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Multiple criteria and growth references have been proposed for extrauterine growth restriction (EUGR). We hypothesized that these may impact the diagnosis of EUGR. The objective was to evaluate the prevalence of EUGR with its different definitions and the concordance according to Fenton, Olsen, and INTERGROWTH-21st in very-low-birthweight (VLBW) infants. This is an observational, retrospective, and multicenter study including VLBW infants from the Spanish SEN1500 Network from 2011 to 2020. Patients with major congenital anomalies, embryopathies, and gestational age less than 24 weeks were excluded. EUGR prevalence was calculated at discharge with cross-sectional, longitudinal, "true" cross-sectional, and "true" longitudinal definitions. Concordance was assessed with Fleiss' kappa coefficient. 23582 VLBW infants from 77 NICUs were included. In total, 50.4% were men with a median of gestational age of 29 (4) weeks. The prevalence of EUGR (cross-sectional, longitudinal, and "true") was variable for weight, length, and head circumference. Overall, the prevalence was higher with Fenton and lower with Olsen (cross-sectional and "true" cross-sectional) and INTERGROWTH-21st (longitudinal and "true" longitudinal). Agreement among the charts by weight was good only for cross-sectional EUGR and moderate for longitudinal, "true" cross-sectional, and "true" longitudinal. Concordance was good or very good for EUGR by length and head circumference.Conclusions: The prevalence of EUGR with the most commonly used definitions was variable in the cohort. Agreement among growth charts was moderate for all the definitions of EUGR by weight except cross-sectional and good or very good for length and head circumference. The choice of reference chart can impact the establishment of the diagnosis of EUGR. What is known: ⢠EUGR has been defined in the literature and daily practice considering weight, length and head circumference with multiple criteria (cross-sectional, longitudinal, and "true" definition) ⢠Different growth charts have been used for EUGR diagnosis What is new: ⢠Prevalence of EUGR is variable depending on the definition and growth chart used in our cohort of VLBW infants ⢠For the most frequently EUGR criteria used, traditionally considering weight, concordance among Fenton, Olsen and INTERGROWTH-21st growth charts is only moderate for all the definitions of EUGR by weight except cross-sectional definition. Concordance among the charts is good or very good for the different criteria of EUGR by head circumference and length.
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Gráficos de Crecimiento , Recién Nacido de muy Bajo Peso , Humanos , Recién Nacido de muy Bajo Peso/crecimiento & desarrollo , Recién Nacido , Estudios Retrospectivos , Masculino , España/epidemiología , Femenino , Prevalencia , Estudios Transversales , Edad GestacionalRESUMEN
BACKGROUND: Many people attending primary care (PC) have anxiety-depressive symptoms and work-related burnout compounded by a lack of resources to meet their needs. The COVID-19 pandemic has exacerbated this problem, and digital tools have been proposed as a solution. OBJECTIVE: We aimed to present the development, feasibility, and potential effectiveness of Vickybot, a chatbot aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout, and detecting suicide risk in patients from PC and health care workers. METHODS: Healthy controls (HCs) tested Vickybot for reliability. For the simulation study, HCs used Vickybot for 2 weeks to simulate different clinical situations. For feasibility and effectiveness study, people consulting PC or health care workers with mental health problems used Vickybot for 1 month. Self-assessments for anxiety (Generalized Anxiety Disorder 7-item) and depression (Patient Health Questionnaire-9) symptoms and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every 2 weeks. Feasibility was determined from both subjective and objective user-engagement indicators (UEIs). Potential effectiveness was measured using paired 2-tailed t tests or Wilcoxon signed-rank test for changes in self-assessment scores. RESULTS: Overall, 40 HCs tested Vickybot simultaneously, and the data were reliably transmitted and registered. For simulation, 17 HCs (n=13, 76% female; mean age 36.5, SD 9.7 years) received 98.8% of the expected modules. Suicidal alerts were received correctly. For the feasibility and potential effectiveness study, 34 patients (15 from PC and 19 health care workers; 76% [26/34] female; mean age 35.3, SD 10.1 years) completed the first self-assessments, with 100% (34/34) presenting anxiety symptoms, 94% (32/34) depressive symptoms, and 65% (22/34) work-related burnout. In addition, 27% (9/34) of patients completed the second self-assessment after 2 weeks of use. No significant differences were found between the first and second self-assessments for anxiety (t8=1.000; P=.34) or depressive (t8=0.40; P=.70) symptoms. However, work-related burnout scores were moderately reduced (z=-2.07, P=.04, r=0.32). There was a nonsignificant trend toward a greater reduction in anxiety-depressive symptoms and work-related burnout with greater use of the chatbot. Furthermore, 9% (3/34) of patients activated the suicide alert, and the research team promptly intervened with successful outcomes. Vickybot showed high subjective UEI (acceptability, usability, and satisfaction), but low objective UEI (completion, adherence, compliance, and engagement). Vickybot was moderately feasible. CONCLUSIONS: The chatbot was useful in screening for the presence and severity of anxiety and depressive symptoms, and for detecting suicidal risk. Potential effectiveness was shown to reduce work-related burnout but not anxiety or depressive symptoms. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising but suggest the need to adapt and enhance the smartphone-based solution to improve engagement. A consensus on how to report UEIs and validate digital solutions, particularly for chatbots, is required.
