Patients' and physicians' beliefs and attitudes towards integrating personalized risk estimates into patient education about left ventricular assist device therapy

BACKGROUND

Personalized risk (PR) estimates may enhance clinical decision making and risk communication by providing individualized estimates of patient outcomes. We explored stakeholder attitudes toward the utility, acceptability, usefulness and best-practices for integrating PR estimates into patient education and decision making about Left Ventricular Assist Device (LVAD).

METHODS AND RESULTS

As part of a 5-year multi-institutional AHRQ project, we conducted 40 interviews with stakeholders (physicians, nurse coordinators, patients, and caregivers), analyzed using Thematic Content Analysis. All stakeholder groups voiced positive views towards integrating PR in decision making. Patients, caregivers and coordinators emphasized that PR can help to better understand a patient's condition and risks, prepare mentally and logistically for likely outcomes, and meaningfully engage in decision making. Physicians felt it can improve their decision making by enhancing insight into outcomes, enhance tailored pre-emptive care, increase confidence in decisions, and reduce bias and subjectivity. All stakeholder groups also raised concerns about accuracy, representativeness and relevance of algorithms; predictive uncertainty; utility in relation to physician's expertise; potential negative reactions among patients; and overreliance.

CONCLUSION

Stakeholders are optimistic about integrating PR into clinical decision making, but acceptability depends on prospectively demonstrating accuracy, relevance and evidence that benefits of PR outweigh potential negative impacts on decision making quality.

Outcome prediction of cardiac arrest with automatically computed gray-white matter ratio on computed tomography images

BACKGROUND

This study aimed to develop an automated method to measure the gray-white matter ratio (GWR) from brain computed tomography (CT) scans of patients with out-of-hospital cardiac arrest (OHCA) and assess its significance in predicting early-stage neurological outcomes.

METHODS

Patients with OHCA who underwent brain CT imaging within 12 h of return of spontaneous circulation were enrolled in this retrospective study. The primary outcome endpoint measure was a favorable neurological outcome, defined as cerebral performance category 1 or 2 at hospital discharge. We proposed an automated method comprising image registration, K-means segmentation, segmentation refinement, and GWR calculation to measure the GWR for each CT scan. The K-means segmentation and segmentation refinement was employed to refine the segmentations within regions of interest (ROIs), consequently enhancing GWR calculation accuracy through more precise segmentations.

RESULTS

Overall, 443 patients were divided into derivation N=265, 60% and validation N=178, 40% sets, based on age and sex. The ROI Hounsfield unit values derived from the automated method showed a strong correlation with those obtained from the manual method. Regarding outcome prediction, the automated method significantly outperformed the manual method in GWR calculation (AUC 0.79 vs. 0.70) across the entire dataset. The automated method also demonstrated superior performance across sensitivity, specificity, and positive and negative predictive values using the cutoff value determined from the derivation set. Moreover, GWR was an independent predictor of outcomes in logistic regression analysis. Incorporating the GWR with other clinical and resuscitation variables significantly enhanced the performance of prediction models compared to those without the GWR.

CONCLUSIONS

Automated measurement of the GWR from non-contrast brain CT images offers valuable insights for predicting neurological outcomes during the early post-cardiac arrest period.

From “exceptional ethics” to public health ethics. Patients and proxies facing COVID-19. Ethics and public health during COVID-19

The study aimed to elicit the perception and ethical considerations of patients and proxies with respect both to the individual medical decisions and public health decisions made during the COVID-19 crisis. It used a qualitative, multi-center study based on semi-directive interviews, conducted by an interdisciplinary team. The analysis was conducted using a thematic analysis approach and an ethical framework. Three themes emerged from the analysis: 1) patients, unlike proxies, did not complain about their diminished role in the decision-making process. Both highlighted the importance of “basic care” as opposed to a technical approach to treatment; 2) despite the transparency of the information process, a deep “crisis of trust” has developed between citizens and public authorities; 3) although both patients and proxies accepted the limitations of personal liberties imposed in the name of public health, they argued that these limitations should respect certain boundaries, both temporal and spacial. Above all, they should not affect basic affective human relationships, even if such boundaries are a factor in an increased risk of infection. The study showed that there is a need to reconsider the definition and the main principles of public health ethics, namely transparency and proportionality.

The process of clinical decision-making in chronic wound care: A scenario-based think-aloud study

AIMS

To undertake a comprehensive investigation into both the process of information acquisition and the clinical decision-making process utilized by primary care nurses in the course of treating chronic wounds.

DESIGN

Scenario-based think-aloud method, enriched by the integration of information processing theory. The study was conducted within the framework of home care nursing organizations situated in [placeholder]. A cohort of primary care nurses (n = 10), each possessing a minimum of one year of nursing experience, was recruited through the collaboration of three home care nursing organizations.

METHODS

Two real-life clinical practice scenarios were employed for the interviews, with the researcher adopting the roles of either the patient or another clinician to enhance the realism of the think-aloud process. Each think-aloud session was promptly succeeded by a subsequent follow-up interview. The Consolidated criteria for Reporting Qualitative research checklist was followed to guarantee a consistent and complete report of the study.

RESULTS

Amidst noticeable variations, a discernible pattern surfaced, delineating three sequential concepts: 1. gathering overarching information, 2. collecting and documenting wound-specific data, and 3. interpreting information to formulate wound treatment strategies. These concepts encompassed collaborative discussions with stakeholders, while the refinement of wound treatment strategies was interwoven within both concepts 2 and 3.

CONCLUSIONS

Evident variations were identified in chronic wound care clinical decision-making, regardless of educational background or experience. These insights hold the potential to inform the development of clinical decision support systems for chronic wound management and provide guidance to clinicians in their decision-making endeavours.

Understanding general practitioners' prescribing choices to patients with chronic low back pain: a discrete choice experiment

BACKGROUND

Although NSAIDs are recommended as a first line analgesic treatment, opioids are very commonly prescribed to patients with low back pain (LBP) despite risks of harms.

AIM

This study aimed to determine factors contributing to general practitioners' (GPs') prescribing choices to patients with chronic LBP in a primary care setting.

METHOD

This discrete choice experiment (DCE) presented 210 GPs with hypothetical scenarios of a patient with chronic LBP. Participants chose their preferred treatment for each choice set, either the opioid, NSAID or neither. The scenarios varied by two patient attributes; non-specific LBP or LBP with referred leg pain (sciatica) and number of comorbidities. The three treatment attributes also varied, being: the type of opioid or NSAID, degree of pain reduction and number of adverse events. The significance of each attribute in influencing clinical decisions was the primary outcome and the degree to which GPs preferred the alternative based on the number of adverse events or the amount of pain reduction was the secondary outcome.

RESULTS

Overall, GPs preferred NSAIDs (45.2%, 95% CI 38.7-51.7%) over opioids (28.8%, 95% CI 23.0-34.7%), however there was no difference between the type of NSAID or opioid preferred. Additionally, the attributes of pain reduction and adverse events did not influence a GP's choice between NSAIDs or opioids for patients with chronic LBP.

CONCLUSION

GPs prefer prescribing NSAIDs over opioids for a patient with chronic low back pain regardless of patient factors of comorbidities or the presence of leg pain (i.e. sciatica).

Management after non-curative endoscopic resection of T1 rectal cancer

Since the introduction of population-based screening, increasing numbers of T1 rectal cancers are detected and removed by local endoscopic resection. Patients can be cured with endoscopic resection alone, but there is a possibility of residual tumor cells remaining after the initial resection. These can be located intraluminally at the resection site or extraluminally in the form of (lymph node) metastases. To decrease the risk of residual cells progressing towards more advanced disease, additional treatment is usually needed. However, with the currently available risk stratification models, it remains challenging to determine who should and should not be further treated after non-curative endoscopic resection. In this review, the different management strategies for patients with non-curatively treated T1 rectal cancers are discussed, along with the available evidence for each strategy and relevant considerations for clinical decision making. Furthermore, we provide practical guidance on the management and surveillance following non-curative endoscopic resection of T1 rectal cancer.

National survey on management of spontaneous pneumothorax from emergency department to specialised treatment: room for improvement

Introduction

Spontaneous pneumothorax (SP) affects both young, otherwise healthy individuals and older persons with known underlying pulmonary disease. Initial management possibilities are evolving and range from observation to chest tube insertion. SP guidelines suggest an individualized approach based on multiple factors such as symptoms, size of pneumothorax, comorbidity and patient preference.

Aim

With this Danish national survey we aimed to map organization of care including involved specialties, treatment choice, training, and follow-up plans to identify aspects, and optimization of spontaneous pneumothorax management.

Method

A survey developed by the national interest group for pleural medicine was sent to all departments of emergency medicine, thoracic surgery, respiratory medicine, and to relevant departments of abdominal or orthopaedic surgery.

Results

The response rate was 75 % (47 of 65). Overall, 21% of responding departments had no guideline for SP management, which was provided by multiple specialties with marked heterogeneity in choice of treatment including tube size, management during admission, and referral procedure to follow-up. Few departments required procedure training, and nearly all of the responders called for improvements in management of pneumothorax.

