Perceptions of C-reactive Protein Measurement Among General Physicians: A Qualitative Study on Diagnostic Value, Clinical Dilemmas, and Professional Growth.

Introduction C-reactive protein (CRP) is a widely used laboratory test for assessing infections, inflammatory diseases, and malignancies, playing a critical role in clinical diagnosis and management. Despite its utility, CRP measurement practices vary among physicians, often influenced by training and clinical experience. This study explores general physicians' perceptions of CRP measurement in clinical practice, focusing on its diagnostic value, associated dilemmas, and impact on clinical growth and decision-making. Methods This qualitative study employed thematic analysis to examine the perceptions of general physicians at Unnan City Hospital, Unnan, Japan regarding CRP measurement. Sixteen general physicians were selected through purposive sampling and participated in one-on-one semi-structured interviews. The interviews were conducted in Japanese, recorded, transcribed verbatim, and analyzed inductively to identify themes. The analysis involved iterative coding and extensive discussion among the research team to ensure the reliability and validity of the findings. Results Three main themes emerged from the analysis: the usefulness of CRP for diagnosis and collaboration, dilemmas associated with CRP usage, and clinical growth through reconsideration of CRP's importance. Physicians highlighted CRP's value in distinguishing inflammatory from non-inflammatory diseases, predicting clinical courses, and facilitating communication with specialists. However, dilemmas arose from discrepancies between CRP levels and clinical symptoms, the influence of various non-specific factors, and habitual testing driven by training, leading to unnecessary tests and diminished clinical skills. Participants recognized the need to view CRP as one of many diagnostic tools, cultivate a habit of questioning its necessity, and reflect on its use to enhance clinical reasoning and professional growth. Conclusions CRP measurement is a valuable diagnostic tool, but effective use requires a balanced and critical approach. Discrepancies between CRP levels and clinical symptoms can lead to over-reliance on laboratory results and unnecessary testing. General physicians should integrate CRP within a broader diagnostic framework, combining it with patient history, physical examination, and other tests. Reflecting on the necessity and implications of CRP measurements can improve clinical reasoning and decision-making, ultimately enhancing patient care and resource management. Future research should explore similar perceptions in diverse healthcare settings and develop strategies to optimize CRP use in clinical practice.

Supplementing Systematic Review Findings with Healthcare System Data: Pilot Projects from the Agency for Healthcare Research and Quality Evidence-based Practice Center Program.

OBJECTIVES: The US Agency for Healthcare Research and Quality (AHRQ), through the Evidence-based Practice Center (EPC) Program, aims to provide health system decision makers with the highest-quality evidence to inform clinical decisions. However, limitations in the literature may lead to inconclusive findings in EPC systematic reviews (SRs). The EPC Program conducted pilot projects to understand the feasibility, benefits, and challenges of utilizing health system data to augment SR findings to support confidence in healthcare decision-making based on real-world experiences. STUDY DESIGN AND SETTING: Three contractors (each an EPC located at a different health system) selected a recently completed systematic review conducted by their center and identified an evidence gap that electronic health record (EHR) data might address. All pilot project topics addressed clinical questions as opposed to care delivery, care organization, or care disparities topics that are common in EPC reports. Topic areas addressed by each EPC included infantile epilepsy, migraine, and hip fracture. EPCs also tracked additional resources needed to conduct supplemental analyses. The workgroup met monthly in 2022-2023 to discuss challenges and lessons learned from the pilot projects. RESULTS: Two supplemental data analyses filled an evidence gap identified in the systematic reviews (raised certainty of evidence, improved applicability) and the third filled a health system knowledge gap. Project challenges fell under three themes: regulatory and logistical issues, data collection and analysis, and interpretation and presentation of findings. Limited ability to capture key clinical variables given inconsistent or missing data within the EHR was a major limitation. The workgroup found that conducting supplemental data analysis alongside an SR was feasible but adds considerable time and resources to the review process (estimated total hours to complete pilot projects ranged from 283-595 across EPCs), and that the increased effort and resources added limited incremental value. CONCLUSION: Supplementing existing systematic reviews with analyses of EHR data is resource intensive and requires specialized skillsets throughout the process. While using EHR data for research has immense potential to generate real-world evidence and fill knowledge gaps, these data may not yet be ready for routine use alongside systematic reviews.

Personalized approach to malignant struma ovarii: Insights from a web-based machine learning tool.

