Adherence of studies involving artificial intelligence in the analysis of ophthalmology electronic medical records to AI-specific items from the CONSORT-AI guideline: a systematic review.

PURPOSE: In the context of ophthalmologic practice, there has been a rapid increase in the amount of data collected using electronic health records (EHR). Artificial intelligence (AI) offers a promising means of centralizing data collection and analysis, but to date, most AI algorithms have only been applied to analyzing image data in ophthalmologic practice. In this review we aimed to characterize the use of AI in the analysis of EHR, and to critically appraise the adherence of each included study to the CONSORT-AI reporting guideline. METHODS: A comprehensive search of three relevant databases (MEDLINE, EMBASE, and Cochrane Library) from January 2010 to February 2023 was conducted. The included studies were evaluated for reporting quality based on the AI-specific items from the CONSORT-AI reporting guideline. RESULTS: Of the 4,968 articles identified by our search, 89 studies met all inclusion criteria and were included in this review. Most of the studies utilized AI for ocular disease prediction (n = 41, 46.1%), and diabetic retinopathy was the most studied ocular pathology (n = 19, 21.3%). The overall mean CONSORT-AI score across the 14 measured items was 12.1 (range 8-14, median 12). Categories with the lowest adherence rates were: describing handling of poor quality data (48.3%), specifying participant inclusion and exclusion criteria (56.2%), and detailing access to the AI intervention or its code, including any restrictions (62.9%). CONCLUSIONS: In conclusion, we have identified that AI is prominently being used for disease prediction in ophthalmology clinics, however these algorithms are limited by their lack of generalizability and cross-center reproducibility. A standardized framework for AI reporting should be developed, to improve AI applications in the management of ocular disease and ophthalmology decision making.

ARTIFICIAL INTELLIGENCE-ENHANCED ANALYSIS OF RETINAL VASCULATURE IN AGE-RELATED MACULAR DEGENERATION.

PURPOSE: To investigate associations between quantitative vascular measurements derived from intravenous fluorescein angiography (IVFA) and baseline characteristics on optical coherence tomography (OCT) in neovascular age-related macular degeneration (nAMD) patients. METHODS: The authors prospectively recruited patients with active choroidal neovascularization secondary to AMD over 50 years old, presenting to a single center in Toronto, Canada from 2017 to 2023. Ultra-widefield IVFA images were processed using the artificial intelligence RETICAD FAassist system to extract quantitative information on blood flow, perfusion, and blood-retinal-barrier (BRB) permeability. Associations between IVFA parameters with functional and anatomical outcomes were examined using univariable and multivariable regression models. RESULTS: Eighty-one nAMD eyes and seven healthy control eyes were included. Compared with healthy controls, BRB permeability in the central and peripheral retina was significantly higher in nAMD patients (P < 0.001). On univariable analysis, BRB permeability measured centrally was significantly associated with central macular thickness (P = 0.035), whereas perfusion and blood flow measured centrally were significantly associated with macular volume (P = 0.043 and 0.037, respectively). On multivariable analysis, BRB permeability remained significantly associated with central macular thickness (P = 0.026). CONCLUSION: Central BRB permeability measured on IVFA was significantly associated with baseline central macular thickness in nAMD patients. Future work should longitudinally explore associations between IVFA parameters and clinical characteristics in diverse nAMD populations.

PARS PLANA VITRECTOMY WITH OR WITHOUT INTERNAL LIMITING MEMBRANE PEEL FOR MACULAR HOLE: A Systematic Review and Meta-Analysis.