Conclusion

This survey suggests that SP management and care is delivered heterogeneously across Danish hospitals with marked difference between respiratory physicians, emergency physicians, general surgeons and thoracic surgeons. It is therefore likely that management is sub-optimal. There is a need for a common Danish SP guideline to ensure optimal treatment across involved specialties.

AI-driven decision support systems and epistemic reliance: a qualitative study on obstetricians' and midwives' perspectives on integrating AI-driven CTG into clinical decision making

BACKGROUND

Given that AI-driven decision support systems (AI-DSS) are intended to assist in medical decision making, it is essential that clinicians are willing to incorporate AI-DSS into their practice. This study takes as a case study the use of AI-driven cardiotography (CTG), a type of AI-DSS, in the context of intrapartum care. Focusing on the perspectives of obstetricians and midwives regarding the ethical and trust-related issues of incorporating AI-driven tools in their practice, this paper explores the conditions that AI-driven CTG must fulfill for clinicians to feel justified in incorporating this assistive technology into their decision-making processes regarding interventions in labor.

METHODS

This study is based on semi-structured interviews conducted online with eight obstetricians and five midwives based in England. Participants were asked about their current decision-making processes about when to intervene in labor, how AI-driven CTG might enhance or disrupt this process, and what it would take for them to trust this kind of technology. Interviews were transcribed verbatim and analyzed with thematic analysis. NVivo software was used to organize thematic codes that recurred in interviews to identify the issues that mattered most to participants. Topics and themes that were repeated across interviews were identified to form the basis of the analysis and conclusions of this paper.

RESULTS

There were four major themes that emerged from our interviews with obstetricians and midwives regarding the conditions that AI-driven CTG must fulfill: (1) the importance of accurate and efficient risk assessments; (2) the capacity for personalization and individualized medicine; (3) the lack of significance regarding the type of institution that develops technology; and (4) the need for transparency in the development process.

CONCLUSIONS

Accuracy, efficiency, personalization abilities, transparency, and clear evidence that it can improve outcomes are conditions that clinicians deem necessary for AI-DSS to meet in order to be considered reliable and therefore worthy of being incorporated into the decision-making process. Importantly, healthcare professionals considered themselves as the epistemic authorities in the clinical context and the bearers of responsibility for delivering appropriate care. Therefore, what mattered to them was being able to evaluate the reliability of AI-DSS on their own terms, and have confidence in implementing them in their practice.

The Effect of Mandatory Triage Questions on Triage Processes: A Qualitative Exploratory Study

INTRODUCTION

The study purpose was to obtain an understanding of both the types of questions mandated for the triage encounter in emergency departments across the United States and how emergency nurses perceive the relevance of these questions to the triage process.

METHODS

A qualitative descriptive exploratory study using focus group data was used. Data were collected at an in-person emergency nursing conference held in September 2022. Data were analyzed using Mayring's 8-step process.

RESULTS

Participants (n = 35) voiced concerns about a lack of expertise at all points in the triage process. The overarching problem is reported as data required by regulatory agencies are conflated with triage assessment information. Participants in this study reported that the conflation of the triage assessment with regulatory compliance is causing significant issues in the ability of emergency nurses to appropriately evaluate patient presentations. Thematic categories were identified as who's assessing the patients? assessment or compliance? important questions, situationally important questions, questions asked before discharge, and the lack of emergency nurse input.

DISCUSSION

The conflation of regulatory data collection with patient assessment at the initial triage encounter challenges the ability of the emergency nurse to rapidly and accurately identify patients at risk of deterioration. We recommend that initial triage processes encompass questions that focus on establishing the stability of the patient and the safety of the waiting room and include inquiry relevant to the patient presentation.

Factors Affecting the Level of Reflective Thinking and Clinical Decision-Making Skills in Medical Faculty Students

Objectives

The aim of this study is to evaluate the reflection skills of students at the Faculty of Medicine and the factors influencing these skills, as well as to measure the impact of students' reflection skills on their clinical decision-making.

Methods

This study is an educational research project conducted on fifth-year Ear Nose Throat (ENT) interns at Vakif University's Faculty of Medicine. The "Reflective Thinking Level Determination Scale" and the "Clinical Decision-Making Scale," which are valid and reliable, were used to assess the reflection skills and clinical decision-making abilities of the 125 students participating in the study.

Results

In our study, the mean score of the sub-dimensions of the Groningen Reflection Skills Scale was 77.04±5.14 for the fifth-year student population surveyed. Scores from the "Self-Reflection" and "Reflective Communication" sub-dimensions of the Groningen Reflection Skills Scale were compared based on gender, participation in summer internships, receipt of scholarships, membership in social sciences clubs, place of residence, school attended, diary-keeping habits, study styles, and cities of residence. Although there were some differences between the groups, these differences were not statistically significant. The total scores of the students on the Clinical Decision-Making Scale sub-dimensions ranged from 98 to 169, with a mean score of 146.18±10.97. A statistically positive and moderate correlation was found between the total scores of the participants on the Groningen Reflection Skills Scale and the total scores they obtained on the Clinical Decision-Making Scale (r=0.403; p=0.001).

Conclusion

Consequently, an increase in the reflection skills of participants is associated with higher clinical decision-making scores. Reflection is the primary means of transitioning students from novices to experts, enhancing both comprehensive learning and learning experiences. Therefore, every medical school should develop a training program for student reflection, along with a feedback and assessment system integrated into the curriculum.

Decision making in breast implant selection for breast reconstruction: A mixed-method study among plastic surgeons

Background

Breast implants and the (dis)advantages of their characteristics (shape, filling, surface, and brand) have been studied extensively. When selecting a specific breast implant, a plastic surgeon makes a trade-off between the various (dis)advantages. However, the factors affecting the choice of their preferred breast implant have not been studied in detail.

Methods

This is a mixed-method study. First, five plastic surgeons were interviewed to identify factors that influence their choice of a breast implant in a reconstructive setting. Second, 42 plastic surgeons were asked to state their preferred implant, weigh the collected factors, and indicate when they would deviate from their preferred implant.

Results

The interviews produced a varied list of factors that influenced the choice of breast implant, including complication rates, marketing, economic, and logistic factors. The results from the survey showed variation in preferred implant and substantial variations in the weighing of these factors. The two most important factors were "study outcomes" and "brand reputation". Ninety percent of the respondents were willing to deviate from their preferred implant, with the patient's preference being the main indication to deviate.

Conclusions

The list of factors that influence the plastic surgeons' choice of a breast implant in a reconstructive setting is extensive and their weighing showed substantial variation. Implant choice was not based solely on scientific evidence. Brand reputation was valued highly, implying that media and marketing may have considerable influence. Therefore, patients must be informed extensively about all aspects of breast implants during shared decision making to obtain true informed consent.

Respecting living kidney donor autonomy: an argument for liberalising living kidney donor acceptance criteria

Doctors routinely refuse donation offers from prospective living kidney donors with certain comorbidities such as diabetes or obesity out of concern for donor wellbeing. This refusal occurs despite the ongoing shortage of kidney transplants and the superior performance of living donor kidney transplants compared to those from deceased donors. In this paper, we argue that this paternalistic refusal by doctors is unjustified and that, within limits, there should be greater acceptance of such donations. We begin by describing possible weak and strong paternalistic justifications of current conservative donor acceptance guidelines and practices. We then justify our position by outlining the frequently under-recognised benefits and the routinely overestimated harms of such donation, before discussing the need to respect the autonomy of willing donors with certain comorbidities. Finally, we respond to a number of possible objections to our proposal for more liberal kidney donor acceptance criteria. We use the situation in Australia as our case study, but our argument is applicable to comparable situations around the world.

Correctly structured problem lists lead to better and faster clinical decision-making in electronic health records compared to non-curated problem lists: A single-blinded crossover randomized controlled trial

BACKGROUND

Correctly structured problem lists in electronic health records (EHRs) offer major benefits to patient care. Without structured lists, diagnosis information is often scatteredly documented in free text, which may contribute to errors and inefficient information retrieval. This study aims to assess whether EHRs with correctly structured problem lists result in better and faster clinical decision-making compared to non-curated problem lists.

METHODS

Two versions of two patient records (A and B) were created in an EHR training environment: one version included diagnosis information structured and coded on the problem list ("correctly structured problem list"), the other version had missing problem list diagnoses and diagnosis information partly documented in free text ("non-curated problem list"). In this single-blinded crossover randomized controlled trial, healthcare providers, who can prescribe medications, from two Dutch university medical center locations first evaluated a randomized version of patient A, then B. Participants were asked to motivate their answer to two medication prescription questions. One (test) question required information similarly presented in both record versions. The second (comparison) question required information documented on problem lists and/or in notes. The primary outcome measure was the correctness of the motivated answer to the comparison question. Secondary outcome measure was the time to answer and motivate both questions correctly.

RESULTS

As planned, 160 participants enrolled. Two were excluded for not meeting inclusion criteria. Correctly structured problem lists increased providers' ability to answer the comparison question correctly (56.3 % versus 33.5 %, McNemar odds ratio 2.80 (1.65-4.93) 95 %-CI). Median time to answer both questions correctly was significantly lower for EHRs with correctly structured problem lists (Wilcoxon-signed-rank test p = 0.00002, with incorrect answers coded equally at slowest time).

