Conformity: the hidden actor in surgical decisions

Conformity in decision making has a relevant impact in surgical environments. This manuscript reveals how group-based opinions can distort the surgeon's individual judgment, even in critical situations. Two key phenomena are analysed: communication cascades and group polarisation, which amplify conformity and lead to extreme and sometimes harmful decisions. It is important to highlight the importance of evidence-based education, critical thinking, and diversification of information sources to counteract the negative effects of conformity. Self-identifying conformist tendencies, encouraging open debate, and implementing constructive dissent strategies can help mitigate the effects of conformity in decision-making. Reviewing authority models and promoting diversity in surgical settings may improve decision-making and the quality of patient care.

Making treatment guideline recommendations in chronic kidney disease and type 2 diabetes more accessible to primary care providers in the United States

Clinical practice guidelines for the management of chronic kidney disease (CKD) associated with type 2 diabetes (T2D) are designed to assist healthcare professionals with clinical decision making by providing recommendations on the screening, detection, management, and treatment of these conditions. However, primary care practitioners (PCPs) may have clinical inertia when it comes to routinely enacting CKD and T2D guideline recommendations in their clinical practices. Guideline developers have published a range of resources with the aim of facilitating easier access to guideline recommendations to support efficient and consistent implementation into clinical practice of PCPs. Challenges remain in providing strategies to reduce inertia in the application of guideline recommendations in primary care. In this review, we explore reasons behind the low level of awareness and poor uptake of published evidence-based care approaches to the optimal management of patients with T2D and CKD. Finally, we present suggestions on strategies to improve the implementation of guideline-directed recommendations in primary care.

Nurses' Anxiety Mediates the Relationship between Clinical Tolerance to Uncertainty and Antibiotic Initiation Decisions in Residential Aged-Care Facilities

HIGHLIGHTS

The impact of non-clinical factors (e.g., resident and family preferences) on prescribing is well-established. There is a gap in the literature regarding the mechanisms through which these preferences are experienced as pressure by prescribers within the unique context of residential aged-care facilities (RACFs).A significant relationship was found between nurses' anxiety, clinical tolerance of uncertainty, and the perceived need for antibiotics and assessment.As such, there is a need to expand stewardship beyond education alone to include interventions that help nurses manage uncertainty and anxiety and include other stakeholders (e.g., family members) when making clinical decisions in the RACF setting.

Clinical value of Alzheimer's disease biomarker testing

INTRODUCTION

In the Investigating the Impact of Alzheimer's Disease Diagnostics in British Columbia (IMPACT-AD BC) study, we aimed to understand how Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarker testing-used in medical care-impacted medical decision-making (medical utility), personal decision-making (personal utility), and health system economics.

METHODS

The study was designed as an observational, longitudinal cohort study. A total of 149 patients were enrolled between February 2019 and July 2021. Patients referred to memory clinics were approached to participate if their dementia specialist ordered AD CSF biomarker testing as part of their routine medical care, and the clinical scenario met the appropriate use criteria for lumbar puncture and AD CSF biomarker testing. For the medical utility pillar, detailed clinical management plans were collected via physician questionnaires pre- and post-biomarker disclosure.

RESULTS

Patients with completed management questionnaires (n = 142) had a median age of 64 (interquartile range: 59-69) years, 48% were female, and 60% had CSF biomarker profiles on the AD continuum. Clinical management changed in 89.4% of cases. AD biomarker testing was associated with decreased need for other diagnostic procedures, including brain imaging (-52.0%) and detailed neuropsychological assessments (-63.2%), increased referrals and counseling (57.0%), and guided AD-related drug prescriptions (+88.4% and -50.0% in biomarker-positive and -negative cases, respectively).

DISCUSSION

AD biomarker testing was associated with significant and positive changes in clinical management, including decreased health care resource use, therapy optimization, and increased patient and family member counseling. While certain changes in management were linked to the AD biomarker profile (e.g., referral to clinical trials), the majority of changes were independent of baseline clinical presentation and level of cognitive impairment, demonstrating a broad value for AD biomarker testing in individuals meeting the appropriate use criteria for testing.

Surveying the Moral Landscape: How Ethical Frameworks Influence the Structure of Return-to-Sport Decision Making

SYNOPSIS: Similar to all areas of health care, sports medicine has ethical considerations when making decisions-return to sport being one. Despite a general consensus on criteria to determine when an athlete is ready to return to sport, there are various scenarios that clinicians encounter that may not fall into a clear "yes" or "no" decision. These scenarios leave the clinician asking what is the "right" decision in a given circumstance? A line of questioning that invokes a moral dimension in supporting athletes when they are returning to sport. To address the moral aspect of a clinical decision, ethical frameworks and theories can guide decisions and resolve ethical dilemmas. The aim of this Viewpoint is to briefly describe 4 ethical frameworks and explore how they might apply in a clinical scenario to guide different ethical analyses and influence the final decision. J Orthop Sports Phys Ther 2024;54(4):1-4. Epub 14 February 2024. doi:10.2519/jospt.2024.12310.

Clinical decision making for VA ECMO weaning in patients with cardiogenic shock A formative qualitative study

Weaning and liberation from VA ECMO in cardiogenic shock patients comprises a complex process requiring a continuous trade off between multiple clinical parameters. In the absence of dedicated international guidelines, we hypothesized a great heterogeneity in weaning practices among ECMO centers due to a variety in local preferences, logistics, case load and individual professional experience. This qualitative study focused on the appraisal of clinicians' preferences in decision processes towards liberation from VA ECMO after cardiogenic shock while using focus group interviews in 4 large hospitals. The goal was to provide novel and unique insights in daily clinical weaning practices. As expected, we found we a great heterogeneity of weaning strategies among centers and professionals, although participants appeared to find common ground in a clinically straightforward approach to assess the feasibility of ECMO liberation at the bedside. This was shown in a preference for robust, easily accessible parameters such as arterial pulse pressure, stable cardiac index ≥2.1 L/min, VTI LVOT and 'eyeballing' LVEF.

Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables

Objective Contrast agents used for radiological examinations are an important cause of acute kidney injury (AKI). We developed and validated a machine learning and clinical scoring prediction model to stratify the risk of contrast-induced nephropathy, considering the limitations of current classical and machine learning models. Methods This retrospective study included 38,481 percutaneous coronary intervention cases from 23,703 patients in a tertiary hospital. We divided the cases into development and internal test sets (8:2). Using the development set, we trained a gradient boosting machine prediction model (complex model). We then developed a simple model using seven variables based on variable importance. We validated the performance of the models using an internal test set and tested them externally in two other hospitals. Results The complex model had the best area under the receiver operating characteristic (AUROC) curve at 0.885 [95% confidence interval (CI) 0.876-0.894] in the internal test set and 0.837 (95% CI 0.819-0.854) and 0.850 (95% CI 0.781-0.918) in two different external validation sets. The simple model showed an AUROC of 0.795 (95% CI 0.781-0.808) in the internal test set and 0.766 (95% CI 0.744-0.789) and 0.782 (95% CI 0.687-0.877) in the two different external validation sets. This was higher than the value in the well-known scoring system (Mehran criteria, AUROC=0.67). The seven precatheterization variables selected for the simple model were age, known chronic kidney disease, hematocrit, troponin I, blood urea nitrogen, base excess, and N-terminal pro-brain natriuretic peptide. The simple model is available at http://52.78.230.235:8081/Conclusions We developed an AKI prediction machine learning model with reliable performance. This can aid in bedside clinical decision making.

Comparing Pharmacotherapies for ADHD in Adults: Evidence From Outcome-Focused Analysis of Food and Drug Administration Drug Label Registration Trials

OBJECTIVE

We appraised whether FDA registration trials for ADHD pharmacotherapy in adults provides comparable information to inform treatment expectations.

METHOD

Comparison of ADHD outcome measure patterns in ADHD pharmacotherapy FDA drug label source studies.

RESULTS

Among stimulants, from fixed-dose titration data, amphetamine agents had numerically higher placebo-corrected symptom improvement and symptom effect sizes than methylphenidate agents. Symptom effect sizes were lower in the flexible dosing registration studies of atomoxetine and viloxazine. Varying responder definitions were analyzable, based on ≥30% symptom improvement and/or CGI-I improvement of "much" or "very much improved." Number of exposures needed to create these responses were lower for stimulants than for viloxazine.

