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Background: Many patients have mixed feelings about end-of-life care, even when facing life-limiting conditions. Motivational interviewing might be useful for supporting patients in evoking reasons for advance care planning. This study aimed to examine the effects of an advance care planning program adopting motivational interviewing among palliative care patients. Methods: A two-arm parallel randomized controlled trial was conducted between January 2018 and December 2019 in the palliative care clinics of two hospitals. Adult patients who were newly referred to palliative care services, with a score of 60 or higher in the Palliative Performance Scale and mentally competent, were eligible for the study. While all participants received palliative care as usual care, those in the intervention group also received the advance care planning program through three home visits. The primary outcome was the readiness to discuss and document end-of-life care decisions, and the secondary outcomes included decisional conflict, perceived stress, and quality of life. Results: A total of 204 participants (mean [SD] age, 74.9 [10.8]; 64.7% male; 80.4% cancer) were recruited. Generalized estimating equation analyses showed a significant improvement in readiness for advance care planning behaviors in the intervention group compared with the control group at 3 months post-allocation (group-by-time interaction, appointing proxy: β = 0.80; 95% CI, 0.25–1.35; p =.005; discussing with family: β = 0.76; 95% CI, 0.22–1.31; p =.006; discussing with medical doctors: β = 0.86; 95% CI, 0.30–1.42; p =.003; documenting: β = 0.89; 95% CI, 0.36–1.41; p <.001). The proportions of signing advance directives and placing a do-not-attempt cardiopulmonary resuscitation order were significantly higher in the intervention group, with a relative risk of 3.43 (95% CI, 1.55–7.60) and 1.16 (95% CI, 1.04–1.28), respectively. The intervention group reported greater improvements in social support and value of life than the control group immediately after the intervention. Significant improvements in decisional conflicts and perceived stress were noted in both groups. Conclusions: Motivational interviewing was effective in supporting patients to resolve ambivalence regarding end-of-life care, thereby increasing their readiness for discussing and documenting their care choices. Trial registration: ClinicalTrials.gov Identifier: NCT04162912 (Registered on 14/11//2019). [ABSTRACT FROM AUTHOR]

Copyright of China Journal of Oral & Maxillofacial Surgery is the property of Shanghai Jiao Tong University, College of Stomatology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Relational autonomy is an alternative concept of autonomy in which an individual is recognized as embedded into society and influenced by relational factors. Social context, including social location, political structure, and social forces, significantly influence an agent to develop and exercise autonomy skills. The relational approach has been applied in clinical practice to identify relational factors impacting patient autonomy and decision-making, yet there is a knowledge gap in how these factors influence the demonstration of relational autonomy in the context of medical decisions of adults. Objective: The present study targeted the existing knowledge of what and how relational factors impact individuals making medical decisions using the theoretical framework of relational autonomy. Methods: A meta-synthesis study was utilized. Four electronic databases, including Embase, OVID Medline, CINAHL, and PubMed, were searched, along with gray literature and reference lists, to identify relevant studies. Results: 23 studies reporting 21 qualitative and two mixed-method studies were reviewed. Four themes emerged from the qualitative findings: (1) supportive relationships facilitate an individual's relational autonomy; (2) obtaining comprehensive information from broader sources helps individuals exercise relational autonomy; (3) undue family pressure impedes the exercising of patient relational autonomy; and (4) healthcare providers' dominant voice hampers the demonstration of relational autonomy. Conclusions: Applying relational autonomy to assist adults in making well-considered decisions is essential. The meta-synthesis suggests establishing a supportive relationship between individuals, healthcare providers, and family. A supportive relationship will allow healthcare providers to make judgments in line with an individual's values and wishes with the aim of promoting relational autonomy. Advance care planning was proposed as the effective solution to obtain a consensus between individuals and their families while respecting an individual's values and preferences. Furthermore, it is considered crucial for healthcare providers to appreciate an individual's values and incorporate their preferences into recommendations. [ABSTRACT FROM AUTHOR]

With the exponential growth in data processing capabilities and the progressive intertwining of medicine with industry, artificial intelligence (AI) has gained widespread application in the medical domain. Currently, AI is extensively utilized across various aspects of trauma orthopedics, including fracture identification, diagnosis and stratification, prevention strategies for falls and fractures, emergency management, and perioperative and prognostic risk assessments. This study delves into the research progress and challenges of AI in orthopedic trauma, including the clinical applications of machine learning, deep learning, and natural language processing. By illuminating these dynamic research avenues, this study aimed to catalyze interdisciplinary collaboration and spur innovation at the intersection of AI and orthopedic trauma, ultimately advancing the frontiers of patient care and clinical practice.