CONCLUSIONS

Correctly structured problem lists lead to better and faster clinical decision-making. Increased structured problem lists usage may be warranted for which implementation policies should be developed.

Managing common ambulatory conditions: Exploring clinical decision making performance between pharmacists and family physicians

Background

Prescribing is part of the expanded scope of practice for pharmacists in Alberta, Canada. Given these responsibilities, clinical decision making (the outcome from the diagnostic and therapeutic decision making process) is an essential skill for pharmacists. The current study compared diagnostic and therapeutic decision-making between Additional Prescribing Authority (APA) pharmacists and family physicians using a set of common ambulatory clinical cases that both practitioners could encounter in the community as part of their daily practice.

Objectives

To explore clinical decision making performance and behaviors between APA pharmacists and family physicians during the assessment and prescribing of common ambulatory conditions.

Methods

Eight written ambulatory clinical cases were developed by a panel of experts in both family medicine and pharmacy that were commonly encountered in both professions' daily practice. Participating APA pharmacists and family physicians reviewed the cases and responded with likely diagnoses, recommended treatments, and reported confidence in therapeutic choices. The responses of 18 APA pharmacists and 9 family physicians in community practices were analyzed.

Results

There were no significant differences in diagnostic accuracy, therapeutic accuracy, confidence in diagnostic choices, and confidence in therapeutic choices between APA pharmacists and family physicians to these common ambulatory presentations.

Conclusions

This study provides preliminary insights regarding the capabilities of pharmacists in the assessment of common ambulatory community conditions and suggests that APA pharmacists are making similar diagnostic and therapeutic decisions to family physicians. Future research could focus on examining the performance of pharmacists trained in different pharmacy education models, as well as their ability to provide clinical assessment in other specialties, or in more uncommon clinical scenarios.

Interventions to reduce peripheral intravenous catheter failure: An international e-Delphi consensus on relevance and feasibility of implementation

BACKGROUND

Around 1 billion peripheral intravenous catheters (PIVC) fail annually worldwide before prescribed intravenous therapy is completed, resulting in avoidable complications, dissatisfaction, and avoidable costs surging to ∼€4bn. We aimed to provide an international consensus on relevance and feasibility of clinical practice guideline recommendations to reduce PIVC failure.

METHODS

e-Delphi study with three rounds through an online questionnaire from March-September 2020 recruiting a multispecialty panel formed by clinicians, managers, academic researchers, and experts in implementation from seven developed and three developing countries, reflecting on experience in PIVC care and implementation of evidence. Further, we included a panel of chronic patients with previous experience in the insert, maintenance, and management of PIVC and intravenous therapy from Ireland and Spain as public and patient involvement (PPI) panel. All experts and patients scored each item on a 4-point Likert scale to assess the relevance and feasibility. We considered consensus descriptor in which the median was 4 with less than or equal to 1,5 interquartile intervals.

FINDINGS

Over 90% participants (16 experts) completed the questionnaire on all rounds and 100% PPI (5 patients) completed round 1 due to high consensus they achieved. Our Delphi approach included 49 descriptors, which resulted in an agreed 30 across six domains emerged from the related to (i) general asepsis and cutaneous antisepsis (n = 4), (ii) catheter adequacy and insertion (n = 3), (iii) catheter and catheter site care (n = 6), (iv) catheter removal and replacement strategies (n = 4), (v) general principles for catheter management (n = 10), and (vi) organisational environment (n = 3).

CONCLUSION

We provide an international consensus of relevant recommendations for PIVC, deemed feasible to implement in clinical settings. In addition, this methodological approach included substantial representation from clinical experts, academic experts, patient and public expertise, mitigating uncertainty during the implementation process with high-value recommendations to prevent PIVC failure based contextual and individual features, and economic resources worldwide.

Early prediction of in-hospital mortality utilizing multivariate predictive modelling of electronic medical records and socio-determinants of health of the first day of hospitalization

BACKGROUND

In France an average of 4% of hospitalized patients die during their hospital stay. To aid medical decision making and the attribution of resources, within a few days of admission the identification of patients at high risk of dying in hospital is essential.

METHODS

We used de-identified routine patient data available in the first 2 days of hospitalization in a French University Hospital (between 2016 and 2018) to build models predicting in-hospital mortality (at ≥ 2 and ≤ 30 days after admission). We tested nine different machine learning algorithms with repeated 10-fold cross-validation. Models were trained with 283 variables including age, sex, socio-determinants of health, laboratory test results, procedures (Classification of Medical Acts), medications (Anatomical Therapeutic Chemical code), hospital department/unit and home address (urban, rural etc.). The models were evaluated using various performance metrics. The dataset contained 123,729 admissions, of which the outcome for 3542 was all-cause in-hospital mortality and 120,187 admissions (no death reported within 30 days) were controls.

RESULTS

The support vector machine, logistic regression and Xgboost algorithms demonstrated high discrimination with a balanced accuracy of 0.81 (95%CI 0.80-0.82), 0.82 (95%CI 0.80-0.83) and 0.83 (95%CI 0.80-0.83) and AUC of 0.90 (95%CI 0.88-0.91), 0.90 (95%CI 0.89-0.91) and 0.90 (95%CI 0.89-0.91) respectively. The most predictive variables for in-hospital mortality in all three models were older age (greater risk), and admission with a confirmed appointment (reduced risk).

CONCLUSION

We propose three highly discriminating machine-learning models that could improve clinical and organizational decision making for adult patients at hospital admission.

Overcoming Barriers to Autologous Stem Cell Transplantation in Multiple Myeloma: Recommendations from a Multidisciplinary Roundtable Discussion

Autologous stem cell transplantation (ASCT) is a standard of care treatment for patients with multiple myeloma (MM). However, only 20% to 30% of patients with MM for whom the procedure is indicated undergo ASCT. Barriers to ASCT may be informational, financial, logistic, or cultural and may affect patients and treating oncologists. Available and accessible accurate ASCT-related information is essential to overcome these barriers. Such resources can be created by blood and marrow transplantation societies and patient advocacy groups, ideally in collaboration with MM specialists at transplant centers. An umbrella office at the society level is also recommended to connect oncologists, advocacy groups, and transplantation specialists; provide informational resources to patients; and conduct research into region- and population-specific barriers to ASCT.

Consensus on post COVID in the Spanish national health system: Results of the CIBERPOSTCOVID eDelphi study

BACKGROUND

In 2021, the Spanish Ministry of Health launched the CIBERPOSTCOVID project to establish what post COVID was. The present study reports the level of agreement among stakeholders on post COVID and its clinical and diagnostic characteristics in the Spanish health system.

METHODS

The agreement on post COVID among clinicians, public health managers, researchers and patients' representatives was explored in a real-time, asynchronous online Delphi. In a two-wave consensus, respondents rated from 1 (total disagreement) to 6 (total agreement) 67 statements related to terminology, duration, etiology, symptoms, impact on quality of life, severity, elements to facilitate diagnosis, applicability in the pediatric population, and risk factors. Consensus was reached when 70 % of ratings for a statement were 5 or 6, with an interquartile range equal or less than 1.

FINDINGS

A total of 333 professionals and patients participated in this eDelphi study. There was agreement that post COVID was "a set of multi-organic symptoms that persist or fluctuate after acute COVID-19 infection and are not attributable to other causes" with a minimum duration of 3 months. The highest levels of agreement were found in the most frequent symptoms and its impacts on everyday activities. Aspects related to the diagnostic process and the measurement of its severity reached a lower level of consensus. There was agreement on the need to rule out previous health problems and assess severity using validated functional scales. However, no agreement was reached on the risk factors or specific features in the pediatric population.

INTERPRETATION

This policy-based consensus study has allowed the characterization of post COVID generating collective intelligence and has contributed to an operational definition applicable in clinical practice, health services management and useful for research purposes in Spain and abroad. Agreements are consistent with existing evidence and reference institutions at European and international level.

PREDICT-TBI: Comparison of Physician Predictions with the IMPACT Model to Predict 6-Month Functional Outcome in Traumatic Brain Injury

BACKGROUND

Predicting functional outcome in critically ill patients with traumatic brain injury (TBI) strongly influences end-of-life decisions and information for surrogate decision makers. Despite well-validated prognostic models, clinicians most often rely on their subjective perception of prognosis. In this study, we aimed to compare physicians' predictions with the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic model for predicting an unfavorable functional outcome at 6 months after moderate or severe TBI.

METHODS

PREDICT-TBI is a prospective study of patients with moderate to severe TBI. Patients were admitted to a neurocritical care unit and were excluded if they died or had withdrawal of life-sustaining treatments within the first 24 h. In a paired study design, we compared the accuracy of physician prediction on day 1 with the prediction of the IMPACT model as two diagnostic tests in predicting unfavorable outcome 6 months after TBI. Unfavorable outcome was assessed by the Glasgow Outcome Scale from 1 to 3 by using a structured telephone interview. The primary end point was the difference between the discrimination ability of the physician and the IMPACT model assessed by the area under the curve.