CONCLUSION

Heterogeneity in the design and analysis of FDA drug label source trials restricts implications for clinical practice. Research conducted using replicated designs, direct comparison of available treatments, and outcome analyses that generalize to clinical care could better inform clinical decision making.

A machine learning model to predict heart failure readmission: toward optimal feature set

Background

Hospital readmissions for heart failure patients remain high despite efforts to reduce them. Predictive modeling using big data provides opportunities to identify high-risk patients and inform care management. However, large datasets can constrain performance.

Objective

This study aimed to develop a machine learning based prediction model leveraging a nationwide hospitalization database to predict 30-day heart failure readmissions. Another objective of this study is to find the optimal feature set that leads to the highest AUC value in the prediction model.

Material and methods

Heart failure patient data was extracted from the 2020 Nationwide Readmissions Database. A heuristic feature selection process incrementally incorporated predictors into logistic regression and random forest models, which yields a maximum increase in the AUC metric. Discrimination was evaluated through accuracy, sensitivity, specificity and AUC.

Results

A total of 566,019 discharges with heart failure diagnosis were recognized. Readmission rate was 8.9% for same-cause and 20.6% for all-cause diagnoses. Random forest outperformed logistic regression, achieving AUCs of 0.607 and 0.576 for same-cause and all-cause readmissions respectively. Heuristic feature selection resulted in the identification of optimal feature sets including 20 and 22 variables from a pool of 30 and 31 features for the same-cause and all-cause datasets. Key predictors included age, payment method, chronic kidney disease, disposition status, number of ICD-10-CM diagnoses, and post-care encounters.

Conclusion

The proposed model attained discrimination comparable to prior analyses that used smaller datasets. However, reducing the sample enhanced performance, indicating big data complexity. Improved techniques like heuristic feature selection enabled effective leveraging of the nationwide data. This study provides meaningful insights into predictive modeling methodologies and influential features for forecasting heart failure readmissions.

A modified model for predicting mortality after transjugular intrahepatic portosystemic shunt: A multicentre study

BACKGROUND AND AIMS

The transjugular intrahepatic portosystemic shunt has controversial survival benefits; thus, patient screening should be performed preoperatively. In this study, we aimed to develop a model to predict post-transjugular intrahepatic portosystemic shunt mortality to aid clinical decision making.

METHODS

A total of 811 patients undergoing transjugular intrahepatic portosystemic shunt from five hospitals were divided into the training and external validation data sets. A modified prediction model of post-transjugular intrahepatic portosystemic shunt mortality (ModelMT ) was built after performing logistic regression. To verify the improved performance of ModelMT , we compared it with seven previous models, both in discrimination and calibration. Furthermore, patients were stratified into low-, medium-, high- and extremely high-risk subgroups.

RESULTS

ModelMT demonstrated a satisfying predictive efficiency in both discrimination and calibration, with an area under the curve of .875 in the training set and .852 in the validation set. Compared to previous models (ALBI, BILI-PLT, MELD-Na, MOTS, FIPS, MELD, CLIF-C AD), ModelMT showed superior performance in discrimination by statistical difference in the Delong test, net reclassification improvement and integrated discrimination improvement (all p < .050). Similar results were observed in calibration. Low-, medium-, high- and extremely high-risk groups were defined by scores of ≤160, 160-180, 180-200 and >200, respectively. To facilitate future clinical application, we also built an applet for ModelMT .

CONCLUSIONS

We successfully developed a predictive model with improved performance to assist in decision making for transjugular intrahepatic portosystemic shunt according to survival benefits.

Taking after a parent: Phenotypic resemblance and the professional familialisation of genomics

This article draws on 2 years' worth of ethnographic observation of team meetings to explore decision-making in an NHS clinical genomics service. The focus of discussions was on ambiguous genomic results known as VUS or Variants of Uncertain Significance, which may be pathogenic but which also may turn out to be benign. In examining decision-making around such results, we note how, in contrast to much policy and promotional material in this area, clinicians in these meetings (clinical geneticists and genetic counsellors) place great emphasis on parental phenotypes and whether the parents of a patient share the symptoms and signs of the suspected condition. This information is then combined with the result of genomic tests to decide whether the variant a patient has is responsible for their condition. This article explores the way in which clinicians attempt to flexibly enrol parents into genomic explanations through informal diagnosis of their possible phenotypes and the way in which actually meeting parents allows some clinicians to trump explanations based on documentary or photographic data. The paper sheds light on the way that earlier scholarly understandings of such decisions (around, say dysmorphology) remain relevant and explores claims that laboratory tests overrule clinical decision-making.

Current Rehabilitation Practices and Return to Sports Criteria After Anterior Cruciate Ligament Reconstruction: A Survey of Physical Therapists in Saudi Arabia

CONTEXT

With the high prevalence of anterior cruciate ligament rupture among young and active individuals, rehabilitation after the injury and surgery should meet the current evidence-based recommendations to restore knee function and reduce the risk of further injury. This study aimed to investigate the current rehabilitation practices and return to sports (RTS) criteria after anterior cruciate ligament reconstruction (ACLR) among physical therapists in Saudi Arabia.

DESIGN

Online cross-sectional survey-based study.

METHODS

A total of 177 physical therapists in Saudi Arabia participated in this survey. The survey included questions about the preferred postoperative timing and frequency of rehabilitation, current views on the importance of preoperative and postoperative rehabilitation to the overall outcomes, the timeframe of RTS, and the decision-making process to RTS.

RESULTS

Most therapists (96.6%) believed preoperative rehabilitation was essential/important to postoperative outcomes. Two-thirds encouraged patients to start rehabilitation program within 1 to 4 days immediately post-ACLR. RTS was permitted 6 to 9 months post-ACLR by 60% of therapists if satisfied with patient progress and capacity. Factors considered before RTS included knee strength (72.9%), functional capacity (86.4%), lower limb and trunk mechanics (62.7%), and psychological readiness (42.2%). Knee strength was assessed by manual muscle testing (39%), handheld dynamometry (15.3%), and isokinetic dynamometer (13.6%). While 60% of the therapists used single-limbed hop for distance for evaluating functional capacity, only 27.1% used a hop test battery.

CONCLUSIONS

The surveyed physical therapists in Saudi Arabia demonstrated variations in the current rehabilitation practices and RTS criteria post-ACLR. Over half of the surveyed therapists considered preoperative rehabilitation essential to postoperative outcomes. However, the therapists should update their perspective with current evidence-based practice regarding the RTS timeframe, psychological readiness assessment for RTS, and knee strength evaluation using objective measurements.

Digital Twins for More Precise and Personalized Treatment

The use of Digital Twins (DTs) or the digital replicas of physical entities has provided benefits to several industry sectors, most notably manufacturing. To date, the application of DTs in the healthcare sector has been minimal, however. But, as pressure increases for more precise and personalized treatments, it behooves us to investigate the potential for DTs in the healthcare context. As a proof-of-concept demonstration prior to working with real patients, we attempt in this paper, to explore the potential for creating and using DTs. We do this in a synthetic environment at this stage, making use of data that is all computer-generated. DTs of synthetic present patients are created making use of data of synthetic past patients. In the real world, the clinical objective for creating such DTs of real patients would be to enable enhanced real-time clinical decision support to enable more precise and personalized care. The objective of the numerical experiment reported in this paper, is to envisage the possibilities and challenges of such an approach. We attempt to better understand the strengths and weaknesses of applying DTs in the healthcare context to support more precise and personalized treatments.

Using Clinical Simulation to Evaluate AI-Enabled Decision Support

Clinical simulation is a useful method for evaluating AI-enabled clinical decision support (CDS). Simulation studies permit patient- and risk-free evaluation and far greater experimental control than is possible with clinical studies. The effect of CDS assisted and unassisted patient scenarios on meaningful downstream decisions and actions within the information value chain can be evaluated as outcome measures. This paper discusses the use of clinical simulation in CDS evaluation and presents a case study to demonstrate feasibility of its application.

