We aimed to statefully validate Retinopathy of Prematurity (ROP) grading by evaluating intergrader variability over age-matched simulated exams. In a prospective retinal photographic grading cohort study, both eyes of twenty patients with five images per eye per visit were graded by twelve expert graders across six weekly visits. For each eye visit, ROP experts graded the Zone, Stage, and Plus, from which the Telemedicine ROP Severity Score (tROP-SS) was calculated. Graders retained knowledge of prior assessments for a given eye and followed International Classification of ROP rules. Intergrader coefficient of variation (CoV) for Zone, Stage, Plus, and tROP-SS remained below 20% across six weeks of age-matched visits. Zone showed the most changes in CoV (p < 0.001) with a minimum at week three of 6.0% (95% CI: 3.0-8.9%). Stage (9.2-13.1%) did not significantly vary over time. CoV of Plus gradually increased (p = 0.002) from week 1 (1.2%, 95% CI: 0.3-2.0%) to week 6 (3.3%, 95% CI: 1.7-4.9%). Agreement for tROP-SS varied over time (p < 0.001) and reached a local minimum at week three (10.5%, 95% CI: 7.3-13.8%). High intergrader agreement in a stateful data set validates the use of tROP-SS as a scoring system to capture week-to-week ROP progression.

OBJECTIVE:This study aims to evaluate the performance of the telemedicine retinopathy of prematurity severity score (tROP-SS) across all 14 NICUs in the TELEROP cohort against the modified ROP activity score (mROP-ActS). DESIGN:Retrospective cohort study. SUBJECTS:The study included 2037 neonates who underwent ROP screening in 14 NICUs via the TELEROP telemedicine network from November 2017 to January 2025. METHODS:We compared the robustness of tROP-SS and mROP-Act systems across all exams. MAIN OUTCOME MEASURES:The primary outcomes studied were the ability to return a score in cases responding to treatment, correlation between the two scores and the ability to assess disease directionality. RESULTS:The study analysed 192 704 photos from 11 368 ROP exams on 2037 patients. tROP-SS generated scores for 100% of exams, demonstrating significant improvements over mROP-ActS, which scored only 92.3% of all exams (p = 0.0136). All patients who met treatment criteria received treatment in both eyes. Among high-risk and treatment warranted (TW) patients, 100.0% exams had a valid tROP-SS exam compared with only 72.73% and 45.27% with a valid mROP-ActS. Only 20.9% high-risk or TW patients had a valid mROP-ActS across all their exams. Incremental increases in tROP-SS were more strongly related to worsening of disease: OR (95% CI) - 3.37 (2.51-4.53) versus 1.57 (1.46-1.69), both p < 0.0001. tROP-SS also demonstrated improved granularity and accuracy in categorizing patients that would ultimately require treatment (AUC: 0.991 vs. 0.825). CONCLUSIONS:tROP-SS was retrospectively evaluated across 14 NICUs, proving to be a more robust scoring system compared to mROP-ActS. The findings support continued use of tROP-SS, supplemented by standard screening protocols to ensure no cases of treatment-warranted ROP are missed. Future research may focus on integrating additional parameters to enhance predictive models to improve early ROP detection.

This brief report describes the incidence and characteristics of ocular abnormalities in healthy term newborn infants (HTNI) in 5,000 consecutive eye examinations from a database of 32,000 infants from 17 hospitals in São Paulo, Brazil. Imaging consisted of five views of the retina (optic nerve center, superior, inferior, nasal, temporal) with 130° wide-angle lens and one view of the anterior segment in each eye. These images were curated on four separate occasions for the presence or absence of ocular abnormality by a pediatric retina specialist. All images were obtained within 72 hours of birth. A total of 59,792 images were curated: Right Eye Normal (21,473 images), Left Eye Normal (21,983 images), Right Eye Abnormal (8,397 images), Left Eye Abnormal (7,939 images). An ocular abnormality appeared in 37.7% of patients; 4.88% showed a referral-warranted pathology. Based on these data, it is not unreasonable to consider instituting universal newborn eye screening in HTNI.

