Bias in Medicine: Lessons Learned and Mitigation Strategies

When Healthcare Professionals Disagree: Finding the Right Balance

Healthcare disagreements are common, but recognising the causes is essential to reaching a moral consensus. The article describes the challenges associated with resolving the disagreements. Therefore, a systematic and timely team-based discussion, ethics consultation with ethicists and the hospital ethics committee, active participation of all members' discussions, and scheduled debriefings are pragmatic ways to find balance when healthcare professionals disagree. Teams need these attempts to build consensus and make moral decisions. It also fosters harmony, prioritises patient and team interests and, most importantly, keeps the team intact.

Concordance of clinician, Chat-GPT4, and ORAD diagnoses against histopathology in Odontogenic Keratocysts and tumours: a 15-Year New Zealand retrospective study

BACKGROUND

This research aimed to investigate the concordance between clinical impressions and histopathologic diagnoses made by clinicians and artificial intelligence tools for odontogenic keratocyst (OKC) and Odontogenic tumours (OT) in a New Zealand population from 2008 to 2023.

METHODS

Histopathological records from the Oral Pathology Centre, University of Otago (2008-2023) were examined to identify OKCs and OT. Specimen referral details, histopathologic reports, and clinician differential diagnoses, as well as those provided by ORAD and Chat-GPT4, were documented. Data were analyzed using SPSS, and concordance between provisional and histopathologic diagnoses was ascertained.

RESULTS

Of the 34,225 biopsies, 302 and 321 samples were identified as OTs and OKCs. Concordance rates were 43.2% for clinicians, 45.6% for ORAD, and 41.4% for Chat-GPT4. Corresponding Kappa value against histological diagnosis were 0.23, 0.13 and 0.14. Surgeons achieved a higher concordance rate (47.7%) compared to non-surgeons (29.82%). Odds ratio of having concordant diagnosis using Chat-GPT4 and ORAD were between 1.4 and 2.8 (p < 0.05). ROC-AUC and PR-AUC were similar between the groups (Clinician 0.62/0.42, ORAD 0.58/0.28, Char-GPT4 0.63/0.37) for ameloblastoma and for OKC (Clinician 0.64/0.78, ORAD 0.66/0.77, Char-GPT4 0.60/0.71).

CONCLUSION

Clinicians with surgical training achieved higher concordance rate when it comes to OT and OKC. Chat-GPT4 and Bayesian approach (ORAD) have shown potential in enhancing diagnostic capabilities.

Navigating Neurologic Illness: Skills in Neuropalliative Care for Persons Hospitalized with Neurologic Disease

Persons hospitalized for neurologic illness face multidimensional care needs. They can benefit from a palliative care approach that focuses on quality of life for persons with serious illness. We describe neurology provider "skills" to help meet these palliative needs: assessing the patient as a whole; facilitating conversations with patients to connect prognosis to care preferences; navigating neurologic illness to prepare patients and care partners for the future; providing high-quality end-of-life care to promote peace in death; and addressing disparities in care delivery.

Cognitive biases in pediatric cardiac care

Medical practitioners are entrusted with the pivotal task of making optimal decisions in healthcare delivery. Despite rigorous training, our confidence in reasoning can fail when faced with pressures, uncertainties, urgencies, difficulties, and occasional errors. Day-to-day decisions rely on swift, intuitive cognitive processes known as heuristic or type 1 decision-making, which, while efficient in most scenarios, harbor inherent vulnerabilities leading to systematic errors. Cognitive biases receive limited explicit discussion during our training as junior doctors in the domain of paediatric cardiology. As pediatric cardiologists, we frequently confront emergencies necessitating rapid decision-making, while contending with the pressures of stress, fatigue, an earnest interest in "doing the right thing" and the impact of parental involvement. This article aims to describe cognitive biases in pediatric cardiology, highlighting their influence on therapeutic interventions for congenital heart disease. Whether future pediatric cardiologists or experienced professionals, understanding and actively combating cognitive biases are essential components of our ongoing medical education. Furthermore, it is our responsibility to thoroughly examine our own practices in our unwavering commitment to providing high-quality care.