Case-Based Learning in a Simulated Electronic Medical Record: Digital Health Education for Nursing Students

Nursing graduates require competence in the use of digital health technologies. The Department of Nursing at the University of Melbourne has integrated an Electronic Medical Record (EMR) training platform into the entry-to-practice curriculum to enhance students' digital literacy. The Case Based Learning (CBL) software, developed by CSIRO and the University of Queensland, presents students with custom-built simulated cases in an EMR. Over 300 entry-to-practice students have used the CBL in 2022. Student experience, acceptability and usability of this software is reported. Data was collected via Qualtrics XM© survey. Student feedback suggests the software was easy to use and has the potential to enhance their understanding of digital health. Students suggested adjustments to the software to maximise their opportunities for clinical decision-making and improve fidelity.

The Application of Large Language Models for Radiologic Decision Making

BACKGROUND AND PURPOSE

Large language models (LLMs) have seen explosive growth, but their potential role in medical applications remains underexplored. Our study investigates the capability of LLMs to predict the most appropriate imaging study for specific clinical presentations in various subspecialty areas in radiology.

METHODS AND MATERIALS

Chat Generative Pretrained Transformer (ChatGPT), by OpenAI and Glass AI by Glass Health were tested on 1,075 clinical scenarios from 11 ACR expert panels to determine the most appropriate imaging study, benchmarked against the ACR Appropriateness Criteria. Two responses per clinical presentation were generated and averaged for the final clinical presentation score. Clinical presentation scores for each topic area were averaged as its final score. The average of the topic scores within a panel determined the final score of each panel. LLM responses were on a scale of 0 to 3. Partial scores were given for nonspecific answers. Pearson correlation coefficient (R-value) was calculated for each panel to determine a context-specific performance.

RESULTS

Glass AI scored significantly higher than ChatGPT (2.32 ± 0.67 versus 2.08 ± 0.74, P = .002). Both LLMs performed the best in the Polytrauma, Breast, and Vascular panels, and performed the worst in the Neurologic, Musculoskeletal, and Cardiac panels. Glass AI outperformed ChatGPT in 10 of 11 panels, except Obstetrics and Gynecology. Maximum agreement was in the Pediatrics, Neurologic, and Thoracic panels, and the most disagreement occurred in the Vascular, Breast, and Urologic panels.

CONCLUSION

LLMs can be used to predict imaging studies, with Glass AI's superior performance indicating the benefits of extra medical-text training. This supports the potential of LLMs in radiologic decision making.

Physically Active Adults with Low Back Pain do not Demonstrate Altered Deadlift Mechanics: A Novel Application of Myotonometry to Estimate Inter-Muscular Load Sharing

Background

Rehabilitation clinicians that work with physically active populations are challenged with how to safely return patients back to performing deadlift movements following low back injury. Application of reliable and valid tests and measures to quantify impairments related to low back pain (LBP) enhances clinical decision making and may affect outcomes. Myotonometry is a non-invasive method to assess muscle stiffness which has demonstrated significant associations with physical performance and musculoskeletal injury.

Hypothesis/Purpose

The purpose of this study was to compare the stiffness of trunk (lumbar multifidus [LM] and longissimus thoracis [LT]) and lower extremity (vastus lateralis [VL] and biceps femoris [BF]) muscles between individuals with and without LBP during the lying, standing, and deadlifting body positions.

Study Design

Cross-sectional cohort comparison.

Methods

Muscle stiffness measures were collected in the VL, BF, LM, and LT muscles with participants in lying (supine and prone), standing, and the trap bar deadlift position. Separate analyses of covariance were conducted to compare absolute and relative muscle stiffness between the groups for each muscle and condition.

Results

Sixty-eight participants (41 female, 21.3 years, 34 LBP) volunteered for the study. Within the deadlift condition there was a significantly greater increase in the percent-muscle stiffness change in the VL (p = .029, 21.9%) and BF (p = .024, 11.2%) muscles in the control group than in the LBP group. There were no differences in percent-muscle stiffness changes for the standing condition nor were there any absolute muscle stiffness differences between the two groups for the three conditions.

Conclusion

No differences in muscle stiffness were identified in the lying, standing, or deadlifting conditions between participants with and without LBP. Differences in percent stiffness changes were noted between groups for the deadlift position, however the differences were modest and within measurement error. Future studies should investigate the utility of myotonometry as a method to identify LBP-related impairments that contribute to chronic and/or recurrent low back injury.

Level of Evidence

Level 3.

How is complexity measured and detected among community dwelling older people aged 65 years and over? A scoping review

AIM

To identify and explore tools that measured and detected complexity of care among community dwelling people aged 65 years and older.

DATA SOURCES

Databases were searched for articles published up to 23 September 2022 including CINAHL, EMBASE and MEDLINE, Cochrane database for trials and grey literature.

METHODS

A scoping review was conducted and reported in accordance with the PRISMA guidelines. Eligible articles included those with participants aged over 65 years, living in the community and studies that included care complexity detection or assessment and how this related to care delivered. Covidence was used to screen titles, abstracts and full-text articles.

RESULTS

Eighteen full texts were reviewed; four studies were included in the final review. All selected studies included people aged over 65 years living in the community. A high level of reliability for the items included in the interventions was found. The selected studies included tools for assessing older person's needs with nurses involved in the assessment.

CONCLUSION

The review identified four tools for measuring complexity in community dwelling older people. Two tools have the capacity to objectively measure complexity due to the holistic nature of items included and appear easy to use to support clinical judgement decisions.

IMPACT

The review places a spotlight on the concept of complexity and highlights the lack of definition of care complexity. The synthesized result highlights the need to explore detection of care complexity of older people further and consider ways of supporting clinical judgement and decision making of community nurses. The use of a validated tool may enhance clinical judgement regarding care complexity and may lead to a more consistent and timely approach to care.

PATIENT OR PUBLIC CONTRIBUTION

During the development phase, the study was presented to a consumer group from the researcher's workplace.

PROSPERO REGISTRATION

CRD42022299336.

Experts' perspectives on how to promote implicit and explicit motor learning in children: A mixed-methods study

BACKGROUND

Little is known about how motor learning strategies (MLSs) can promote implicit and explicit motor learning processes. This study aimed to explore experts' perspectives on therapists' use of MLSs to promote specific learning processes in children with and without developmental coordination disorder (DCD).

METHODS

In this mixed-methods study, two consecutive digital questionnaires were used to ascertain the opinions of international experts. Questionnaire 2 explored the findings of Questionnaire 1 in greater depth. In order to reach a certain level of agreement about the classification of MLSs as promoting either (more) implicit or (more) explicit motor learning, 5-point Likert scales were used in addition to open-ended questions. The open-ended questions were analysed with a conventional analysis approach. Open coding was performed by two reviewers independently. Categories and themes were discussed within the research team, taking both questionnaires as one dataset.

RESULTS

Twenty-nine experts from nine different countries with different backgrounds in research, education and/or clinical care completed the questionnaires. The results of the Likert scales showed large variation. Two themes emerged from the qualitative analyses: (1) Experts found it difficult to classify MLSs as promoting either implicit or explicit motor learning, and (2) experts stressed the need for clinical decisionmaking when choosing MLSs.

CONCLUSIONS

Insufficient insight was gained into how MLSs could promote (more) implicit or (more) explicit motor learning in children in general and in children with DCD specifically. But this study demonstrated the importance of clinical decisionmaking to model and adapt MLSs to child, task and environment, with therapists' knowledge of MLSs being an important prerequisite. Research is needed to better understand the various learning mechanisms of children and how MLSs can be used to manipulate these mechanisms.

Teaching Strategies for Developing Clinical Reasoning Skills in Nursing Students: A Systematic Review of Randomised Controlled Trials

BACKGROUND

Clinical reasoning (CR) is a holistic and recursive cognitive process. It allows nursing students to accurately perceive patients' situations and choose the best course of action among the available alternatives. This study aimed to identify the randomised controlled trials studies in the literature that concern clinical reasoning in the context of nursing students.