Abstract Objective With the ongoing evolution of the healthcare system and shifts in cultural paradigms, there is a pressing need to delve into the medical decision-making behaviors of general Chinese public and understand their underlying motivations. This research seeks to elucidate the prevailing tendencies in these decision-making processes and to empirically validate the pivotal factors that shape their choices, offering valuable insights for healthcare policymakers and institutions. Method A comprehensive survey was administered to 2,696 Chinese residents to examine their medical decision-making patterns. These patterns were classified into two primary categories: Unilateral Decision-making (Doctor-dominant, Family-centric, and Patient-driven subtypes) and Collaborative Decision-making (Doctor-led, Doctor-Patient, Patient-Family, and Doctor-Patient-Family subtypes). Binary logistic regression analysis was employed to empirically pinpoint the significant factors influencing these decision-making frameworks. Results The study's analysis reveals distinct preferences in medical decision-making among Chinese residents. In the Collaborative Decision-making category, chosen by 70.81% of participants, the subtypes are as follows: Doctor-led (29.90%), Doctor-Patient (13.54%), Patient-Family (2.93%), and Doctor-Patient-Family (24.44%). The Unilateral Decision-making, preferred by 29.19%, includes Doctor-dominant (23.22%), Family-centric (1.74%), and Patient-driven (4.23%) models. The preference for Collaborative Decision-making is associated with higher educational levels, specific marital statuses (particularly married but childless), and choices of rural residents' basic medical insurance or occupational basic medical insurance. In contrast, Unilateral Decision-making correlates with males, individuals with religious beliefs, certain occupational roles (like civil servants), and holders of commercial or publicly funded medical insurance. Conclusion This study elucidates the complex interplay of socio-cultural and individual determinants shaping medical decision-making in China. The findings reveal a marked inclination towards collaborative models, closely linked to educational level, marital status, and specific insurance types, reflecting an evolving trend towards participatory healthcare. Simultaneously, the persistence of unilateral models, influenced by gender, religious beliefs, and occupational roles, highlights the heterogeneity within Chinese healthcare preferences. These insights are crucial for policymakers and healthcare practitioners, underscoring the need for adaptable, culturally attuned healthcare frameworks that cater to this diversity, thereby enhancing patient engagement and healthcare efficacy.

Objective: With the ongoing evolution of the healthcare system and shifts in cultural paradigms, there is a pressing need to delve into the medical decision-making behaviors of general Chinese public and understand their underlying motivations. This research seeks to elucidate the prevailing tendencies in these decision-making processes and to empirically validate the pivotal factors that shape their choices, offering valuable insights for healthcare policymakers and institutions. Method: A comprehensive survey was administered to 2,696 Chinese residents to examine their medical decision-making patterns. These patterns were classified into two primary categories: Unilateral Decision-making (Doctor-dominant, Family-centric, and Patient-driven subtypes) and Collaborative Decision-making (Doctor-led, Doctor-Patient, Patient-Family, and Doctor-Patient-Family subtypes). Binary logistic regression analysis was employed to empirically pinpoint the significant factors influencing these decision-making frameworks. Results: The study's analysis reveals distinct preferences in medical decision-making among Chinese residents. In the Collaborative Decision-making category, chosen by 70.81% of participants, the subtypes are as follows: Doctor-led (29.90%), Doctor-Patient (13.54%), Patient-Family (2.93%), and Doctor-Patient-Family (24.44%). The Unilateral Decision-making, preferred by 29.19%, includes Doctor-dominant (23.22%), Family-centric (1.74%), and Patient-driven (4.23%) models. The preference for Collaborative Decision-making is associated with higher educational levels, specific marital statuses (particularly married but childless), and choices of rural residents' basic medical insurance or occupational basic medical insurance. In contrast, Unilateral Decision-making correlates with males, individuals with religious beliefs, certain occupational roles (like civil servants), and holders of commercial or publicly funded medical insurance. Conclusion: This study elucidates the complex interplay of socio-cultural and individual determinants shaping medical decision-making in China. The findings reveal a marked inclination towards collaborative models, closely linked to educational level, marital status, and specific insurance types, reflecting an evolving trend towards participatory healthcare. Simultaneously, the persistence of unilateral models, influenced by gender, religious beliefs, and occupational roles, highlights the heterogeneity within Chinese healthcare preferences. These insights are crucial for policymakers and healthcare practitioners, underscoring the need for adaptable, culturally attuned healthcare frameworks that cater to this diversity, thereby enhancing patient engagement and healthcare efficacy. [ABSTRACT FROM AUTHOR]

Abstract Background Electronic health records (EHRs) are widely accepted to enhance the health care quality, patient monitoring, and early prevention of various diseases, even when there is incomplete or missing information in them. Aim The present review sought to investigate the impact of EHR implementation on healthcare quality and medical decision in the context of epidemiological investigations, considering missing or incomplete data. Methods Google scholar, Medline (via PubMed) and Scopus databases were searched for studies investigating the impact of EHR implementation on healthcare quality and medical decision, as well as for studies investigating the way of dealing with missing data, and their impact on medical decision and the development process of prediction models. Electronic searches were carried out up to 2022. Results EHRs were shown that they constitute an increasingly important tool for both physicians, decision makers and patients, which can improve national healthcare systems both for the convenience of patients and doctors, while they improve the quality of health care as well as they can also be used in order to save money. As far as the missing data handling techniques is concerned, several investigators have already tried to propose the best possible methodology, yet there is no wide consensus and acceptance in the scientific community, while there are also crucial gaps which should be addressed. Conclusions Through the present thorough investigation, the importance of the EHRs’ implementation in clinical practice was established, while at the same time the gap of knowledge regarding the missing data handling techniques was also pointed out.