PURPOSE: To compare the efficacy and safety of pars plana vitrectomy with and without internal limiting membrane (ILM) peeling for macular hole (MH). METHODS: A systematic literature search on Ovid MEDLINE, Embase, Cochrane Library, and Google Scholar was performed from January 2000 to 2023. The primary outcome was the final best-corrected visual acuity (BCVA). Secondary outcomes included MH closure rates and the need for repeat surgery. The authors performed a random-effects meta-analysis on Review Manager 5.4. RESULTS: Fourteen studies on 880 eyes were included. Pars plana vitrectomy with and without ILM peel achieved a similar final BCVA ( P = 0.66). However, pars plana vitrectomy without ILM peeling achieved a significantly better final BCVA in eyes with closed MHs (WMD = 0.05 logMAR, 95% CI, 0.01-0.10, P = 0.02). Pars plana vitrectomy with ILM peeling achieved a significantly higher primary MH closure rate (RR = 1.21, 95% CI, 1.04-1.42, P = 0.02) and lower incidence of MH reoperation (RR = 0.19, 95% CI, 0.11-0.33, P < 0.001). The final MH closure rate ( P = 0.12) and incidence of MH recurrence ( P = 0.25) were similar between groups. CONCLUSION: Pars plana vitrectomy with and without ILM peel achieved a similar final BCVA. However, pars plana vitrectomy without ILM peeling achieved a better final BCVA in eyes with closed MHs. ILM peeling achieved a greater primary MH closure rate and reduced need for reoperation.

ASSOCIATION OF INTRAVENOUS FLUORESCEIN ANGIOGRAPHY AND ADAPTIVE OPTICS IMAGING IN DIABETIC RETINOPATHY: A Prospective Case Series.

PURPOSE: To our knowledge, we present the first case series investigating the relationship between adaptive optics (AO) imaging and intravenous fluorescein angiography (IVFA) parameters in patients with diabetic retinopathy. METHODS: Consecutive patients with diabetic retinopathy older than age 18 years presenting to a single center in Toronto, Canada, from 2020 to 2021 were recruited. Adaptive optics was performed with the RTX1 camera (Imagine Eyes, Orsay, France) at retinal eccentricities of 2° and 4°. Intravenous fluorescein angiography was assessed with the artificial intelligence-based RETICAD system to extract blood flow, perfusion, and blood-retinal-barrier (BRB) permeability at the same retinal locations. Correlations between AO and IVFA parameters were calculated using Pearson's correlation coefficient. RESULTS: Across nine cases, a significant positive correlation existed between photoreceptor spacing on AO and BRB permeability (r = 0.303, P = 0.027), as well as perfusion (r = 0.272, P = 0.049) on IVFA. When stratified by location, a significant positive correlation between photoreceptor dispersion and both BRB permeability and perfusion (r = 0.770, P = 0.043; r = 0.846, P = 0.034, respectively) was observed. Cone density was also negatively correlated with BRB permeability (r = -0.819, P = 0.046). CONCLUSION: Photoreceptor spacing on AO was significantly correlated with BRB permeability and perfusion on IVFA in patients with diabetic retinopathy. Future studies with larger sample sizes are needed to understand the relationship between AO and IVFA parameters in diverse patient populations.

Pars Plana Vitrectomy with or without Internal Limiting Membrane Peel for Epiretinal Membrane: A Systematic Review and Meta-Analysis.

BACKGROUND: The safety and effectiveness of pars plana vitrectomy (PPV) with internal limiting membrane (ILM) peeling remains poorly understood for the treatment of epiretinal membrane (ERM). OBJECTIVES: Our study aims to compare the safety and effectiveness of PPV with and without ILM peeling for ERM. METHODS: A systematic literature search was conducted on Ovid MEDLINE, Embase, Cochrane Library, and Google Scholar from January 2000 to January 2023 for comparative studies reporting visual and anatomical outcomes for patients with ERM that received PPV with or without ILM peeling. Primary outcomes included best-corrected visual acuity (BCVA) at last study observation and change in BCVA from baseline. Secondary outcomes included retinal thickness (RT) at last study observation, change in RT from baseline, risk of ERM recurrence, and adverse events. A random-effects meta-analysis was performed. Risk of bias of randomized controlled trials was assessed using the Risk of Bias 2 tool of observational studies using the Risk of Bias in Non-randomized Studies of Interventions-I tool. The certainty of evidence of outcomes was evaluated using Grading of Recommendations, Assessment, Development and Evaluation criteria. RESULTS: Nineteen studies reporting on 1,291 eyes at baseline were included. PPV with and without ILM peel achieved a similar BCVA at last study observation (p = 0.68) and change in BCVA from baseline (p = 0.79). These findings remained consistent irrespective of whether simultaneous phacoemulsification was performed. PPV with ILM peel achieved a significantly lower incidence of ERM recurrence (risk ratio [RR] = 0.26, 95% CI = [0.13, 0.51], p < 0.0001) and additional surgery (RR = 0.17, 95% CI = [0.04, 0.74], p = 0.02) compared to PPV without ILM peel. CONCLUSION: PPV with and without ILM peel achieved a similar BCVA at last study observation in ERM patients. Patients treated with PPV and ILM peel also had a reduced risk of ERM recurrence and lower reoperation risk. These conclusions are associated with a moderate certainty of evidence and potential for bias from multiple non-randomized studies.