METHODS

A comprehensive search of PubMed, Scopus, Embase, and the Cochrane Controlled Register of Trials (CENTRAL) was performed to identify relevant studies published up to October 2023. The following inclusion criteria were examined: (a) clinical reasoning, clinical judgment, and critical thinking in nursing students as a primary study aim; (b) articles published for the last eleven years; (c) research conducted between January 2012 and September 2023; (d) articles published only in English and Spanish; and (e) Randomised Clinical Trials. The Critical Appraisal Skills Programme tool was utilised to appraise all included studies.

RESULTS

Fifteen papers were analysed. Based on the teaching strategies used in the articles, two groups have been identified: simulation methods and learning programs. The studies focus on comparing different teaching methodologies.

CONCLUSIONS

This systematic review has detected different approaches to help nursing students improve their reasoning and decision-making skills. The use of mobile apps, digital simulations, and learning games has a positive impact on the clinical reasoning abilities of nursing students and their motivation. Incorporating new technologies into problem-solving-based learning and decision-making can also enhance nursing students' reasoning skills. Nursing schools should evaluate their current methods and consider integrating or modifying new technologies and methodologies that can help enhance students' learning and improve their clinical reasoning and cognitive skills.

The diagnostic likelihood ratio function and modified test for trend: Identifying, evaluating, and validating nontraditional biomarkers in case-control studies

The ROC curve and its associated summary statistic, the AUC, are used to identify informative diagnostic biomarkers under the assumption that risk of disease is a monotone function of the biomarker. We refer to biomarkers that meet this assumption as traditional, and those that do not as nontraditional. Nontraditional biomarkers most often arise when both low and high biomarker values are associated with an outcome of interest, such as blood pressure with medical complications or leukocyte count with ICU prognosis. Since nontraditional biomarkers do not meet the assumptions for ROC-based analyses, we propose using the discrete diagnostic likelihood ratio (DLR) function to evaluate a wider class of informative biomarkers. We obtain the DLR function using the multinomial logistic regression (MLR) model to improve upon existing estimation techniques, and implement a likelihood ratio test to identify candidate informative traditional and nontraditional biomarkers. We propose a modification of the Cochran-Armitage test for trend that separates biomarkers deemed informative into traditional and nontraditional categories. The statistical properties of the likelihood ratio test and modified test for trend are explored under simulation. Together, these methods achieve the identification, evaluation, and validation of biomarkers from early discovery research. Finally, we show that incorporating covariates into the MLR model results in a covariate-adjusted DLR function that is useful for integrating multiple sources of information in clinical decision making. The methods are applied to gene expression data from subjects with high grade serous ovarian cancer, where stage, early stage vs late stage, is the outcome of interest.

Determinants Affecting the Clinical Implementation of a Molecularly Informed Molecular Tumor Board Recommendation: Experience from a Tertiary Cancer Center

Molecular Tumor Boards (MTBs) converge state-of-the-art next-generation sequencing (NGS) methods with the expertise of an interdisciplinary team consisting of clinicians, pathologists, human geneticists, and molecular biologists to provide molecularly informed guidance in clinical decision making to the treating physician. In the present study, we particularly focused on elucidating the factors impacting on the clinical translation of MTB recommendations, utilizing data generated from gene panel mediated comprehensive genomic profiling (CGP) of 554 patients at the MTB of the Comprehensive Cancer Center Erlangen, Germany, during the years 2016 to 2020. A subgroup analysis of cases with available follow-up data (n = 332) revealed 139 cases with a molecularly informed MTB recommendation, which was successfully implemented in the clinic in 44 (31.7%) of these cases. Here, the molecularly matched treatment was applied in 45.4% (n = 20/44) of cases for ≥6 months and in 25% (n = 11/44) of cases for 12 months or longer (median time to treatment failure, TTF: 5 months, min: 1 month, max: 38 months, ongoing at data cut-off). In general, recommendations were preferentially implemented in the clinic when of high (i.e., tier 1) clinical evidence level. In particular, this was the case for MTB recommendations suggesting the application of PARP, PIK3CA, and IDH1/2 inhibitors. The main reason for non-compliance to the MTB recommendation was either the application of non-matched treatment modalities (n = 30)/stable disease (n = 7), or deteriorating patient condition (n = 22)/death of patient (n = 9). In summary, this study provides an insight into the factors affecting the clinical implementation of molecularly informed MTB recommendations, and careful considerations of these factors may guide future processes of clinical decision making.

Utilizing predictive machine-learning modelling unveils feature-based risk assessment system for hyperinflammatory patterns and infectious outcomes in polytrauma

Purpose

Earlier research has identified several potentially predictive features including biomarkers associated with trauma, which can be used to assess the risk for harmful outcomes of polytraumatized patients. These features encompass various aspects such as the nature and severity of the injury, accompanying health conditions, immune and inflammatory markers, and blood parameters linked to organ functioning, however their applicability is limited. Numerous indicators relevant to the patients` outcome are routinely gathered in the intensive care unit (ICU) and recorded in electronic medical records, rendering them suitable predictors for risk assessment of polytraumatized patients.

Methods

317 polytraumatized patients were included, and the influence of 29 clinical and biological features on the complication patterns for systemic inflammatory response syndrome (SIRS), pneumonia and sepsis were analyzed with a machine learning workflow including clustering, classification and explainability using SHapley Additive exPlanations (SHAP) values. The predictive ability of the analyzed features within three days after admission to the hospital were compared based on patient-specific outcomes using receiver-operating characteristics.

Results

A correlation and clustering analysis revealed that distinct patterns of injury and biomarker patterns were observed for the major complication classes. A k-means clustering suggested four different clusters based on the major complications SIRS, pneumonia and sepsis as well as a patient subgroup that developed no complications. For classification of the outcome groups with no complications, pneumonia and sepsis based on boosting ensemble classification, 90% were correctly classified as low-risk group (no complications). For the high-risk groups associated with development of pneumonia and sepsis, 80% of the patients were correctly identified. The explainability analysis with SHAP values identified the top-ranking features that had the largest impact on the development of adverse outcome patterns. For both investigated risk scenarios (infectious complications and long ICU stay) the most important features are SOFA score, Glasgow Coma Scale, lactate, GGT and hemoglobin blood concentration.

Conclusion

The machine learning-based identification of prognostic feature patterns in patients with traumatic injuries may improve tailoring personalized treatment modalities to mitigate the adverse outcomes in high-risk patient clusters.

Diagnostic testing in children: A qualitative study of pediatricians' considerations

AIMS AND OBJECTIVES

Studies in adult medicine have shown that physicians base testing decisions on the patient's clinical condition but also consider other factors, including local practice or patient expectations. In pediatrics, physicians and parents jointly decide on behalf of a (young) child. This might demand more explicit and more complex deliberations, with sometimes conflicting interests. We explored pediatricians' considerations in diagnostic test ordering and the factors that influence their deliberation.

METHOD

We performed in-depth, semistructured interviews with a purposively selected heterogeneous sample of 20 Dutch pediatricians. We analyzed transcribed interviews inductively using a constant comparative approach, and clustered data across interviews to derive common themes.

RESULTS

Pediatricians perceived test-related burden in children higher compared with adults, and reported that avoiding an unjustified burden causes them to be more restrictive and deliberate in test ordering. They felt conflicted when parents desired testing or when guidelines recommended diagnostic tests pediatricians perceived as unnecessary. When parents demanded testing, they would explore parental concern, educate parents about harms and alternative explanations of symptoms, and advocate watchful waiting. Yet they reported sometimes performing tests to appease parents or to comply with guidelines, because of feared personal consequences in the case of adverse outcomes.

CONCLUSION

We obtained an overview of the considerations that are weighed in pediatric test decisions. The comparatively strong focus on prevention of harm motivates pediatricians to critically appraise the added value of testing and drivers of low-value testing. Pediatricians' relatively restrictive approach to testing could provide an example for other disciplines. Improved guidelines and physician and patient education could help to withstand the perceived pressure to test.

Effects of matched vs. unmatched physical therapy interventions on pain or disability in patients with neck pain - a systematic review and meta-analysis

BACKGROUND

The interventions performed in most randomized controlled trials (RCTs) on neck pain patients are standardized, irrespective of the high heterogeneity of patients. However, clinicians tend to choose an intervention based on the patients' clinical characteristics, and thus match the treatment to the patient.