OBJECTIVES: Malignant struma ovarii (MSO) is a rare ovarian tumor characterized by mature thyroid tissue. The diverse symptoms and uncommon nature of MSO can create difficulties in its diagnosis and treatment. This study aimed to analyze data and use machine learning methods to understand the prognostic factors and potential management strategies for MSO. METHODS: In this retrospective cohort, the Surveillance, Epidemiology, and End Results (SEER) database provided the data used for this study's analysis. To identify the prognostic variables, we conducted Cox regression analysis and constructed prognostic models using five machine learning algorithms to predict the 5-year survival. A validation method incorporating the area under the curve of the receiver operating characteristic curve was used to validate the accuracy and reliability of the machine learning models. We also investigated the role of multiple therapeutic options using the Kaplan-Meier survival analysis. RESULTS: The study population comprised 329 patients. Multivariate Cox regression analysis revealed that older age, unmarried status, chemotherapy, and the total number of tumors in patients were poor prognostic factors. Machine learning models revealed that the multilayer perceptron accurately predicted outcomes, followed by the random forest classifier, gradient boosting classifier, K-nearest neighbors, and logistic regression models. The factors that contributed the most were age, marital status, and the total number of tumors in the patients. CONCLUSION: The present study offers a comprehensive approach for the treatment and prognosis assessment of patients with MSO. The machine learning models we have developed serve as a practical, personalized tool to aid in clinical decision-making processes.

Views and perceptions of advanced life support practitioners on initiating, withholding and terminating resuscitation in out-of-hospital cardiac arrest in the Emergency Medical Services of South Africa.

Introduction: This study aimed to explore the views and perceptions of Advanced Life Support (ALS) practitioners in two South African provinces on initiating, withholding, and terminating resuscitation in OHCA. Methodology: Semi-structured one-on-one interviews were conducted with operational ALS practitioners working within the prehospital setting in the Western Cape and Free State provinces. Recorded interviews were transcribed and subjected to inductive-dominant, manifest content analysis. After familiarisation with the data, meaning units were condensed, codes were applied and collated into categories that were then assessed, reviewed, and refined repeatedly. Results: A total of 18 ALS providers were interviewed. Five main categories were developed from the data analysis: 1) assessment of prognosis, 2) internal factors affecting decision-making, 3) external factors affecting decision-making, 4) system challenges, and 5) ideas for improvement. Factors influencing the assessment of prognosis were history, clinical presentation, and response to resuscitation. Internal factors affecting decision-making were driven by emotion and contemplation. External factors affecting decision-making included family, safety, and disposition. System challenges relating to bystander response and resources were identified. Ideas for improvement in training and support were brought forward. Conclusion: Many factors influence OHCA decision-making in the Western Cape and Free State provinces, and numerous system challenges have been identified. The findings of this study can be used as a frame of reference for prehospital emergency care personnel and contribute to the development of context-specific guidelines.

Acute care nurses' decisions to recognise and respond to patient improvement: A qualitative study.

AIM: To explore and describe acute care nurses' decisions to recognise and respond to improvement in patients' clinical states as they occurred in the real-world clinical environment. DESIGN: A descriptive study. METHODS: Nine medical and eleven surgical nurses in a large Australian metropolitan hospital were individually observed during nurse-patient interactions and followed up in interview to describe their reasoning and clinical judgements behind observed decisions. Verbal description of observations and interviews were recorded and transcribed. Reflexive thematic analysis was used to analyse the data. RESULTS: The three themes constructed from the data were as follows: nurses checking in; nurses reaching judgements about improvements; and nurses deciding on the best person to respond. Acute care nurses made targeted assessment decisions based on predicted safety risks related to improvement in clinical states. Subjective and objective cues were used to assess for and make judgements about patient improvement. Acute care nurses' judgment of patient safety and a desire to promote patient centred care guided their decisions to select the appropriate person to manage improvement. CONCLUSIONS: The outcomes of this research have demonstrated that the proven safety benefits of acute care nurses' decision making in response to deterioration extend to improvement in patients' clinical states. In response to improvement, acute care nurses' decisions protect patients from harm and promote recovery. IMPLICATIONS FOR PATIENT CARE: Early recognition and response to improvement enable acute care nurses to protect patients from risks of unnecessary treatment and promote recovery. IMPACT: This study makes explicit nurses' essential safety role in recognising and responding to improvement in patients' clinical states. Healthcare policy and education must reflect the equal importance of assessment for and management of deterioration and improvement to ensure patients are protected and provided with safe care.