PURPOSE:To delineate the trends of the United States population eligible for retinopathy of prematurity (ROP) screening as defined by the Joint Statement Screening Guidelines of the American Academies of Pediatrics and Ophthalmology from the Centers for Disease Control using the Wide-ranging Online Data for Epidemiologic Research (WONDER) Database. DESIGN:National, retrospective study. SUBJECTS:Infants with ROP in the United States between 2003 and 2022. METHODS:Data collected from WONDER database over the 20-year period 2003-2022. MAIN OUTCOME MEASURED:The parameters of state, infant birth weight (BW), and last menstrual period estimated gestational age (EGA). Four categories of qualification for ROP Screening eligibility were created: BW, EGA, combined BW and EGA (double eligible infants), and Unique Eligible Infants (UEI). RESULTS:The number of eligible for ROP screening in the U.S peaked at 56,106 in 2007 and has steadily declined to 41,083 in 2022, averaging 47,088 per year throughout the study period. During the first ten-year period, there was an average of 50,895 eligible infants per year vs 43,281 infants per year during the second ten-year period. This was a statistically significant trend. BW slightly surpassed EGA as a driver for screening eligibility every year. Both the numbers of eligible micropremature (24-26 weeks GA and/or BW 600-800 g) infants and numbers of eligible nanopremature (<24 weeks GA and/or BW <600 g) infants mirrored the trendline overall eligibility trends. At the state level, Texas surpassed California in 2012 in terms of the highest number of eligible infants, and Florida surpassed New York in 2011 as the state with the third most eligible infants. These changes persisted until the end of the study period. State level changes were driven by EGA. For micropremature infants, California and New York demonstrated a decline in eligibility driven by both BW and EGA. CONCLUSION:Consistent with a drop in overall births, the numbers of eligible infants for ROP screening at birth have been decreasing since its peak in 2007, with stabilization in the 2020's. Nationally, BW drives eligibility. Both micro- and nano-premature infants have decreased in a manner that corresponds to overall eligibility with nano-premature infants having a slight relative decrease. This data adds important context to studies on infant survivability and ROP screening epidemiology.

PURPOSE:This study compared two imaging grading techniques to assess the utility of longitudinal image-based analysis in retinopathy of prematurity (ROP) screening: (1) time-limited without image comparison (a proxy for bedside indirect ophthalmoscopy, termed sBIO) and time-unlimited with image comparison (for telemedicine grading, termed TELE) screening. We tested two hypotheses: (1) H1: TELE was superior to sBIO for the detection of change (Tempo)-same, better, or worse and (2) H2: granular data of change (e.g., at the image and feature level) is integrated by graders to achieve the Tempo assessment. DESIGN:Prospective reliability analysis. METHODS:Gold standard reference (GS) was a published curated ROP image database consisting of both Tempo and granular level changes (image and components) from 40 patients in 2 sets. Graders were divided into 2 cohorts. There were two screening techniques: (1) sBIO with time limited review of 10 minutes/patient, access to prior notes and drawings and (2) TELE with unlimited review time, access to prior weeks' images, notes and schematics. Graders switched techniques and sets after 6 weeks. H1 outcome was comparison of graders' weekly Tempo scores to GS-Gestalt and for H2 was Tempo score compared to GS-View and GS-Component. RESULTS:H1 demonstrated no difference-accuracy of sBIO and TELE compared to GS was 51.7% and 51.9% respectively (P = .95). Highest agreement occurred when all exams exhibited no change (91.5% sBIO vs 93.5% TELE, P = .46) and worst agreement was when exams always demonstrated worsening (46.5% sBIO vs 47.1% TELE, P = .93). Both sets of graders did worse in weeks 7-12, irrespective of technique. H2 demonstrated that Tempo assessment did not correlate with granular data changes in the GS for View level and Component level assessments-overall agreement dropped to 31.4% for Tempo vs GS-VIEW (31.2% for sBIO, 31.5% for TELE) and 4.6% for Tempo vs GS-COMPONENT (4.9% for sBIO, 4.3% for TELE). CONCLUSIONS:Detection of ROP Tempo was independent of screening technique by expert pediatric retina graders. Both groups did significantly better in the first half of the study, indicative of a fatigue factor. This is the first study in ROP history to demonstrate that graders integrate image and retinal features in various ways that can be in contradiction of their assessment of overall disease progression.

