RESUMEN
BACKGROUND: Neurobehavioural comorbidities have a detrimental effect on the quality of life of people with epilepsy, yet tracking their impact is challenging as behaviour may vary with seizures and anti-seizure medication (ASM) side effects. Smartphones have the potential to monitor day-to-day neurobehavioural patterns objectively. We present the case of a man in his late twenties with drug-resistant focal epilepsy in whom we ascertained the effects of ASM withdrawal and a convulsive seizure on his touchscreen interactions. METHODS: Using a dedicated app, we recorded over 185 days the timestamps of 718,357 interactions. We divided the various smartphone behaviours according to the next-interval dynamics of the interactions by using a joint interval distribution (JID). During two ASM load transitions, namely before versus during tapering and tapering versus restarting medication, we used cluster-based permutation tests to compare the JIDs. We also compared the JID of the seizure day to the average of the previous 3 days. RESULTS: The cluster-based permutation tests revealed significant differences, with accelerated next-interval dynamics during tapering and a reversal upon medication restart. The day of the convulsion exhibited a marked slowing of next-interval dynamics compared to the preceding 3 days. CONCLUSION: Our findings suggest that the temporal dynamics of smartphone touchscreen interactions may help monitor neurobehavioural comorbidities in neurological care.
RESUMEN
We experience a life that is full of ups and downs. The ability to bounce back after adverse life events such as the loss of a loved one or serious illness declines with age, and such isolated events can even trigger accelerated aging. How humans respond to common day-to-day perturbations is less clear. Here, we infer the aging status from smartphone behavior by using a decision tree regression model trained to accurately estimate the chronological age based on the dynamics of touchscreen interactions. Individuals (N = 280, 21 to 87 y of age) expressed smartphone behavior that appeared younger on certain days and older on other days through the observation period that lasted up to ~4 y. We captured the essence of these fluctuations by leveraging the mathematical concept of critical transitions and tipping points in complex systems. In most individuals, we find one or more alternative stable aging states separated by tipping points. The older the individual, the lower the resilience to forces that push the behavior across the tipping point into an older state. Traditional accounts of aging based on sparse longitudinal data spanning decades suggest a gradual behavioral decline with age. Taken together with our current results, we propose that the gradual age-related changes are interleaved with more complex dynamics at shorter timescales where the same individual may navigate distinct behavioral aging states from one day to the next. Real-world behavioral data modeled as a complex system can transform how we view and study aging.
Asunto(s)
Envejecimiento , Teléfono Inteligente , Humanos , Anciano , Persona de Mediana Edad , Masculino , Adulto , Femenino , Envejecimiento/fisiología , Anciano de 80 o más Años , Adulto Joven , Resiliencia PsicológicaRESUMEN
Aim: To investigate the limitations of diagnosing glaucoma in patients with coexistent neurodegenerative disease (NDD) by collecting information on demographics, examination findings, optical coherence tomography (OCT), and visual field (VF) tests. Materials and methods: Retrospective cohort study of patients with primary open-angle glaucoma and coexistent dementia, multiple sclerosis (MS), Parkinson's disease (PD), or cerebrovascular accident (CVA) from 2014 to 2020. We included patients with a minimum of 3 years of follow-up. Demographics, ophthalmic exam, OCT, and VF findings were reported and compared across NDD groups using the Chi-squared and analysis of variance tests. Results: We included 199 patients with glaucoma and coexistent NDD, including dementia (51.3%), CVA (11.2%), PD (18.1%), and MS (19.6%). Cupping, neuroretinal rim thinning, pallor, and peripapillary atrophy of the optic nerve were most frequently observed. There was a high number of missing values from OCT to VF tests, and zero patients had a complete OCT or VF test. Additionally, 67.8 and 77.4% of patients received <1 OCT and VF/year, respectively. Retinal nerve fiber layer (RNFL) thinning was observed most frequently in the superior (33.2% OD and 30.7% OS) and inferior (25.6% OD and 30.2% OS) quadrants, with the most significant thinning seen in CVA patients compared to other NDDs (p < 0.05). Glaucoma hemifield tests (GHTs) were abnormal in 23.1% OD and 22.6% OS, and the average mean deviation was -7.43 [standard deviation (SD) 8.23] OD and -8.79 (SD 7.99) OS. Conclusion: The OCT and VF tests are frequently unavailable and may be confounded in patients with coexistent glaucoma and NDDs, complicating glaucoma diagnosis and management. Clinical significance: Diagnosing and managing glaucoma in patients with coexistent NDD is difficult, given the lack of available and reliable OCT and VF testing data. Providers may be forced to rely on intraocular pressure (IOP) and other imperfect measures. How to cite this article: Ciociola EC, Patel K, Blahnik T, et al. A Retrospective Cohort Study on the Difficulties of Diagnosing and Managing Glaucoma in Patients with Coexistent Neurodegenerative Disease. J Curr Glaucoma Pract 2023;17(3):126-133.