Markerless Motion Capture to Quantify Functional Performance in Neurodegeneration: Systematic Review.

BACKGROUND: Markerless motion capture (MMC) uses video cameras or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia. OBJECTIVE: The primary objective of this systematic review was to investigate the application of MMC using full-body tracking, to quantify functional performance in people with dementia, mild cognitive impairment, and Parkinson disease. METHODS: A systematic search of the Embase, MEDLINE, CINAHL, and Scopus databases was conducted between November 2022 and February 2023, which yielded a total of 1595 results. The inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full-text screening, out of which 26 eligible studies that met the selection criteria were included in the review. . RESULTS: Primarily, the selected studies focused on gait analysis (n=24), while other functional tasks, such as sit to stand (n=5) and stepping in place (n=1), were also explored. However, activities of daily living were not evaluated in any of the included studies. MMC models varied across the studies, encompassing depth cameras (n=18) versus standard video cameras (n=5) or mobile phone cameras (n=2) with postprocessing using deep learning models. However, only 6 studies conducted rigorous comparisons with established gold-standard motion capture models. CONCLUSIONS: Despite its potential as an effective tool for analyzing movement and posture in individuals with dementia, mild cognitive impairment, and Parkinson disease, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real world.

Creating virtual patients using large language models: scalable, global, and low cost.

Virtual patients (VPs) have long been used to teach and assess clinical reasoning. VPs can be programmed to simulate authentic patient-clinician interactions and to reflect a variety of contextual permutations. However, their use has historically been limited by the high cost and logistical challenges of large-scale implementation. We describe a novel globally-accessible approach to develop low-cost VPs at scale using artificial intelligence (AI) large language models (LLMs). We leveraged OpenAI Generative Pretrained Transformer (GPT) to create and implement two interactive VPs, and created permutations that differed in contextual features. We used systematic prompt engineering to refine a prompt instructing ChatGPT to emulate the patient for a given case scenario, and then provide feedback on clinician performance. We implemented the prompts using GPT-3.5-turbo and GPT-4.0, and created a simple text-only interface using the OpenAI API. GPT-4.0 was far superior. We also conducted limited testing using another LLM (Anthropic Claude), with promising results. We provide the final prompt, case scenarios, and Python code. LLM-VPs represent a 'disruptive innovation' - an innovation that is unmistakably inferior to existing products but substantially more accessible (due to low cost, global reach, or ease of implementation) and thereby able to reach a previously underserved market. LLM-VPs will lay the foundation for global democratization via low-cost-low-risk scalable development of educational and clinical simulations. These powerful tools could revolutionize the teaching, assessment, and research of management reasoning, shared decision-making, and AI evaluation (e.g. 'software as a medical device' evaluations).

Safety of treating acute pulmonary embolism at home: an individual patient data meta-analysis.

BACKGROUND AND AIMS: Home treatment is considered safe in acute pulmonary embolism (PE) patients selected by a validated triage tool (e.g. simplified PE severity index score or Hestia rule), but there is uncertainty regarding the applicability in underrepresented subgroups. The aim was to evaluate the safety of home treatment by performing an individual patient-level data meta-analysis. METHODS: Ten prospective cohort studies or randomized controlled trials were identified in a systematic search, totalling 2694 PE patients treated at home (discharged within 24 h) and identified by a predefined triage tool. The 14- and 30-day incidences of all-cause mortality and adverse events (combined endpoint of recurrent venous thromboembolism, major bleeding, and/or all-cause mortality) were evaluated. The relative risk (RR) for 14- and 30-day mortalities and adverse events is calculated in subgroups using a random effects model. RESULTS: The 14- and 30-day mortalities were 0.11% [95% confidence interval (CI) 0.0-0.24, I2 = 0) and 0.30% (95% CI 0.09-0.51, I2 = 0). The 14- and 30-day incidences of adverse events were 0.56% (95% CI 0.28-0.84, I2 = 0) and 1.2% (95% CI 0.79-1.6, I2 = 0). Cancer was associated with increased 30-day mortality [RR 4.9; 95% prediction interval (PI) 2.7-9.1; I2 = 0]. Pre-existing cardiopulmonary disease, abnormal troponin, and abnormal (N-terminal pro-)B-type natriuretic peptide [(NT-pro)BNP] at presentation were associated with an increased incidence of 14-day adverse events [RR 3.5 (95% PI 1.5-7.9, I2 = 0), 2.5 (95% PI 1.3-4.9, I2 = 0), and 3.9 (95% PI 1.6-9.8, I2 = 0), respectively], but not mortality. At 30 days, cancer, abnormal troponin, and abnormal (NT-pro)BNP were associated with an increased incidence of adverse events [RR 2.7 (95% PI 1.4-5.2, I2 = 0), 2.9 (95% PI 1.5-5.7, I2 = 0), and 3.3 (95% PI 1.6-7.1, I2 = 0), respectively]. CONCLUSIONS: The incidence of adverse events in home-treated PE patients, selected by a validated triage tool, was very low. Patients with cancer had a three- to five-fold higher incidence of adverse events and death. Patients with increased troponin or (NT-pro)BNP had a three-fold higher risk of adverse events, driven by recurrent venous thromboembolism and bleeding.