Identifying and planning treatment for retinopathy of prematurity (ROP) using telemedicine is becoming increasingly ubiquitous, necessitating a grading system to help caretakers of at-risk infants gauge disease severity. The modified ROP Activity Scale (mROP-ActS) factors zone, stage, and plus disease into its scoring system, addressing the need for assessing ROP’s totality of binocular burden via indirect ophthalmoscopy. However, there is an unmet need for an alternative score which could facilitate ROP identification and gauge disease improvement or deterioration specifically on photographic telemedicine exams. Here, we propose such a system (Telemedicine ROP Severity Score [TeleROP-SS]), which we have compared against the mROP-ActS. In our statistical analysis of 1568 exams, we saw that TeleROP-SS was able to return a score in all instances based on the gradings available from the retrospective SUNDROP cohort, while mROP-ActS obtained a score of 80.8% in right eyes and 81.1% in left eyes. For treatment-warranted ROP (TW-ROP), TeleROP-SS obtained a score of 100% and 95% in the right and left eyes respectively, while mROP-ActS obtained a score of 70% and 63% respectively. The TeleROP-SS score can identify disease improvement or deterioration on telemedicine exams, distinguish timepoints at which treatments can be given, and it has the adaptability to be modified as needed.

Supplementary Data 1 from Molecular Inversion Probe Analysis of Gene Copy Alterations Reveals Distinct Categories of Colorectal Carcinoma

Five-field 130° wide-angle imaging is the standard of care for retinopathy of prematurity (ROP) screening with an ideal hypothetical composite field-of-view (FOV) of 180°. We hypothesized that in many real-world scenarios the effective composite FOV is considerably less than ideal. This observational retrospective study analyzed the effective FOV of fundus photos of patients screened for ROP as part of the Stanford University Network for Diagnosis of Retinopathy of Prematurity (SUNDROP) initiative. Five fundus photos were selected from each eye per image session. Effective FOV was defined as the largest circular area centered on the optic disc that encompassed retina in each of the four cardinal views. Seventy-three subjects were analyzed, 35 without ROP and 34 with ROP. Mean effective FOV was 144.55 ± 6.62° ranging from 130.00 to 153.71°. Effective FOV was not correlated with the presence or absence of ROP, gestational age, birth weight, or postmenstrual age. Mean effective FOV was wider in males compared to females. Standard five-field 130° fundus photos yielded an average effective FOV of 144.54° in the SUNDROP cohort. This implies that an imaging FOV during ROP screening considerably less than the hypothetical ideal of 180° is sufficient for detecting treatment warranted ROP.

Treatment outcomes in retinopathy of prematurity (ROP) are closely correlated with the location (i.e. zone) of disease, with more posterior zones having poorer outcomes. The most posterior zone, Zone I, is defined as a circle centered on the optic nerve with radius twice the distance from nerve to fovea, or subtending an angle of 30 degrees. Because the eye enlarges and undergoes refractive changes during the period of ROP screening, the absolute area of Zone I according to these definitions may likewise change. It is possible that these differences may confound accurate assessment of risk in patients with ROP. In this study, we estimated the area of Zone I in relation to different ocular parameters to determine how variability in the size and refractive power of the eye may affect zoning. Using Gaussian optics, a model was constructed to calculate the absolute area of Zone I as a function of corneal power, anterior chamber depth, lens power, lens thickness, and axial length (AL), with Zone I defined as a circle with radius set by a 30-degree visual angle. Our model predicted Zone I area to be most sensitive to changes in AL; for example, an increase of AL from 14.20 to 16.58 mm at postmenstrual age 32 weeks was calculated to expand the area of Zone I by up to 72%. These findings motivate several hypotheses which upon future testing may help optimize treatment decisions for ROP.

