with a substantial survival benefit (hazard ratio: 0.97, 95% confidence interval, 0.95–0.98, P≤0.001). On multivariable logistic regression, factors associated with undergoing surgery at a high-volume center (>9 cases per year) included private insurance, care at an academic center, completion of high school education, and greater travel distance.

Conclusions:
This National Cancer Database study utilizing multivariable analysis and restricted cubic splines suggests the threshold definition of a high-volume esophagectomy center as one that performs at least 10 operations a year.
Perioperative management of pressure injury: a best practice implementation project
Authors: Menšíková Andrea , Klugarová Jitka , Klugar Miloslav , Menšík Ivo , Soukopová Žaneta , Pokorná Andrea 
Published: August 2022

Abstract

Objectives:
This project aimed to set up a control mechanism for the prevention of pressure injuries during surgery.

Introduction:
Structured and comprehensive risk assessment is effective in identifying individuals at risk for pressure injuries. The subsequent use of proper positioning aids (modern gel-filled positioning aids used to position the head and limbs: floating limb concept) reduces the incidence of surgery-related pressure injuries.

Methods:
The best practice implementation project used the JBI's Practical Application of Clinical Evidence System and Getting Research into Practice audit tool for promoting change in local healthcare practice. The study was carried out from January 2020 to February 2021 at the private clinic of aesthetic surgery (Brno, Czech Republic). A baseline audit involving 27 patients was undertaken and measured against six best practice recommendations. This step was followed by the implementation of targeted strategies and finally, a postimplementation follow-up audit was conducted.

Results:
The baseline audit results showed significant deficits between current practice and best practice in all but two criteria. Barriers to implementation of nursing clinical handover best practice criteria were identified by the project team and an education strategy was implemented, documentation for recording possible risks of pressure injuries was created, and new positioning aids were purchased and introduced into clinical practice. There were significantly improved outcomes across all best practice criteria in the follow-up audit.

Conclusion:
Clinical audits were proved to promote best practice in healthcare. Focused education, provision, and use of relevant tools and aids can have an immediate and positive impact on clinical practice. Future audits are planned to ensure the sustainability of practice changes.
Administration of chemotherapy in patients admitted to a haematology service: a best practice implementation project
Authors: Coutinho Verónica Rita Dias , Santos Cristina Maria de Oliveira , Rodrigues Catarina Isabel , Santos Catarina Isabel Geraldes , Apóstolo João Luis Alves , Cardoso Daniela Filipa Baptista , Klugarova Jitka , Klugar Miloslav 
Published: August 2022

Abstract

Objectives:
To promote evidence-based practices related to the prevention of adverse events associated with medication administration (only chemotherapy) in a hospital service.

Introduction:
The medication management process in a hospital setting is highly complex, going through multiple stages from drug selection, procurement and storage, to prescription, validation, dispensing, preparation, administration and monitoring.

Methods:
An evidence implementation project based on an audit and feedback approach was conducted from December 2019 to April 2021 using the JBI Practical Application of Clinical Evidence System and Getting Research into Practice.

Results:
The results of the baseline audit showed that the 10 audit criteria were mostly met; however, two of the criteria (criterion 6: the expiry date of medication is checked before use and criterion 7: the nurse who prepares the medication administers the medication to the patient) had low compliance (respectively, 0 and 67.9%). After identifying the barriers and implementing strategies to deal with the identified barriers, we verified a significant improvement in compliance with best practices (criterion 6 improved to 64.3% and criterion 7 to 78.6%).

Conclusion:
This implementation project was a success, achieving a great improvement of the implementation of evidence-based guidelines concerning the prevention of adverse events associated with medication administration in a hospital in central Portugal. More such projects should be planned to sustain the implementation of evidence-based methods to improve health outcomes, patient safety, costs and health systems.
A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data
Authors: Abdulazeem Hebatullah , Whitelaw Sera , Schauberger Gunther , Klug Stefanie J. 
Published: August 2022