Background: Electronic health records (EHRs) are widely accepted to enhance the health care quality, patient monitoring, and early prevention of various diseases, even when there is incomplete or missing information in them. Aim: The present review sought to investigate the impact of EHR implementation on healthcare quality and medical decision in the context of epidemiological investigations, considering missing or incomplete data. Methods: Google scholar, Medline (via PubMed) and Scopus databases were searched for studies investigating the impact of EHR implementation on healthcare quality and medical decision, as well as for studies investigating the way of dealing with missing data, and their impact on medical decision and the development process of prediction models. Electronic searches were carried out up to 2022. Results: EHRs were shown that they constitute an increasingly important tool for both physicians, decision makers and patients, which can improve national healthcare systems both for the convenience of patients and doctors, while they improve the quality of health care as well as they can also be used in order to save money. As far as the missing data handling techniques is concerned, several investigators have already tried to propose the best possible methodology, yet there is no wide consensus and acceptance in the scientific community, while there are also crucial gaps which should be addressed. Conclusions: Through the present thorough investigation, the importance of the EHRs' implementation in clinical practice was established, while at the same time the gap of knowledge regarding the missing data handling techniques was also pointed out. [ABSTRACT FROM AUTHOR]

Disease assessment involves two stages of decision-making process. The first process is to infer the development trend of the disease through the existing judgment conditions, which is to make a positive estimation (prediction) decision. The second process is to update the judgment conditions for different disease states and optimize the clinical assessment evidence by fusing disease progression data, that is, to make a reverse evaluation (optimization) decision by reviewing historical diagnostic and treatment data to summarize the best judgment conditions for the disease characteristics. Therefore, we construct a three-way bidirectional decision method for multi-modal incomplete labeling information, considering the mixed data features with no labels and labels, and the bidirectional decision features of positive prediction and reverse optimization. Specifically, the method first introduces semi-supervised learning (SSL) into the rough sets, constructs a rough sets model based on cosine similarity relation, generates pseudo-labels for incomplete information, and explains the positive prediction decision process principle. Second, the gradient space is constructed on the predictive information system by the three-way decision-making principle, the loss function formed by the combination of KL divergence and cross entropy loss function is used to find the direction of the fastest decline in attribute information value, and the optimal decision rule and the automatic updating strategy of the threshold value are obtained. At the same time, the principle of the reverse optimization decision process is explained. Finally, multimodal information from pathological tissue images is used to evaluate clinical progress problem. A pathological tissue images dataset includes 2000 colorectal cancer and 300 kidney disease cases used for simulation experiments. The proposed three-way bidirectional decision-making model can be widely applied to actual decision-making scenarios for evaluating clinical progress of different diseases. Compared with previous studies, this method can realize objective calculation and automatic update of threshold and loss values and effectively solve complex prediction and optimization decision-making problems. • Three-way decision-making and semi-supervised learning integrated model was constructed. • The multi-modal decision information method was discussed. • Automatic update strategy of thresholds and loss function of three-way decision were presented. • 2300 realistic histopathological images were used for validation. [ABSTRACT FROM AUTHOR]

Patients with worsening heart failure with reduced ejection fraction (HFrEF) spend a large proportion of time in the hospital and other health care facilities. The benefits of guideline-directed medical therapy (GDMT) in the outpatient setting have been shown in large randomized controlled trials. However, the decision to initiate, continue, switch, or withdraw HFrEF medications in the inpatient setting is often based on multiple factors and subject to significant variability across providers. Based on available data, in well-selected, treatment-naïve patients who are hemodynamically stable and clinically euvolemic after stabilization during hospitalization for HF, elements of GDMT can be safely initiated. Inpatient continuation of GDMT for HFrEF appears safe and well-tolerated in most hemodynamically stable patients. Hospitalization is also a potential time for switching from an angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker to sacubitril/valsartan therapy in eligible patients, and is the subject of ongoing study. Therapy withdrawal or need for dose reduction is rarely required, but if needed identifies a particularly at-risk group of patients with progressive HF. If recurrent intolerance to neurohormonal blockers is observed, these patients should be evaluated for advanced HF therapies. There is an enduring need for using the teachable moment of HFrEF hospitalization for optimal initiation, continuation, and switching of GDMT to improve post-discharge patient outcomes and the quality of chronic HFrEF care.