Non-Obstetric Maternal Mortality Trends by Race in the United States.

OBJECTIVES: Public health interventions to reduce maternal mortality have largely focused on obstetric causes of death. However, previous studies have noted that non-obstetrics factors, such as motor vehicle accidents, substance overdoses, homicides, and suicides, may account for a large proportion of maternal deaths. The study objective was to examine trends in maternal deaths from non-obstetric causes across races in the United States (US). METHODS: A population-based cross-sectional study was conducted on 80,710,348 live births using data from the "Birth Data" and "Mortality Multiple Cause" files compiled by the Centers for Disease Control and Prevention from 2000 to 2019. The annual incidence of maternal deaths attributed to non-obstetric causes (/100,000 live-births) during pregnancy and up to 42 days postpartum were calculated across racial groups. Then the effects of race on the risk of non-obstetric maternal mortality and temporal changes over the study period were examined using logistic regression models. RESULTS: From 2000 to 2019, a total 7,334 women died during pregnancy, childbirth, and within 42 days postpartum from non-obstetric causes, representing 34.5% (7,334/21,241) of all maternal mortality. Of non-obstetric deaths, 31.3% were caused by transport accidents and 27.3% by accidental poisoning. American Indian women were found to have the highest risk of non-obstetric maternal mortality (OR 2.20,95% CI 1.90-2.56), and 46.1% (176/382) of all deaths among pregnant American Indian women were caused by non-obstetric complications. Risk of non-obstetric maternal mortality increased overall during the 20-year study period, with a greater increase among Black (1.15, 1.13-1.17) and American Indian women (1.17, 1.13-1.21). CONCLUSION: Non-obstetric causes of death have become increasingly prevalent in the US, especially in American Indian women. Novel interventions to address these non-obstetric factors should especially target American Indian women to improve maternal outcomes.

Racial disparities in national maternal mortality trends in the United States from 2000 to 2019: a population-based study on 80 million live births.

PURPOSE: In the United States (US), deaths during pregnancy and childbirth have increased over the past 2 decades compared to other high-income countries, and there have been reports that racial disparities in maternal mortality have widened. The study objective was to examine recent trends in maternal mortality in the US by race. METHODS: Our population-based cross-sectional study used data from the Centers for Disease Control and Prevention's 2000-2019 "Birth Data" and "Mortality Multiple Cause" data files from the US to calculate maternal mortality during pregnancy, childbirth, and puerperium across race. Logistic regression models estimated the effects of race on the risk of maternal mortality and examined temporal changes in risk across race. RESULTS: A total of 21,241 women died during pregnancy and childbirth, with 65.5% caused by obstetrical complications and 34.5% by non-obstetrical causes. Black women, compared with White women, had greater risk of maternal mortality (OR 2.13, 95% CI 2.06-2.20), as did American Indian women (2.02, 1.83-2.24). Overall maternal mortality risk increased during the 20-year study period, with an annual increase of 2.4 and 4.7/100,000 among Black and American Indian women, respectively. CONCLUSIONS: Between 2000 and 2019, maternal mortality in the US increased, overall and especially in American Indian and Black women. Targeted public health interventions to improve maternal health outcomes should become a priority.

