The Alvarado score for predicting acute appendicitis: a systematic review

Background: The Alvarado score can be used to stratify patients with symptoms of suspected appendicitis; the validity of the score in certain patient groups and at different cut points is still unclear. The aim of this study was to assess the discrimination (diagnostic accuracy) and calibration performance of the Alvarado score. Methods: A systematic search of validation studies in Medline, Embase, DARE and The Cochrane library was performed up to April 2011. We assessed the diagnostic accuracy of the score at the two cut-off points: score of 5 (1 to 4 vs. 5 to 10) and score of 7 (1 to 6 vs. 7 to 10). Calibration was analysed across low (1 to 4), intermediate (5 to 6) and high (7 to 10) risk strata. The analysis focused on three sub-groups: men, women and children. Results: Forty-two studies were included in the review. In terms of diagnostic accuracy, the cut-point of 5 was good at 'ruling out' admission for appendicitis (sensitivity 99% overall, 96% men, 99% woman, 99% children). At the cut-point of 7, recommended for 'ruling in' appendicitis and progression to surgery, the score performed poorly in each subgroup (specificity overall 81%, men 57%, woman 73%, children 76%). The Alvarado score is well calibrated in men across all risk strata (low RR 1.06, 95% CI 0.87 to 1.28; intermediate 1.09, 0.86 to 1.37 and high 1.02, 0.97 to 1.08). The score over-predicts the probability of appendicitis in children in the intermediate and high risk groups and in women across all risk strata. Conclusions: The Alvarado score is a useful diagnostic 'rule out' score at a cut point of 5 for all patient groups. The score is well calibrated in men, inconsistent in children and over-predicts the probability of appendicitis in women across all strata of risk

Sound propagation and bubble motion in a cavitating channel

Ponencia presentada en el XIX Congreso Internacional de Acústica (ICA2007), Madrid, 2-7 Sep 2007.-- PACS: 43.35.Ei.The acoustic field and the emergence, distribution, and motion of bubbles in two rectangular water channels is investigated at ultrasonic frequencies around 20 kHz. The transducers are positioned at one channel end. We identify a near-field and a far-field region by measuring amplitude and phase of the acoustic pressure within the channels at low intensity. At higher ultrasonic power, cavitation bubbles close to the transducer show net drift into the channel, while bubbles in the far field form streamers fixed in space. Inbetween, a hopping bubble motion is observed. This can be reproduced by a calculation of bubble drift taking into account Bjerknes forces and rectified gas diffusion into the bubbles.Peer reviewe

Impact of community-based interventions on out-of-hospital cardiac arrest outcomes: a systematic review and meta-analysis

Abstract Survival following out-of-hospital cardiac arrest (OHCA) remains low, typically less than 10%. Bystander cardiopulmonary resuscitation (CPR) and bystander-AED use have been shown to improve survival by up to fourfold in individual studies. Numerous community-based interventions have been implemented worldwide in an effort to enhance rates of bystander-CPR, bystander-AED use, and improve OHCA survival. This systematic review and meta-analysis aims to evaluate the effect of such interventions on OHCA outcomes. Medline and Embase were systematically searched from inception through July 2021 for studies describing the implementation and effect of one or more community-based interventions targeting OHCA outcomes. Two reviewers screened articles, extracted data, and evaluated study quality using the Newcastle–Ottawa Scale. For each outcome, data were pooled using random-effects meta-analysis. Of the 2481 studies identified, 16 met inclusion criteria. All included studies were observational. They reported a total of 1,081,040 OHCAs across 11 countries. The most common interventions included community-based CPR training (n = 12), community-based AED training (n = 9), and dispatcher-assisted CPR (n = 8). Health system interventions (hospital or paramedical services) were also described in 11 of the included studies. Evidence certainty among all outcomes was low or very low according to GRADE criteria. On meta-analysis, community-based interventions with and without health system interventions were consistently associated with improved OCHA outcomes: rates of bystander-CPR, bystander-AED use, survival, and survival with a favorable neurological outcome. Bystander CPR—14 studies showed a significant increase in post-intervention bystander-CPR rates (n = 285 752; OR 2.26 [1.74, 2.94]; I2 = 99%, and bystander AED use (n = 37 882; OR 2.08 [1.44, 3.01]; I2 = 54%) and durvival—10 studies, pooling survival to hospital discharge and survival to 30 days (n = 79 206; OR 1.59 [1.20, 2.10]; I2 = 95%. The results provide foundational support for the efficacy of community-based interventions in enhancing OHCA outcomes. These findings inform our recommendation that communities, regions, and countries should implement community-based interventions in their pre-hospital strategy for OHCA. Further research is needed to identify which specific intervention types are most effective