Objectives The present study sought to explore how decision making is influenced by aging, framing, and social distance in the medical domain. Based on Socioemotional Selectivity Theory, we predicted that social distance would moderate age differences of framing effects as a result of older adults' emphasis on close partners. Methods Younger and middle-aged (N = 206) and older (N = 208) adults from Shanghai, China completed 2 medical decision tasks in which they were presented with different descriptions of social distance, namely deciding for close relatives or for strangers. Participants' risk preferences were measured. Results The results showed that framing effects were a function of social distance in older adults. Older adults showed smaller framing effects when making decisions for strangers as their preference for the riskier option was reduced in the loss-framed condition. For younger and middle-aged adults, framing effects existed consistently regardless of social distance. Discussion These findings suggest that social distance moderates age differences in framing effects in medical decision-making. It also highlights a potential way to improve older adults' medical decision-making quality: having older adults imagine as if they are making medical decisions for a stranger. [ABSTRACT FROM AUTHOR]

Abstract Background Cancer patients’ end-of-life care may involve complex decision-making processes. Colombia has legislation regarding provision of and access to palliative care and is the only Latin American country with regulation regarding euthanasia. We describe medical end-of-life decision-making practices among cancer patients in three Colombian hospitals. Methods Cancer patients who were at the end-of-life and attended in participating hospitals were identified. When these patients deceased, their attending physician was invited to participate. Attending physicians of 261 cancer patients (out of 348 identified) accepted the invitation and answered a questionnaire regarding end-of-life decisions: a.) decisions regarding the withdrawal or withholding of potentially life-prolonging medical treatments, b.) intensifying measures to alleviate pain or other symptoms with hastening of death as a potential side effect, and c.) the administration, supply or prescription of drugs with an explicit intention to hasten death. For each question addressing the first two decision types, we asked if the decision was fully or partially made with the intention or consideration that it may hasten the patient’s death. Results Decisions to withdraw potentially life-prolonging treatment were made for 112 (43%) patients, 16 of them (14%) with an intention to hasten death. For 198 patients (76%) there had been some decision to not initiate potentially life-prolonging treatment. Twenty-three percent of patients received palliative sedation, 97% of all patients received opioids. Six patients (2%) explicitly requested to actively hasten their death, for two of them their wish was fulfilled. In another six patients, medications were used with the explicit intention to hasten death without their explicit request. In 44% (n = 114) of all cases, physicians did not know if their patient had any advance care directives, 26% (n = 38) of physicians had spoken to the patient regarding the possibility of certain treatment decisions to hasten death where this applied. Conclusions Decisions concerning the end of life were common for patients with cancer in three Colombian hospitals, including euthanasia and palliative sedation. Physicians and patients often fail to communicate about advance care directives and potentially life-shortening effects of treatment decisions. Specific end-of-life procedures, patients’ wishes, and availability of palliative care should be further investigated.

Objectives: Family conferences constitute a vital medium for facilitating open communication between a medical team, a patient, and the patient’s family. Confirming the patient’s wishes and incorporating their family’s views during the formulation of decisions for end-stage medical care are crucial. The objective of this study was to determine the communication patterns arising between the health-care team, the patient, and the patient’s family during a family conference for making decisions about end-stage medical care. Methods: This 5-year retrospective analysis reviewed charts for 125 family conference minutes concerning decisions for end-stage medical care; the charts were sourced from 108 patients residing in a regional teaching hospital in Southern Taiwan between 2009 and 2014. Content analysis was conducted to observe the common communication patterns during these family conferences. Results: Although some family conferences reached an agreement that patient willingness and autonomy should be prioritized, few conferences actually involved the patients. Some conferences were even held on the condition of no patient involvement. Our qualitative research identified several family conference communication patterns as follows: (a) patient-oriented patterns, where the patient’s thoughts were considered to deliberate the medical decisions; (b) family-oriented patterns, where family members made decisions on behalf of the patient; and (c) medical-oriented patterns, where physicians were trusted to make decisions. Conclusions: The results of this study can serve as a reference for developing effective family conference communication patterns in which patient autonomy in making decisions concerning end-stage medical care is respected, thus promoting shared decision-making. [ABSTRACT FROM AUTHOR]