ChatGPT-4: An assessment of an upgraded artificial intelligence chatbot in the United States Medical Licensing Examination.

PURPOSE: ChatGPT-4 is an upgraded version of an artificial intelligence chatbot. The performance of ChatGPT-4 on the United States Medical Licensing Examination (USMLE) has not been independently characterized. We aimed to assess the performance of ChatGPT-4 at responding to USMLE Step 1, Step 2CK, and Step 3 practice questions. METHOD: Practice multiple-choice questions for the USMLE Step 1, Step 2CK, and Step 3 were compiled. Of 376 available questions, 319 (85%) were analyzed by ChatGPT-4 on March 21st, 2023. Our primary outcome was the performance of ChatGPT-4 for the practice USMLE Step 1, Step 2CK, and Step 3 examinations, measured as the proportion of multiple-choice questions answered correctly. Our secondary outcomes were the mean length of questions and responses provided by ChatGPT-4. RESULTS: ChatGPT-4 responded to 319 text-based multiple-choice questions from USMLE practice test material. ChatGPT-4 answered 82 of 93 (88%) questions correctly on USMLE Step 1, 91 of 106 (86%) on Step 2CK, and 108 of 120 (90%) on Step 3. ChatGPT-4 provided explanations for all questions. ChatGPT-4 spent 30.8 ± 11.8 s on average responding to practice questions for USMLE Step 1, 23.0 ± 9.4 s per question for Step 2CK, and 23.1 ± 8.3 s per question for Step 3. The mean length of practice USMLE multiple-choice questions that were answered correctly and incorrectly by ChatGPT-4 was similar (difference = 17.48 characters, SE = 59.75, 95%CI = [-100.09,135.04], t = 0.29, p = 0.77). The mean length of ChatGPT-4's correct responses to practice questions was significantly shorter than the mean length of incorrect responses (difference = 79.58 characters, SE = 35.42, 95%CI = [9.89,149.28], t = 2.25, p = 0.03). CONCLUSIONS: ChatGPT-4 answered a remarkably high proportion of practice questions correctly for USMLE examinations. ChatGPT-4 performed substantially better at USMLE practice questions than previous models of the same AI chatbot.

The future of AI clinicians: assessing the modern standard of chatbots and their approach to diagnostic uncertainty.

BACKGROUND: Artificial intelligence (AI) chatbots have demonstrated proficiency in structured knowledge assessments; however, there is limited research on their performance in scenarios involving diagnostic uncertainty, which requires careful interpretation and complex decision-making. This study aims to evaluate the efficacy of AI chatbots, GPT-4o and Claude-3, in addressing medical scenarios characterized by diagnostic uncertainty relative to Family Medicine residents. METHODS: Questions with diagnostic uncertainty were extracted from the Progress Tests administered by the Department of Family and Community Medicine at the University of Toronto between 2022 and 2023. Diagnostic uncertainty questions were defined as those presenting clinical scenarios where symptoms, clinical findings, and patient histories do not converge on a definitive diagnosis, necessitating nuanced diagnostic reasoning and differential diagnosis. These questions were administered to a cohort of 320 Family Medicine residents in their first (PGY-1) and second (PGY-2) postgraduate years and inputted into GPT-4o and Claude-3. Errors were categorized into statistical, information, and logical errors. Statistical analyses were conducted using a binomial generalized estimating equation model, paired t-tests, and chi-squared tests. RESULTS: Compared to the residents, both chatbots scored lower on diagnostic uncertainty questions (p < 0.01). PGY-1 residents achieved a correctness rate of 61.1% (95% CI: 58.4-63.7), and PGY-2 residents achieved 63.3% (95% CI: 60.7-66.1). In contrast, Claude-3 correctly answered 57.7% (n = 52/90) of questions, and GPT-4o correctly answered 53.3% (n = 48/90). Claude-3 had a longer mean response time (24.0 s, 95% CI: 21.0-32.5 vs. 12.4 s, 95% CI: 9.3-15.3; p < 0.01) and produced longer answers (2001 characters, 95% CI: 1845-2212 vs. 1596 characters, 95% CI: 1395-1705; p < 0.01) compared to GPT-4o. Most errors by GPT-4o were logical errors (62.5%). CONCLUSIONS: While AI chatbots like GPT-4o and Claude-3 demonstrate potential in handling structured medical knowledge, their performance in scenarios involving diagnostic uncertainty remains suboptimal compared to human residents.