A realist evaluation protocol: assessing the effectiveness of a rapid response team model for mental state deterioration in acute hospitals.

Background: Mental state deterioration poses significant challenges in healthcare, impacting patients and providers. Symptoms like confusion and agitation can lead to prolonged hospital stays, increased costs, and the use of restrictive interventions. Despite its prevalence, there's a lack of consensus on effective practices for managing mental state deterioration in acute hospital settings. To address this gap, a rapid response team model has been proposed as a potential intervention, aiming to provide early identification and targeted interventions. Methods: Based on realist evaluation steps, first, initial program theories are formulated to understand the logic behind the intervention. Second, literature synthesis identifies empirical evidence on contexts, mechanisms, and outcomes elements, refining initial theories. During the third step, data will be collected using qualitative methods such as field observations and interviews, as well as quantitative methods such as surveys of the staff, audits of electronic medical records, and analysis of incident records of mental state deterioration. Analysing this data informs configurations of contexts, mechanisms, and outcomes. In the fifth step, the configurations are synthesised, presenting refined, evidence-informed program theories. Conclusion: This study addresses the knowledge gap by evaluating the rapid response model's effectiveness in managing mental state deterioration in acute hospital settings. Realist principles guide the exploration of causal mechanisms and their interaction with specific implementation contexts. The objective is to identify what works, for whom, and under what circumstances, aiming to manage deterioration, reduce restrictive interventions, and enhance the experience for patients and staff by implementing a proactive model of care. The findings contribute to evidence-based approaches for managing mental state deterioration in hospital settings, informing policy and practice in this crucial area of healthcare.

Artificial intelligence-based personalized clinical decision-making for patients with localized prostate cancer: surgery versus radiotherapy.

BACKGROUND: Surgery and radiotherapy are primary nonconservative treatments for prostate cancer (PCa). However, personalizing treatment options between these treatment modalities is challenging due to unclear criteria. We developed an artificial intelligence (AI)-based model that can identify patients with localized PCa who would benefit more from either radiotherapy or surgery, thereby providing personalized clinical decision-making. MATERIAL AND METHODS: Data from consecutive patients with localized PCa who received radiotherapy or surgery with complete records of clinicopathological variables and follow-up results in 12 registries of the Surveillance, Epidemiology, and End Results database were analyzed. Patients from 7 registries were randomly assigned to training (TD) and internal validation datasets (IVD) at a 9:1 ratio. The remaining 5 registries constituted the external validation dataset (EVD). TD was divided into training-radiotherapy (TRD) and training-surgery (TSD) datasets, and IVD was divided into internal-radiotherapy (IRD) and internal-surgery (ISD) datasets. Six models for radiotherapy and surgery were trained using TRD and TSD to predict radiotherapy survival probability (RSP) and surgery survival probability (SSP), respectively. The models with the highest concordance index (C-index) on IRD and ISD were chosen to form the final treatment recommendation model (FTR). FTR recommendations were based on the higher value between RSP and SSP. Kaplan-Meier curves were generated for patients receiving recommended (consistent group) and nonrecommended treatments (inconsistent group), which were compared using the log-rank test. RESULTS: The study included 118 236 patients, categorized into TD (TRD: 44 621; TSD: 41 500), IVD (IRD: 4949; ISD: 4621), and EVD (22 545). Both radiotherapy and surgery models accurately predicted RSP and SSP (C-index: 0.735-0.787 and 0.769-0.797, respectively). The consistent group exhibited higher survival rates than the inconsistent group, particularly among patients not suitable for active surveillance (P < .001). CONCLUSION: FTR accurately identifies patients with localized PCa who would benefit more from either radiotherapy or surgery, offering clinicians an effective AI tool to make informed choices between these 2 treatments.