Copyright of Notfall & Rettungsmedizin is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Cancer patients' end-of-life care may involve complex decision-making processes. Colombia has legislation regarding provision of and access to palliative care and is the only Latin American country with regulation regarding euthanasia. We describe medical end-of-life decision-making practices among cancer patients in three Colombian hospitals. Methods: Cancer patients who were at the end-of-life and attended in participating hospitals were identified. When these patients deceased, their attending physician was invited to participate. Attending physicians of 261 cancer patients (out of 348 identified) accepted the invitation and answered a questionnaire regarding end-of-life decisions: a.) decisions regarding the withdrawal or withholding of potentially life-prolonging medical treatments, b.) intensifying measures to alleviate pain or other symptoms with hastening of death as a potential side effect, and c.) the administration, supply or prescription of drugs with an explicit intention to hasten death. For each question addressing the first two decision types, we asked if the decision was fully or partially made with the intention or consideration that it may hasten the patient's death. Results: Decisions to withdraw potentially life-prolonging treatment were made for 112 (43%) patients, 16 of them (14%) with an intention to hasten death. For 198 patients (76%) there had been some decision to not initiate potentially life-prolonging treatment. Twenty-three percent of patients received palliative sedation, 97% of all patients received opioids. Six patients (2%) explicitly requested to actively hasten their death, for two of them their wish was fulfilled. In another six patients, medications were used with the explicit intention to hasten death without their explicit request. In 44% (n = 114) of all cases, physicians did not know if their patient had any advance care directives, 26% (n = 38) of physicians had spoken to the patient regarding the possibility of certain treatment decisions to hasten death where this applied. Conclusions: Decisions concerning the end of life were common for patients with cancer in three Colombian hospitals, including euthanasia and palliative sedation. Physicians and patients often fail to communicate about advance care directives and potentially life-shortening effects of treatment decisions. Specific end-of-life procedures, patients' wishes, and availability of palliative care should be further investigated. [ABSTRACT FROM AUTHOR]

En 2021, la Commission d'Éthique de la Société française de Radiothérapie Oncologique (SFRO) s'est saisie de la thématique délicate de la pratique des soins à visée palliative en oncologie radiothérapique. L'oncologie radiothérapie joue un rôle central dans la prise en charge des patients atteints de cancer en phase palliative. Mais derrière la dénomination large de radiothérapie palliative, on retrouve en réalité un grand nombre de situations relevant d'enjeux éthiques très divers. Le rôle de l'oncologue radiothérapeute sera de prendre en compte de multiples facteurs mobilisés à l'occasion d'un processus décisionnel complexe. Si la question de l'indication thérapeutique, et du choix technique permettant de la mettre en œuvre reste centrale, la réflexion ne saurait se limiter à ces seuls aspects décisionnel et technique. Il est aussi question de pouvoir créer les conditions d'un soin attentif à la singularité des personnes et de construire au-delà de la technicité, une authentique relation de soin. C'est au travers de ce travail éthique quotidien, en lien étroit avec les personnes malades, et dans des conditions indispensables de pluri disciplinarité et de pluri professionnalité, que se déploie pleinement notre rôle fondamental de soignant. In 2021, the Ethics Commission of the SFRO has chosen the issue of the practice of palliative care in radiotherapy oncology. Radiation oncology plays a central role in the care of patients with cancer in palliative phase. But behind the broad name of palliative radiotherapy, we actually find a large variety of situations involving diverse ethical issues. Radiation oncologists have the delicate task to take into account multiple factors throughout a complex decision-making process. While the question of the therapeutic indication and the technical choice allowing it to be implemented remains central, reflection cannot be limited to these decision-making and technical aspects alone. It is also a question of being able to create the conditions for a singularity focused care and to build an authentic care relationship, beyond technicity. It is through this daily ethical work, in close collaboration with patients, and under essential conditions of multidisciplinarity and multiprofessionalism, that our fundamental role as caregiver can be deployed. [ABSTRACT FROM AUTHOR]

The emergence of personalized medicine and its exceptional advancements reveal new needs regarding the availability of adequate medical decision-making models. Considering detailed data on this medicine, the creation of a medical decision-making system may encounter many inhibitory factors, such as data representation, data reduction, data classification, and overall processing complexity. To address these challenges, this paper aims to create a useful model that can classify new patient data using efficient computations by choosing the best data processing series. Our methodology represents data with a recent model in the first task. During the second task, we continue with distance matrix production. The third task aims to reduce the dimensions of the last matrix. The fourth task applies a classification according to the results of reduced dimensionality. We have tested several distance measurements, dimensionality reduction methods, and classification techniques to achieve maximum performance. The evaluation results of the proposed model have shown excellent performance. Its F-measure can achieve an impressive rating with several classifiers (F-measure = 0.917, F-measure = 0.923, F-measure = 0.987 by 3-NN, random forest (RF) and support vector machine (SVM) classifiers). In addition to these performance measures, the computation time is also taken into account to choose among the proposed model's derived methods (time = 2 ms, time = 76 ms, time = 118 ms for the 3-NN, RF, and SVM classifiers, respectively). According to the performance and processing time criteria, we defined three use-case scenarios. However, we recommend using the RF classifier for the data reduced by the t-distributed stochastic neighbor embedding (TSNE) technique in practical cases to compromise performance and speed criteria.