OBJECTIVES

To investigate the effectiveness of interventions matched to the clinical characteristics of patients with neck pain versus the same, but unmatched treatment for improving pain or disability.

DESIGN

A systematic review and meta-analysis conducted following Cochrane guidelines.

METHODS

Databases searches were performed from inception to September 2023. RCTs were included if the patients in the experimental group received a treatment matched to clinical presentation or to clinicians' assessment, if the patients in the control group received a similar but unmatched treatment, and if pain or disability were reported as outcome measures.

RESULTS

The literature search produced 9516 records of which 27 met the inclusion criteria. Matched exercise therapy was superior to unmatched exercise for pain (SMD -0.57; 95% CI -0.95, -0.18) and for disability (SMD -0.69; 95% CI -1.14, -0.23) at short term, but not at intermediate-term follow-up. Matched manual treatment was not superior to unmatched manual therapy for pain or for disability at short or intermediate-term follow-up.

CONCLUSIONS

Results suggest that matching exercise to movement limitation, trapezius myalgia, or forward head position may lead to better outcomes in the short term, but not in the intermediate-term. Matched manual therapy was not superior to unmatched treatment either short or intermediate-term. Further research is warranted to verify if those criteria are potentially useful matching criteria.

An immediate implant approach to replace failing maxillary anterior dentition due to orthodontically induced severe root resorption

Incomplete orthodontic therapy can lead to severe root resorption, resulting in mobile and non-restorable teeth. This clinical report presents the diagnosis, treatment planning and oral rehabilitation of a young woman with failing dentition in the anterior maxilla due to orthodontically induced root resorption. The patient's chief complaint was mobile maxillary anterior teeth 2 years after discontinuing orthodontic treatment. Radiographic and clinical evaluations revealed a missing right first premolar and left premolars and grade III mobility from the right canine to the left lateral incisor. Due to a hopeless prognosis, extraction of the maxillary anterior teeth was planned, followed by grafting procedures. Four implants were immediately placed in the fresh sockets of the canine and central sites, and a removable provisional appliance was delivered to contour the soft tissues involved. The final restorations consisted of two three-unit layered zirconia implant-supported fixed dental prostheses. Well-planned immediate implant therapy and zirconia restorations can successfully replace mobile teeth with severe root resorption caused by external surface resorption from incomplete orthodontic treatment. Combining grafting procedures during implant placement can replace hard tissue lost due to extractions, whereas provisional restorations can re-establish optimal tissue architecture in the aesthetic zone. The present case offers insight into effective strategies for treating non-compliant or uncooperative patients with failing dentition due to orthodontically induced root resorption.

Beliefs and practice patterns of spinal thrust manipulation for mechanical low back pain of physical therapists in the state of Minnesota

INTRODUCTION

The primary purpose of this study was to examine the perceptions and utilization of spinal thrust manipulation (STM) techniques of physical therapists who treat patients with low back pain (LBP) in the State of Minnesota. A secondary purpose was to investigate differences between physical therapists who perform STM and those who do not.

METHODS

A cross-sectional design was utilized through the completion of an electronic survey. 74 respondents completed the survey. Descriptive measures were recorded as frequencies for categorical data or mean ± standard deviation for continuous data. For between-group comparisons, chi-square analyses were used for categorical items of nominal or ordinal data and t-tests were utilized for continuous data. The alpha level was set at p < 0.05.

RESULT

60.2% of respondents reported using STM when treating patients with LBP. 69.9% of respondents utilize a classification system. 76.7% of individuals answered correctly regarding the Minnesota State practice act. Of those who use STM, 81.8% utilize a Clinical Prediction Rule. Respondents who use STM were more likely to have a specialist certification (chi-square = 6.471, p = 0.011) and to have completed continuing education courses on manual therapy (chi-square = 4.736, p = 0.030).

DISCUSSION/CONCLUSIONS

Physical therapists who perform STM are more likely to have a better understanding of their state practice act, be board certified, and have completed continuing education in manual therapy.

Clinical supervision strategies, learning, and critical thinking of nursing students

OBJECTIVE

To identify the supervisory strategies that Nursing students consider facilitators of the development of critical thinking skills in clinical teaching.

METHODS

This is a qualitative study, within the interpretative paradigm, using the focus group methodology. Eight undergraduate nursing students participated in the study.

RESULTS

Participants recognized the indispensability of critical thinking for professional responsibility and quality of care and highlighted the importance of using supervisory strategies adapted to their needs, learning objectives, and the context of clinical practice.

FINAL CONSIDERATIONS

This study highlights the urgent need to establish, within the Nursing curricula, clinical supervision strategies that promote critical thinking and favor the development of skills for good clinical judgment, problem solving, and safe, effective, and ethical decision-making.

Use of Large Language Models to Predict Neuroimaging

PURPOSE

Large language models (LLMs) have demonstrated a level of competency within the medical field. The aim of this study was to explore the ability of LLMs to predict the best neuroradiologic imaging modality given specific clinical presentations. In addition, the authors seek to determine if LLMs can outperform an experienced neuroradiologist in this regard.

METHODS

ChatGPT and Glass AI, a health care-based LLM by Glass Health, were used. ChatGPT was prompted to rank the three best neuroimaging modalities while taking the best responses from Glass AI and the neuroradiologist. The responses were compared with the ACR Appropriateness Criteria for 147 conditions. Clinical scenarios were passed into each LLM twice to account for stochasticity. Each output was scored out of 3 on the basis of the criteria. Partial scores were given for nonspecific answers.

RESULTS

ChatGPT and Glass AI scored 1.75 and 1.83, respectively, with no statistically significant difference. The neuroradiologist scored 2.20, significantly outperforming both LLMs. ChatGPT was also found to be the more inconsistent of the two LLMs, with the score difference between both outputs being statistically significant. Additionally, scores between different ranks output by ChatGPT were statistically significant.

CONCLUSIONS

LLMs perform well in selecting appropriate neuroradiologic imaging procedures when prompted with specific clinical scenarios. ChatGPT performed the same as Glass AI, suggesting that with medical text training, ChatGPT could significantly improve its function in this application. LLMs did not outperform an experienced neuroradiologist, indicating the need for continued improvement in the medical context.

Development and applicability of a risk assessment tool for hospital-acquired mobility impairment in ambulatory older adults

BACKGROUND

Mobility loss is common in hospitalized older adults, and resources to prevent mobility impairment are finite. Our goal was to use routinely collected data to develop a risk assessment tool that identifies individuals at risk of losing the ability to walk during hospitalization on the first hospital day. Second, we determined if the tool could inform the use of mobility-preserving interventions.

METHODS

We included patients admitted to a general medical service, aged ≥65 years, who walked occasionally or frequently on admission (Braden Scale Activity subset > = 3). Patients were considered to have a new mobility impairment if, at discharge, their ability to walk was severely limited or nonexistent or they were confined to bed (Braden Scale Activity subset <3). We used predictors available on the first hospital day to develop (2017-18 cohort) and validate (2019 cohort) a risk assessment tool. We determined the association between predicted risk and therapy use in the validation cohort to highlight the model's clinical utility.

RESULTS

5542 patients were included (median age 76 years, 48% women); 7.6% were discharged unable to walk. The model included 5 predictors: age, medication administrations, Glasgow Coma Scale verbal score, serum albumin, and urinary catheter presence. In the validation cohort, the model discriminated well (c-statistic 0.75) and was strongly associated with hospital-acquired mobility impairment (lowest decile 1%, highest decile 25%). In the validation cohort, therapy consultation ordering increased linearly with predicted risk; however, observed mobility impairment increased exponentially.

CONCLUSION

The tool assesses the risk of mobility impairment in all ambulatory hospitalized older adults on the first hospital day. Further, it identifies at-risk older adults who may benefit from mobility interventions.

Clinical decision-making and the nursing process in digital health systems: An integrated systematic review

AIMS

To identify how the nursing process (assessment, planning, intervention and outcome evaluation) has been incorporated into digital health systems (electronic medical records, electronic care plans and clinical decision support systems) to gain an understanding of known benefits and challenges posed to nurses' decision-making processes.