Distant Multilevel Spinal Metastasis Secondary to Hypopharyngeal Squamous Cell Carcinoma

Head and neck squamous cell carcinomas account for most head and neck malignancies. While multi-modality treatment may be offered for locally advanced cancer, distant metastasis still occurs in a significant number of patients. This paper aims to present a rare case of a patient who developed bony metastases in the cervical spine from a primary hypopharyngeal malignancy status post-laryngopharyngectomy. We report a case of a male patient presenting with acute-on-chronic hypercapnic and hypoxic respiratory failure with two months of dysphagia and weight loss. On arrival, a barium swallow revealed mucosal irregularity of the upper thoracic esophagus as well as narrowing and stenosis. A direct laryngoscopy with biopsy revealed squamous cell carcinoma of the hypopharynx. CT neck and chest were obtained for staging. He underwent a total laryngopharyngectomy, bilateral neck dissections, and a free flap. His final staging was pT4aN2c cM0. Three months post-admission, during inpatient radiation therapy, the patient reported midline neck pain with focal bone tenderness, and an MRI was obtained of his cervical and thoracic spine with a report concerning spinal metastasis.A subsequent bone biopsy showed findings consistent with osseous metastasis from a primary hypopharyngeal squamous cell carcinoma. After multidisciplinary goals of care discussions, the patient ultimately decided to be discharged to inpatient hospice. This report highlights a rare case of hypopharyngeal carcinoma metastasis to the cervical spine. Despite its rarity and poor prognosis, such a metastasis should be considered in the differential diagnosis of patients with a history of hypopharyngeal squamous cell carcinoma and localizing symptoms.

Alternative approaches to analyzing ventilator-free days, mortality and duration of ventilation in critical care research

OBJECTIVE

To discuss the strengths and limitations of ventilator-free days and to provide a comprehensive discussion of the different analytic methods for analyzing and interpreting this outcome.

METHODS

Using simulations, the power of different analytical methods was assessed, namely: quantile (median) regression, cumulative logistic regression, generalized pairwise comparison, conditional approach and truncated approach. Overall, 3,000 simulations of a two-arm trial with n = 300 per arm were computed using a two-sided alternative hypothesis and a type I error rate of α = 0.05.

RESULTS

When considering power, median regression did not perform well in studies where the treatment effect was mainly driven by mortality. Median regression performed better in situations with a weak effect on mortality but a strong effect on duration, duration only, and moderate mortality and duration. Cumulative logistic regression was found to produce similar power to the Wilcoxon rank-sum test across all scenarios, being the best strategy for the scenarios of moderate mortality and duration, weak mortality and strong duration, and duration only.

CONCLUSION

In this study, we describe the relative power of new methods for analyzing ventilator-free days in critical care research. Our data provide validation and guidance for the use of the cumulative logistic model, median regression, generalized pairwise comparisons, and the conditional and truncated approach in specific scenarios.

Survival bias in pediatric hemorrhagic shock: Are we misrepresenting the data?

BACKGROUND

Studies of hemorrhage following pediatric injury often use the occurrence of transfusion as a surrogate definition for the clinical need for a transfusion. Using this approach, patients who are bleeding but die before receiving a transfusion are misclassified as not needing a transfusion. In this study, we aimed to evaluate the potential for this survival bias and to estimate its presence among a retrospective observational cohort of children and adolescents who died from injury.

METHODS

We obtained patient, injury, and resuscitation characteristics from the 2017 to 2020 Trauma Quality Improvement Program database of children and adolescents (younger than 18 years) who arrived with or without signs of life and died. We performed univariate analysis and a multivariable logistic regression to analyze the association between the time to death and the occurrence of transfusion within 4 hours after hospital arrival controlling for initial vital signs, injury type, body regions injured, and scene versus transfer status.