We propose a cloud-based multimodal dialog platform for the remote assessment and monitoring of Amyotrophic Lateral Sclerosis (ALS) at scale. This paper presents our vision, technology setup, and an initial investigation of the efficacy of the various acoustic and visual speech metrics automatically extracted by the platform. 82 healthy controls and 54 people with ALS (pALS) were instructed to interact with the platform and completed a battery of speaking tasks designed to probe the acoustic, articulatory, phonatory, and respiratory aspects of their speech. We find that multiple acoustic (rate, duration, voicing) and visual (higher order statistics of the jaw and lip) speech metrics show statistically significant differences between controls, bulbar symptomatic and bulbar pre-symptomatic patients. We report on the sensitivity and specificity of these metrics using five-fold cross-validation. We further conducted a LASSO-LARS regression analysis to uncover the relative contributions of various acoustic and visual features in predicting the severity of patients' ALS (as measured by their self-reported ALSFRS-R scores). Our results provide encouraging evidence of the utility of automatically extracted audiovisual analytics for scalable remote patient assessment and monitoring in ALS.

PURPOSE:To compare neonatal eye screening using the red reflex test (RRT) versus the wide-field digital imaging (WFDI) system.METHODS:Prospective cohort study. Newborns (n = 380, 760 eyes) in the Maternity Ward of Irmandade Santa Casa de Misericórdia de São Paulo hospital from May to July 2014 underwent RRT by a paediatrician and WFDI performed by the authors. Wide-field digital imaging (WFDI) images were analysed by the authors. Validity of the paediatrician's RRT was assessed by unweighted kappa [κ] statistic, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).RESULTS:While WFDI showed abnormalities in 130 eyes (17.1%), RRT was only abnormal in 13 eyes (1.7%). Wide-field digital imaging (WFDI) detected treatable retina pathology that RRT missed including hyphema, CMV retinitis, FEVR and a vitreous haemorrhage. The sensitivity of the paediatrician's RRT to detect abnormalities was poor at 0.77% (95% confidence interval, CI, 0.02%-4.21%) with a PPV of only 7.69% (95% CI, 1.08%-38.85%). Overall, there was no agreement between screening modalities (κ = -0.02, 95% CI, -0.05 to 0.01). The number needed to screen to detect ocular abnormalities using WFDI was 5.9 newborns and to detect treatable abnormalities was 76 newborns.CONCLUSION:While RRT detects gross abnormalities that preclude visualization of the retina (i.e. media opacities and very large tumours), only WFDI consistently detects subtle treatable retina and optic nerve pathology. With a higher sensitivity than the current gold standard, universal WFDI allows for early detection and management of potentially blinding ophthalmic disease missed by RRT.

Universal newborn eye screening can identify ocular abnormalities early and help mitigate long-term visual impairment. Traditional neonatal and infant eye screening is administered by neonatologists and pediatricians using the red reflex test. If this test identifies an ocular abnormality, then the patient is examined by an ophthalmologist. Notably, the red reflex test may be unable to detect amblyogenic posterior segment pathology. Recent studies using fundus imaging and telemedicine show reduced cost of human resources and increased sensitivity compared with traditional approaches. In this review, the authors discuss universal newborn eye screening pilot programs with regard to disease prevalence, referral-warranted disease, and cost-effectiveness. [Ophthalmic Surg Lasers Imaging Retina. 2021;52:S6-S16.].

Artificial intelligence (AI) applications are diverse and serve varied functions in clinical practice. The most successful products today are clinical decision tools used by physicians, but autonomous AI is gaining traction. Widespread use of AI is limited in part because of concerns about bias, fault-tolerance, and specificity. Adoption of AI often depends on removing cost and complexity in clinical workflow integration, providing clear incentives for use, and providing clear demonstration of clinical outcome. Existing wide-angle photographic screening could be integrated into the clinical workflow based on prior implementations for premature babies and linked with AI interpretation with existing technology. Incidence of retinal abnormality, clinical considerations, AI performance, grading variation for AI-augmented human grading, and cost and policy aspects play a significant role. Improved outcomes for newborns and a relatively high estimated incidence of abnormality have been named as benefits to counterweigh costs in the long term. [Ophthalmic Surg Lasers Imaging Retina. 2021;52:S17-S22.].