BACKGROUND

Nursing terminologies, including the International Classification for Nursing Practice (ICNP), and Nursing Minimum Data Set's (NMDS), have been developed to improve standardised language integration of components of nursing care into digital systems. However, there is limited evidence regarding whether the complete nursing process is effectively being incorporated into digital health systems.

METHODS

An integrative systematic review following PRISMA guidelines. A search strategy was applied to extract articles from included databases: CINAHL, MEDLINE, SCOPUS and Web of Science Core Collection. Articles were limited to English language and published January 2007-March 2022 and assessed using a pre-determined eligibility criteria. Quality assessment and a narrative synthesis were conducted.

RESULTS

A total of 3321 articles were identified, and 27 studies included. There were (n = 10) qualitative, (n = 4) quantitative non-randomised controlled trials, (n = 3) quantitative descriptive studies and (n = 10) mixed methods. Nurse assessment and planning components were the most comprehensive phases incorporated into digital health systems, and interventions and outcome evaluation were scarcely reported.

CONCLUSIONS

Inadequate capture of nursing work is a problem unresolved by digital health systems. This omission may be hindering nurse clinical decision-making for patient care and limiting the visibility of the nursing role in health care interventions and the associated impact on patient outcomes.

RELEVANCE TO CLINICAL PRACTICE

Further research is needed on how digital systems can support nurses to apply the full nursing process and to further evaluate patient outcomes. Digital systems can support health-service level evaluation through capturing missed nursing care and the consequences on patients utilising nurse-sensitive-outcomes; however, this is not yet being realised.

Verifying measurements on Siemens Atellica® instruments using clinically acceptable analytical performance specifications

Measurements on clinical chemistry analysers must be verified to demonstrate applicability to their intended clinical use. We verified the performance of measurements on the Siemens Atellica® Solution chemistry analysers against the clinically acceptable analytical performance specifications, CAAPS, including the component of intra-individual biological variation, CVI. The relative standard uncertainty of measurement, i.e. analytical variation, CVA, was estimated for six example measurands, haemoglobin A1c in whole blood (B-HbA1c), albumin in urine (U-Alb), and the following measurands in plasma: sodium (P-Na), pancreatic amylase (P-AmylP), low-density lipoprotein cholesterol (P-LDL-C), and creatinine (P-Crea). Experimental CVA was calculated from single-instrument imprecision using control samples, variation between measurements on parallel instruments, and estimation of bias with pooled patient specimens. Each obtained CVA was compared with previously developed CAAPS. The calculated CVA was 1.4% for B-HbA1c (CAAPS 1.9% for single diagnostic testing, CAAPS 2.0% for monitoring after duplicate tests; IFCC units), 10.9% for U-Alb (CAAPS 44.9%), 1.2% for P-Na (CAAPS 0.6%, after triplicate testing 1.5%), 8.2% for P-AmylP (CAAPS 22.9%). The CVA was 4.9% for P-LDL-C (CAAPS for cardiovascular risk stratification 4.9% after four replicates), and 4.2% for P-Crea (CAAPS 8.0%). Three of the six measurands fulfilled the estimated clinical need. Results from P-Na measurements indicate a general need for improving the P-Na assays for emergency patients. It is necessary to consider CVI when creating diagnostic targets for laboratory tests, as emphasised by the CAAPS estimates of B-HbA1c and P-LDL-C.

A systematic review of measurement uncertainty visualizations in the context of standardized assessments

This systematic review summarized findings of 29 studies evaluating visual presentation formats appropriate for communicating measurement uncertainty associated with standardized clinical assessment instruments. Studies were identified through systematic searches of multiple databases (Medline, Embase, PsycInfo, ERIC, Scopus, and Web of Science). Strikingly, we found no studies which were conducted using samples of clinicians and included clinical decision-making scenarios. Included studies did however find that providing participants with information about measurement uncertainty may increase awareness of uncertainty and promote more optimal decision making. Formats which visualize the shape of the underlying probability distribution were found to promote more accurate probability estimation and appropriate interpretations of the underlying probability distribution shape. However, participants in the included studies did not seem to benefit from the additional information provided by such plots during decision-making tasks. Further explorations into how presentations of measurement uncertainty impact clinical decision making are needed to examine whether findings of the included studies generalize to clinician populations. This review provides an important overview of pitfalls associated with formats commonly used to communicate measurement uncertainty in clinical assessment instruments, and a potential starting point for further explorations into promising alternatives. Finally, our review offers specific recommendations on how remaining research questions might be addressed.

Evaluating GPT as an Adjunct for Radiologic Decision Making: GPT-4 Versus GPT-3.5 in a Breast Imaging Pilot

OBJECTIVE

Despite rising popularity and performance, studies evaluating the use of large language models for clinical decision support are lacking. Here, we evaluate ChatGPT (Generative Pre-trained Transformer)-3.5 and GPT-4's (OpenAI, San Francisco, California) capacity for clinical decision support in radiology via the identification of appropriate imaging services for two important clinical presentations: breast cancer screening and breast pain.

METHODS

We compared ChatGPT's responses to the ACR Appropriateness Criteria for breast pain and breast cancer screening. Our prompt formats included an open-ended (OE) and a select all that apply (SATA) format. Scoring criteria evaluated whether proposed imaging modalities were in accordance with ACR guidelines. Three replicate entries were conducted for each prompt, and the average of these was used to determine final scores.

RESULTS

Both ChatGPT-3.5 and ChatGPT-4 achieved an average OE score of 1.830 (out of 2) for breast cancer screening prompts. ChatGPT-3.5 achieved a SATA average percentage correct of 88.9%, compared with ChatGPT-4's average percentage correct of 98.4% for breast cancer screening prompts. For breast pain, ChatGPT-3.5 achieved an average OE score of 1.125 (out of 2) and a SATA average percentage correct of 58.3%, as compared with an average OE score of 1.666 (out of 2) and a SATA average percentage correct of 77.7%.

DISCUSSION

Our results demonstrate the eventual feasibility of using large language models like ChatGPT for radiologic decision making, with the potential to improve clinical workflow and responsible use of radiology services. More use cases and greater accuracy are necessary to evaluate and implement such tools.

Decline of thrombolysis rates before endovascular therapy in patients with acute anterior circulation large vessel occlusion ischemic stroke: A multicenter analysis from the German Stroke Registry

INTRODUCTION

In recent years, the role of intravenous thrombolysis (IVT) before endovascular stroke treatment (EVT) has been discussed intensively. Whether the discussion was accompanied by changing rates of bridging IVT is unknown.

METHODS

Data were extracted from the prospectively maintained German Stroke Registry, including patients treated with EVT at one of 28 stroke centers in Germany between 2016 and 2021. Primary outcome parameters were the rate of bridging IVT (a) in the entire registry cohort and (b) in patients without formal contraindications to IVT (i.e. recent oral anticoagulants, time window ⩾4.5 h, extensive early ischemic changes) adjusted for demographic and clinical confounders.

RESULTS

10,162 patients (52.8% women, median age 77 years, median National Institutes of Health Stroke Scale score 14) were analyzed. In the entire cohort, the rate of bridging IVT decreased from 63.8% in 2016 to 43.6% in 2021 (average absolute annual decrease 3.1%, 95% CI 2.4%-3.8%), while the proportion of patients with at least one formal contraindication increased by only 1.2% annually (95% CI 0.6%-1.9%). Among 5460 patients without record of formal contraindications, the rate of bridging IVT decreased from 75.5% in 2016 to 63.2% in 2021 and was significantly associated with admission date in a multivariable model (average absolute annual decrease 1.4%, 95% CI 0.6%-2.2%). Clinical factors associated with lower odds of bridging IVT included diabetes mellitus, carotid-T-occlusion, dual antiplatelet therapy, and direct admission to a thrombectomy center.

CONCLUSION

We observed a substantial decline in bridging IVT rates independent of demographic confounders and not explained by an increase in contraindications. This observation deserves further exploration in independent populations.