RESULTS

We included 6,063 children who died from either a blunt or penetrating injury. We observed that children who died within 15 minutes had lower odds of receiving a transfusion (odds ratio, 0.1; 95% confidence interval, 0.1-0.2) compared with those who survived longer. We estimated that survival bias that occurs when using transfusion administration alone to define hemorrhagic shock may occur in up to 11% of all children who died following a blunt or penetrating injury but less than 1% of all children managed as trauma activations.

CONCLUSION

Using the occurrence of transfusion alone may underestimate the number of children who die from uncontrolled hemorrhage early after injury. Additional variables than just transfusion administration are needed to more accurately identify the presence of hemorrhagic shock among injured children and adolescents.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.

Understanding and Mitigating Bias in Imaging Artificial Intelligence

Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model development, with potential for exacerbating health disparities. However, bias in imaging AI is a complex topic that encompasses multiple coexisting definitions. Bias may refer to unequal preference to a person or group owing to preexisting attitudes or beliefs, either intentional or unintentional. However, cognitive bias refers to systematic deviation from objective judgment due to reliance on heuristics, and statistical bias refers to differences between true and expected values, commonly manifesting as systematic error in model prediction (ie, a model with output unrepresentative of real-world conditions). Clinical decisions informed by biased models may lead to patient harm due to action on inaccurate AI results or exacerbate health inequities due to differing performance among patient populations. However, while inequitable bias can harm patients in this context, a mindful approach leveraging equitable bias can address underrepresentation of minority groups or rare diseases. Radiologists should also be aware of bias after AI deployment such as automation bias, or a tendency to agree with automated decisions despite contrary evidence. Understanding common sources of imaging AI bias and the consequences of using biased models can guide preventive measures to mitigate its impact. Accordingly, the authors focus on sources of bias at stages along the imaging machine learning life cycle, attempting to simplify potentially intimidating technical terminology for general radiologists using AI tools in practice or collaborating with data scientists and engineers for AI tool development. The authors review definitions of bias in AI, describe common sources of bias, and present recommendations to guide quality control measures to mitigate the impact of bias in imaging AI. Understanding the terms featured in this article will enable a proactive approach to identifying and mitigating bias in imaging AI. Published under a CC BY 4.0 license. Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Rouzrokh and Erickson in this issue.

Sports Medicine Patient Experience: Implicit Bias Mitigation and Communication Strategies

Unconscious bias, also known as implicit bias, is the principal contributor to the perpetuation of discrimination and is a robust determinant of people's decision-making. Unconscious bias occurs despite conscious nonprejudiced intentions and interferes with the actions of the reflective and conscious side. Education and self-awareness about implicit bias and its potentially harmful effects on judgment and behavior may lead individuals to pursue corrective action and follow implicit bias mitigation communication strategies. Team physicians must follow existing communication strategies and guidelines to mitigate unconscious bias and begin an evolution toward nonbiased judgment and decision-making to improve athlete care.

Measurement and Mitigation of Bias in Artificial Intelligence: A Narrative Literature Review for Regulatory Science

Artificial intelligence (AI) is increasingly being used in decision making across various industries, including the public health arena. Bias in any decision-making process can significantly skew outcomes, and AI systems have been shown to exhibit biases at times. The potential for AI systems to perpetuate and even amplify biases is a growing concern. Bias, as used in this paper, refers to the tendency toward a particular characteristic or behavior, and thus, a biased AI system is one that shows biased associations entities. In this literature review, we examine the current state of research on AI bias, including its sources, as well as the methods for measuring, benchmarking, and mitigating it. We also examine the biases and methods of mitigation specifically relevant to the healthcare field and offer a perspective on bias measurement and mitigation in regulatory science decision making.