RESULTS

Of the 93 patients with inclusion and exclusion criteria, 80 patients reached the primary end point. At 6 months, 29 patients (36%) had unfavorable outcome. A total of 31 clinicians participated in the study. Physicians' predictions showed an area under the curve of 0.79 (95% confidence interval 0.68-0.89), against 0.80 (95% confidence interval 0.69-0.91) for the laboratory IMPACT model, with no statistical difference (p = 0.88). Both approaches were well calibrated. Agreement between physicians was moderate (κ = 0.56). Lack of experience was not associated with prediction accuracy (p = 0.58).

CONCLUSIONS

Predictions made by physicians for functional outcome were overall moderately accurate, and no statistical difference was found with the IMPACT models, possibly due to a lack of power. The significant variability between physician assessments suggests prediction could be improved through peer reviewing, with the support of the IMPACT models, to provide a realistic expectation of outcome to families and guide discussions about end-of-life decisions.

FedScore: A privacy-preserving framework for federated scoring system development

OBJECTIVE

We propose FedScore, a privacy-preserving federated learning framework for scoring system generation across multiple sites to facilitate cross-institutional collaborations.

MATERIALS AND METHODS

The FedScore framework includes five modules: federated variable ranking, federated variable transformation, federated score derivation, federated model selection and federated model evaluation. To illustrate usage and assess FedScore's performance, we built a hypothetical global scoring system for mortality prediction within 30 days after a visit to an emergency department using 10 simulated sites divided from a tertiary hospital in Singapore. We employed a pre-existing score generator to construct 10 local scoring systems independently at each site and we also developed a scoring system using centralized data for comparison.

RESULTS

We compared the acquired FedScore model's performance with that of other scoring models using the receiver operating characteristic (ROC) analysis. The FedScore model achieved an average area under the curve (AUC) value of 0.763 across all sites, with a standard deviation (SD) of 0.020. We also calculated the average AUC values and SDs for each local model, and the FedScore model showed promising accuracy and stability with a high average AUC value which was closest to the one of the pooled model and SD which was lower than that of most local models.

CONCLUSION

This study demonstrates that FedScore is a privacy-preserving scoring system generator with potentially good generalizability.

The relation between thrombus burden and early mortality risk in inpatients diagnosed with COVID-19-related acute pulmonary embolism: a retrospective cohort study

BACKGROUND

COVID-19-related acute pulmonary thromboembolism (APE) is associated with poor outcomes in patients with COVID-19. There are studies investigating the association between thrombus burden and high risk of early mortality in the pre-COVID-19 period. This study aimed to evaluate the relationship between clot burden and early mortality risk in COVID-19-related APE patients.

METHODS

In this single-center retrospective cohort study, the data of hospitalized adult patients followed up for COVID-19-related APE between April 1, 2020, and April 1, 2021, were electronically collected. A radiologist evaluated the computed tomography (CT) findings and calculated the Mastora scores to determine clot burden. The early mortality risk group of each patient was determined using 2019 the European Society of Cardiology guidelines.

RESULTS

Of the 87 patients included in the study, 58 (66.7%) were male, and the mean age was 62.5±16.2 years. There were 53 (60.9%) patients with a low risk of mortality, 18 (20.7%) with an intermediate-low risk, and 16(18.4%) with an intermediate-high/high risk. The median total simplified Mastora scores were 11.0, 18.5, and 31.5 in the low, the intermediate-low, and the intermediate-high/high-risk groups, respectively (p = 0.002). With the 80.61% of post-hoc power of the study, intermediate-high/high early mortality risk was associated statistically significantly with the total simplified Mastora score (adj OR = 1.06, 95%CI = 1.02-1.11,p = 0.009). Total simplified Mastora score was found to predict intermediate-high/high early mortality risk with a probability of 0.740 (95% CI = 0.603-0.877): At the optimal cut-off value of 18.5, it had 75.0% sensitivity, 66.2% specificity, 33.3% positive predictive value, and 92.2% negative predictive value.

CONCLUSIONS

The total simplified Mastora score was found to be positively associated with early mortality risk and could be useful as decision support for the risk assessment in hospitalized COVID-19 patients. Evaluation of thrombus burden on CT angiography performed for diagnostic purposes can accelerate the decision of close monitoring and thrombolytic treatment of patients with moderate/high risk of early mortality.

Implementation and assessment of a novel drug interaction tool (TLC-act) in an entry-to-practice doctor of pharmacy program

BACKGROUND AND PURPOSE

Drug-drug interaction (DDI) assessment is an important role that pharmacists have in practice. Students often struggle with this complex clinical reasoning skill. TLC-Act is a tool that was created to mirror the steps and clinical checkpoints that pharmacists complete when assessing DDIs. Through integration of TLC-Act in the pharmacy curriculum, students will be better prepared for assessing and evaluating DDIs when in practice.

EDUCATIONAL ACTIVITY AND SETTING

For the 2021-2022 academic year, an asynchronous educational activity to teach students how to use TLC-Act was created and implemented. Five videos that encompassed multiple facets of TLC-Act including an introduction to the tool and how to use it, an example application of the tool to a patient case, and the clinical utility of using TLC-Act in the hospital and community settings. Students were instructed to view all five videos and then complete a patient case that focused on the DDI between ciprofloxacin and metformin.

FINDINGS

A pre- and post-activity survey was disseminated to 640 students across the first three years of the program to gather students' perspectives on the educational activity. Overall, survey response rates were 32% for the pre- and 23% for the post-activity surveys.

SUMMARY

The TLC-Act educational activity improved students' skills with managing DDIs.

A Machine-Learning Approach to Assess Factors Associated With Hospitalization of Children and Youths in Psychiatric Crisis

OBJECTIVE

The authors used a machine-learning approach to model clinician decision making regarding psychiatric hospitalization of children and youths in crisis and to identify factors associated with the decision to hospitalize.

METHODS

Data consisted of 4,786 mobile crisis response team assessments of children and youths, ages 4.0-19.5 years (mean±SD=14.0±2.7 years, 56% female), in Nevada. The sample assessments were split into training and testing data sets. A random-forest machine-learning algorithm was used to identify variables related to the decision to hospitalize a child or youth after the crisis assessment. Results from the training sample were externally validated in the testing sample.

RESULTS

The random-forest model had good performance (area under the curve training sample=0.91, testing sample=0.92). Variables found to be important in the decision to hospitalize a child or youth were acute suicidality, followed by poor judgment or decision making, danger to others, impulsivity, runaway behavior, other risky behaviors, nonsuicidal self-injury, psychotic or depressive symptoms, sleep problems, oppositional behavior, poor functioning at home or with peers, depressive or schizophrenia spectrum disorders, and age.

CONCLUSIONS

In crisis settings, clinicians were found to mostly focus on acute factors that increased risk for danger to self or others (e.g., suicidality, poor judgment), current psychiatric symptoms (e.g., psychotic symptoms), and functioning (e.g., poor home functioning, problems with peer relationships) when deciding whether to hospitalize or stabilize a child or youth. To reduce psychiatric hospitalization, community-based services should target interventions to address these important factors associated with the need for a higher level of care among youths in psychiatric crisis.

Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways

The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results.

What if It Were Me? A Qualitative Exploratory Study of Emergency Nurses' Clinical Decision Making Related to Obstetrical Emergencies in the Context of a Post-Roe Environment

INTRODUCTION

Previous research describes a significant knowledge deficit in obstetrical care in emergency settings. In a post-Roe environment, additional medicolegal challenges are documented across the obstetrics and gynecology landscape, but an understudied care setting is the emergency department, where patients may present to a practice environment where there is limited or no obstetrical care available. It is unknown how emergency nurses make decisions around these types of presentations. The purpose of this study was to explore the clinical decision-making processes of emergency nurses in the care of patients with obstetrical emergencies in the context of limited or absent access to abortion care and the impact of those processes on patient care.

METHODS

Qualitative exploratory approach using interview data (n = 13) and situational analysis was used.

RESULTS

Situational mapping uncovered human elements comprised nurses, providers, pregnant people, and families; nonhuman elements comprised legislation, education, and legal understanding. Social worlds mapping included challenges of inexperience, conflict about clinical responsibility, uncertainty about the meaning of legislation, and passivity around implications for patient care. Positional mapping yielded both the overlapping discourses around the phenomenon of interest and the area of silence around abortion-limiting legislation.

DISCUSSION

We found that emergency nurses in states with abortion care-limiting laws had significant self-reported deficits in both education and training around the management of obstetrical emergencies. In this sample, there was a surprising lack of awareness of care-limiting legislation and the clinical, ethical, and legal implications for both emergency care staff and for patients.

A dual-tracer approach using [11C]CH and [18F]FDG in HCC clinical decision making

BACKGROUND

Early detection of recurrent or progressive HCC remains the strongest prognostic factor for survival. Dual tracer PET/CT imaging with [11C]CH and [18F]FDG can further increase detection rates as both tracers entail different metabolic pathways involved in HCC development. We investigated dual-tracer PET/CT in clinical decision making in patients suspected of recurrent or progressive HCC. All HCC patients who underwent both [11C]CH and [18F]FDG PET/CT in our institute from February 2018 to December 2021 were included. Both tracer PET/CT were within 4 weeks of each other with at least 6-month follow-up. Patients underwent dual tracer PET/CT because of unexplained and suspicious CT/MRI or sudden rise of serum tumour markers. A detected lesion was considered critical when the finding had prognostic consequences leading to treatment changes.