Prehospital Clinical Decision-Making for Medication Administration for Behavioral Emergencies

Introduction

Prehospital behavioral emergency protocols provide guidance on when a medication may be necessary for prehospital behavioral emergency. However, the final decision of which medication to administer to a patient is made independently by paramedics. The authors evaluated circumstances in a prehospital behavioral emergency when paramedics considered chemical restraints, and factors that go into choosing which medications to administer.

Methods

A qualitative research design was used involving paramedics from a Midwestern County in the United States, between November 18 and 26, 2019. A total of 149 paramedics were asked to complete a survey consisting of two open-ended questions to measure their clinical decision-making process and factors considered when selecting a medication from a behavioral emergencies protocol. An immersion-crystallization approach was used to analyze the content of the interviews.

Results

There was a 53% (n = 79) response rate. Six major themes emerged regarding the paramedics' decisions to use medication for behavioral emergencies: safety of the patients and paramedics, inability to use calming techniques, severity of the behavioral emergency, inability to assess the patient due to presentation, etiology of the behavioral episode, and other factors, such as age, size, and weight of the patient. Six major themes emerged regarding factors considered when choosing medication for behavioral emergency: etiology of the behavioral emergency, patient presentation, the patients' history and age, desired effect and intended outcome of the medication, and other factors.

Conclusions

Emergency medical services (EMS) paramedics relied on several factors, such as safety of all parties involved and etiology of the behavioral emergency in deciding when, and which medication to use in a behavioral emergency. The findings could help EMS administrators to develop protocols, such as how paramedics respond and treat patients with behavioral health emergencies.

Toward a Value-Based Therapy Recommendation Model

Patient value is an important factor in clinical decision making, but conventionally, it is not incorporated in the decision processes. Clinical decision making has some clinical guidelines as a reference. There are very few value-based clinical guidelines, but knowledge about how values affect decision making is mentioned in some scattered studies in the literature. We use a literature review method to extract evidence and integrate it as part of the decision-making model. In this paper, a value-based therapy recommendation comprehensive model is proposed. A literature analysis is conducted to collect value-based evidence. The patients' values are defined and classified with fine granularity. Categorized values and candidate therapies are used in combination as filtering keywords to build this literature database. The literature analysis method generates a literature database used as a source of arguments for influencing decision making based on values. Then, a formalism model is put forward to integrate the value-based evidence with clinical evidence, and the literature databases and clinical guidelines are collected and analyzed to populate the evidence repository. During the decision-making processes, the evidence repository is utilized to match patients' clinical information and values. Decision-makers can dynamically adjust the relative importance of the two pieces of evidence to obtain a treatment plan that is more suitable for the patient. A prototype system was implemented using a case study for breast cancer and validated for feasibility and effectiveness through controlled experiments.

Vascular pathology in patients with alveolar echinococcosis: framework for assessment and clinical management - a retrospective case series

OBJECTIVE

Alveolar echinococcosis (AE) is a parasitic liver disease with infiltrative growth similar to solid organ malignancies. Major vascular damage is frequent and often remains untreated until catastrophic events precipitate. Detailed clinical and radiological assessment is required to guide individualised treatment decisions. Standardised radiological reporting templates of malignancies with profiles resembling AE are candidates for adaptation. Our objectives are to describe vascular pathology in AE and establish a framework for structured evaluation as the basis for treatment decisions and monitoring.

DESIGN

Retrospective case series.

RESULTS

69 patients (37.1%) had vascular involvement: portal vein (PV) 24.7%, hepatic vein (HV) 22.6% inferior vena cava (IVC) 13.4%. Significant stenosis/occlusion of vessels was present in 15.1% of PV, in 13.4% of HV and in 7.5% of IVC involvement. Vascular pathology needing specific treatment or monitoring was present in 8.6% of patients. The most frequent clinical presentation was high grade IVC stenosis or occlusion which was seen in 11 patients of the cohort.

CONCLUSION

Advanced AE requires early multidisciplinary assessment to prevent progressive impairment of liver function due to vascular damage. The focus at first presentation is on complete evaluation of vascular (and biliary) involvement. The focus in non-resectable AE is on prevention of vascular (and biliary) complications while suppressing growth of AE lesions by benzimidazole treatment to improve the quality of life of patients. We developed a framework for standardised vascular assessment and follow-up of patients with AE to recognise and treat complications early.

Preemptive Venoarterial Extracorporeal Membrane Oxygenation for Liver Transplantation-Judicious Candidate Selection

Portopulmonary hypertension is a relatively common pathologic condition in patients with end-stage liver disease. Traditionally, severe pulmonary hypertension is regarded as a contraindication to liver transplantation (LT) due to a high perioperative mortality rate. Recently, extracorporeal membrane oxygenation (ECMO) has been utilized for intraoperative management of LT. As venoarterial (VA) ECMO may benefit certain high-risk LT patients by reducing the ventricular workload by the equivalent of the programmed flow rate, its usage requires multidisciplinary planning with considerations of the associated complications. We highlighted two cases at our single-center institution as examples of high-risk pulmonary hypertension patients undergoing LT on planned VA ECMO. These patients both survived the intraoperative period; however, they had drastically different postoperative outcomes, generating discussions on the importance of judicious patient selection. Since ECMO has removed the barrier of intraoperative survivability, the patient selection process may need to put weight on the patient's potential for postoperative recovery and rehabilitation. Considerations on LT recipients undergoing preemptive ECMO need to expand from the ability of the patients to withstand the demands of the surgery during the immediate perioperative period to the long-term postoperative recovery course.

Diagnostic value of Kaiser score combined with breast vascular assessment from breast MRI for the characterization of breast lesions

Objectives

The Kaiser scoring system for breast magnetic resonance imaging is a clinical decision-making tool for diagnosing breast lesions. However, the Kaiser score (KS) did not include the evaluation of breast vascularity. Therefore, this study aimed to use KS combined with breast vascular assessment, defined as KS^*, and investigate the effectiveness of KS^* in differentiating benign from malignant breast lesions.

Methods

This retrospective study included 223 patients with suspicious breast lesions and pathologically verified results. The histopathological diagnostic criteria were according to the fifth edition of the WHO classification of breast tumors. The KS^* was obtained after a joint evaluation combining the original KS and breast vasculature assessment. The receiver operating characteristic (ROC) curve was used for comparing differences in the diagnostic performance between KS^* and KS, and the area under the receiver operating characteristic (AUC) was compared.

Results

There were 119 (53.4%) benign and 104 (46.6%) malignant lesions in total. The overall sensitivity, specificity, and accuracy of increased ipsilateral breast vascularity were 69.2%, 76.5%, and 73.1%, respectively. The overall sensitivity, specificity, and accuracy of AVS were 82.7%, 76.5%, and 79.4%, respectively. For all lesions included the AUC of KS^* was greater than that of KS (0.877 vs. 0.858, P = 0.016). The largest difference in AUC was observed in the non-mass subgroup (0.793 vs. 0.725, P = 0.029).

Conclusion

Ipsilaterally increased breast vascularity and a positive AVS sign were significantly associated with malignancy. KS combined with breast vascular assessment can effectively improve the diagnostic ability of KS for breast lesions, especially for non-mass lesions.

Simultaneous Quantitative SARS-CoV-2 Antigen and Host Antibody Detection and Pre-Screening Strategy at the Point of Care

As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73-0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49-0.55]) compared to case incidence rate (0.65 [0.62-0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.

Predicting Colorectal Surgery Readmission Risk: a Surgery-Specific Predictive Model

Most current predictive models for risk of readmission were primarily designed from non-surgical patients and often utilize administrative data alone. Models built upon comprehensive data sources specific to colorectal surgery may be key to implementing interventions aimed at reducing readmissions. This study aimed to develop a predictive model for risk of 30-day readmission specific to colorectal surgery patients including administrative, clinical, laboratory, and socioeconomic status (SES) data. Patients admitted to the colorectal surgery service who underwent surgery and were discharged from an academic tertiary hospital between 2017 and 2019 were included. A total of 1549 patients met eligibility criteria for this retrospective split-sample cohort study. The 30-day readmission rate of the cohort was 19.62%. A multivariable logistic regression was developed (C=0.70, 95% CI 0.61-0.73), which outperformed two internationally used readmission risk prediction indices (C=0.58, 95% CI 0.52-0.65) and (C=0.60, 95% CI 0.53-0.66). Tailored surgery-specific readmission models with comprehensive data sources outperform the most used readmission indices in predicting 30-day readmission in colorectal surgery patients. Model performance is improved by using more comprehensive datasets that include administrative and socioeconomic details about a patient, as well as clinical information used for decision-making around the time of discharge.