This presentation describes creation of a large, open data platform, comprising speech and video recordings of patients diagnosed with amyotrophic lateral sclerosis (ALS) and healthy controls. Each subject in the collection is interviewed by a virtual agent, Nina, emulating the role of a neurologist or speech pathologist walking them through speaking exercises. The collected data is made available to the academic and research community to foster acceleration of the development of biomarkers, diagnostics, therapies, and fundamental scientific understanding of ALS.

To describe a database of longitudinally graded telemedicine retinal images to be used as a comparator for future studies assessing grader recall bias and ability to detect typical progression (e.g. International Classification of Retinopathy of Prematurity (ICROP) stages) as well as incremental changes in retinopathy of prematurity (ROP). Cohort comprised of retinal images from 84 eyes of 42 patients who were sequentially screened for ROP over 6 consecutive weeks in a telemedicine program and then followed to vascular maturation or treatment, and then disease stabilization. De-identified retinal images across the 6 weekly exams (2520 total images) were graded by an ROP expert based on whether ROP had improved, worsened, or stayed the same compared to the prior week’s images, corresponding to an overall clinical “gestalt” score. Subsequently, we examined which parameters might have influenced the examiner’s ability to detect longitudinal change; images were graded by the same ROP expert by image view (central, inferior, nasal, superior, temporal) and by retinal components (vascular tortuosity, vascular dilation, stage, hemorrhage, vessel growth), again determining if each particular retinal component or ROP in each image view had improved, worsened, or stayed the same compared to the prior week’s images. Agreement between gestalt scores and view, component, and component by view scores was assessed using percent agreement, absolute agreement, and Cohen’s weighted kappa statistic to determine if any of the hypothesized image features correlated with the ability to predict ROP disease trajectory in patients. The central view showed substantial agreement with gestalt scores (κ = 0.63), with moderate agreement in the remaining views. Of retinal components, vascular tortuosity showed the most overall agreement with gestalt (κ = 0.42–0.61), with only slight to fair agreement for all other components. This is a well-defined ROP database graded by one expert in a real-world setting in a masked fashion that correlated with the actual (remote in time) exams and known outcomes. This provides a foundation for subsequent study of telemedicine’s ability to longitudinally assess ROP disease trajectory, as well as for potential artificial intelligence approaches to retinal image grading, in order to expand patient access to timely, accurate ROP screening.

Funding information Center for Innovation in Global Health Seed Grant; Lang Fund for Environmental Anthropology Abstract Modelling of emerging vector borne diseases serves as an important complement to clinical studies of modern zoonoses. This article presents an archaeo-historic epidemiological modelling study of Rift Valley fever (RVF), using data-driven neural network technology. RVF affects both human and animal populations, can rapidly decimate herds causing catastrophic economic hardship, and is identified as a Category A biodefense pathogen by the US Center for Disease Control. Despite recent origins circa the early 1900s, little is known about the circumstances of its inception nor the relationships between factors that affect transmission. This evidence could be vital as the disease continues to expand from its epicentre in Kenya to other parts of Africa and the Arabian Peninsula. RVF is a relevant case for archaeological/palaeopathological investigations of disease as it intersects between numerous human, animal, spatial, temporal, and sociopolitical dimensions. By integrating landscape archaeology, historical evidence, and climatic data, with evidence of human behaviour gathered through ethnoarchaeological study, this article presents an applied framework for human–animal palaeopathology. This framework aligns with the One Health approach that observes disease to be intrinsically tied to ecological and societal factors. We provide a useable alternative way of thinking about disease modelling in the present and the past, ultimately seeking to support efforts to accurately predict future impacts. Tapping into longitudinal evidence from the last 50–300 years offers a powerful way to respond to the threat zoonoses will pose to human populations around the world as the climate warms.

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