AbstractAimWith the rapid advances in technology and data science, machine learning (ML) is being adopted by the health care sector; but there is a lack of literature addressing the health conditions targeted by the ML prediction models within primary health care (PHC). To fill this gap in knowledge, we conducted a systematic review following the PRISMA guidelines to identify the health conditions targeted by ML in PHC.MethodsWe searched the Cochrane Library, Web of Science, PubMed, Elsevier, BioRxiv, Association of Computing Machinery (ACM), and IEEE Xplore databases for studies published from January 1990 to January 2022. We included any primary study addressing ML diagnostic or prognostic predictive models that were supplied completely or partially by real-world PHC data. We performed literature screening, data extraction, and risk of bias assessment. Health conditions were categorized according to international classification of diseases. Extracted date were analyzed quantitatively and qualitatively.ResultsWe identified 109 studies investigating 42 health conditions. These studies included 273 ML prediction models supplied by the PHC data of 24.2 million participants from 19 countries. We found that 82% of the studies were retrospective. 76.6% of the studies reported diagnostic predictive ML models. 77% of all reported models aimed for models’ development without external validation. Risk of bias assessment revealed that 90.8% of the studies were of high or unclear risk of bias. The most frequently reported health conditions were Alzheimer’s disease and diabetes mellitus.ConclusionsTo the best of our knowledge, this is the first review to investigate the extent of the health conditions targeted by the ML prediction models within PHC settings. Our study provides an important summary on the presently available ML models in PHC, which can be used in further research and implementation efforts.
How Important Are Study Designs? A Simulation Assessment of Vaccine Effectiveness Estimation Bias with Time-Varying Vaccine Coverage, and Heterogeneous Testing and Baseline Attack Rates
Authors: Suah Jing Lian , Bar-Zeev Naor , Knoll Maria Deloria 
Published: August 2022

AbstractObjectiveWe studied how commonly used vaccine effectiveness (VE) study designs (variations of cohorts, and test-negative designs) perform under epidemiological nuances more prominent in the COVID-19 era, specifically time-varying vaccine coverage, and heterogeneous testing behaviour and baseline attack rates with selection on willingness to vaccinate.MethodologyWe simulated data from a multi-parameter conceptual model of the epidemiological environment using 888125 parameter sets. Four configurations of cohorts, and two test-negative designs, were conducted on the simulated data, from which estimation bias is computed. Finally, stratified and fixed effects linear regressions were estimated to quantify the sensitivity of estimation bias to model parameters.FindingsIrrespective of study designs, dynamic vaccine coverage, and heterogeneous testing behaviour and baseline attack rates are important determinants of bias. Study design choices have non-trivial effects on VE estimation bias even if these factors are absent. The importance of these sources of bias differ across study designs.ConclusionA re-benchmarking of methodology, especially for studying COVID-19 VE, and implementation of vaccine-preventable disease surveillance systems that minimise these sources of bias, are warranted.HighlightsThis paper simulated a theoretical model with frictions in vaccination, testing, baseline disease risks, and heterogeneous vaccine effectiveness to evaluate estimation bias across four cohort and two test-negative designs.In theory, bias depends on behavioural asymmetries (in testing, and baseline risk) between the vax-willing and vax-unwilling, and the speed of vaccination rollout.There is intrinsic estimation bias across all study designs, with the direction and magnitude contingent on specific conditions.In scenarios that may be reflective of past SARS-CoV-2 waves, the degree of bias can be substantial, attributable to variation in assumed testing and baseline risk frictions.A regression-based decomposition indicates that study designs have visibly different primary sources of estimation bias, and degree of robustness in general.This study warrants a re-benchmarking of methodology and reporting checklists for VE research, and informs the design of cost-effective surveillance by quantifying part of the bias-implementation cost trade-off.
Identifiability and inference of phylogenetic birth-death models
Authors: Legried Brandon , Terhorst Jonathan 
Published: August 2022