Machine Learning and Bias in Medical Imaging: Opportunities and Challenges

Bias in health care has been well documented and results in disparate and worsened outcomes for at-risk groups. Medical imaging plays a critical role in facilitating patient diagnoses but involves multiple sources of bias including factors related to access to imaging modalities, acquisition of images, and assessment (ie, interpretation) of imaging data. Machine learning (ML) applied to diagnostic imaging has demonstrated the potential to improve the quality of imaging-based diagnosis and the precision of measuring imaging-based traits. Algorithms can leverage subtle information not visible to the human eye to detect underdiagnosed conditions or derive new disease phenotypes by linking imaging features with clinical outcomes, all while mitigating cognitive bias in interpretation. Importantly, however, the application of ML to diagnostic imaging has the potential to either reduce or propagate bias. Understanding the potential gain as well as the potential risks requires an understanding of how and what ML models learn. Common risks of propagating bias can arise from unbalanced training, suboptimal architecture design or selection, and uneven application of models. Notwithstanding these risks, ML may yet be applied to improve gain from imaging across all 3A's (access, acquisition, and assessment) for all patients. In this review, we present a framework for understanding the balance of opportunities and challenges for minimizing bias in medical imaging, how ML may improve current approaches to imaging, and what specific design considerations should be made as part of efforts to maximize the quality of health care for all.

Implementation of a novel peer review academy by Surgery and the Association of Women Surgeons

BACKGROUND

A novel Peer Review Academy was developed as a collaborative effort between the Association of Women Surgeons and the journal Surgery to provide formal training in peer review. We aimed to describe the outcomes of this initiative using a mixed methods approach.

METHODS

We developed a year-long curriculum with monthly online didactic sessions. Women surgical trainee mentees were paired 1:1 with rotating women surgical faculty mentors for 3 formal peer review opportunities. We analyzed pre-course and post-course surveys to evaluate mentee perceptions of the academy and assessed changes in mentee review quality over time with blinded scoring of unedited reviews. Semi-structured interviews were conducted upon course completion.

RESULTS

Ten women surgical faculty mentors and 10 women surgical trainees from across the United States and Canada successfully completed the Peer Review Academy. There were improvements in the mentees' confidence for all domains of peer review evaluated, including overall confidence in peer review, study novelty, study design, analytic approach, and review formatting (all, P ≤ .02). The mean score of peer review quality increased over time (59.2 ± 10.8 vs 76.5 ± 9.4; P = .02). In semi-structured interviews, important elements were emphasized across the Innovation, Implementation Process, and Individuals Domains, including the values of (1) a comprehensive approach to formal peer review education; (2) mentoring relationships between women faculty and resident surgeons; and (3) increasing diversity in the scientific peer review process.

CONCLUSION

Our novel Peer Review Academy was feasible on a national scale, resulting in significant qualitative and quantitative improvements in women surgical trainee skillsets, and has the potential to grow and diversify the existing peer review pool.

Delayed amyotrophic lateral sclerosis diagnosis with subtle cardiac manifestations: Was anchoring bias contributory?

Amyotrophic lateral sclerosis (ALS) is a rare, progressive neurodegenerative disease affecting both upper and lower motor neurons. Throughout medical training, it is taught that the most recognizable clinical presentation involves both motor and bulbar changes. Given the complexity of the diagnosis however, it is no surprise that there is significant multisystem involvement secondary to the autonomic dysfunction associated with the disease. The clinical cognitive biases that exist due to prior educational training and patient provided chief complaint can mislead clinicians and prevent a holistic, inclusive approach toward each patient encounter. This can delay diagnosis and increase unnecessary healthcare spending. In a disease with such a poor prognosis, this effect can be catastrophic, resulting in unacceptable medical, functional, and psychosocial outcomes. As clinicians, it is imperative to acknowledge these cognitive biases through introspection, which can improve clinical outcomes and ultimately patient quality of life for those facing this devastating disease. We report a case of a 55-year-old female who presented with a chief complaint of palpitations and minimal slurred speech on multiple encounters, subsequently leading to a focused cardiovascular workup. It was not until after several hospital encounters that a thorough functional and neuromuscular exam was performed, which ultimately helped to broaden the differential and lead to the diagnosis of ALS. Unfortunately, due to this delayed diagnosis, the patient's functionality was beyond repair. Given the underlying cognitive biases that are present in all clinicians, we hypothesize this patient's sex, presenting symptom, and primary chief complaint misled clinicians to perform limited history and physical examinations, therefore, leading to a narrowed differential. If diagnosed in a timely fashion, vital services such as rehabilitation could have provided this patient with the necessary medical, functional, and psychosocial support to face this devastating disease.