RESULTS

Nineteen patients who underwent [11C]CH and [18F]FDG PET/CT were included of which all but six patients were previously treated for HCC. Dual-tracer critical finding detection rate was 95%, with [18F]FDG 68%, and [11C]CH 84%. Intrahepatic HCC recurrence finding rate was 65% for both tracers. [18F]FDG found more ablation site recurrences (4/5) compared to [11C]CH (2/5). Only [11C]CH found two needle tract metastases. Both tracers found 75% of the positive lymph nodes. Two new primary tumours were found, one by [18F]FDG and both by [11C]CH.

CONCLUSIONS

Our study favours a dual-tracer approach in HCC staging in high-risk patients or when conventional imaging is non-conclusive.

Design, validation and piloting of clinical vignettes to analyze critical care clinical decision processes during the COVID-19 pandemic in three different countries (Spain, Chile and United States)

Background

The use of heuristics in clinical decision-making processes increases in contexts of high uncertainty, such as those in Intensive Care Units (ICU. Given the impossibility of empirically studying their impact on real-world conditions, clinical vignettes were developed with the goal of identifying the use of heuristics in the care of critically ill patients during the COVID-19 pandemic in different clinical contexts.

Methodology

Vignettes were designed by critical care physicians in Spain to assess the use of representativeness, availability, and status quo heuristics in the care of critically ill patients during the COVID-19 pandemic. The construct, internal and external validity of the vignettes designed in Spain, the United States and Chile were evaluated. A questionnaire was piloted with the vignettes being validated in the three aforementioned countries through a computer application built for this purpose.

Results

16 study vignettes grouped into 5 models were created: each model included between 2 and 4 vignettes. The vignettes designed were closed-response vignettes with 2-3 possible alternatives. The vignettes, initially developed in Spain in Spanish, were translated to English and adapted to the Spanish used in Chile. The clinical content of the vignettes was not modified during the translation process.

Conclusions

The vignettes allow for the study of the use of heuristics in critical care clinical decision making in the context of the COVID-19 pandemic. The piloting and validation process used can serve as a model for similar multinational studies exploring clinical decision making.

Treatment decisions and the use of MEK inhibitors for children with neurofibromatosis type 1-related plexiform neurofibromas

Neurofibromatosis type 1 (NF1), the most common tumor predisposition syndrome, occurs when NF1 gene variants result in loss of neurofibromin, a negative regulator of RAS activity. Plexiform neurofibromas (PN) are peripheral nerve sheath tumors that develop in patients with NF1 and are associated with substantial morbidity and for which, until recently, the only treatment was surgical resection. However, surgery carries several risks and a proportion of PN are considered inoperable. Understanding the genetic underpinnings of PN led to the investigation of targeted therapies as medical treatment options, and the MEK1/2 inhibitor selumetinib has shown promising efficacy in pediatric patients with NF1 and symptomatic, inoperable PN. In a phase I/II trial, most children (approximately 70%) achieved reduction in tumor volume accompanied by improvements in patient-reported outcomes (decreased tumor-related pain and improvements in quality of life, strength, and range of motion). Selumetinib is currently the only licensed medical therapy indicated for use in pediatric patients with symptomatic, inoperable NF1-PN, with approval based on the results of this pivotal clinical study. Several other MEK inhibitors (binimetinib, mirdametinib, trametinib) and the tyrosine kinase inhibitor cabozantinib are also being investigated as medical therapies for NF1-PN. Careful consideration of multiple aspects of both disease and treatments is vital to reduce morbidity and improve outcomes in patients with this complex and heterogeneous disease, and clinicians should be fully aware of the risks and benefits of available treatments. There is no single treatment pathway for patients with NF1-PN; surgery, watchful waiting, and/or medical treatment are options. Treatment should be individualized based on recommendations from a multidisciplinary team, considering the size and location of PN, effects on adjacent tissues, and patient and family preferences. This review outlines the treatment strategies currently available for patients with NF1-PN and the evidence supporting the use of MEK inhibitors, and discusses key considerations in clinical decision-making.

Towards electronic health record-based medical knowledge graph construction, completion, and applications: A literature study

With the growth of data and intelligent technologies, the healthcare sector opened numerous technology that enabled services for patients, clinicians, and researchers. One major hurdle in achieving state-of-the-art results in health informatics is domain-specific terminologies and their semantic complexities. A knowledge graph crafted from medical concepts, events, and relationships acts as a medical semantic network to extract new links and hidden patterns from health data sources. Current medical knowledge graph construction studies are limited to generic techniques and opportunities and focus less on exploiting real-world data sources in knowledge graph construction. A knowledge graph constructed from Electronic Health Records (EHR) data obtains real-world data from healthcare records. It ensures better results in subsequent tasks like knowledge extraction and inference, knowledge graph completion, and medical knowledge graph applications such as diagnosis predictions, clinical recommendations, and clinical decision support. This review critically analyses existing works on medical knowledge graphs that used EHR data as the data source at (i) representation level, (ii) extraction level (iii) completion level. In this investigation, we found that EHR-based knowledge graph construction involves challenges such as high complexity and dimensionality of data, lack of knowledge fusion, and dynamic update of the knowledge graph. In addition, the study presents possible ways to tackle the challenges identified. Our findings conclude that future research should focus on knowledge graph integration and knowledge graph completion challenges.

Eliciting Low-Risk Thyroid Cancer Treatment Preferences using Clinical Vignettes: A Pilot Study

OBJECTIVE

While surgical resection has been the traditional standard treatment for small (≤1 cm), differentiated thyroid cancers, active surveillance and radiofrequency ablation are increasingly considered. The aim of this study was to explore patient preferences in thyroid cancer treatment using a series of clinical vignettes.

METHODS

Thyroid cancer survivors and general population volunteers were recruited to rank experience-driven clinical vignettes in order of preference. Rankings were compared using Wilcoxon signed rank. Formative qualitative methods were used to develop and refine clinical vignettes that captured four treatments-thyroid lobectomy (TL), total thyroidectomy (TT), active surveillance (AS), and radiofrequency ablation (RFA)-along with six treatment complications. Content was validated via interviews with five academic subspecialists.

RESULTS

Nineteen volunteers participated (10 survivors, 9 general population). Treatment complications were ranked lower than uncomplicated counterparts in 99.0% of cases, indicating excellent comprehension. Counter to our hypothesis, among uncomplicated vignettes, median rankings were 1 for AS, 2 for RFA, 3.5 for TL, and 5 for TT. Trends were consistent between thyroid cancer survivors and the general population. Active surveillance was significantly preferred over RFA (p = 0.02) and TT (p <0.01). Among surgical options, TL was significantly preferred over TT (p <0.01).

CONCLUSION

When treatments for low-risk thyroid cancer are described clearly and accurately through clinical vignettes, patients may be more likely to choose less invasive treatment options over traditional surgical resection.

Nurse decision-making when managing noradrenaline in the intensive care unit: A naturalistic observational study

OBJECTIVE

Intensive care nurses care for critically ill patients in a complex, fast paced environment. Management of noradrenaline (norepinephrine) is core business for intensive care nurses and nurse decision-making on noradrenaline is poorly understood. The study objective was to investigate decision-making processes nurses use when caring for intensive care unit patients receiving noradrenaline.

RESEARCH METHODOLOGY

A qualitative exploratory design used the Cognitive Continuum Theory as a framework for naturalistic observations and interviews in two medical/surgical intensive care units in Melbourne, Australia.

MAIN OUTCOME MEASURES

Observational and interview data from field notes and audiovisual recordings were transcribed and coded to develop themes using reflexive thematic analysis.

FINDINGS

Fourteen nurse and patient dyads were recruited to observational sessions from December 2019 to June 2021. Three major themes developed were Learning through doing; Individualised patient care; and Clinical expertise, with six supporting sub-themes. Nurses learned to manage noradrenaline experientially and developed titration and weaning strategies to support decision-making. Blood pressure targets and monitor alarms were used consistently to aid decision-making processes. Nurses were observed practicing across the cognitive continuum depending on knowledge structure, complexity of interventions, response time, and patient acuity.

CONCLUSION

Experiential learning of complex and high-risk interventions in the absence of guidelines or algorithms meant nurses developed their own titration and weaning strategies based on constant evaluation and re-evaluation of patient cues. Patient heterogeneity, cue ambiguity and a dynamic practice environment contributed to decision-making complexity that would benefit from development of evidence-based practice resources.

IMPLICATIONS FOR CLINICAL PRACTICE

Nurses learn to manage noradrenaline through experiential learning, using blood pressure targets and monitor alarms to support decision-making when titrating and weaning noradrenaline. Nurses develop noradrenaline titration and weaning strategies to support decision-making in the absence of guidelines or algorithms. Supporting nurse decision-making and streamlining practice would reduce practice variation and cognitive workload.