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Agotamiento Profesional , COVID-19 , Humanos , Femenino , Adulto , Masculino , Depresión/diagnóstico , Depresión/psicología , Pandemias , Estudios de Factibilidad , Reproducibilidad de los Resultados , Personal de Salud , Atención Primaria de SaludRESUMEN
OBJETIVE: To evaluate SAR-COV-2 pacients' features. To analyse de diferences between those who required hospital care and those who didn't. DESIGN: Observational, descriptive and retrospective study. SETTING: Twomedical practices of an urban health center in Salamanca (Spain). PARTICIPANTS: ≥18 years diagnosed with SAR-CoV-2 between March 11th and April 20th. MAIN MEASUREMENTS: clinical-epidemiological chatacteristics, diagnosis, treatment and outcome at the end of study RESULTS: 122 patients (63.9% female), 19.7% social and health care workers y 4.9% from nursing homes. Predominant age group: 46-60 years. 67.2% without comorbility. Predomint symptoms: low-grade fever (73.5%), cough (65.2%) y fever (43%). Average age of the patients requiring hospital care was higher: 59.85 (DE16.22) versus 50.78 (DE17.88) P=.013. 63.6% of all the patients monitored by Primary Health Care and 14.1% of patients that required assistance did not present dyspnea P=.001. Only 2.5% of the hospital-assisted patients, compared to 61.5% of Primary Health Care, were not tested P=.0001. 26 patients were attendedn at an emergency room: 11(9%) stayed and 2 (1.6%) passed away. No antibiotic or inhaler treatment for 52.5% and 70.5% respectively. The most used antipyretic treatment was paracetamol (78.7%). CONCLUSIONS: Prevalence in females, comorbility-free patients and in age range: 46-60 years. Complementary and confirmatory test were performed mainly in hospital care. Predominance of mild symptoms and favourable evolution. Highliting the role played by Primary Health Care in detection, early intervention and monitoring of severe cases.
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COVID-19 , Servicios Urbanos de Salud/estadística & datos numéricos , Salud Urbana/estadística & datos numéricos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , COVID-19/diagnóstico , COVID-19/epidemiología , COVID-19/terapia , Femenino , Humanos , Masculino , Persona de Mediana Edad , Pandemias , Estudios Retrospectivos , España/epidemiología , Resultado del Tratamiento , Adulto JovenRESUMEN
Toxocara cati is one of the causative agents of human toxocariasis. Serological methods are used for diagnosis in paratenic hosts like humans but the humoral immune response triggered by this parasite is unknown. We characterized the humoral immune response to T. cati excretory-secretory antigens (TES) in pigs as animal model during the acute and chronic stages of infection. ELISA and Western Blot techniques were used to determine antibody response. Pigs were experimentally inoculated with 100,000 infective Toxocara cati eggs. Blood was collected at 7, 14, 21 and 28 days post-inoculation (d.p.i.) to assess the acute stage of infection and 90, 120 and 180 d. p.i. for chronic stage analysis. ELISA showed values higher than the cut-off of specific IgM and IgG at 7 d. p.i. with significant differences at 0 and 7 d. p.i. for IgM and at 14, 21 and 28 d. p.i. for IgG in the acute stage. Higher and stable levels were detected in the chronic stage. Western Blot showed bands from 102 to 38 kDa detected by specific IgM and IgG. More immunogenic bands were identified by specific IgG. In the chronic stage of infection a band near 31 kDa was the only band detected by IgM until 150 d. p.i. Specific IgG recognized bands between 102 and 31 kDa. This study demonstrates how the humoral immune response evolves in the acute and chronic stages of infection and provides evidence on the role of the pig as a paratenic host of T. cati.