RESUMEN
PURPOSE OF REVIEW: Diabetic macular edema (DME) is the accumulation of fluid in the extracellular space within the macula and is a major cause of visual impairment among patients with diabetes. First-line treatment for DME includes pharmacotherapy with intravitreal anti-vascular endothelial growth factor medications and intravitreal corticosteroids. Alternative therapeutic strategies include laser photocoagulation for non-center involving DME, and surgical options such as pars plana vitrectomy (PPV) with or without internal limiting membrane (ILM) peel in cases with vitreoretinal interface anomalies or DME refractory to pharmacotherapy, and the Port Delivery System (PDS) for sustained release of anti-vascular endothelial growth factor (VEGF) medication. Our aim is to review the existing literature on surgical management of DME including imaging changes in chronic DME and the clinical relevance of surgical intervention. RECENT FINDINGS: Imaging changes associated with DME and a worse prognosis include disorganization of the retinal layer, disruption of both the external limiting membrane (ELM) and ellipsoid zone, and vitreomacular interface abnormalities. Studies involving pars plana vitrectomy with and without ILM peel show anatomic improvement but may not always be associated with significant change in visual outcomes. Early studies lacked detailed imaging of the retinal layers and PPV was likely performed as a last resort. In addition, the novel PDS is surgically implanted into the pars plana and works as a drug reservoir with controlled release of drug. However, it has been recalled in patients with wet age-related macular degeneration due to issues with dislodgement. Surgical interventions for DME include pars plana vitrectomy with and without ILM peel and new surgical therapies for DME such as the PDS and subretinal gene therapy have the potential to reduce the risk of DME progression.
Asunto(s)
Diabetes Mellitus , Retinopatía Diabética , Edema Macular , Humanos , Edema Macular/cirugía , Edema Macular/etiología , Retinopatía Diabética/cirugía , Retinopatía Diabética/complicaciones , Factores de Crecimiento Endotelial , Vitrectomía/efectos adversos , Vitrectomía/métodos , Tomografía de Coherencia Óptica/efectos adversos , Coagulación con Láser/efectos adversos , Coagulación con Láser/métodos , Estudios Retrospectivos , Diabetes Mellitus/etiologíaRESUMEN
The idea that abnormal human activities follow multi-day rhythms is found in ancient beliefs on the moon to modern clinical observations in epilepsy and mood disorders. To explore multi-day rhythms in healthy human behavior our analysis includes over 300 million smartphone touchscreen interactions logging up to 2 years of day-to-day activities (N401 subjects). At the level of each individual, we find a complex expression of multi-day rhythms where the rhythms occur scattered across diverse smartphone behaviors. With non-negative matrix factorization, we extract the scattered rhythms to reveal periods ranging from 7 to 52 days - cutting across age and gender. The rhythms are likely free-running - instead of being ubiquitously driven by the moon - as they did not show broad population-level synchronization even though the sampled population lived in northern Europe. We propose that multi-day rhythms are a common trait, but their consequences are uniquely experienced in day-to-day behavior.
RESUMEN
Non-compliance to intravitreal anti-vascular endothelial growth factor (anti-VEGF) therapy can result in increased disease activity in neovascular age-related macular degeneration (nAMD). Our study aims to determine effects of unplanned delay in anti-VEGF injection treatment for nAMD. This retrospective observational study included patients with delays in receiving intravitreal injections for nAMD treatment from March to May 2020 by at least 21 days. Baseline demographic and clinical characteristics, visual acuity (VA), central macular thickness (CMT) measured on optical coherence tomography (OCT), and duration of delayed treatment were analyzed for 3 time points, the pre-delay visit (v1) and post-delay visits (v2 and v3). Data were compared to age-matched controls treated for nAMD in 2019 without delay. Demographic characteristics were compared using two-sample t-tests for continuous variables and Pearson's chi-square tests for categorical variables. For the two primary outcomes of interest, VA and CMT, means and standard deviations were reported for each combination of group and time. Each outcome was modeled using a linear mixed model with the group, time and group-time interaction as fixed effects. A total of 69 patients (99 eyes) in the treatment delay group and 44 patients (69 eyes) in the control group were identified. Statistically significant differences between control and delayed groups were detected for VA (difference in mean logMAR = 0.16; 95% CI 0.06, 0.27; p = 0.002) and CMT (difference in mean CMT = 29; 95% CI 12, 47; p = 0.001) at v2. No differences were detected for v1 and v3 time points for both outcomes. An unplanned delay in intravitreal injection treatment for nAMD resulted in an increase in CMT and worsening of VA compared to controls observed at v2. At v3, CMT and VA recovered to near v1 levels. This study demonstrates that a one-time, brief interruption in treatment for nAMD results in reversible, temporary worsening.