Survival and infection rates of microvascular free flaps in pediatric mandibular reconstruction: A systematic review and meta-analysis.

BACKGROUND: Vascularized free tissue transfer has been established as an effective method in the reconstruction of mandibular defects. However, a limited understanding of its efficacy in pediatric patients persists due to its infrequent presentation. The aim of this study is to systematically consolidate the survival and infection rates of free flaps in pediatric mandibular reconstruction. METHODS: A systematic literature search was conducted on Ovid Medline, Embase, and Cochrane Library for studies published up to January 2024. We included peer-reviewed studies reporting on survival and infection outcomes associated with free flap mandibular reconstruction in pediatric patients (<18 years). We performed a random-effects meta-analysis with the inverse-variance weighted approach to estimate survival and infection rates. Heterogeneity was assessed by I2, and publication bias was examined using Egger's test. RESULTS: A total of 26 studies, reporting on 463 free flaps and 439 pediatric patients with a mean age of 10.7 years, were included in our study. Most free flaps originated from the fibula (n = 392/463, 84.7%) and benign tumors were the most common cause for mandibular reconstruction (n = 179/463, 38.7%). The pooled estimate for survival of flaps was 96% (95% CI: 93-97, I2 = 0%), and recipient-site infections were estimated to occur in 9% (95% CI: 6-13, I2 = 0%) of cases. The most common reported complications within the study timeframe were early malocclusion (n = 28/123, 21.4%) and bite abnormalities (18/131, 13.7%). CONCLUSION: Free tissue transfer for mandibular reconstruction in pediatric patients is effective and safe. Further research is required to explore functionality following mandibular reconstruction in diverse pediatric populations.

Artificial Intelligence Chatbots' Understanding of the Risks and Benefits of Computed Tomography and Magnetic Resonance Imaging Scenarios.

PURPOSE: Patients may seek online information to better understand medical imaging procedures. The purpose of this study was to assess the accuracy of information provided by 2 popular artificial intelligence (AI) chatbots pertaining to common imaging scenarios' risks, benefits, and alternatives. METHODS: Fourteen imaging-related scenarios pertaining to computed tomography (CT) or magnetic resonance imaging (MRI) were used. Factors including the use of intravenous contrast, the presence of renal disease, and whether the patient was pregnant were included in the analysis. For each scenario, 3 prompts for outlining the (1) risks, (2) benefits, and (3) alternative imaging choices or potential implications of not using contrast were inputted into ChatGPT and Bard. A grading rubric and a 5-point Likert scale was used by 2 independent reviewers to grade responses. Prompt variability and chatbot context dependency were also assessed. RESULTS: ChatGPT's performance was superior to Bard's in accurately responding to prompts per Likert grading (4.36 ± 0.63 vs 3.25 ± 1.03 seconds, P < .0001). There was substantial agreement between independent reviewer grading for ChatGPT (κ = 0.621) and Bard (κ = 0.684). Response text length was not statistically different between ChatGPT and Bard (2087 ± 256 characters vs 2162 ± 369 characters, P = .24). Response time was longer for ChatGPT (34 ± 2 vs 8 ± 1 seconds, P < .0001). CONCLUSIONS: ChatGPT performed superior to Bard at outlining risks, benefits, and alternatives to common imaging scenarios. Generally, context dependency and prompt variability did not change chatbot response content. Due to the lack of detailed scientific reasoning and inability to provide patient-specific information, both AI chatbots have limitations as a patient information resource.