Objectives: identifying effective summary formats is fundamental to multiple fields including science communication, systematic reviews, evidence-based policy and medical decision-making. This study tested whether table or text-only formats lead to better comprehension of the potential harms and benefits of different options, here in a medical context. Design: pre-registered, longitudinal experiment: between-subjects factorial 2 (message format) × 2 topic (therapeutic or preventative intervention) on comprehension and later recall (CONSORT-SPI 2018). Setting: longitudinal online survey experiment. Participants: 2305 census-matched UK residents recruited through the survey panel firm YouGov. Primary outcome measure: comprehension of harms and benefits and knowledge recall after six weeks. Results: fact boxes—simple tabular messages—led to more comprehension (d = 0.39) and slightly more knowledge recall after six weeks (d = 0.12) compared to the same information in text. These patterns of results were consistent between the two medical topics and across all levels of objective numeracy and education. Fact boxes were rated as more engaging than text, and there were no differences between formats in treatment decisions, feeling informed or trust. Conclusions: the brief table format of the fact box improved the comprehension of harms and benefits relative to the text-only control. Effective communication supports informed consent and decision-making and brings ethical and practical advantages. Fact boxes and other summary formats may be effective in a wide range of communication contexts.

Patient portals are consumer health applications that allow patients to view their health information. Portals facilitate the interactions between patients and their caregivers by offering secure messaging. Patients communicate different needs through portal messages. Medical needs contain requests for delivery of care (e.g. reporting new symptoms). Automating the classification of medical decision complexity in portal messages has not been investigated. We trained two multiclass classifiers, multinomial Naïve Bayes and random forest on 500 message threads, to quantify and label the complexity of decision-making into four classes: no decision, straightforward, low, and moderate. We compared the performance of the models to using only the number of medical terms without training a machine learning model. Our analysis demonstrated that machine learning models have better performance than the model that did not use machine learning. Moreover, machine learning models could quantify the complexity of decision-making that the messages contained with 0.59, 0.45, and 0.58 for macro, micro, and weighted precision and 0.63,0.41, and 0.63 for macro, micro, and weighted recall. This study is one of the first to attempt to classify patient portal messages by whether they involve medical decision-making and the complexity of that decision-making. Machine learning classifiers trained on message content resulted in better message thread classification than classifiers that employed medical terms in the messages alone. [ABSTRACT FROM AUTHOR]

Abstract In health care for older adults, patients with multimorbidity usually receive the same interventions as those patients without multimorbidity. However, standard curative or life-sustaining treatment options have to be considered carefully in view of the maximally attainable result in older and frail patients. To guide such complex medical decisions, we present a compact deliberation framework that could assist physician(s) in charge of the medical treatment of a specific elderly patient to systematize his own thinking about treatment and decisional responsibilities, in case of an intercurrent disease. The framework includes four questions to be addressed when deciding on a single urgent standard curative or life-sustaining intervention in acute medical problems of an elderly patient with multimorbidity: 1) What is known about the patient’s aims and preferences? 2) Will the intervention be effective? 3) Will the intervention support the aims and preferences of the patient? 4) In view of the aims and preferences, will the risks and benefits be in balance? If all four considerations are answered favorably, the intervention will fit patient-centered and appropriate care for frail older patients with multimorbidity. Application to a patient case illustrates how our framework can improve the quality of the shared decision-making process in care for older people and helps clarify medical and moral considerations regarding how to appropriately treat the individual patient.

In this paper, the author intends to reflect on the evolution of the right to parental authority and rights of the youth who is suffering from cancer. The legislator reconsidered the place of the minor patient’s will. The parents of the young person must respect the rights of the minor patient, according to his age, his faculty of discernment and maturity. The authors present the most significant results of an empirical study of exploratory type through individual interviews with young patients, parents and health professionals.

Background: Patients with tetralogy of Fallot (TOF) often have arrhythmias, commonly being atrial fibrillation (AF). Radiofrequency ablation is an effective treatment for AF and does not usually cause severe postoperative hypoxemia, but the risk of complications may increase in patients with conditions such as TOF., Case Summary: We report a young male patient with a history of TOF repair who developed severe hypoxemia after radiofrequency ablation for AF and was ultimately confirmed to have a new right-to-left shunt. The patient subsequently underwent atrial septal occlusion and eventually recovered., Conclusion: Radiofrequency ablation may cause iatrogenic atrial septal injury; thus possible complications should be predicted in order to ensure successful treatment and patient safety., Competing Interests: Conflict-of-interest statement: The authors declare that they have no conflict of interest to disclose., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background: Medical decision-making capacity is impaired in Alzheimer's disease and mild cognitive impairment. Medical decision-making capacity depends on many different cognitive functions and varies due to situation and cognitive, social, and emotional status of the patient. Our aim was to analyze dementia patients' capacity to estimate risks and benefits in different clinical trials and determine how cognitive decline affects their attitude toward possible participation and proxy consent. Methods: Groups: Alzheimer's disease (n = 20), mild cognitive impairment (n = 21) and healthy controls (n = 33). Two hypothetical clinical trials, a standardized interview and three visual analogue scales were used to investigate decisions, estimations, reasoning, and attitudes. Results: A general positive attitude toward participation in clinical trials was shown among all groups. Both patients and controls motivated possible participation as "own-benefit" in the low-risk trial and to "help-others" in the high-risk trial. Individuals who accepted to participate in the high-risk trial scored lower in medical decision-making capacity in comparison to participants who would not have participated (p <.01). Patients in the Alzheimer's disease but not mild cognitive impairment and healthy control groups underestimated risks and overestimated benefits in the high-risk/low-benefit trial (p <.05). A family member was most frequently chosen as possible proxy (91%). Conclusions: Medical decisions and research consent should be interpreted with caution in patients who are already in early stages of dementia, as the patients' acceptance to participate in high-risk trials may be due an insufficient decisional capacity and risk analysis, accelerated by a general desire to make good to society. We emphasize the use of a standardized tool to evaluate medical decisional capacity in clinical research. [ABSTRACT FROM AUTHOR]

