Deep Learning Approach for Differentiating Etiologies of Pediatric Retinal Hemorrhages: A Multicenter Study

Khosravi, Pooya; Huck, Nolan A.; Shahraki, Kourosh; Hunter, Stephen C.; Danza, Clifford Neil; Kim, So Young; Forbes, Brian J.; Dai, Shuan; Levin, Alex V.; Binenbaum, Gil; Chang, Peter D.; Suh, Donny W.

doi:10.3390/ijms242015105

Cited by 3 publications

(2 citation statements)

References 52 publications

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“…These tools can analyze large datasets derived from medical records, treatment guidelines, and the scientific literature to identify statistically significant associations between interventions and outcomes ( 68 ). For example, an AI system could review thousands of cases involving a particular drug or procedure to determine whether it is linked to higher complication rates after controlling for other clinical factors ( 69 ). However, AI has limitations when determining causation.…”

Section: Medical Malpractice Liability Assessmentmentioning

confidence: 99%

AI and professional liability assessment in healthcare. A revolution in legal medicine?

Terranova,

Cestonaro,

Fava

et al. 2024

Front. Med.

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The adoption of advanced artificial intelligence (AI) systems in healthcare is transforming the healthcare-delivery landscape. Artificial intelligence may enhance patient safety and improve healthcare outcomes, but it presents notable ethical and legal dilemmas. Moreover, as AI streamlines the analysis of the multitude of factors relevant to malpractice claims, including informed consent, adherence to standards of care, and causation, the evaluation of professional liability might also benefit from its use. Beginning with an analysis of the basic steps in assessing professional liability, this article examines the potential new medical-legal issues that an expert witness may encounter when analyzing malpractice cases and the potential integration of AI in this context. These changes related to the use of integrated AI, will necessitate efforts on the part of judges, experts, and clinicians, and may require new legislative regulations. A new expert witness will be likely necessary in the evaluation of professional liability cases. On the one hand, artificial intelligence will support the expert witness; however, on the other hand, it will introduce specific elements into the activities of healthcare workers. These elements will necessitate an expert witness with a specialized cultural background. Examining the steps of professional liability assessment indicates that the likely path for AI in legal medicine involves its role as a collaborative and integrated tool. The combination of AI with human judgment in these assessments can enhance comprehensiveness and fairness. However, it is imperative to adopt a cautious and balanced approach to prevent complete automation in this field.

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Section: Medical Malpractice Liability Assessmentmentioning

confidence: 99%

AI and professional liability assessment in healthcare. A revolution in legal medicine?

Terranova,

Cestonaro,

Fava

et al. 2024

Front. Med.

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“…RH in AHT: Severe retinal hemorrhages (RHs) are a prevalent finding in infants diagnosed with abusive head trauma (AHT), with as many as two-thirds exhibiting distinct characteristics: bilaterality, involvement of multiple retinal layers, numerousness, and extension to the ora serrata [12][13][14][15]. Notably, unilateral severe RH has also been reported [11].…”

Section: Retinal Hemorrhage In Abusive Vs Non-abusive Head Traumamentioning

confidence: 99%

An Update to Biomechanical and Biochemical Principles of Retinal Injury in Child Abuse

Shahraki,

Suh

2024

Children

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Abusive head trauma (AHT) is an extreme form of physical child abuse, a subset of which is shaken baby syndrome (SBS). While traumatic injury in children is most readily observed as marks of contusion on the body, AHT/SBS may result in internal injuries that can put the life of the child in danger. One pivotal sign associated with AHT/SBS that cannot be spotted with the naked eye is retinal injury (RI), an early sign of which is retinal hemorrhage (RH) in cases with rupture of the retinal vasculature. If not addressed, RI can lead to irreversible outcomes, such as visual loss. It is widely assumed that the major cause of RI is acceleration–deceleration forces that are repeatedly imposed on the patient during abusive shaking. Still, due to the controversial nature of this type of injury, few investigations have ever sought to delve into its biomechanical and/or biochemical features using realistic models. As such, our knowledge regarding AHT-/SBS-induced RI is significantly lacking. In this mini-review, we aim to provide an up-to-date account of the traumatology of AHT-/SBS-induced RI, as well as its biomechanical and biochemical features, while focusing on some of the experimental models that have been developed in recent years for studying retinal hemorrhage in the context of AHT/SBS.

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Should Ocular Hemorrhage Screening be Conducted in Newborns with Acidosis?

Unal,

Kara,

Demirel

et al. 2024

Am J Perinatol

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Objective Ocular hemorrhages (OHs) may cause visual disturbances and incidence vary from 18 to 39% in newborns. Precipitated/instrumental delivery and perinatal asphyxia were predefined risk factors. Acidosis can interfere with coagulation and disrupt the pressure of ocular capillaries and put infants with moderate acidosis with or without hypoxic–ischemic encephalopathy at risk for OH. We aimed to evaluate the OH in neonates with fetal acidosis. Study Design Neonates >34 weeks are included if pH < 7.10 and BE < −12 mmol/L within the first hour. Ophthalmologic examinations for retinal (RH), vitreous, and anterior chamber (hyphema) hemorrhage were done within the third day. RH was staged according to Egge's classification. Follow-up of the patients was continued until the age of 2. Clinical characteristics of newborns were analyzed. Results Sixty-two neonates (38 ± 2.3 weeks, 2,971 ± 612 g) were included. pH = 6.91 ± 0.16, BE = − 17.2 ± 5.3 mmol/L. OH was found in 22 (36.7%) neonates (hyphema n = 2, vitreous n = 2, RH n = 21). Thirty-eight eyes with RH were staged (Stage 3: n = 15 [39.5%]; Stage 2: n =11 [28.9%]; Stage 1: n = 12 [31.6%]). Vaginal delivery (OR: 4.9, 95% CI [1.4–17.8]) and advanced resuscitation at the delivery room (OR: 8.8; 95% CI [1.9–41.7]) were found to increase the risk of RH. Conclusion Approximately one-third of neonates with moderate to severe acidosis exhibited RH when examined on the third day. Contrary to previous studies that reported mild RH in otherwise healthy neonates, our findings revealed that neonates with moderate to severe acidosis predominantly presented with Stage 3 RH. While the higher incidence of RH in vaginally delivered infants is consistent with previous studies, the identification of advanced resuscitation as a risk factor is a new addition to the literature. The findings in our study highlight the importance of retinal examination in neonates with acidosis in the presence of intubation during resuscitation. Key Points

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Deep Learning Approach for Differentiating Etiologies of Pediatric Retinal Hemorrhages: A Multicenter Study

Cited by 3 publications

References 52 publications

AI and professional liability assessment in healthcare. A revolution in legal medicine?

AI and professional liability assessment in healthcare. A revolution in legal medicine?

An Update to Biomechanical and Biochemical Principles of Retinal Injury in Child Abuse

Should Ocular Hemorrhage Screening be Conducted in Newborns with Acidosis?

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