Asunto(s)
Degeneración Macular , Degeneración Macular Húmeda , Humanos , Ranibizumab , Inhibidores de la Angiogénesis , Estudios Retrospectivos , Factor A de Crecimiento Endotelial Vascular , Tiempo de Tratamiento , Resultado del Tratamiento , Degeneración Macular/tratamiento farmacológico , Inyecciones Intravítreas , Degeneración Macular Húmeda/tratamiento farmacológicoRESUMEN
Smartphones touchscreen interactions may help resolve if and how real-world behavioral dynamics are shaped by aging. Here, in a sample spanning the adult life span (16 to 86 years, N = 598, accumulating 355 million interactions), we clustered the smartphone interactions according to their next inter-touch interval dynamics. There were age-related behavioral losses at the clusters occupying short intervals (â¼100 ms, R2 â¼ 0.8) but gains at the long intervals (â¼4 s, R2 â¼ 0.4). Our approach revealed a sophisticated form of behavioral aging where individuals simultaneously demonstrated accelerated aging in one behavioral cluster versus a deceleration in another. Contrary to the common notion of a simple behavioral decline with age based on conventional cognitive tests, we show that the nature of aging systematically varies according to the underlying dynamics. Of all the imaginable factors determining smartphone interactions, age-sensitive cognitive and behavioral processes may dominatingly shape smartphone dynamics.
RESUMEN
Smartphones offer unique opportunities to trace the convoluted behavioral patterns accompanying healthy aging. Here we captured smartphone touchscreen interactions from a healthy population (N = 684, â¼309 million interactions) spanning 16 to 86 years of age and trained a decision tree regression model to estimate chronological age based on the interactions. The interactions were clustered according to their next interval dynamics to quantify diverse smartphone behaviors. The regression model well-estimated the chronological age in health (mean absolute error = 6 years, R2 = 0.8). We next deployed this model on a population of stroke survivors (N = 41) to find larger prediction errors such that the estimated age was advanced by 6 years. A similar pattern was observed in people with epilepsy (N = 51), with prediction errors advanced by 10 years. The smartphone behavioral model trained in health can be used to study altered aging in neurological diseases.
Asunto(s)
Carcinoma de Células Renales , Oftalmopatías , Neoplasias Renales , Síndromes Paraneoplásicos , Autoanticuerpos , Carcinoma de Células Renales/complicaciones , Carcinoma de Células Renales/diagnóstico , Oftalmopatías/complicaciones , Femenino , Humanos , Neoplasias Renales/complicaciones , Neoplasias Renales/diagnóstico , Masculino , Síndromes Paraneoplásicos/complicaciones , Síndromes Paraneoplásicos/etiologíaRESUMEN
A range of abnormal electrical activity patterns termed epileptiform discharges can occur in the brains of persons with epilepsy. These epileptiform discharges can be monitored and recorded with implanted devices that deliver therapeutic neurostimulation. These continuous recordings provide an opportunity to study the behavioral correlates of epileptiform discharges as the patients go about their daily lives. Here, we captured the smartphone touchscreen interactions in eight patients in conjunction with electrographic recordings (accumulating 35,714 h) and by using an artificial neural network model addressed if the behavior reflected the epileptiform discharges. The personalized model outputs based on smartphone behavioral inputs corresponded well with the observed electrographic data (R: 0.2-0.6, median 0.4). The realistic reconstructions of epileptiform activity based on smartphone use demonstrate how day-to-day digital behavior may be converted to personalized markers of disease activity in epilepsy.
RESUMEN
Using polysomnography over multiple weeks to characterize an individual's habitual sleep behavior while accurate, is difficult to upscale. As an alternative, we integrated sleep measurements from a consumer sleep-tracker, smartphone-based ecological momentary assessment, and user-phone interactions in 198 participants for 2 months. User retention averaged >80% for all three modalities. Agreement in bed and wake time estimates across modalities was high (rho = 0.81-0.92) and were adrift of one another for an average of 4 min, providing redundant sleep measurement. On the ~23% of nights where discrepancies between modalities exceeded 1 h, k-means clustering revealed three patterns, each consistently expressed within a given individual. The three corresponding groups that emerged differed systematically in age, sleep timing, time in bed, and peri-sleep phone usage. Hence, contrary to being problematic, discrepant data across measurement modalities facilitated the identification of stable interindividual differences in sleep behavior, underscoring its utility to characterizing population sleep and peri-sleep behavior.