Objectives: To compare the principles laid down by French law and recommendations with the reality experienced in the field concerning the degree of parental involvement in decisions to limit or stop active treatment in neonatal intensive care. Methods: Qualitative research based on semi-directive interviews with paediatricians and parents conducted during immersion placements in three French Neonatal Resuscitation Units. Results: Most paediatricians interviewed expressed some hesitation in defining precisely the role of parents in the decision-making process. Disparities in practices can be observed and multiple terms are used to designate the role of parents, depending on their involvement in the decision. Discussion: The necessary adjustment during the decision-making process requires that paediatricians recognize the «lay» competence of parents in a form of equal relationships, respect for the role of each and consideration of the uniqueness of each newborn child. It seems necessary to further deepen ethical questioning within medical teams in order to foster an attitude of questioning - personal and collective - carried by a real ethical concern. [ABSTRACT FROM AUTHOR]

Antiepileptic drugs (AEDs) are the first choice in magnetic resonance imaging (MRI)-negative patients with epilepsy, although the responses to AEDs are diverse. Preoperative evaluation and postoperative prognosis in MRI-negative epilepsy have been reported. However, there are few tools for predicting the response to AEDs. Herein, we developed an AED response scale based on clinical factors and video-electroencephalography (VEEG) in MRI-negative patients with epilepsy. A total of 132 consecutive patients with MRI-negative epilepsy at the Epilepsy Center of Henan Provincial People's Hospital between August 2016 and August 2018 were included. Patients were further divided into drug-responsive epilepsy ([DSE-MRI (−)]; n = 101) and drug-resistant epilepsy ([DRE-MRI (−)]; n = 31) groups. The clinical and VEEG factors were evaluated in univariate analyses and multivariate logistic regression analyses. A scale was derived and the scores categorized into 3 risk levels of DRE-MRI (−). A scale was established based on 4 independent risk factors for DRE-MRI (−). The scale had a sensitivity of 83.87%, specificity of 80.20%, positive likelihood ratio of 4.24, negative likelihood ratio of 0.20, and showed good discrimination with the area under the curve (AUC) of 0.886 (0.826–0.946). The categorization of the risk score based on this scale was: low risk (0–3 points), medium risk (3–5 points), and high risk (> 5 points). We established a DRE-MRI (−) scale with a good sensitivity and specificity, which may be useful for clinicians when making medical decisions in patients with MRI-negative epilepsy. • AEDs are the first choice in MRI-negative epilepsy patients. • A scale was established based on clinical factors and VEEG, which showed a good discrimination and may be useful for making medical decisions in patients with MRI-negative epilepsy. • The risk lever was categorized as low risk (0–3 points), medium risk (3–5 points), and high risk (> 5 points) [ABSTRACT FROM AUTHOR]

Multi-state processes (Webster, 2019) are commonly used to model the complex clinical evolution of diseases where patients progress through different states. In recent years, machine learning and deep learning algorithms have been proposed to improve the accuracy of these models' predictions (Wang et al., 2019). However, acceptability by patients and clinicians, as well as for regulatory compliance, require interpretability of these algorithms's predictions. Existing methods, such as the Permutation Feature Importance algorithm, have been adapted for interpreting predictions in black-box models for 2-state processes (corresponding to survival analysis). For generalizing these methods to multi-state models, we introduce a novel model-agnostic interpretability algorithm called Multi-State Counterfactual Perturbation Feature Importance (MS-CPFI) that computes feature importance scores for each transition of a general multi-state model, including survival, competing-risks, and illness-death models. MS-CPFI uses a new counterfactual perturbation method that allows interpreting feature effects while capturing the non-linear effects and potentially capturing time-dependent effects. Experimental results on simulations show that MS-CPFI increases model interpretability in the case of non-linear effects. Additionally, results on a real-world dataset for patients with breast cancer confirm that MS-CPFI can detect clinically important features and provide information on the disease progression by displaying features that are protective factors versus features that are risk factors for each stage of the disease. Overall, MS-CPFI is a promising model-agnostic interpretability algorithm for multi-state models, which can improve the interpretability of machine learning and deep learning algorithms in healthcare. • Multi-state processes can model the complex evolution of diseases. • Deep learning algorithms improve the accuracy of these models' predictions. • Acceptability for regulatory compliance requires interpretability of these algorithms. • Permutation Feature Importance algorithm must be extended for this purpose. • Our new model-agnostic method detect clinically important features of disease progression. [ABSTRACT FROM AUTHOR]