Clinical features and outcomes of influenza and RSV coinfections: a report from Canadian immunization research network serious outcomes surveillance network

BACKGROUND

Influenza and RSV coinfections are not commonly seen but are concerning as they can lead to serious illness and adverse clinical outcomes among vulnerable populations. Here we describe the clinical features and outcomes of influenza and RSV coinfections in hospitalized adults.

METHODS

A cohort study was performed with pooled active surveillance in hospitalized adults ≥ 50 years from the Serious Outcomes Surveillance Network of the Canadian Immunization Research Network (CIRN SOS) during the 2012/13, 2013/14, and 2014/15 influenza seasons. Descriptive statistics summarized the characteristics of influenza/RSV coinfections. Kaplan-Meier estimated the probability of survival over the first 30 days of hospitalization.

RESULTS

Over three influenza seasons, we identified 33 cases of RSV and influenza coinfection, accounting for 2.39 cases per 1,000 hospitalizations of patients with acute respiratory illnesses. Adults aged 50 + years commonly reported cough (81.8%), shortness of breath (66.7%), sputum production (45.5%), weakness (33.3%), fever (27.3%), and nasal congestion (24.2%) as constitutional and lower respiratory tract infection symptoms. The mortality rate was substantial (12.1%), and age, comorbidity burden, and frailty were associated with a higher risk for adverse clinical outcomes.

CONCLUSIONS

Older adults are at higher risk for complications from influenza and RSV coinfections, especially those over 65 with a high comorbidity burden and frailty.

Limitations in Medical Research: Recognition, Influence, and Warning

Background

As the number of limitations increases in a medical research article, their consequences multiply and the validity of findings decreases. How often do limitations occur in a medical article? What are the implications of limitation interaction? How often are the conclusions hedged in their explanation?

Objective

To identify the number, type, and frequency of limitations and words used to describe conclusion(s) in medical research articles.

Methods

Search, analysis, and evaluation of open access research articles from 2021 and 2022 from the Journal of the Society of Laparoscopic and Robotic Surgery and 2022 Surgical Endoscopy for type(s) of limitation(s) admitted to by author(s) and the number of times they occurred. Limitations not admitted to were found, obvious, and not claimed. An automated text analysis was performed for hedging words in conclusion statements. A limitation index score is proposed to gauge the validity of statements and conclusions as the number of limitations increases.

Results

A total of 298 articles were reviewed and analyzed, finding 1,764 limitations. Four articles had no limitations. The average was between 3.7% and 6.9% per article. Hedging, weasel words and words of estimative probability description was found in 95.6% of the conclusions.

Conclusions

Limitations and their number matter. The greater the number of limitations and ramifications of their effects, the more outcomes and conclusions are affected. Wording ambiguity using hedging or weasel words shows that limitations affect the uncertainty of claims. The limitation index scoring method shows the diminished validity of finding(s) and conclusion(s).

Pitfalls in scalp EEG: Current obstacles and future directions

Although electroencephalography (EEG) serves a critical role in the evaluation and management of seizure disorders, it is commonly misinterpreted, resulting in avoidable medical, social, and financial burdens to patients and health care systems. Overinterpretation of sharply contoured transient waveforms as being representative of interictal epileptiform abnormalities lies at the core of this problem. However, the magnitude of these errors is amplified by the high prevalence of paroxysmal events exhibited in clinical practice that compel investigation with EEG. Neurology training programs, which vary considerably both in the degree of exposure to EEG and the composition of EEG didactics, have not effectively addressed this widespread issue. Implementation of competency-based curricula in lieu of traditional educational approaches may enhance proficiency in EEG interpretation amongst general neurologists in the absence of formal subspecialty training. Efforts in this regard have led to the development of a systematic, high-fidelity approach to the interpretation of epileptiform discharges that is readily employable across medical centers. Additionally, machine learning techniques hold promise for accelerating accurate and reliable EEG interpretation, particularly in settings where subspecialty interpretive EEG services are not readily available. This review highlights common diagnostic errors in EEG interpretation, limitations in current educational paradigms, and initiatives aimed at resolving these challenges.