Clinician approaches to spinal manipulation for persistent spinal pain after lumbar surgery: systematic review and meta-analysis of individual patient data

BACKGROUND

This review aimed to identify variables influencing clinicians' application of spinal manipulative therapy (SMT) for persistent spine pain after lumbar surgery (PSPS-2). We hypothesized markers of reduced clinical/surgical complexity would be associated with greater odds of applying SMT to the lumbar region, use of manual-thrust lumbar SMT, and SMT within 1-year post-surgery as primary outcomes; and chiropractors would have increased odds of using lumbar manual-thrust-SMT compared to other practitioners.

METHODS

Per our published protocol, observational studies describing adults receiving SMT for PSPS-2 were included. PubMed, Web of Science, Scopus, OVID, PEDro, and Index to Chiropractic Literature were searched from inception to January 6, 2022. Individual patient data (IPD) were requested from contact authors when needed for selection criteria. Data extraction and a customized risk-of-bias rubric were completed in duplicate. Odds ratios (ORs) for primary outcomes were calculated using binary logistic regressions, with covariates including age, sex, symptom distribution, provider, motion segments, spinal implant, and surgery-to-SMT interval.

RESULTS

71 articles were included describing 103 patients (mean age 52 ± 15, 55% male). The most common surgeries were laminectomy (40%), fusion (34%), and discectomy (29%). Lumbar SMT was used in 85% of patients; and of these patients was non-manual-thrust in 59%, manual-thrust in 33%, and unclear in 8%. Clinicians were most often chiropractors (68%). SMT was used > 1-year post-surgery in 66% of cases. While no primary outcomes reached significance, non-reduced motion segments approached significance for predicting use of lumbar-manual-thrust SMT (OR 9.07 [0.97-84.64], P = 0.053). Chiropractors were significantly more likely to use lumbar-manual-thrust SMT (OR 32.26 [3.17-327.98], P = 0.003). A sensitivity analysis omitting high risk-of-bias cases (missing ≥ 25% IPD) revealed similar results.

CONCLUSIONS

Clinicians using SMT for PSPS-2 most often apply non-manual-thrust SMT to the lumbar spine, while chiropractors are more likely to use lumbar-manual-thrust SMT relative to other providers. As non-manual-thrust SMT may be gentler, the proclivity towards this technique suggests providers are cautious when applying SMT after lumbar surgery. Unmeasured variables such as patient or clinician preferences, or limited sample size may have influenced our findings. Large observational studies and/or international surveys are needed for an improved understanding of SMT use for PSPS-2. Systematic review registration PROSPERO (CRD42021250039).

Interpretation and Analysis of Individual Diagnostic Tests and Performance

Diagnostic tests are performed daily by bovine practitioners at the individual and population level. At the individual level, they help not only for making a diagnosis, but can also serve to rule in or rule out a specific condition, monitor treatment response, establish a prognosis, or to determine infection status. Performing an individual diagnostic test is technical; however, its interpretation and contextualization requires medical and epidemiologic skills that veterinary practitioners are able to master. This article shows the added value of the context of test prescription and correct interpretation highlighting the central role of the veterinary practitioner.

Digital cough monitoring - A potential predictive acoustic biomarker of clinical outcomes in hospitalized COVID-19 patients

PURPOSE

Recent developments in the field of artificial intelligence and acoustics have made it possible to objectively monitor cough in clinical and ambulatory settings. We hypothesized that time patterns of objectively measured cough in COVID-19 patients could predict clinical prognosis and help rapidly identify patients at high risk of intubation or death.

METHODS

One hundred and twenty-three patients hospitalized with COVID-19 were enrolled at University of Florida Health Shands and the Centre Hospitalier de l'Université de Montréal. Patients' cough was continuously monitored digitally along with clinical severity of disease until hospital discharge, intubation, or death. The natural history of cough in hospitalized COVID-19 disease was described and logistic models fitted on cough time patterns were used to predict clinical outcomes.

RESULTS

In both cohorts, higher early coughing rates were associated with more favorable clinical outcomes. The transitional cough rate, or maximum cough per hour rate predicting unfavorable outcomes, was 3·40 and the AUC for cough frequency as a predictor of unfavorable outcomes was 0·761. The initial 6 h (0·792) and 24 h (0·719) post-enrolment observation periods confirmed this association and showed similar predictive value.

INTERPRETATION

Digital cough monitoring could be used as a prognosis biomarker to predict unfavorable clinical outcomes in COVID-19 disease. With early sampling periods showing good predictive value, this digital biomarker could be combined with clinical and paraclinical evaluation and is well adapted for triaging patients in overwhelmed or resources-limited health programs.

The living kidney donor profile index fails to discriminate allograft survival: implications for its use in kidney paired donation programs

The inclusion of blood group- and human leukocyte antigen-compatible donor and recipient pairs (CPs) in kidney paired donation (KPD) programs is a novel strategy to increase living donor (LD) transplantation. Transplantation from a donor with a better Living Donor Kidney Profile Index (LKDPI) may encourage CP participation in KPD programs. We undertook parallel analyses using data from the Scientific Registry of Transplant Recipients and the Australia and New Zealand Dialysis and Transplant Registry to determine whether the LKDPI discriminates death-censored graft survival (DCGS) between LDs. Discrimination was assessed by the following: (1) the change in the Harrell C statistic with the sequential addition of variables in the LKDPI equation to reference models that included only recipient factors and (2) whether the LKDPI discriminated DCGS among pairs of prognosis-matched LD recipients. The addition of the LKDPI to reference models based on recipient variables increased the C statistic by only 0.02. Among prognosis-matched pairs, the C statistic in Cox models to determine the association of the LKDPI with DCGS was no better than chance alone (0.51 in the Scientific Registry of Transplant Recipient and 0.54 in the Australia and New Zealand Dialysis and Transplant Registry cohorts). We conclude that the LKDPI does not discriminate DCGS and should not be used to promote CP participation in KPD programs.

Clinician use of data elements from cardiovascular implantable electronic devices in clinical practice

Background

Cardiovascular implantable electronic devices (CIEDs) capture an abundance of data for clinicians to review and integrate into the clinical decision-making process. The multitude of data from different device types and vendors presents challenges for viewing and using the data in clinical practice. Efforts are needed to improve CIED reports by focusing on key data elements used by clinicians.

Objective

The purpose of this study was to uncover the extent to which clinicians use the specific types of data elements from CIED reports in clinical practice and explore clinicians' perceptions of CIED reports.

Methods

A brief, web-based, cross-sectional survey study was deployed using snowball sampling from March 2020 through September 2020 to clinicians who are involved in the care of patients with CIEDs.

Results

Among 317 clinicians, the majority specialized in electrophysiology (EP) (80.1%), were from North America (88.6%), and were white (82.2%). Over half (55.3%) were physicians. Arrhythmia episodes and ventricular therapies rated the highest among 15 categories of data presented, and nocturnal or resting heart rate and heart rate variability were rated the lowest. As anticipated, clinicians specializing in EP reported using the data significantly more than other specialties across nearly all categories. A subset of respondents offered general comments describing preferences and challenges related to reviewing reports.

Conclusion

CIED reports contain an abundance of information that is important to clinicians; however, some data are used more frequently than others, and reports could be streamlined for users to improve access to key information and facilitate more efficient clinical decision making.

What predicts large vessel occlusion in mild stroke patients?

BACKGROUND AND PURPOSE

Mild acute ischemic stroke (AIS) patients with large vessel occlusion (LVO) may benefit from thrombolysis or thrombectomy therapy. However, the predictors for LVO in mild AIS patients have not been extensively explored. We aimed to investigate the predictors for LVO in mild AIS patients.

METHODS

We collected the data of consecutive AIS patients with a National Institutes of Health Stroke Scale (NIHSS) score ≤ 5 from The Third China National Stroke Registry - a prospective nationwide registry of AIS or transient ischemic attack (TIA) patients in China from August 2015 to March 2018. Patients were divided into LVO and non-LVO group based on the vascular imaging during the hospitalization. Multivariable regression analyses involving clinical characteristics and NIHSS subitems was performed to detect the predictors for LVO.

RESULT

A total of 7653 mild AIS patients from The Third China National Stroke Registry were included in this study. Among them, 620 patients (8.1%) had LVO. The level of consciousness (adjusted odds ratio, 1.87; 95% confidence interval, 1.08 to 3.23), visual field (adjusted odds ratio, 2.10; 95% confidence interval, 1.43 to 3.06) and sensory (adjusted odds ratio, 0.75; 95% confidence interval, 0.60 to 0.94) were predictors for mild AIS patients with LVO.

CONCLUSIONS

Impaired LOC, visual field and sensory were independently predictors for LVO in mild stroke patients. Further studies are warranted to test these predictors in prehospital setting and in other population.