Health professionals implicit bias of patients with low socioeconomic status (SES) and its effects on clinical decision-making: a scoping review.

OBJECTIVES: Research indicates that people with lower socioeconomic status (SES) receive inferior healthcare and experience poorer health outcomes compared with those with higher SES, in part due to health professional (HP) bias. We conducted a scoping review of the impact of HP bias about SES on clinical decision-making and its effect on the care of adults with lower SES. DESIGN: JBI scoping review methods were used to perform a systematic comprehensive search for literature. The scoping review protocol has been published in BMJ Open. DATA SOURCES: Medline, Embase, ASSIA, Scopus and CINAHL were searched, from the first available start date of the individual database to March 2023. Two independent reviewers filtered and screened papers. ELIGIBILITY CRITERIA: Studies of all designs were included in this review to provide a comprehensive map of the existing evidence of the impact of HP bias of SES on clinical decision-making and its effect on the care for people with lower SES. DATA EXTRACTION AND SYNTHESIS: Data were gathered using an adapted JBI data extraction tool for systematic scoping reviews. RESULTS: Sixty-seven papers were included from 1975 to 2023. 35 (73%) of the included primary research studies reported an association between HP SES bias and decision-making. Thirteen (27%) of the included primary research studies did not find an association between HP SES bias and decision-making. Stereotyping and bias can adversely affect decision-making when the HP is fatigued or has a high cognitive load. There is evidence of intersectionality which can have a powerful cumulative effect on HP assessment and subsequent decision-making. HP implicit bias may be mitigated through the assertiveness of the patient with low SES. CONCLUSION: HP decision-making is at times influenced by non-medical factors for people of low SES, and assumptions are made based on implicit bias and stereotyping, which compound or exacerbate health inequalities. Research that focuses on decision-making when the HP has a high cognitive load, would help the health community to better understand this potential influence.

Frailty means falling between the cracks: A qualitative study exploring emergency nurses' understanding of frailty and its use in informing clinical decision-making related to acuity, care, and disposition.

THE PURPOSE: Of this study was to understand emergency nurses' use of frailty to inform care, disposition decision-making, and further assessment. METHODS: A qualitative, descriptive, exploratory approach was used. Field notes from group discussions held during a conference presession on frailty and post-session evaluation data were analyzed. RESULTS: Two common ideas threaded these discussions: frailty as vulnerability to "falling through the cracks" and that of an iceberg. Participants stressed the broad and expansive ramifications of frailty, and lack of structure/process to accurately describe, quantify, and utilize the concept. Participants described issues of physical and emotional/social fragility, including being unable to complete activities of daily living independently; also of concern were the patients' social determinants of health and financial challenges. CONCLUSION: The conceptual understanding of frailty encompassed physical, social, cognitive, and access deficits. Emergency nurses are aware of this concept and would conduct formal frailty screening if provided with training, time, and resources.

Attitudes Towards Non-directiveness Among Medical Geneticists in Germany and Switzerland.

The principle of non-directiveness remains an important tenet in genetics. However, the concept has encountered growing criticism over the last two decades. There is an ongoing discussion about its appropriateness for specific situations in genetics, especially in light of recent significant advancements in genetic medicine. Despite the debate surrounding non-directiveness, there is a notable lack of up-to-date international research empirically investigating the issue from the perspective of those who actually do genetic counselling. Addressing this gap, our article delves into the viewpoints and experiences of medical geneticists in Germany and Switzerland. Twenty qualitative interviews were analysed employing reflexive thematic analysis. Participants' responses revealed substantial uncertainties and divergences in their understanding and application of the concept. It seems to cause distress since many geneticists stated that the principle was difficult to put into clinical practice and was no longer ethically justified given the increasing likelihood of therapeutic implications resulting from genomic testing outcomes. The insights provided by our qualitative empirical study accord with the ongoing theoretical debate regarding the definition, legitimacy, and feasibility of the principle. An adequately nuanced understanding and application of non-directiveness seems crucial to circumvent the risks inherent in the principle, while promoting patient autonomy and beneficence.

Managing the Labyrinth of Complex Ethical Issues in Anesthesia Practice: The Anesthesiologist's Ariadne's Thread.