How the COVID-19 Pandemic Contributed to Diagnostic Bias

Diagnosis bias in the medical field is a recognized entity that can contribute to misdiagnoses and incorrect management. It remains a constant challenge that must be recognized and addressed. Several factors play a role in the formation of preconceptions which influence the physicians' decision-making process. The aim of this paper is to present a case that was misdiagnosed and mistakenly managed due to diagnosis bias during the coronavirus disease 2019 (COVID-19) pandemic. We also suggest two ways to reduce the risk of diagnosis bias. Multi-inflammatory syndrome of children (MIS-C) was described during the COVID-19 pandemic. The rise in the incidence of MIS-C masked the diagnosis of other diseases that present in a similar fashion. In this paper, we describe the case of a seven-year-old girl, who presented in 2020, with acute onset respiratory distress. Her chest images were suggestive of COVID-19 pneumonitis which prompted the physicians to complete the MIS-C workup by performing an echocardiogram. A large aneurysm of the left main artery was seen which led to a preliminary diagnosis of MIS-C. A repeat echocardiography, 48 hours after the initiation of MIS-C treatment, was suggestive of a large coronary fistula complicated by infective endocarditis and multiple septic pulmonary emboli. It can be inferred that the misdiagnosis occurred as a result of availability and premature-closure biases. Efforts to decrease such biases include group decision-making and using checklists during the assessment of a patient.

Strategies to Counteract Impact of Harmful Bias in Selection of Medical Residents

Human biases impact medical care in ways that perpetuate health disparities. Research has demonstrated that biases negatively affect patient outcomes and stifle diversity across the physician workforce, further compounding health disparities by worsening patient-physician concordance. Taken as one, the application, interview, recruitment, and selection processes employed by residency programs has been one of the critical junctures where bias has exacerbated inequities among future physicians. In this article, the authors define diversity and bias, review the history of bias in residency programs' processes for selecting residents, explore the impact of this history on workforce demographics, and discuss ways to optimize and work toward equity in the practices used by residency programs to select residents.

Biologically inspired gastrointestinal stapler design: "Getting to Zero" complications

As next generation stapling devices enter the marketplace with robotic adaptations, tri-staple technology, preloaded reinforcement materials, etc., in this perspective piece we assert that a "refresh" in our understanding of the mechanisms of action of these devices is needed. While much attention has been paid to explain the mechanical features of one device versus another, it seems that little to no attention is being paid to understand how an intestinal anastomosis responds biologically to the variations in their use and design. Here we will review various aspects of gastrointestinal stapling in the context of emerging technology in the field and expose the gaps in knowledge that exist regarding the effect of gastrointestinal stapling on the biology of healing.

Development and validation of a Bayesian network predicting neurosurgical intervention after injury in children and adolescents

BACKGROUND

Timely surgical decompression improves functional outcomes and survival among children with traumatic brain injury and increased intracranial pressure. Previous scoring systems for identifying the need for surgical decompression after traumatic brain injury in children and adults have had several barriers to use. These barriers include the inability to generate a score with missing data, a requirement for radiographic imaging that may not be immediately available, and limited accuracy. To address these limitations, we developed a Bayesian network to predict the probability of neurosurgical intervention among injured children and adolescents (aged 1-18 years) using physical examination findings and injury characteristics observable at hospital arrival.

METHODS

We obtained patient, injury, transportation, resuscitation, and procedure characteristics from the 2017 to 2019 Trauma Quality Improvement Project database. We trained and validated a Bayesian network to predict the probability of a neurosurgical intervention, defined as undergoing a craniotomy, craniectomy, or intracranial pressure monitor placement. We evaluated model performance using the area under the receiver operating characteristic and calibration curves. We evaluated the percentage of contribution of each input for predicting neurosurgical intervention using relative mutual information (RMI).