Ideally, decisions regarding one’s health should be made after assessing the objective probabilities of relevant outcomes. Nevertheless, previous beliefs and emotional reactions also have a role in decision-making. Furthermore, the comprehension of probabilities is commonly affected by the presentation format, and by numeracy. This study aimed to assess the extent to which the influence of these factors might vary between different medical conditions. A sample of university students were presented with two health scenarios containing statistical information on the prevalence of breast cancer and hypertension either through icon arrays (N = 71) or natural frequencies (N = 72). They also received information regarding a preventive measure (mammogram/low-sodium diet) and the likelihood of a positive mammogram or a rich-sodium diet either when suffering or not suffering from the disease. Before seeing the data, participants rated the severity of the disease and the inconvenience of the preventive measure. After reading the health scenario, participants had to rate its difficulty, and how worrisome it was. They had also to rate the prior probability of suffering from this medical condition, and the posterior probability of it, provided a positive mammogram or a rich-sodium diet. Finally, they rated the extent to which they would recommend the preventive measures. All the rates used the same 1 (little)-8 (a great deal) scale. Participants’ numeracy was also assessed. The scenarios differed significantly in perceived severity and worry, with the cancer scenario obtaining higher scores. Importantly, regression analyses showed that the recommendations in the two health scenarios depended on different variables. A model taking into consideration severity and worry rates best explained decisions in the cancer scenario; in contrast, in the hypertension scenario the model that best explained the recommendations comprised both the posterior probability estimate and the severity rate. Neither numeracy nor presentation format affected recommendation but both affected difficulty, worrying and probability rates. We conclude that previous perceptions of the severity of a health condition modulate the use of probabilistic information for decision-making. The roles of presentation format and numeracy in enabling patients to understand statistical information are also discussed.

Objective: To review the current applications of machine learning in orthopaedic trauma and anticipate its future role in clinical practice., Methods: A comprehensive literature review was conducted to assess the status of machine learning algorithms in orthopaedic trauma research, both nationally and internationally., Results: The rapid advancement of computer data processing and the growing convergence of medicine and industry have led to the widespread utilization of artificial intelligence in healthcare. Currently, machine learning plays a significant role in orthopaedic trauma, demonstrating high performance and accuracy in various areas including fracture image recognition, diagnosis stratification, clinical decision-making, evaluation, perioperative considerations, and prognostic risk prediction. Nevertheless, challenges persist in the development and clinical implementation of machine learning. These include limited database samples, model interpretation difficulties, and universality and individualisation variations., Conclusion: The expansion of clinical sample sizes and enhancements in algorithm performance hold significant promise for the extensive application of machine learning in supporting orthopaedic trauma diagnosis, guiding decision-making, devising individualized medical strategies, and optimizing the allocation of clinical resources.

Ideally, decisions regarding one’s health should be made after assessing the objective probabilities of relevant outcomes. Nevertheless, previous beliefs and emotional reactions also have a role in decision-making. Furthermore, the comprehension of probabilities is commonly affected by the presentation format, and by numeracy. This study aimed to assess the extent to which the influence of these factors might vary between different medical conditions. A sample of university students were presented with two health scenarios containing statistical information on the prevalence of breast cancer and hypertension either through icon arrays (N = 71) or natural frequencies (N = 72). They also received information regarding a preventive measure (mammogram/low-sodium diet) and the likelihood of a positive mammogram or a richsodium diet either when suffering or not suffering from the disease. Before seeing the data, participants rated the severity of the disease and the inconvenience of the preventive measure. After reading the health scenario, participants had to rate its difficulty, and how worrisome it was. They had also to rate the prior probability of suffering from this medical condition, and the posterior probability of it, provided a positive mammogram or a rich-sodium diet. Finally, they rated the extent to which they would recommend the preventive measures. All the rates used the same 1 (little)-8 (a great deal) scale. Participants’ numeracy was also assessed. The scenarios differed significantly in perceived severity and worry, with the cancer scenario obtaining higher scores. Importantly, regression analyses showed that the recommendations in the two health scenarios depended on different variables. A model taking into consideration severity and worry rates best explained decisions in the cancer scenario; in contrast, in the hypertension scenario the model that best explained the recommendations comprised both the posterior probability estimate and the severity rate. Neither numeracy nor presentation format affected recommendation but both affected difficulty, worrying and probability rates. We conclude that previous perceptions of the severity of a health condition modulate the use of probabilistic information for decision-making. The roles of presentation format and numeracy in enabling patients to understand statistical information are also discussed. [ABSTRACT FROM AUTHOR]