Quantitative approaches in clinical reproductive endocrinology

Understanding the human hypothalamic-pituitary-gonadal (HPG) axis presents a major challenge for medical science. Dysregulation of the HPG axis is linked to infertility and a thorough understanding of its dynamic behaviour is necessary to both aid diagnosis and to identify the most appropriate hormonal interventions. Here, we review how quantitative models are being used in the context of clinical reproductive endocrinology to: 1. analyse the secretory patterns of reproductive hormones; 2. evaluate the effect of drugs in fertility treatment; 3. aid in the personalization of assisted reproductive technology (ART). In this review, we demonstrate that quantitative models are indispensable tools enabling us to describe the complex dynamic behaviour of the reproductive axis, refine the treatment of fertility disorders, and predict clinical intervention outcomes.

Development of a score map to guide interpretation of WOMAC Pain scores prior to knee arthroplasty

BACKGROUND

Scores from patient reported outcome measures (PROMs) are challenging to interpret for both clinicians and patients. PROMs obtained prior to knee arthroplasty (KA) could be used to inform important decisions related to KA made by both patients and clinicians. The purpose of this study was to develop a "score map" to allow for efficient and meaningful use of PROMs scores for patients considering KA.

METHODS

Knee arthroplasty data obtained between one day and twelve months preoperatively from two multicenter studies were combined and used to develop and test the accuracy of a Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain Scale score map. To develop the score map, individual item scores were used to determine the most probable responses to items for the entire range of possible WOMAC Pain scores. Predicted WOMAC Pain scores, using the most probable response for each possible score on the score map, were compared to actual presurgical WOMAC Pain scores using Weighted Kappa (Κ_w) agreement coefficients. The score map is an easy-to-use graphical display of the entire range of WOMAC Pain scores from no pain to extreme pain for each item comprising the WOMAC Pain scale.

RESULTS

Data from 780 patients were used in the analyses. The score map predicted WOMAC Pain scores and showed substantial agreement with actual WOMAC Pain scores Κ_w = 0.68 (95 %CI = 0.58, 0.77) to Κ_w = 0.77 (95 % CI = 0.75, 0.79). Perfect prediction of actual scores occurred between 55.1 % and 62.5 % of the time for all WOMAC Pain items.

CONCLUSION

The WOMAC Pain score map has potential for facilitating a variety of important clinical decisions and discussions between patients and practitioners during healthcare encounters related to KA candidacy. For example, by comparing a patents' scores to literature-based estimates, patients may better understand how their WOMAC Pain scores compare to other persons who underwent KA, how much a score may change, on average, after surgery and whether this change might be acceptable to them.

Role of the faecal immunochemical test in patients with risk-stratified suspected colorectal cancer symptoms: A systematic review and meta-analysis to inform the ACPGBI/BSG guidelines

Background

The UK National Institute for Health and Care Excellence (NICE), recommended in 2017 the use of the faecal immunochemical test (FIT) to guide investigations in patients presenting with NICE-defined low-risk symptoms suspicious for colorectal cancer (CRC). At that time, NICE did not recommend FIT use for high-risk symptoms. This is the first systematic review to evaluate the diagnostic accuracy of FIT in NICE-defined high and low-risk symptoms and was designed to inform the joint ACPGBI/BSG guidelines.

Methods

We performed a systematic literature review and meta-analysis. PROSPERO registration number CRD42021224674. Medline and EMBASE databases were searched from inception to 31st March 2022. We included studies recruiting adult patients presenting with suspected CRC symptoms in whom FIT was performed and diagnostic accuracy data for CRC detection could be derived at a limit of detection (LoD) and/or 10 µg haemoglobin/gram faeces threshold in four commonly used analysers. FIT performance was assessed for high-risk, low-risk and individual symptoms where possible. Bivariate meta-analysis was performed where study numbers allowed.

Findings

Thirty-one studies (79566 patients) met inclusion criteria. At 10 µg/g, for "all symptoms" (n = 35,945) sensitivity and specificity were 91.0% (95% CI: 88.9, 92.7) and 75.2% (95% CI: 69.6, 80.1); for "high-risk" symptoms (n = 18,264), 88.7% (95% CI: 84.4, 92.0) and 78.5% (95% CI: 73.0, 83.2); and for "low-risk" symptoms (n = 2161), 88.7% (95% CI: 78.1, 95.3) and 88.5% (95% CI: 87.1, 89.9), respectively. At LoD, for "all symptoms" (n = 26,056) sensitivity and specificity were 94.7% (95% CI: 90.5, 97.1) and 66.5% (95% CI: 58.7, 73.6); for "high-risk" symptoms (n = 16,768), 92.8% (95% CI: 86.4, 96.3) and 70.3% (95% CI: 66.5, 73.8); and for "low-risk" symptoms (n = 2082), 94.7% (95% CI: 85.4, 98.9) and 71.9% (95% CI: 69.9, 73.9), respectively. Summary estimates were similar across different analysers.

Interpretation

FIT sensitivity for CRC detection is maximised at the LoD; its performance is similar in high and low-risk symptoms, and across different analysers where a common threshold is used. FIT performance for CRC detection is adequate and transferrable to clinical diagnostic pathways.

Funding

This review was part-funded by NHS England awarded to RM Partners. RB and RC were funded by research fellowships awarded by Croydon University Hospital.

Decision making in frail patients at risk of postoperative delirium: A case study and literature review

Preoperative frailty is strongly associated with risks of postoperative delirium. However, gaps exist in targeted recommendations for clinical decision making related to surgical interventions in frail older patients. A case study is presented involving a frail 74-year-old referred to the palliative care team for assistance with clinical decision making and in weighing risks and benefits of a surgical intervention. A literature review on the quantification of postoperative delirium risk and how this information might inform medical decision making in frail surgical patients did not identify clear clinical guidelines. In the absence of practice guidelines, the Patient Priorities Care model is proposed as a framework to help providers working with patients and caregivers facing complex medical decisions to better align interventions with patient values.

The Episodic Tool: An innovative approach to teach clinical decision making in advanced health assessment

Advanced health assessment (AHA) serves as the foundational course in advanced practice nurse education in which students apply clinical decision-making skills to gather appropriate subjective and objective data and to begin to formulate diagnostic hypotheses. Summative objective structured clinical exams (OSCEs) have been used in AHA courses to evaluate students' clinical competence. After implementing summative OSCEs in AHA, we found that students struggled with evaluations requiring critical thinking skills and subsequently designed a teaching tool to address this gap. An Episodic Tool was created for the six main body systems with a chief complaint and three age and gender combinations. In small groups, students used the tool to identify pertinent history and physical exam components for a specific age and gender. A faculty-facilitated group discussion followed. A pre/post design was used in this quality improvement project to compare OSCE and oral clinical exam (OCE) scores. OCEs were used in 2020 due to COVID-19 limitations. There was a statistically significant increase of 7 % in the mean OCE/OSCE scores after implementation of the tool (p < .001). Qualitative feedback from students and faculty suggested the tool effectively enhanced students' critical thinking and clinical decision-making skills and promoted consistency across course sections.

Prescribing of anticoagulation for atrial fibrillation in primary care

Atrial fibrillation (AF) is common in primary care patients. Many patients who could benefit from anticoagulation do not receive it. The objective of this study was to describe anticoagulation prescribing by primary care physicians. We conducted an observational study in the Cleveland Clinic Health System among patients with AF and ≥ 1 primary care appointment between 2015 and 2018 and their physicians. We estimated differences in the odds of an eligible patient receiving anticoagulation versus not and a DOAC versus warfarin using two mixed effects logistic regression models, adjusted for patient sociodemographic factors, history of falls or dementia, and CHA2DS2-VASc and HAS-BLED scores. We categorized physicians into prescribing tertiles, based on their adjusted prescribing rate, which we included as predictors in the models. Among 5253 patients, 47% received anticoagulation. Of those, 56% received a DOAC. CHA2DS2-VASc and HAS-BLED scores were not associated with anticoagulation prescription. Black race was negatively associated with receiving anticoagulation overall (aOR:0.71; 95%CI:0.56-0.89) and with prescription for a DOAC (aOR:0.65; 95%CI:0.45-0.93). Among 195 physicians, the anticoagulation prescribing rate ranged from 27% to 57% and DOAC rates ranged from 34% to 69%. Physician prescribing tertile was associated with odds of a patient receiving anticoagulation overall (aOR:1.51; 95%CI: 1.13-2.01 for the highest versus lowest tertile), but not DOAC prescriptions. When prescribing anticoagulation, physicians appear not to consider risk of stroke or bleeding but patient race is an important determinant. Seeing a physician with a high anticoagulation prescribing rate was strongly associated with a patient receiving it, suggesting a lack of individualization.

How Do Treatment Protocols Affect the Use of Engagement Practices in Youth Mental Health Services?

PURPOSE

Treatment engagement poses challenges for youth mental health providers. With the expansion of evidence-based treatments (EBTs), providers face complex decisions regarding how to engage youth and families using available information sources. This study investigated how EBT protocols are associated with the selection and delivery of engagement practices.

METHOD

Twenty engagement practices were coded in a sample of digital recordings of early treatment sessions (N = 193) from the Child STEPs in California study, a randomized trial testing modular treatment and community-implemented treatment for youth mental health problems. Data were collected on which protocols mental health providers reportedly used to guide their sessions and the protocols in which they had received training. We examined which information sources (i.e., the guiding protocol, other protocols in training history, unspecified source) were associated with observed engagement practices.