RESUMEN
Striatal dopamine and smartphone behavior have both been linked with behavioral variability. Here, we leverage day-to-day logs of natural, unconstrained smartphone behavior and establish a correlation between a measure of smartphone social activity previously linked with behavioral variability and a measure of striatal dopamine synthesis capacity using [18F]-DOPA PET in (N = 22) healthy adult humans. Specifically, we find that a higher proportion of social app interactions correlates with lower dopamine synthesis capacity in the bilateral putamen. Permutation tests and penalized regressions provide evidence that this link between dopamine synthesis capacity and social versus non-social smartphone interactions is specific. These observations provide a key empirical grounding for current speculations about dopamine's role in digital social behavior.
RESUMEN
Cognitive output and physical activity levels fluctuate surrounding sleep. The ubiquitous digitization of behavior via smartphones is a promising avenue for addressing how these fluctuations occur in daily living. Here, we logged smartphone touchscreen interactions to proxy cognitive fluctuations and contrasted these to physical activity patterns logged on wrist-worn actigraphy. We found that both cognitive and physical activities were dominated by diurnal (â¼24 h) and infra-radian (â¼7 days) rhythms. The proxy measures of cognitive performance-tapping speed, unlocking speed, and app locating speed-contained lower-powered diurnal rhythm than physical activity. The difference between cognitive and physical activity was vivid during bedtime as people continued to interact with their smartphones at physical rest. The cognitive performance measures in this period were worse than those in the hour before or after bedtime. We suggest that the rhythms underlying cognitive activity in the real world are distinct from those underlying physical activity, and this discord may be a hallmark of modern human behavior.
Asunto(s)
Anticuerpos Monoclonales Humanizados/efectos adversos , Movimientos Oculares/efectos de los fármacos , Síndrome de Miller Fisher/inducido químicamente , Oftalmoplejía/etiología , Anciano de 80 o más Años , Anticuerpos Monoclonales Humanizados/uso terapéutico , Antineoplásicos Inmunológicos/efectos adversos , Antineoplásicos Inmunológicos/uso terapéutico , Carcinoma de Células Escamosas/tratamiento farmacológico , Humanos , Hidroxietilrutósido , Masculino , Síndrome de Miller Fisher/complicaciones , Síndrome de Miller Fisher/diagnóstico , Oftalmoplejía/fisiopatología , Neoplasias Cutáneas/diagnóstico por imagenRESUMEN
PURPOSE OF REVIEW: To compile and report the ocular manifestations of coronavirus disease 2019 (COVID-19) infection and summarize the ocular side effects of investigational treatments of this disease. RECENT FINDINGS: Conjunctivitis is by far the most common ocular manifestation of COVID-19 with viral particles being isolated from tears/secretions of infected individuals. Multiple therapeutic options are being explored across a variety of medication classes with diverse ocular side effects. SUMMARY: Eye care professionals must exercise caution, as conjunctivitis may be the presenting or sole finding of an active COVID-19 infection. While no currently studied therapeutic agents have been found to reliably treat COVID-19, early vaccination trials are progressing and show promise. A video abstract is available for a more detailed summary. VIDEO ABSTRACT: http://links.lww.com/COOP/A36.
Asunto(s)
Betacoronavirus/aislamiento & purificación , Conjuntivitis Viral/diagnóstico , Infecciones por Coronavirus/diagnóstico , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos/etiología , Drogas en Investigación/efectos adversos , Oftalmopatías/inducido químicamente , Neumonía Viral/diagnóstico , Lágrimas/virología , COVID-19 , Conjuntivitis Viral/tratamiento farmacológico , Conjuntivitis Viral/virología , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos/prevención & control , Oftalmopatías/prevención & control , Humanos , Pandemias , SARS-CoV-2RESUMEN
The distribution of intervals between human actions such as email posts or keyboard strokes demonstrates distinct properties at short versus long timescales. For instance, at long timescales, which are presumably controlled by complex process such as planning and decision making, it has been shown that those interevent intervals follow a scale-invariant (or power-law) distribution. In contrast, at shorter timescales-which are governed by different processes such as sensorimotor skill-they do not follow the same distribution and we know little about how they relate to the scale-invariant pattern. Here, we analyzed 9 million intervals between smartphone screen touches of 84 individuals which span several orders of magnitudes (from milliseconds to hours). To capture these intervals, we extend a priority-based generative model to smartphone touching events. At short timescale, the model is governed by refractory effects, while at longer timescales, the intertouch intervals are governed by the priority difference between smartphone tasks and other tasks. The flexibility of the model allows us to capture interindividual variations at short and long timescales, while its tractability enables efficient model fitting. According to our model, each individual has a specific power-law exponent which is tightly related to the effective refractory time constant suggesting that motor processes which influence the fast actions are related to the higher cognitive processes governing the longer interevent intervals.