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Anticuerpos Antihelmínticos/biosíntesis , Inmunidad Humoral , Enfermedades de los Porcinos/inmunología , Toxocara/inmunología , Toxocariasis/inmunología , Análisis de Varianza , Animales , Anticuerpos Antihelmínticos/sangre , Área Bajo la Curva , Western Blotting , Gatos , Modelos Animales de Enfermedad , Ensayo de Inmunoadsorción Enzimática , Heces/parasitología , Inmunoglobulina G/biosíntesis , Inmunoglobulina G/sangre , Inmunoglobulina M/biosíntesis , Inmunoglobulina M/sangre , Masculino , Curva ROC , Sensibilidad y Especificidad , Porcinos , Enfermedades de los Porcinos/parasitología , Toxocariasis/parasitologíaRESUMEN
PURPOSE: To compare the effects of lateral meniscus posterior root avulsion left in situ, its repair, and meniscectomy on contact pressure distribution in both tibiofemoral compartments at different flexion angles. METHODS: Eight cadaveric knees were tested under compressive 1000 N load for 4 lateral meniscus conditions (intact, posterior root avulsion, transosseous root repair, and total meniscectomy) at flexion angles 0°, 30°, 60°, and 90°. Contact area and pressure distribution were registered using K-scan pressure sensors inserted between menisci and tibial plateau. RESULTS: In the lateral compartment, root detachment decreased contact area (P = .017, 0° and 30°; P = .012, 60° and 90°) and increased mean (P = .012, all angles) and maximum (P = .025, 0° and 30°; P = .017, 60°; P = .012, 90°) pressures relative to intact condition. Repair restored all measured parameters close to intact at 0°, but effectiveness decreased with flexion angle, yielding no significant effect at 90°. Meniscectomy produced higher decreases than root avulsion in contact area (P = .012, 0° and 90°; P = .05, 30° and 60°) and increases in mean (P = .017, 0° and 30°; P = .018, 90°) and maximum pressure (P = .012, 0°; P = .036, 30°). In the medial compartment, lesion changed the contact area at high flexion angles only, while meniscectomy induced greater changes at all angles. CONCLUSIONS: Lateral meniscus posterior root avulsion generates significant alterations in contact area and pressures at lateral knee compartment for flexion angles between full extension and 90°. Meniscectomy causes greater disorders than the avulsion left in situ. Transosseous repair with a single suture restores these alterations to conditions close to intact at 0° and 30° but not at 60° and 90°. CLINICAL RELEVANCE: Altered contact mechanics after lateral meniscus posterior root avulsion might have degenerative consequences. Transosseous repair with one suture should be revised to effectively restore contact mechanics at high flexion angles.
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Traumatismos de la Rodilla/cirugía , Articulación de la Rodilla/fisiopatología , Reimplantación/métodos , Suturas , Lesiones de Menisco Tibial , Anciano , Anciano de 80 o más Años , Fenómenos Biomecánicos , Cadáver , Femenino , Humanos , Traumatismos de la Rodilla/fisiopatología , Articulación de la Rodilla/cirugía , Masculino , Meniscos Tibiales/cirugía , Persona de Mediana Edad , Presión , Rango del Movimiento ArticularRESUMEN
Digital twin technology is emerging as a transformative paradigm for personalized medicine in the management of chronic conditions. In this article, we explore the concept and key characteristics of a digital twin and its applications in chronic non-communicable metabolic disease management, with a focus on diabetes case studies. We cover various types of digital twin models, including mechanistic models based on ODEs, data-driven ML algorithms, and hybrid modeling strategies that combine the strengths of both approaches. We present successful case studies demonstrating the potential of digital twins in improving glucose outcomes for individuals with T1D and T2D, and discuss the benefits and challenges of translating digital twin research applications to clinical practice.
