Standardisierte Kontrastmittelsonographie (CEUS) in der klinischen Akut- und Notfallmedizin sowie Intensivmedizin (CEUS-Akut)

Die Anaesthesiologie -     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

Glycaemic control for patients with severe acute brain injury: Protocol for a systematic review

Background

Hyperglycaemia is common in patients with acute brain injury admitted to an intensive care unit (ICU). Many studies have found associations between development of hyperglycaemia and increased mortality in hospitalised patients. However, the optimal target for blood glucose control is unknown. We want to conduct a systematic review with meta-analysis and trial sequential analysis to explore the beneficial and harmful effects of restrictive versus liberal glucose control on patient outcomes in adults with severe acute brain injury.

Methods

We will systematically search medical databases including CENTRAL, Embase, MEDLINE and trial registries. We will search the following websites for ongoing or unpublished trials: http://www.controlled-trials.com/ , http://www.clinicaltrials.gov/ , www.eudraCT.com , http://centerwatch.com/ , The Cochrane Library's CENTRAL, PubMed, EMBASE, Science Citation Index Expanded and CINAHL. Two authors will independently review and select trials and extract data. We will include randomised trials comparing levels of glucose control in our analyses and observational studies will be included to address potential harms. The primary outcomes are defined as all-cause mortality, functional outcome and health-related quality of life. Secondary outcomes include serious adverse events including hypoglycaemia, length of ICU stay and duration of mechanical ventilation, and explorative outcomes including intracranial pressure and infection. Trial Sequential Analysis will be used to investigate the risk of type I error due to repetitive testing and to further explore imprecision. Quality of trials will be evaluated using the Cochrane Risk of Bias tool, and quality of evidence will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

Discussion

The results of the systematic review will be disseminated through peer-reviewed publication. With the review, we hope to inform future randomised clinical trials and improve clinical practice.     

Patient navigation across the cancer care continuum: An overview of systematic reviews and emerging literature

Patient navigation is a strategy for overcoming barriers to reduce disparities and to improve access and outcomes. The aim of this umbrella review was to identify, critically appraise, synthesize, and present the best available evidence to inform policy and planning regarding patient navigation across the cancer continuum. Systematic reviews examining navigation in cancer care were identified in the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Embase, Cumulative Index of Nursing and Allied Health (CINAHL), Epistemonikos, and Prospective Register of Systematic Reviews (PROSPERO) databases and in the gray literature from January 1, 2012, to April 19, 2022. Data were screened, extracted, and appraised independently by two authors. The JBI Critical Appraisal Checklist for Systematic Review and Research Syntheses was used for quality appraisal. Emerging literature up to May 25, 2022, was also explored to capture primary research published beyond the coverage of included systematic reviews. Of the 2062 unique records identified, 61 systematic reviews were included. Fifty-four reviews were quantitative or mixed-methods reviews, reporting on the effectiveness of cancer patient navigation, including 12 reviews reporting costs or cost-effectiveness outcomes. Seven qualitative reviews explored navigation needs, barriers, and experiences. In addition, 53 primary studies published since 2021 were included. Patient navigation is effective in improving participation in cancer screening and reducing the time from screening to diagnosis and from diagnosis to treatment initiation. Emerging evidence suggests that patient navigation improves quality of life and patient satisfaction with care in the survivorship phase and reduces hospital readmission in the active treatment and survivorship care phases. Palliative care data were extremely limited. Economic evaluations from the United States suggest the potential cost-effectiveness of navigation in screening programs.     

Trends in radiation dose for low grade gliomas across the United States

Journal of Neuro-Oncology - Adjuvant radiation is often used in patients with low grade gliomas with high-risk characteristics with a recommended dose of 45–54&nbsp;Gy. We used the...     

A comparison of the academic impact of plastic surgery units in the United Kingdom and Ireland using bibliometric analysis

Academic output is just one aspect of a successful career as a plastic surgeon. However, for those with a strong interest in academia, the academic output of a department will likely be a key factor when deciding how to rank jobs. The aim of this study was to quantify and rank the academic output of plastic surgery units across the UK and Ireland. The Institute for Scientific Information (ISI) Web of Science Bibliometric analysis tool was used to collate cumulative (1950–2016), 10 year (2006–2016) and 3 years (2013–2015) research output data for plastic surgery units in the UK and Ireland. Sixty-six plastic surgery units were identified. Departments were ranked for each time period according to the number of papers produced, number of citations (Nc) and h-index (a measure of the impact of scientific output). The top 3 departments for number of papers in the last 10 years were The Royal Free Hospital, London (226) Broomfield Hospital, Chelmsford (218), and Morriston Hospital and Swansea (188). The top 3 for h-number were The Royal Free Hospital (21) Wythenshawe Hospital, Manchester (18) and Morriston Hospital (17). Academic output varies across plastic surgery units in the UK and Ireland. A number of departments have consistently maintained high academic outputs across the years and will be of interest to surgeons hoping to pursue a career in academia.     

Differentiating poor validity from probable impairment on the medical symptom validity test: a cross-validation study

Aims: In neuropsychological evaluations, it is often difficult to ascertain whether poor performance on measures of validity is due to poor effort or malingering, or whether there is genuine cognitive impairment. Dunham and Denney created an algorithm to assess this question using the Medical Symptom Validity Test (MSVT). We assessed the ability of their algorithm to detect poor validity versus probable impairment, and concordance of failure on the MSVT with other freestanding tests of performance validity.

Methods: Two previously published datasets (n?=?153 and n?=?641, respectively) from outpatient neuropsychological evaluations were used to test Dunham and Denney’s algorithm, and to assess concordance of failure rates with the Test of Memory Malingering and the forced choice measure of the California Verbal Learning Test, two commonly used performance validity tests.

Results: In both datasets, none of the four cutoff scores for failure on the MSVT (70%, 75%, 80%, or 85%) identified a poor validity group with proportionally aligned failure rates on other freestanding measures of performance validity. Additionally, the protocols with probable impairment did not differ from those with poor validity on cognitive measures.

Conclusions: Despite what appeared to be a promising approach to evaluating failure on the easy MSVT subtests when clinical data are unavailable (as recommended in the advanced interpretation program, or advanced interpretation [AI], of the MSVT), the current findings indicate the AI remains the gold standard for doing so. Future research should build on this effort to address shortcomings in measures of effort in neuropsychological evaluations.