Facing ethical dilemmas is challenging and sometimes becomes a real burden for anesthesiologists, particularly because they rarely have previous or long-standing patient relationships that help inform clinical decision-making. Although there is no ideal algorithm that can fit all clinical situations, some basic moral and ethical principles, which should be part of every clinician's armamentarium, can guide the decision-making process. Dealing with conflicting views among providers and/or patients can be distressing but can lead to meaningful professional and personal growth for each clinician.

Assessing Decision Fatigue in General Practitioners' Prescribing Decisions Using the Australian BEACH Data Set.

BACKGROUND: General practitioners (GPs) make numerous care decisions throughout their workdays. Extended periods of decision making can result in decision fatigue, a gradual shift toward decisions that are less cognitively effortful. This study examines whether observed patterns in GPs' prescribing decisions are consistent with the decision fatigue phenomenon. We hypothesized that the likelihood of prescribing frequently overprescribed medications (antibiotics, benzodiazepines, opioids; less effortful to prescribe) will increase and the likelihood of prescribing frequently underprescribed medications (statins, osteoporosis medications; more effortful to prescribe) will decrease over the workday. METHODS: This study used nationally representative primary care data on GP-patient encounters from the Bettering the Evaluation and Care of Health program from Australia. The association between prescribing decisions and order of patient encounters over a GP's workday was assessed with generalized linear mixed models accounting for clustering and adjusting for patient, provider, and encounter characteristics. RESULTS: Among 262,456 encounters recorded by 2,909 GPs, the odds of prescribing antibiotics significantly increased by 8.7% with 15 additional patient encounters (odds ratio [OR] = 1.087; confidence interval [CI] = 1.059-1.116). The odds of prescribing decreased significantly with 15 additional patient encounters by 6.3% for benzodiazepines (OR = 0.937; CI = 0.893-0.983), 21.9% for statins (OR = 0.791; CI = 0.753-0.831), and 25.0% for osteoporosis medications (OR = 0.750; CI = 0.690-0.814). No significant effects were observed for opioids. All findings were replicated in confirmatory analyses except the effect of benzodiazepines. CONCLUSIONS: GPs were increasingly likely to prescribe antibiotics and were less likely to prescribe statins and osteoporosis medications as the workday wore on, which was consistent with decision fatigue. There was no convincing evidence of decision fatigue effects in the prescribing of opioids or benzodiazepines. These findings establish decision fatigue as a promising target for optimizing prescribing behavior. HIGHLIGHTS: We found that as general practitioners progress through their workday, they become more likely to prescribe antibiotics that are reportedly overprescribed and less likely to prescribe statins and osteoporosis medications that are reportedly underprescribed.This change in decision making over time is consistent with the decision fatigue phenomenon. Decision fatigue occurs when we make many decisions without taking a rest break. As we make those decisions, we become gradually more likely to make decisions that are less difficult.The findings of this study show that decision fatigue is a possible target for improving guideline-compliant prescribing of pharmacologic medications.

Clinical reasoning and clinical judgment in nursing research: A bibliometric analysis.

AIMS: To characterize the thematic foci, structure, and evolution of nursing research on clinical reasoning and judgment. DESIGN: Bibliometric analysis. METHODS: We used a bibliometric method to analyze 1528 articles. DATA SOURCE: We searched the Scopus bibliographic database on January 7, 2024. RESULTS: Through a keyword co-occurrence analysis, we found the most frequent keywords to be clinical judgment, clinical reasoning, nursing education, simulation, nursing, clinical decision-making, nursing students, nursing assessment, critical thinking, nursing diagnosis, patient safety, nurses, nursing process, clinical competence, and risk assessment. The focal themes, structure, and evolution of nursing research on clinical reasoning and judgment were revealed by keyword mapping, clustering, and time-tracking. CONCLUSION: By assessing key nursing research areas, we extend the current discourse on clinical reasoning and clinical judgment for researchers, educators, and practitioners. Critical challenges must still be met by nursing professionals with regard to their use of clinical reasoning and judgment within their clinical practice. Further knowledge and comprehension of the clinical reasoning process and the development of clinical judgment must be successfully translated from research to nursing education and practice. IMPLICATIONS FOR THE PROFESSION: This study highlights the nursing knowledge gaps with regard to nurses' use of clinical reasoning and judgment and encourages nursing educators and professionals to focus on developing nurses' clinical reasoning and judgment with regard to their patients' safety. IMPACT: In addressing nurses' use of clinical reasoning and judgment, and with regard to patient safety in particular, this study found that, in certain clinical settings, the use of clinical reasoning and judgment remains a challenge for nursing professionals. This study should thus have an effect on nursing academics' research choices, on nursing educators' teaching practices, and on nurses' clinical practices. REPORTING METHOD: Relevant EQUATOR guidelines have been adhered to by employing recognized bibliometric reporting methods.