Medical Text Simplification Using Reinforcement Learning (TESLEA): Deep Learning–Based Text Simplification Approach

BackgroundIn most cases, the abstracts of articles in the medical domain are publicly available. Although these are accessible by everyone, they are hard to comprehend for a wider audience due to the complex medical vocabulary. Thus, simplifying these complex abstracts is essential to make medical research accessible to the general public. ObjectiveThis study aims to develop a deep learning–based text simplification (TS) approach that converts complex medical text into a simpler version while maintaining the quality of the generated text. MethodsA TS approach using reinforcement learning and transformer–based language models was developed. Relevance reward, Flesch-Kincaid reward, and lexical simplicity reward were optimized to help simplify jargon-dense complex medical paragraphs to their simpler versions while retaining the quality of the text. The model was trained using 3568 complex-simple medical paragraphs and evaluated on 480 paragraphs via the help of automated metrics and human annotation. ResultsThe proposed method outperformed previous baselines on Flesch-Kincaid scores (11.84) and achieved comparable performance with other baselines when measured using ROUGE-1 (0.39), ROUGE-2 (0.11), and SARI scores (0.40). Manual evaluation showed that percentage agreement between human annotators was more than 70% when factors such as fluency, coherence, and adequacy were considered. ConclusionsA unique medical TS approach is successfully developed that leverages reinforcement learning and accurately simplifies complex medical paragraphs, thereby increasing their readability. The proposed TS approach can be applied to automatically generate simplified text for complex medical text data, which would enhance the accessibility of biomedical research to a wider audience

Evaluation of the Canadian Clinical Practice Guidelines Risk Prediction Tool for Acute Aortic Syndrome: The RIPP Score

Introduction. Acute aortic syndrome (AAS) is a rare clinical syndrome with a high mortality rate. The Canadian clinical practice guideline for the diagnosis of AAS was developed in order to reduce the frequency of misdiagnoses. As part of the guideline, a clinical decision aid was developed to facilitate clinician decision-making (RIPP score). The aim of this study is to validate the diagnostic accuracy of this tool and assess its performance in comparison to other risk prediction tools that have been developed. Methods. This was a historical case-control study. Consecutive cases and controls were recruited from three academic emergency departments from 2002–2020. Cases were identified through an admission, discharge, or death certificated diagnosis of acute aortic syndrome. Controls were identified through presenting complaint of chest, abdominal, flank, back pain, and/or perfusion deficit. We compared the clinical decision tools’ C statistic and used the DeLong method to test for the significance of these differences and report sensitivity and specificity with 95% confidence intervals. Results. We collected data on 379 cases of acute aortic syndrome and 1340 potential eligible controls; 379 patients were randomly selected from the final population. The RIPP score had a sensitivity of 99.7% (98.54–99.99). This higher sensitivity resulted in a lower specificity (53%) compared to the other clinical decision aids (63–86%). The DeLong comparison of the C statistics found that the RIPP score had a higher C statistic than the ADDRS (−0.0423 (95% confidence interval −0.07–0.02); P<0.0009) and the AORTAs score (−0.05 (−0.07 to −0.02); P = 0.0002), no difference compared to the Lovy decision tool (0.02 (95% CI −0.01–0.05 P<0.25)) and decreased compared to the Von Kodolitsch decision tool (0.04 (95% CI 0.01–0.07 P<0.008)). Conclusion. The Canadian clinical practice guideline’s AAS clinical decision aid is a highly sensitive tool that uses readily available clinical information. It has the potential to improve diagnosis of AAS in the emergency department