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Inteligencia Artificial , Enfermedades Metabólicas , Humanos , Enfermedades Metabólicas/genética , Enfermedades Metabólicas/metabolismo , Medicina de Precisión/métodos , GemelosRESUMEN
Predicting the potential distribution and coexistence of suitable geographic areas for Chagas disease vectors in the Americas is a crucial task for understanding the eco-epidemiological dynamics of this disease. The potential distribution and coexistence of 3 species-Rhodnius prolixus (Hemiptera: Reduviidae), Cavernicola pilosa (Hemiptera: Reduviidae), and Rhodnius pictipes (Hemiptera: Reduviidae) were modeled. Presence records were obtained and environmental variables were selected based on correlation analysis, Jackknife analysis and knowledge of the biology and natural history of the species. The MaxEnt algorithm included in the kuenm package of R software was used for modeling the potential distribution, and various scenarios of the BAM diagram (Biotic, Abiotic, and Movement variables) were evaluated. The variables contributing to the final models were different for each species. Rhodnius pictipes showed a potential distribution in South America, particularly in Brazil, Bolivia, Peru, Colombia, Venezuela, Guyana, and Suriname. Areas with environmentally suitable conditions for R. prolixus were located in southern Brazil, Peru, Colombia, southern Mexico, Guatemala, El Salvador, and Honduras, whereas for C. pilosa they were in southeastern Brazil, southeastern Central America, Peru, Ecuador, Colombia, Venezuela, Guyana, Suriname, and French Guiana. Co-occurrence analysis revealed distinct patterns in the neotropical region, with some areas indicating the potential distribution of 1 or more species. In Brazil, occurrence and co-occurrence areas were concentrated in the northwest and southeast regions. Overall, this study provides valuable information on the potential distribution and coexistence of vectors, which can inform targeted vector control strategies and contribute to global efforts in combating Chagas disease.
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Extrauterine growth restriction (EUGR) has been used in the literature and clinical practice to describe inadequate growth in preterm infants. Significant variability is seen in the criteria for EUGR, with no standard definition reached to date. Moreover, no consensus on the optimal timing for assessment or the ideal growth monitoring tool has been achieved, and an ongoing debate persists on the appropriate terminology to express poor postnatal growth. To ensure an adequate understanding of growth and early intervention in preterm infants at higher risk, it is critical to relate the diagnostic criteria of EUGR to the ability to predict adverse outcomes, such as neurodevelopmental outcomes. This narrative review was conducted to present evidence that evaluates neurodevelopmental outcomes in preterm infants with EUGR, comparing separately the different definitions of this concept by weight (cross-sectional, longitudinal and "true" EUGR). In this article, we highlight the challenges of comparing various published studies on the subject, even when subclassifying by the definition of EUGR, due to the significant variability on the criteria used for each definition and for the evaluation of neurodevelopmental outcomes in different papers. This heterogeneity compromises the obtention of a single firm conclusion on the relation between different definitions of EUGR and adverse neurodevelopmental outcomes.
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Intervención Educativa Precoz , Recien Nacido Prematuro , Recién Nacido , Lactante , Humanos , Estudios Transversales , ConsensoRESUMEN
OBJECTIVE: Artificial intelligence and machine learning are transforming many fields including medicine. In diabetes, robust biosensing technologies and automated insulin delivery therapies have created a substantial opportunity to improve health. While the number of manuscripts addressing the topic of applying machine learning to diabetes has grown in recent years, there has been a lack of consistency in the methods, metrics, and data used to train and evaluate these algorithms. This manuscript provides consensus guidelines for machine learning practitioners in the field of diabetes, including best practice recommended approaches and warnings about pitfalls to avoid. METHODS: Algorithmic approaches are reviewed and benefits of different algorithms are discussed including importance of clinical accuracy, explainability, interpretability, and personalization. We review the most common features used in machine learning applications in diabetes glucose control and provide an open-source library of functions for calculating features, as well as a framework for specifying data sets using data sheets. A review of current data sets available for training algorithms is provided as well as an online repository of data sources. SIGNIFICANCE: These consensus guidelines are designed to improve performance and translatability of new machine learning algorithms developed in the field of diabetes for engineers and data scientists.