RESULTS

The final model included four predictor variables, including the Glasgow Coma Scale score (RMI, 31.9%), pupillary response (RMI, 11.6%), mechanism of injury (RMI, 5.8%), and presence of prehospital cardiopulmonary resuscitation (RMI, 0.8%). The model achieved an area under the receiver operating characteristic curve of 0.90 (95% confidence interval [CI], 0.89-0.91) and had a calibration slope of 0.77 (95% CI, 0.29-1.26) with a y intercept of 0.05 (95% CI, -0.14 to 0.25).

CONCLUSION

We developed a Bayesian network that predicts neurosurgical intervention for all injured children using four factors immediately available on arrival. Compared with a binary threshold model, this probabilistic model may allow clinicians to stratify management strategies based on risk.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.

Diagnostic nightmare: intra-intestinal bleed masks intra-abdominal bleed after colonoscopy

Colonoscopy is a widely used method of screening, diagnosis and intervention. Complications are infrequent and generally present as colonic perforation or colonic hemorrhage. A rare and life-threatening complication of colonoscopy is splenic injury or rupture. We present a case report of an 81-year-old female who was admitted with hemodynamic instability and tachycardia due to gastrointestinal (GI) bleeding and developed hemoperitoneum within 24 hours following colonoscopy. The initial computed tomography (CT) scan was misdiagnosed due to the patient history of GI bleed, and the iatrogenic splenic injury was recognized only during a second CT after continued hemodynamic instability. The patient's initial diagnosis of a GI bleed masked the intraperitoneal bleed and led to a delayed diagnosis of splenic rupture and increased morbidity. This patient required an emergent laparotomy with a total splenectomy with lysis of adhesions.

The measurable impact of a diversity, equity, and inclusion editor on diversifying content, authorship, and peer review participation in the Journal of Vascular Surgery

OBJECTIVE

Women and minorities remain under-represented in academic vascular surgery. This under-representation persists in the editorial peer review process which may contribute to publication bias. In 2020, the Journal of Vascular Surgery (JVS) addressed this by diversifying the editorial board and creating a new Editor of Diversity, Equity, and Inclusion (DEI). The impact of a DEI editor on modifying the output of JVS has not yet been examined. We sought to determine the measurable impact of a DEI editor on diversifying perspectives represented in the journal, and on contributing to changes in the presence of DEI subject matter across published journal content.

METHODS

The authorship and content of published primary research articles, editorials, and special articles in JVS were examined from November 2019 through July 2022. Publications were examined for the year prior to initiation of the DEI Editor (pre), the year following (post), and from September 2021 to July 2022, accounting for the average 47-week time period from submission to publication in JVS (lag). Presence of DEI topics and women authorship were compared using χ² tests.

RESULTS

During the period examined, the number of editorials, guidelines, and other special articles dedicated to DEI topics in the vascular surgery workforce or patient population increased from 0 in the year prior to 4 (16.7%) in the 11-month lag period. The number of editorials, guidelines, and other special articles with women as first or senior authors nearly doubled (24% pre, 44.4% lag; P = .31). Invited commentaries and discussions were increasingly written by women as the study period progressed (18.7% pre, 25.9% post, 42.6% lag; P = .007). The number of primary research articles dedicated to DEI topics increased (5.6% pre, 3.3% post, 8.1% lag; P = .007). Primary research articles written on DEI topics were more likely to have women first or senior authors than non-DEI specific primary research articles (68.0% of all DEI vs 37.5% of a random sampling of non-DEI primary research articles; P < .001). The proportion of distinguished peer reviewers increased (from 2.8% in 2020 to 21.9% in 2021; P < .001).

CONCLUSIONS

The addition of a DEI editor to JVS significantly impacted the diversification of topics, authorship of editorials, special articles, and invited commentaries, as well as peer review participation. Ongoing efforts are needed to diversify subject matter and perspective in the vascular surgery literature and decrease publication bias.