RESULTS

In sessions guided by a protocol, most observed engagement practices were accounted for by the guiding protocol (p < .001), rather than protocols in training history or unspecified sources (p < .001). In sessions not guided by a protocol, most observed practices were accounted for by training history (p < .001). Practice frequency and extensiveness was generally greater when a protocol guided the session.

CONCLUSIONS

Inclusion in protocols is associated with the selection and delivery of engagement practices, but this strategy might be insufficient for supporting the use of the full range of engagement practices supported by evidence. Supports are needed that leverage the engagement evidence base to ensure that selected practices empirically fit the engagement needs of youth and families.

Effect of consumer-grade wearable device data on clinician decision making during post-discharge telephone calls after pediatric surgery

BACKGROUND

During post-discharge telephone calls after pediatric surgery, clinicians must rely on parents/caregivers' assessment of symptoms, which can be inaccurate and often lead to unnecessary emergency department (ED) visits. Physiology (heart rate and physical activity) data from consumer-grade wearables, e.g., Fitbit™, may inform clinical decision making, yet there has been little study of clinician interpretation of this data. This study assessed whether wearable data availability, during simulated telephone calls about postoperative, post-discharge pediatric patients, affects clinician decision making.

METHODS

Three simulated telephone call scenarios were presented to a diverse group of pediatric surgery clinicians. The scenarios were based on actual postoperative patients (scenarios 1 and 3 have worrisome symptoms and scenario 2 has non-worrisome symptoms) who had worn a Fitbit™ postoperatively. Each scenario was presented to clinicians (1) without any wearable data; (2) with "concerning" wearable data; and (3) with "reassuring" wearable data. Clinicians rated their likelihood, on a scale of 1-10, of recommending an emergency department (ED) visit for the three instances of each scenario, 10 being definitely ED.

RESULTS

Twenty-four (24) clinicians participated in the study. When presented with "reassuring" wearable data, clinicians' likelihood of recommending an ED visit decreased from a median score of 6 to 1 (p < 0.001) for scenario 1 and from 9 to 3 (p < 0.001) for scenario 3. When presented with "concerning" wearable data, the median likelihood of recommending an ED visit increased from 1 to 6 (p = 0.003) for scenario 2.

CONCLUSION

This study showed that wearable data affect clinicians' decision making and may be useful in triaging postoperative, post-discharge pediatric patients.

LEVEL OF EVIDENCE

V.

How doctors manage conflicts with families of critically ill patients during conversations about end-of-life decisions in neonatal, pediatric, and adult intensive care

PURPOSE

Intensive care is a stressful environment in which team-family conflicts commonly occur. If managed poorly, conflicts can have negative effects on all parties involved. Previous studies mainly investigated these conflicts and their management in a retrospective way. This study aimed to prospectively explore team-family conflicts, including its main topics, complicating factors, doctors' conflict management strategies and the effect of these strategies.

METHODS

Conversations between doctors in the neonatal, pediatric, and adult intensive care unit of a large university-based hospital and families of critically ill patients were audio-recorded from the moment doubts arose whether treatment was still in patients' best interest. Transcripts were coded and analyzed using a qualitative deductive approach.

RESULTS

Team-family conflicts occurred in 29 out of 101 conversations (29%) concerning 20 out of 36 patients (56%). Conflicts mostly concerned more than one topic. We identified four complicating context- and/or family-related factors: diagnostic and prognostic uncertainty, families' strong negative emotions, limited health literacy, and burden of responsibility. Doctors used four overarching strategies to manage conflicts, namely content-oriented, process-oriented, moral and empathic strategies. Doctors mostly used content-oriented strategies, independent of the intensive care setting. They were able to effectively address conflicts in most conversations. Yet, if they did not acknowledge families' cues indicating the existence of one or more complicating factors, conflicts were likely to linger on during the conversation.

CONCLUSION

This study underlines the importance of doctors tailoring their communication strategies to the concrete conflict topic(s) and to the context- and family-related factors which complicate a specific conflict.

Effect of risk, expectancy, and trust on clinicians' intent to use an artificial intelligence system -- Blood Utilization Calculator

A gap exists between the capabilities of artificial intelligence (AI) technologies in healthcare and the extent to which clinicians are willing to adopt these systems. Our study addressed this gap by leveraging 'expectancy-value theory' and 'modified extended unified theory of acceptance and use of technology' to understand why clinicians may be willing or unwilling to adopt AI systems. The study looked at the 'expectancy,' 'trust,' and 'perceptions' of clinicians related to their intention of using an AI-based decision support system known as the Blood Utilization Calculator (BUC). The study used purposive sampling to recruit BUC users and administered a validated online survey from a large hospital system in the Midwest in 2021. The findings captured the significant effect of 'perceived risk' (negatively) and 'expectancy' (positively) on clinicians' 'trust' in BUC. 'Trust' was also found to mediate the relationship of 'perceived risk' and 'expectancy' with the 'intent to use BUC.' The study's findings established pathways for future research and have implications on factors influencing BUC use.

Reducing non-attendance in outpatient appointments: predictive model development, validation, and clinical assessment

Background

Non-attendance to scheduled hospital outpatient appointments may compromise healthcare resource planning, which ultimately reduces the quality of healthcare provision by delaying assessments and increasing waiting lists. We developed a model for predicting non-attendance and assessed the effectiveness of an intervention for reducing non-attendance based on the model.

Methods

The study was conducted in three stages: (1) model development, (2) prospective validation of the model with new data, and (3) a clinical assessment with a pilot study that included the model as a stratification tool to select the patients in the intervention. Candidate models were built using retrospective data from appointments scheduled between January 1, 2015, and November 30, 2018, in the dermatology and pneumology outpatient services of the Hospital Municipal de Badalona (Spain). The predictive capacity of the selected model was then validated prospectively with appointments scheduled between January 7 and February 8, 2019. The effectiveness of selective phone call reminders to patients at high risk of non-attendance according to the model was assessed on all consecutive patients with at least one appointment scheduled between February 25 and April 19, 2019. We finally conducted a pilot study in which all patients identified by the model as high risk of non-attendance were randomly assigned to either a control (no intervention) or intervention group, the last receiving phone call reminders one week before the appointment.

Results

Decision trees were selected for model development. Models were trained and selected using 33,329 appointments in the dermatology service and 21,050 in the pneumology service. Specificity, sensitivity, and accuracy for the prediction of non-attendance were 79.90%, 67.09%, and 73.49% for dermatology, and 71.38%, 57.84%, and 64.61% for pneumology outpatient services. The prospective validation showed a specificity of 78.34% (95%CI 71.07, 84.51) and balanced accuracy of 70.45% for dermatology; and 69.83% (95%CI 60.61, 78.00) for pneumology, respectively. The effectiveness of the intervention was assessed on 1,311 individuals identified as high risk of non-attendance according to the selected model. Overall, the intervention resulted in a significant reduction in the non-attendance rate to both the dermatology and pneumology services, with a decrease of 50.61% (p<0.001) and 39.33% (p=0.048), respectively.

Conclusions

The risk of non-attendance can be adequately estimated using patient information stored in medical records. The patient stratification according to the non-attendance risk allows prioritizing interventions, such as phone call reminders, to effectively reduce non-attendance rates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07865-y.

Contextualizing care: An essential and measurable clinical competency

Contextualizing care is the process of adapting research evidence to patient life context. The failure to do so, when it results in a care plan that is not likely to achieve its intended aim, is a contextual error. There is substantial evidence that contextual errors are common, adversely affect patient outcomes and health care costs, and are preventable. This evidence comes from over 5000 mostly incognito recordings of physician-patient encounters over a range of practice settings that have been analyzed along with the medical records of each encounter utilizing a specialized coding algorithm. Educational and practice improvement interventions have been tested at the medical student, resident, and attending level, each with evidence of benefits and limitations. The author argues that contextualizing care is an essential clinician competency and proposes an evidence-informed strategy for building and reinforcing the requisite skills across the continuum of medical education and professional development.

Current advancements in application of artificial intelligence in clinical decision-making by gastroenterologists in gastrointestinal bleeding

Artificial Intelligence (AI) is a type of intelligence that comes from machines or computer systems that mimics human cognitive function. Recently, AI has been utilized in medicine and helped clinicians make clinical decisions. In gastroenterology, AI has assisted colon polyp detection, optical biopsy, and diagnosis of Helicobacter pylori infection. AI also has a broad role in the clinical prediction and management of gastrointestinal bleeding. Machine learning can determine the clinical risk of upper and lower gastrointestinal bleeding. AI can assist the management of gastrointestinal bleeding by identifying high-risk patients who might need urgent endoscopic treatment or blood transfusion, determining bleeding stigmata during endoscopy, and predicting recurrence of gastrointestinal bleeding. The present review will discuss the role of AI in the clinical prediction and management of gastrointestinal bleeding, primarily on how it could assist gastroenterologists in their clinical decision-making compared to conventional methods. This review will also discuss challenges in implementing AI in routine practice.