Development Plan for the Clinical Application of Maternity and Child Health Mobile App.

In 2021, the World Health Organization designated the theme for World Patient Safety Day as "Safe Maternal and Newborn Care" with the aim of raising awareness of the importance of maternal and newborn safety and improving their overall safety. Many healthcare institutions in Taiwan currently provide printed materials such as childbirth guidelines and nursing instructions to patients. However, mobile applications in the current digital world might be more handy to assist pregnant women in understanding the changes during pregnancy and provide relevant health education in order to help reduce pregnancy and childbirth complications, as well as decrease maternal and neonatal mortality rates.

[Advances in clinical repair techniques for localized knee cartilage lesions].

Objective: To summarize the classic and latest treatment techniques for localized knee cartilage lesions in clinical practice and create a new comprehensive clinical decision-making process. Methods: The advantages and limitations of various treatment methods for localized knee cartilage lesions were summarized by extensive review of relevant literature at home and abroad in recent years. Results: Currently, there are various surgical methods for treating localized knee cartilage injuries in clinical practice, each with its own pros and cons. For patients with cartilage injuries less than 2 cm 2 and 2-4 cm 2 with bone loss are recommended to undergo osteochondral autograft (OAT) and osteochondral allograft (OCA) surgeries. For patients with cartilage injuries less than 2 cm 2 and 2-4 cm 2 without bone loss had treatment options including bone marrow-based techniques (micro-fracture and ogous matrix induced chondrogenesis), autologous chondrocyte implantation (ACI)/matrix-induced ACI, particulated juvenile allograft cartilage (PJAC), OAT, and OCA. For patients with cartilage injuries larger than 4 cm 2 with bone loss were recommended to undergo OCA. For patients with cartilage injuries larger than 4 cm 2 without bone loss, treatment options included ACI/matrix-induced ACI, OAT, and PJAC. Conclusion: There are many treatment techniques available for localized knee cartilage lesions. Treatment strategy selection should be based on the size and location of the lesion, the extent of involvement of the subchondral bone, and the level of evidence supporting each technique in the literature.

Preoperative prediction of microvascular invasion: new insights into personalized therapy for early-stage hepatocellular carcinoma.

Owing to advances in diagnosis and treatment methods over past decades, a growing number of early-stage hepatocellular carcinoma (HCC) diagnoses has enabled a greater of proportion of patients to receive curative treatment. However, a high risk of early recurrence and poor prognosis remain major challenges in HCC therapy. Microvascular invasion (MVI) has been demonstrated to be an essential independent predictor of early recurrence after curative therapy. Currently, biopsy is not generally recommended before treatment to evaluate MVI in HCC according clinical guidelines due to sampling error and the high risk of tumor cell seeding following biopsy. Therefore, the postoperative histopathological examination is recognized as the gold standard of MVI diagnosis, but this lagging indicator greatly impedes clinicians in selecting the optimal effective treatment for prognosis. As imaging can now noninvasively and completely assess the whole tumor and host situation, it is playing an increasingly important role in the preoperative assessment of MVI. Therefore, imaging criteria for MVI diagnosis would be highly desirable for optimizing individualized therapeutic decision-making and achieving a better prognosis. In this review, we summarize the emerging image characteristics of different imaging modalities for predicting MVI. We also discuss whether advances in imaging technique have generated evidence that could be practice-changing and whether advanced imaging techniques will revolutionize therapeutic decision-making of early-stage HCC.

Exploring treatment decision-making in chronic myeloid leukemia in chronic phase.

The introduction of tyrosine kinase inhibitors (TKIs) has transformed the treatment of chronic myeloid leukemia (CML). Each approved TKI has its own risk-benefit profile, and patients have choices across lines of therapy. Identifying the initial and subsequent treatment that will lead to the best possible outcome for individual patients is challenging. In this review, we summarize data for each approved TKI across lines of therapy in patients with CML in chronic phase, highlighting elements of each agent's safety and efficacy profile that may impact patient selection, and provide insights into individualized treatment sequencing decision-making aimed at optimizing patient outcomes.