No adults allowed: Adolescents and Medical Decision Making.

The majority of the literature focused on whether consent should be extended to the adolescent population arises from themes adapted from American tort law. In contrast to the USA, Ontario does not delineate an age of consent for medical treatment and relying on American guidelines to guide practice in Ontario is problematic. While the literature is saturated with discussions for and against seeking adolescent consent, there are currently no bioethical guidelines on adolescent consent in the province of Ontario. This paper explores adolescent refusal of care and adolescent request for care in opposition to parental wishes. The paper seeks to answer the following questions: What is the difference between an adolescent and an adult in medical decision-making? What are the barriers to seeking adolescent consent? And, can the neurobiological argument be an accurate guide for obtaining adolescent consent?

Comparative Performance of ChatGPT and Bard in a Text-Based Radiology Knowledge Assessment.

PURPOSE: Bard by Google, a direct competitor to ChatGPT, was recently released. Understanding the relative performance of these different chatbots can provide important insight into their strengths and weaknesses as well as which roles they are most suited to fill. In this project, we aimed to compare the most recent version of ChatGPT, ChatGPT-4, and Bard by Google, in their ability to accurately respond to radiology board examination practice questions. METHODS: Text-based questions were collected from the 2017-2021 American College of Radiology's Diagnostic Radiology In-Training (DXIT) examinations. ChatGPT-4 and Bard were queried, and their comparative accuracies, response lengths, and response times were documented. Subspecialty-specific performance was analyzed as well. RESULTS: 318 questions were included in our analysis. ChatGPT answered significantly more accurately than Bard (87.11% vs 70.44%, P < .0001). ChatGPT's response length was significantly shorter than Bard's (935.28 ± 440.88 characters vs 1437.52 ± 415.91 characters, P < .0001). ChatGPT's response time was significantly longer than Bard's (26.79 ± 3.27 seconds vs 7.55 ± 1.88 seconds, P < .0001). ChatGPT performed superiorly to Bard in neuroradiology, (100.00% vs 86.21%, P = .03), general & physics (85.39% vs 68.54%, P < .001), nuclear medicine (80.00% vs 56.67%, P < .01), pediatric radiology (93.75% vs 68.75%, P = .03), and ultrasound (100.00% vs 63.64%, P < .001). In the remaining subspecialties, there were no significant differences between ChatGPT and Bard's performance. CONCLUSION: ChatGPT displayed superior radiology knowledge compared to Bard. While both chatbots display reasonable radiology knowledge, they should be used with conscious knowledge of their limitations and fallibility. Both chatbots provided incorrect or illogical answer explanations and did not always address the educational content of the question.

Cleft lip and/or palate mortality trends in the USA: a retrospective population-based study.

BACKGROUND: Cleft lip and/or palate (CL/P) is one of the most common congenital anomalies worldwide. Although CL/P management may require a series of interventions, mortality resulting from CL/P alone is rare. This study aims to examine recent trends of CL/P mortality rates in the USA. METHODS: A retrospective population-based study was conducted using official US birth and death certificate data from the Centers for Disease Control and Prevention from 2000 to 2019. Annual mortality rates per 1000 births with CL/P were calculated across sex and racial groups. Multivariable logistic regression models estimated the effects of sex and race on the risk of mortality with CL/P, and linear regression models were used to examine temporal changes in mortality rate across sex and race. RESULTS: From 2000 to 2019, 1119 deaths occurred in patients with documented CL/P, for an overall incidence of 20.3 deaths per 1000 births with CL/P (95% CI 18.9 to 22.8). Of these, Patau syndrome was the listed cause of death in 167 cases (14.9%). Black individuals (OR 1.93, 95% CI 1.85 to 2.01), Hispanic (1.54, 1.49 to 1.58) and American Indian individuals (1.28, 1.20 to 1.35) were at a greater risk of CL/P mortality compared with white individuals. Additionally, females were also at a greater risk (1.35, 1.21 to 1.49). A significant upward trend in CL/P mortality was observed in Hispanic (r2=0.70, p<0.01) and American Indian individuals (r2=0.81, p<0.01) from 2000 to 2019. CONCLUSIONS: Cleft birth and mortality surveillance is essential in healthcare and prevention planning. Future studies are required to understand the differences in CL/P mortality rates across various sociodemographic groups.