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Inteligencia Artificial , Diabetes Mellitus , Humanos , Control Glucémico , Aprendizaje Automático , Diabetes Mellitus/tratamiento farmacológico , AlgoritmosRESUMEN
In the work described here, two techniques for the recovery of anthocyanins from potato peel were studied and compared. One of the techniques employed was supercritical fluid extraction (SFE) with pure CO2 or with CO2 and ethanol as cosolvent and the other technique was pressurized liquid extraction (PLE), where the solvent used was ethanol in water acidified to pH 2.6. The effects of pressure and temperature were studied and the anthocyanin contents obtained were statistically analyzed. In SFE the use of low pressure (100 bar) and high temperature (65 °C) was desirable for the anthocyanin extraction. With PLE the anthocyanin contents are increased considerably, and the best yields were obtained at 100 bar and 80 °C. This result is in correspondence with antioxidant activity index values (1.66) obtained in a DPPH antioxidant activity assay. In the extracts obtained with PLE the phenolic compounds were also determined, but the main compounds presented in the extract are anthocyanins.
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Antocianinas/aislamiento & purificación , Depuradores de Radicales Libres/aislamiento & purificación , Extractos Vegetales/aislamiento & purificación , Solanum/química , Análisis de Varianza , Antocianinas/química , Compuestos de Bifenilo/química , Dióxido de Carbono/química , Etanol/química , Depuradores de Radicales Libres/química , Radicales Libres/química , Interacciones Hidrofóbicas e Hidrofílicas , Presión Hidrostática , Extracción Líquido-Líquido/métodos , Fenoles/química , Fenoles/aislamiento & purificación , Picratos/química , Extractos Vegetales/química , Solventes/químicaRESUMEN
Meta-analysis is used to test a variant of a Developmental Origins of Adult Health and Disease (DOHaD)'s conjecture known as predictive adaptive response (PAR). According to it, individuals who are exposed to mismatches between adverse or constrained in utero conditions, on the one hand, and postnatal obesogenic environments, on the other, are at higher risk of developing adult chronic conditions, including obesity, type 2 diabetes (T2D), hypertension and cardiovascular disease. We argue that migrant populations from low and middle to high-income countries offer a unique opportunity to test the conjecture. A database was constructed from an exhaustive literature search of peer-reviewed papers published prior to May 2021 contained in PUBMED and SCOPUS using keywords related to migrants, DOHaD, and associated health outcomes. Random effects meta-regression models were estimated to assess the magnitude of effects associated with migrant groups on the prevalence rate of T2D and hypertension in adults and overweight/obesity in adults and children. Overall, we used 38 distinct studies and 78 estimates of diabetes, 59 estimates of hypertension, 102 estimates of overweight/obesity in adults, and 23 estimates of overweight/obesity in children. Our results show that adult migrants experience higher prevalence of T2D than populations at destination (PR 1.48; 95% CI 1.35-1.65) and origin (PR 1.80; 95% CI 1.40-2.34). Similarly, there is a significant excess of obesity prevalence in children migrants (PR 1.22; 95% CI 1.04-1.43) but not among adult migrants (PR 0.89; 95% CI 0.80-1.01). Although the total effect of migrant status on prevalence of hypertension is centered on zero, some migrant groups show increased risks. Finally, the size of estimated effects varies significantly by migrant groups according to place of destination. Despite limitations inherent to all meta-analyses and admitting that some of our findings may be accounted for alternative explanations, the present study shows empirical evidence consistent with selected PAR-like conjectures.
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Diabetes Mellitus Tipo 2 , Migrantes , Humanos , Migrantes/estadística & datos numéricos , Diabetes Mellitus Tipo 2/epidemiología , Diabetes Mellitus Tipo 2/etiología , Hipertensión/epidemiología , Femenino , Obesidad/epidemiología , Embarazo , Prevalencia , AdultoRESUMEN
OBJECTIVE: To evaluate PCT measurement in the diagnosis of bloodstream infection (BSI) in hospitalized patients aged 75+. METHOD: Descriptive, retrospective, monocentric study conducted in France, in patients with at least one blood culture and PCT and CRP measurements within the 24 hours before or after blood culture. RESULTS: The mean PCT and CRP values for the 118 (15.2%) positive blood cultures were 18.90 ng/ml [95%CI: 0.007-334.7] and 153.93 mg/l [1-557], respectively. With a threshold of 0.3 ng/ml, PCT measurement had a sensitivity of 84%, a specificity of 53%, a PPV of 24%, and an NPV of 95%, making it possible to rule out BSI in 350 (45.1%) patients (α-risk=5%). CONCLUSION: PCT measurement may eliminate BSI diagnosis more quickly than does blood culture reducing the inadequate and detrimental use of antibiotic therapy. A prospective study is required to validate its usefulness and confirm the cut-off value in geriatric populations.