AbstractRecent theoretical work on phylogenetic birth-death models offers differing viewpoints on whether they can be estimated using lineage-through-time data. Louca and Pennell (2020) showed that the class of models with continuously differentiable rate functions is nonidentifiable: any such model is consistent with an infinite collection of alternative models, which are statistically indistinguishable regardless of how much data are collected. Legried and Terhorst (2022a) qualified this grave result by showing that identifiability is restored if only piecewise constant rate functions are considered.Here, we contribute new theoretical results to this discussion, in both the positive and negative directions. Our main result is to prove that models based on piecewise polynomial rate functions of any order and with any (finite) number of pieces are statistically identifiable. In particular, this implies that spline-based models with an arbitrary number of knots are identifiable. The proof is simple and self-contained, relying mainly on basic algebra. We complement this positive result with a negative one, which shows that even when identifiability holds, rate function estimation is still a difficult problem. To illustrate this, we prove some rates-of-convergence results for hypothesis testing using birth-death models. These results are information-theoretic lower bounds which apply to all potential estimators.
A Spatiotemporal History of Key San Francisco Estuary Pelagic Fish Species
Authors: Stompe Dylan K. , Moyle Peter B. , Oken Kiva L. , Hobbs James A. , Durand John R. 
Published: August 2022

AbstractEstuaries across the globe have been subject to extensive abiotic and biotic changes and are often monitored to track trends in species abundance. The San Francisco Estuary is a novel ecosystem that has been deeply altered by anthropogenic factors, resulting in fish declines over the past 100 years. To track these species declines, a patchwork of monitoring programs has operated regular fish surveys dating back to the late 1950s. While most of these surveys are designed to track population-scale changes in fish abundance, they are methodologically distinct, with different target species, varying spatial coverage and sample frequency, and differing gear types. To remediate for individual survey limitations, we modeled pelagic fish distributions with integrated data from many sampling programs. We fit binomial generalized linear mixed models with spatial and spatiotemporal random effects to map annual trends in the distribution of detection probabilities of striped bass, Delta smelt, longfin smelt, threadfin shad, and American shad for the years 1980 to 2017. Detection probabilities decreased dramatically for these fishes in the Central and South Delta, especially after the year 2000. In contrast, Suisun Marsh, one of the largest tidal marshes on the west coast of the United States, acted as a refuge habitat with reduced levels of decline or even increased detection probabilities for some species. Our modeling approach demonstrates the power of utilizing disparate datasets to identify regional trends in the distribution of estuarine fishes.
The western redcedar genome reveals low genetic diversity in a self-compatible conifer
Authors: Shalev Tal J. , Gamal El-Dien Omnia , Yuen Macaire M.S. , Shengqiang Shu , Jackman Shaun D. , Warren René L. , Coombe Lauren , van der Merwe Lise , Stewart Ada , Boston Lori B. , Plott Christopher , Jenkins Jerry , He Guifen , Yan Juying , Yan Mi , Guo Jie , Breinholt Jesse W. , Neves Leandro G. , Grimwood Jane , Rieseberg Loren H. , Schmutz Jeremy , Birol Inanc , Kirst Matias , Yanchuk Alvin D. , Ritland Carol , Russell John H. , Bohlmann Joerg 
Published: August 2022

AbstractWe assembled the 9.8 Gbp genome of western redcedar (WRC, Thuja plicata), an ecologically and economically important conifer species of the Cupressaceae. The genome assembly, derived from a uniquely inbred tree produced through five generations of self-fertilization (selfing), was determined to be 86% complete by BUSCO analysis – one of the most complete genome assemblies for a conifer. Population genomic analysis revealed WRC to be one of the most genetically depauperate wild plant species, with an effective population size of approximately 300 and no significant genetic differentiation across its geographic range. Nucleotide diversity, π, is low for a continuous tree species, with many loci exhibiting zero diversity, and the ratio of π at zero-to four-fold degenerate sites is relatively high (∼ 0.33), suggestive of weak purifying selection. Using an array of genetic lines derived from up to five generations of selfing, we explored the relationship between genetic diversity and mating system. While overall heterozygosity was found to decline faster than expected during selfing, heterozygosity persisted at many loci, and nearly 100 loci were found to deviate from expectations of genetic drift, suggestive of associative overdominance. Non-reference alleles at such loci often harbor deleterious mutations and are rare in natural populations, implying that balanced polymorphisms are maintained by linkage to dominant beneficial alleles. This may account for how WRC remains responsive to natural and artificial selection, despite low genetic diversity.