The SPR systems model as a conceptual foundation for rapid integrated risk appraisals: lessons from Europe

Coastal floodplains are complex regions that form the interface between human, physical and natural systems. This paper describes the development, application and evaluation of a conceptual foundation for quantitative integrated floodplain risk assessments using the recently-developed SPR systems model. The SPR systems model is a conceptual model that combines the well-established Source–Pathway–Receptor (SPR) approach with the concept of system diagrams. In comparison to the conventional approach, the systems model provides spatially explicit quasi-2D descriptions of the floodplain in terms of constituent elements and possible element linkages. The quasi-2D SPR, as it will henceforth be referred to in this paper, is not the final product of this work, but is an important intermediate stage which has been pursued as part of a wider European flood risk project THESEUS (www.theseusproject.eu). Further research is currently on-going to provide full quantification of the quasi-2D SPR, and to add further refinements such that hydraulic assessments could follow on easily and rapidly from the results of these appraisals.The first part of the paper synthesises current conceptual treatment of coastal floodplains and identifies areas for improvement in describing coastal floodplains as complex systems. The synthesis demonstrates that the conceptual foundation of a ‘typical’ flood risk study often achieves a less comprehensive and integrated description of the floodplain than the quantitative models which it informs. From this synthesis, the quasi-2D SPR is identified as a more robust and informative conceptual foundation for an integrated risk assessment. The quasi-2D SPR has been applied to seven European coastal floodplains as part of the THESEUS project. The second part of the paper discusses in detail the application of the quasi-2D SPR to three contrasting floodplain systems — an estuary, a coastal peninsula and a mixed open coast/estuary site. The quasi-2D SPR provides a consistent approach for achieving comprehensive floodplain descriptions that are individual to each coastal floodplain. These are obtained through a robust, participatory model-building exercise, that facilitates developing a shared understanding of the system. The constructed model is a powerful tool for structuring and integrating existing knowledge across multiple disciplines. Applications of the quasi-2D SPR provide key insights into the characteristics of complex coastal floodplains — insights that will inform the quantification process. Finally, the paper briefly describes the on-going quantitative extension to the quasi-2D SPR

Derivation and validation of a clinical decision rule to risk‐stratify COVID‐19 patients discharged from the emergency department: The CCEDRRN COVID discharge score

Abstract Objective To risk‐stratify COVID‐19 patients being considered for discharge from the emergency department (ED). Methods We conducted an observational study to derive and validate a clinical decision rule to identify COVID‐19 patients at risk for hospital admission or death within 72 hours of ED discharge. We used data from 49 sites in the Canadian COVID‐19 Emergency Department Rapid Response Network (CCEDRRN) between March 1, 2020, and September 8, 2021. We randomly assigned hospitals to derivation or validation and prespecified clinical variables as candidate predictors. We used logistic regression to develop the score in a derivation cohort and examined its performance in predicting short‐term adverse outcomes in a validation cohort. Results Of 15,305 eligible patient visits, 535 (3.6%) experienced the outcome. The score included age, sex, pregnancy status, temperature, arrival mode, respiratory rate, and respiratory distress. The area under the curve was 0.70 (95% confidence interval [CI] 0.68–0.73) in derivation and 0.71 (95% CI 0.68–0.73) in combined derivation and validation cohorts. Among those with a score of 3 or less, the risk for the primary outcome was 1.9% or less, and the sensitivity of using 3 as a rule‐out score was 89.3% (95% CI 82.7–94.0). Among those with a score of ≥9, the risk for the primary outcome was as high as 12.2% and the specificity of using 9 as a rule‐in score was 95.6% (95% CI 94.9–96.2). Conclusion The CCEDRRN COVID discharge score can identify patients at risk of short‐term adverse outcomes after ED discharge with variables that are readily available on patient arrival