Time is tissue: Barriers to timely transfusion after pediatric injury

ABSTRACT

Strategies to improve outcomes among children and adolescents in hemorrhagic shock have primarily focused on component resuscitation, pharmaceutical coagulation adjuncts, and hemorrhage control techniques. Many of these strategies have been associated with better outcomes in children, but the barriers to their use and the impact of timely use on morbidity and mortality have received little attention. Because transfusion is uncommon in injured children, few studies have identified and described barriers to the processes of using these interventions in bleeding patients, processes that move from the decision to transfuse, to obtaining the necessary blood products and adjuncts, and to delivering them to the patient. In this review, we identify and describe the steps needed to ensure timely blood transfusion and propose practices to minimize barriers in this process. Given the potential impact of time on hemorrhage associated outcomes, ensuring timely intervention may have a similar or greater impact than the interventions themselves.

Recommended first-line management of brain metastases from melanoma: A multicenter survey of clinical practice

BACKGROUND

Radiotherapy (RT) and surgery (Sx) are effective in treating brain metastases. However, immune checkpoint inhibitors (ICI) have shown activity against asymptomatic melanoma brain metastases (MBM). BRAF/MEK inhibitors can be used to treat BRAF V600 mutation positive (BRAF+) MBM.

METHOD

We conducted an international survey among experts from medical oncology (MO), clinical oncology (CO), radiation oncology (RO), and neurosurgery (NS) about treatment recommendations for patients with asymptomatic BRAF+ or BRAF mutation negative (BRAF-) MBM. Eighteen specific clinical scenarios were presented and a total of 267 responses were collected. Answers were grouped and compared using Fisher's exact test.

RESULTS

In most MBM scenarios, survey respondents, regardless of specialty, favored RT in addition to systemic therapy. However, for patients with BRAF+ MBM, MO and CO were significantly more likely than RO and NS to recommend BRAF/MEK inhibitors alone, without the addition of RT, including the majority of MO (51%) for patients with 1-3 MBM, all <2cm. Likewise, for BRAF- MBM, MO and CO more commonly recommended single or dual agent ICI only and dual agent ICI therapy alone was the most common recommendation from MO or CO for MBM <2cm. When at least 1 of 3 MBM (BRAF+ or BRAF-) was >2cm, upfront Sx was recommended by all groups with the exception that MO and RO recommended RT for BRAF- MBM.

CONCLUSIONS

In most clinical settings involving asymptomatic MBM, experts recommended RT in addition to systemic therapy. However, recommendations varied significantly according to specialty, with MO and CO more commonly recommending dual systemic therapy alone for up to 9 BRAF- MBM <2cm.

Thinking Outside the Box

Clinical decision-making process is very complex and influenced by multiple aspects. As diagnosis likelihood assessment is often based on intuitive thinking, data misinterpretation, and diagnostic errors may commonly occur. We present a peculiar clinical case of a 27-year-old obese woman admitted to the emergency department after an inaugural episode of seizures. She had an oncologic disease. She was febrile and hypertensive at first evaluation. The report evolves around the diagnostic assessment, hampered by incongruent anamneses, incorrect data interpretation, and a pinch of clinical obstination, which nearly culminated in two deaths. Then, we discuss the series of biases that have confused the physicians. The only way to escape the intuitive thinking trap is to be humbly aware of our own thinking method’s limitations and to learn about the biases that often lead us into errors. Sometimes, thinking outside the box is the key.

Practical guide for the use of medical evidence in scientific publication: Recommendations for the medical student: Narrative review

Currently, the adaptation of scientific evidence in clinical problem solving is based on the evidence-based medicine method. Medical students and health professionals should have an adequate knowledge of this method and thus provide adequate health care and increasingly provide high quality scientific publications that can be subsequently integrated in different clinical scenarios. Several scales and tools have been proposed as guides to recognize the different levels of quality of the available evidence, their degrees of recommendation and the biases and fallacies that may occur both in the clinical and research areas, with the aim of identifying the best available evidence. However, few students and professionals are aware of them and make proper use of them. Therefore, it is necessary to synthesize these tools in an understandable and practical way.