Asunto(s)
Modelos Teóricos , Teléfono Inteligente , Tacto , Humanos , CinéticaAsunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Atención a la Salud/organización & administración , Oftalmopatías/terapia , Neurología/métodos , Oftalmología/métodos , Neumonía Viral/epidemiología , Telemedicina/organización & administración , COVID-19 , Implementación de Plan de Salud/organización & administración , Humanos , Pandemias , Selección de Paciente , Consulta Remota/instrumentación , SARS-CoV-2RESUMEN
Body movements drop with sleep, and this behavioural signature is widely exploited to infer sleep duration. However, a reduction in body movements may also occur in periods of intense cognitive activity, and the ubiquitous use of smartphones may capture these wakeful periods otherwise hidden in the standard measures of sleep. Here, we continuously captured the gross body movements using standard wrist-worn accelerometers to quantify sleep (actigraphy) and logged the timing of the day-to-day touchscreen events ('tappigraphy'). Using these measures, we addressed how the gross body movements overlap with the cognitively engaging digital behaviour (from n = 79 individuals, accumulating ~1400 nights). We find that smartphone use was distributed across a broad spectrum of physical activity levels, but consistently peaked at rest. We estimated the putative sleep onset and wake-up times from the actigraphy data to find that these times were well correlated to the estimates from tappigraphy (R2 = 0.9 for sleep-onset time and wake-up time). However, actigraphy overestimated sleep as virtually all of the users used their phones during the putative sleep period. Interestingly, the probability of touches remained greater than zero for ~2 h after the putative sleep onset, and ~2 h before the putative wake-up time. Our findings suggest that touchscreen interactions are widely integrated into modern sleeping habits-surrounding both sleep onset and waking-up periods-yielding a new approach to measuring sleep. Smartphone interactions can be leveraged to update the behavioural signatures of sleep with these peculiarities of modern digital behaviour.
RESUMEN
While pathologies of the central nervous system (CNS) are often associated with neuropsychological deficits, adequate quantification and monitoring of such deficits remains challenging. Due to their complex nature, comprehensive neuropsychological evaluations are needed, which are time-consuming, resource-intensive and do not adequately account for daily or hourly fluctuations of a patient's condition. Innovative approaches are required to improve the diagnostics and continuous monitoring of brain function, ideally in the form of a simple, objective, time-saving and inexpensive tool that overcomes the aforementioned weaknesses of conventional assessments. As smartphones are widely used and integrated in virtually every aspect of our lives, their potential regarding the acquisition of data representing an individual's behavior and health is enormous. Alterations in a patient's physical or mental health state may be recognized as behavioral deviation from the physiological range of the normal population, but also in comparison to the patient's individual baseline assessment. As smartphone-based assessment allows for continuous monitoring and therefore accounts for possible fluctuations or transiently occurring abnormalities in a patient's neurologic state, it may serve as a surveillance tool in the acute setting for early recognition of complications, or in the long-term outpatient setting to quantify rehabilitation or disease progress. This may be particularly interesting for regions of the world where healthcare resources for comprehensive clinical/neuropsychological examinations are insufficient or distances to healthcare providers are long. Here, we highlight the potential of smartphone-based behavioral monitoring in healthcare. Clinical Trial Registration: www.clinicaltrials.gov, identifier NCT03516162.
RESUMEN
Unconstrained day-to-day activities are difficult to quantify and how the corresponding movements shape the brain remain unclear. Here, we recorded all touchscreen smartphone interactions at a sub-second precision and show that the unconstrained day-to-day behavior captured on the phone reflects in the simple sensorimotor computations measured in the laboratory. The behavioral diversity on the phone, the speed of interactions, the amount of social & non-social interactions, all uniquely influenced the trial-to-trial motor variability used to measure the amount of intrinsic neuronal noise. Surprisingly, both the motor performance and the early somatosensory cortical signals (assessed using EEG in passive conditions) became noisier with increased social interactions. Inter-individual differences in how people use the smartphone can help thus decompose the structure of low-level sensorimotor computations.