Limited Clinical Impact of Ultralow-Dose Computed Tomography in Suspected Community-Acquired Pneumonia

Patients clinically suspected of community-acquired pneumonia (CAP) were randomized between ultralow-dose chest computed tomography ([ULDCT] 261 patients) and chest radiograph ([CXR] 231 patients). We did not find evidence that performing ULDCT instead of CXR affects antibiotic treatment policy or patient outcomes. However, in a subgroup of afebrile patients, there were more patients diagnosed with CAP in the ULDCT group (ULDCT, 106 of 608 patients; CXR, 71 of 654 patients; P = .001).

Planning management for complex colorectal polyps: a qualitative assessment of factors influencing decision-making among colonoscopists

OBJECTIVE

Endoscopic therapy is the recommended primary treatment for most complex colorectal polyps, but high colonic resection rates are reported. The aim of this qualitative study was to understand and compare between specialities, the clinical and non-clinical factors influencing decision making when planning management.

DESIGN

Semi-structured interviews were performed among colonoscopists across the UK. Interviews were conducted virtually and transcribed verbatim. Complex polyps were defined as lesions requiring further management planning rather than those treatable at the time of endoscopy. A thematic analysis was performed. Findings were coded to identify themes and reported narratively.

RESULTS

Twenty colonoscopists were interviewed. Four major themes were identified including gathering information regarding the patient and their polyp, aids to decision making, barriers in achieving optimal management and improving services. Participants advocated endoscopic management where possible. Factors such as younger age, suspicion of malignancy, right colon or difficult polyp location lead towards surgical intervention and were similar between surgical and medical specialties. Availability of expertise, timely endoscopy and challenges in referral pathways were reported barriers to optimal management. Experiences of team decision-making strategies were positive and advocated in improving complex polyp management. Recommendations based on these findings to improve complex polyp management are provided.

CONCLUSION

The increasing recognition of complex colorectal polyps requires consistency in decision making and access to a full range of treatment options. Colonoscopists advocated the availability of clinical expertise, timely treatment and education in avoiding surgical intervention and providing good patient outcomes. Team decision-making strategies for complex polyps may provide an opportunity to coordinate and improve these issues.

Joint Asian Pacific Association of Gastroenterology (APAGE)-Asian Pacific Society of Digestive Endoscopy (APSDE) clinical practice guidelines on the use of non-invasive biomarkers for diagnosis of colorectal neoplasia

Screening for colorectal cancer (CRC) is effective in reducing CRC related mortality. Current screening methods include endoscopy based and biomarker based approaches. This guideline is a joint official statement of the Asian Pacific Association of Gastroenterology (APAGE) and the Asian Pacific Society of Digestive Endoscopy (APSDE), developed in response to the increasing use of, and accumulating supportive evidence for the role of, non-invasive biomarkers for the diagnosis of CRC and its precursor lesions. A systematic review of 678 publications and a two stage Delphi consensus process involving 16 clinicians in various disciplines was undertaken to develop 32 evidence based and expert opinion based recommendations for the use of faecal immunochemical tests, faecal based tumour biomarkers or microbial biomarkers, and blood based tumour biomarkers for the detection of CRC and adenoma. Comprehensive up-to-date guidance is provided on indications, patient selection and strengths and limitations of each screening tool. Future research to inform clinical applications are discussed alongside objective measurement of research priorities. This joint APAGE-APSDE practice guideline is intended to provide an up-to-date guide to assist clinicians worldwide in utilising non-invasive biomarkers for CRC screening; it has particular salience for clinicians in the Asia-Pacific region.

Clinical decision making of implant guidance methods guided by new classification of surgical area mouth ope-ning

When selecting implant guidance methods or judging whether the patient can be implanted, many doctors ignore or only use visual inspection to estimate a patient's mouth opening. This phenomenon often leads to failure to complete the implantation due to insufficient mouth opening or the deflection of the implant due to limited angle, resulting in the high incidence of corresponding complications. The main reason is that doctors lack accurate analysis and control of the overall geometric conditions of the intraoral surgical area, and three-dimensional position blocking of surgical instruments occurs during the operation. In the past, mouth opening was defined as the distance between the incisor edges of the upper and lower central incisors when the patient opens his mouth widely, and the implant area could be in any missing tooth position. When it is in the posterior tooth area, the specific measurement scheme of the mouth opening could not be simply equivalent to the previous measurement method in the anterior tooth area. However, how to measure quickly and conveniently the mouth opening of any surgical area to determine whether it could be implanted and meet the needs of the selected guidance method remains unclear. This paper introduces new concepts, establishes new classification and corresponding accurate measurement scheme of implant area, and establishes a decision tree of implant methods guided by the actually measured value. Results provide a quantitative basis for rational formulation and implementation of implant treatment.

Feasibility of an online consensus approach for the diagnosis of cognitive impairment and dementia in rural South Africa

INTRODUCTION

We describe the development and feasibility of using an online consensus approach for diagnosing cognitive impairment and dementia in rural South Africa.

METHODS

Cognitive assessments, clinical evaluations, and informant interviews from Cognition and Dementia in the Health and Aging in Africa Longitudinal Study (HAALSI Dementia) were reviewed by an expert panel using a web-based platform to assign a diagnosis of cognitively normal, mild cognitive impairment (MCI), or dementia.

RESULTS

Six hundred thirty-five participants were assigned a final diagnostic category, with 298 requiring adjudication conference calls. Overall agreement between each rater's independent diagnosis and final diagnosis (via the portal or consensus conference) was 78.3%. A moderate level of agreement between raters' individual ratings and the final diagnostic outcomes was observed (average κ coefficient = 0.50).

DISCUSSION

Findings show initial feasibility in using an online consensus approach for the diagnosis of cognitive impairment and dementia in remote, rural, and low-resource settings.

Decomposing clinical practice guidelines panels' deliberation into decision theoretical constructs

RATIONALE, AIMS AND OBJECTIVES: The development of clinical practice guidelines (CPG) suffers from the lack of an explicit and transparent framework for synthesising the key elements necessary to formulate practice recommendations. We matched deliberations of the American Society of Haematology (ASH) CPG panel for the management of pulmonary embolism (PE) with the corresponding decision-theoretical constructs to assess agreement of the panel recommendations with explicit decision modelling.

METHODS

Five constructs were identified of which three were used to reformulate the panel's recommendations: (1) standard, expected utility threshold (EUT) decision model; (2) acceptable regret threshold model (ARg) to determine the frequency of tolerable false negative (FN) or false positive (FP) recommendations, and (3) fast-and-frugal tree (FFT) decision trees to formulate the entire strategy for management of PE. We compared four management strategies: withhold testing versus d-dimer → computerized pulmonary angiography (CTPA) ('ASH-Low') versus CTPA→ d-dimer ('ASH-High') versus treat without testing.

RESULTS

Different models generated different recommendations. For example, according to EUT, testing should be withheld for prior probability PE < 0.13%, a clinically untenable threshold which is up to 15 times (2/0.13) below the ASH guidelines threshold of ruling out PE (at post probability of PE ≤ 2%). Three models only agreed that the 'ASH low' strategy should be used for the range of pretest probabilities of PE between 0.13% and 13.27% and that the 'ASH high' management should be employed in a narrow range of the prior PE probabilities between 90.85% and 93.07%. For all other prior probabilities of PE, choosing one model did not ensure coherence with other models.

CONCLUSIONS

CPG panels rely on various decision-theoretical strategies to develop its recommendations. Decomposing CPG panels' deliberation can provide insights if the panels' deliberation retains a necessary coherence in developing guidelines. CPG recommendations often do not agree with the EUT decision analysis, widely used in medical decision-making modelling.