Diagnostic methods for primary vitreoretinal lymphoma: A systematic review.

Primary vitreoretinal lymphoma is a potentially aggressive intraocular malignancy with poor systemic prognosis and sometimes significant diagnostic delays as it may masquerade as chronic uveitis. Despite the variety of diagnostic techniques, it is unclear which modality is most accurate in the diagnosis of PVRL. A systematic literature search was conducted on Ovid MEDLINE, EMBASE and the Cochrane Controlled Register of Trials for studies published between January, 2000, and June, 2023. Randomized controlled trials (RCTs) reporting on the following diagnostic tools used to diagnose patients with PVRL were included: cytology, flow cytometry, MYD88 L265P mutation, CD79B mutation, interleukin 10/interleukin-6 (IL-10/IL-6) ratio, polymerase chain reaction (PCR) for monoclonal immunoglobulin heavy chain (IgH) and immunoglobulin kappa light chain (IgK) rearrangements, and imaging findings. The aggregated sensitivity of each diagnostic modality was reported and compared using the chi-squared (χ2) test. A total of 662 eyes from 29 retrospective studies reporting on patients diagnosed with PVRL were included. An IL-10/IL-6 ratio greater than 1 had the highest sensitivity (89.39%, n = 278/311 eyes, n = 16 studies) for PVRL, where the sensitivity was not significantly different when only vitreous samples were drawn (88.89%, n = 232/261 eyes, n = 13 studies) compared to aqueous samples (83.33%, n = 20/24, n = 2) (p = 0.42). Flow cytometry of vitreous samples gave a positive result in 66/75 eyes (88.00%, n = 6 studies) with PVRL, and monoclonal IgH rearrangements on PCR gave a positive result in 354/416 eyes (85.10%, n = 20 studies) with PVRL. MYD88 L265P and CD79B mutation analysis performed poorly, yielding a positive result in 63/90 eyes (70.00%, n = 8 studies) with PVRL, and 20/57 eyes (35.09%, n = 4 studies) with PVRL, respectively. Overall, our systematic review found that an IL-10/IL-6 ratio greater or equal to one may provide the highest sensitivity in identifying patients with PVRL. Future studies are needed to employ multiple diagnostic tools to aid in the detection of PVRL and to further establish nuanced guidelines when determining the optimal diagnostic tool to use in diverse patient populations.

Physical and Psychosocial Challenges as Predictors of Vision Difficulty in Children: A Nationally Representative Survey Analysis.

PURPOSE: To elicit associations between vision difficulties and physical or psychosocial challenges in children in the United States. METHODS: Children aged 2-17 years old from the 2021 National Health Interview Survey with data pertaining to vision difficulty were included in our retrospective, population-based analysis. Our primary aim was investigating physical and psychosocial challenges as predictors of vision difficulty. Logistic regression models were performed on Stata version 17.0 (StataCorp LLC, College Station, Texas). Analyses were accompanied by an odds ratio (OR) and 95% confidence interval (CI). RESULTS: A total of 7,373 children had data pertaining to their level of vision difficulty and were included in our sample. In our multivariable analysis, children with a good/fair (OR = 1.84, 95% CI = [1.31, 2.60], p < 0.01), or poor (OR = 5.08, 95% CI = [1.61, 16.04], p < 0.01) general health status had higher odds of vision difficulty relative to children with an excellent/very good health status. Furthermore, children with difficulties hearing (OR = 8.67, 95% CI = [5.25, 14.31], p < 0.01), communicating (OR = 1.96, 95% CI = [1.18, 3.25], p < 0.01), learning (OR = 1.93, 95% CI = [1.27, 2.93], p < 0.01), and making friends (OR = 1.94, 95% CI = [1.12, 3.36], p = 0.02) had higher odds of vision difficulty. Nonetheless, the following factors were only predictors of vision difficulty in our univariable analysis: requiring equipment for mobility (p < 0.01), experiencing anxiety (p < 0.01), and experiencing depression (p < 0.01). CONCLUSION: Several factors pertaining to physical and psychosocial challenges in children are associated with vision difficulty. Future research should further explore potential causal links between vision difficulty and physical or psychosocial factors to aid in coordinating public health efforts dedicated to vision health equity.

The impact of multidisciplinary cancer conferences on overall survival: a meta-analysis.

BACKGROUND: Multidisciplinary cancer conferences consist of regular meetings between diverse specialists working together to share clinical decision making in cancer care. The aim of this study was to systematically review and meta-analyze the effect of multidisciplinary cancer conference intervention on the overall survival of patients with cancer. METHODS: A systematic literature search was conducted on Ovid MEDLINE, EMBASE, and the Cochrane Controlled Register of Trials for studies published up to July 2023. Studies reporting on the impact of multidisciplinary cancer conferences on patient overall survival were included. A standard random-effects model with the inverse variance-weighted approach was used to estimate the pooled hazard ratio of mortality (multidisciplinary cancer conference vs non-multidisciplinary cancer conference) across studies, and the heterogeneity was assessed by I2. Publication bias was examined using funnel plots and the Egger test. RESULTS: A total of 134 287 patients with cancer from 59 studies were included in our analysis, with 48 467 managed by multidisciplinary cancer conferences and 85 820 in the control arm. Across all cancer types, patients managed by multidisciplinary cancer conferences had an increased overall survival compared with control patients (hazard ratio = 0.67, 95% confidence interval = 0.62 to 0.71, I2 = 84%). Median survival time was 30.2 months in the multidisciplinary cancer conference group and 19.0 months in the control group. In subgroup analysis, a positive effect of the multidisciplinary cancer conference intervention on overall survival was found in breast, colorectal, esophageal, hematologic, hepatocellular, lung, pancreatic, and head and neck cancer. CONCLUSIONS: Overall, our meta-analysis found a significant positive effect of multidisciplinary cancer conferences compared with controls. Further studies are needed to establish nuanced guidelines when optimizing multidisciplinary cancer conference integration for treating diverse patient populations.

Google Gemini and Bard artificial intelligence chatbot performance in ophthalmology knowledge assessment.

PURPOSE: With the popularization of ChatGPT (Open AI, San Francisco, California, United States) in recent months, understanding the potential of artificial intelligence (AI) chatbots in a medical context is important. Our study aims to evaluate Google Gemini and Bard's (Google, Mountain View, California, United States) knowledge in ophthalmology. METHODS: In this study, we evaluated Google Gemini and Bard's performance on EyeQuiz, a platform containing ophthalmology board certification examination practice questions, when used from the United States (US). Accuracy, response length, response time, and provision of explanations were evaluated. Subspecialty-specific performance was noted. A secondary analysis was conducted using Bard from Vietnam, and Gemini from Vietnam, Brazil, and the Netherlands. RESULTS: Overall, Google Gemini and Bard both had accuracies of 71% across 150 text-based multiple-choice questions. The secondary analysis revealed an accuracy of 67% using Bard from Vietnam, with 32 questions (21%) answered differently than when using Bard from the US. Moreover, the Vietnam version of Gemini achieved an accuracy of 74%, with 23 (15%) answered differently than the US version of Gemini. While the Brazil (68%) and Netherlands (65%) versions of Gemini performed slightly worse than the US version, differences in performance across the various country-specific versions of Bard and Gemini were not statistically significant. CONCLUSION: Google Gemini and Bard had an acceptable performance in responding to ophthalmology board examination practice questions. Subtle variability was noted in the performance of the chatbots across different countries. The chatbots also tended to provide a confident explanation even when providing an incorrect answer.