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Infecciones Bacterianas , Sepsis , Humanos , Anciano , Polipéptido alfa Relacionado con Calcitonina , Estudios Retrospectivos , Biomarcadores , Proteína C-Reactiva/análisis , Sepsis/diagnóstico , Curva ROCRESUMEN
BACKGROUND: Physical activity (PA) can cause increased hypoglycemia (glucose <70 mg/dL) risk in people with type 1 diabetes (T1D). We modeled the probability of hypoglycemia during and up to 24 h following PA and identified key factors associated with hypoglycemia risk. METHODS: We leveraged a free-living dataset from Tidepool comprised of glucose measurements, insulin doses, and PA data from 50 individuals with T1D (6448 sessions) for training and validating machine learning models. We also used data from the T1Dexi pilot study that contains glucose management and PA data from 20 individuals with T1D (139 session) for assessing the accuracy of the best performing model on an independent test dataset. We used mixed-effects logistic regression (MELR) and mixed-effects random forest (MERF) to model hypoglycemia risk around PA. We identified risk factors associated with hypoglycemia using odds ratio and partial dependence analysis for the MELR and MERF models, respectively. Prediction accuracy was measured using the area under the receiver operating characteristic curve (AUROC). RESULTS: The analysis identified risk factors significantly associated with hypoglycemia during and following PA in both MELR and MERF models including glucose and body exposure to insulin at the start of PA, low blood glucose index 24 h prior to PA, and PA intensity and timing. Both models showed overall hypoglycemia risk peaking 1 h after PA and again 5-10 h after PA, which is consistent with the hypoglycemia risk pattern observed in the training dataset. Time following PA impacted hypoglycemia risk differently across different PA types. Accuracy of hypoglycemia prediction using the fixed effects of the MERF model was highest when predicting hypoglycemia during the first hour following the start of PA (AUROCVALIDATION = 0.83 and AUROCTESTING = 0.86) and decreased when predicting hypoglycemia in the 24 h after PA (AUROCVALIDATION = 0.66 and AUROCTESTING = 0.68). CONCLUSION: Hypoglycemia risk after the start of PA can be modeled using mixed-effects machine learning to identify key risk factors that may be used within decision support and insulin delivery systems. We published the population-level MERF model online for others to use.
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Diabetes Mellitus Tipo 1 , Hipoglucemia , Humanos , Hipoglucemiantes , Proyectos Piloto , Automonitorización de la Glucosa Sanguínea , Hipoglucemia/inducido químicamente , Glucemia , Glucosa , Insulina , Aprendizaje Automático , Ejercicio FísicoRESUMEN
BACKGROUND: People with multiple sclerosis (PwMS) fall frequently causing injury, social isolation, and decreased quality of life. Identifying locations and behaviors associated with high fall risk could help direct fall prevention interventions. Here we describe a smart-home system for assessing how mobility metrics relate to real-world fall risk in PwMS. METHODS: We performed a secondary analysis of a dataset of real-world falls collected from PwMS to identify patterns associated with increased fall risk. Thirty-four individuals were tracked over eight weeks with an inertial sensor comprising a triaxial accelerometer and time-of-flight radio transmitter, which communicated with beacons positioned throughout the home. We evaluated associations between locations in the home and movement behaviors prior to a fall compared with time periods when no falls occurred using metrics including gait initiation, time-spent-moving, movement length, and an entropy-based metric that quantifies movement complexity using transitions between rooms in the home. We also explored how fall risk may be related to the percent of times that a participant paused while walking (pauses-while-walking). RESULTS: Seventeen of the participants monitored sustained a total of 105 falls that were recorded. More falls occurred while walking (52%) than when stationary despite participants being largely sedentary, only walking 1.5±3.3% (median ± IQR) of the time that they were in their home. A total of 28% of falls occurred within one second of gait initiation. As the percentage of pauses-while-walking increased from 20 to 60%, the likelihood of a fall increased by nearly 3 times from 0.06 to 0.16%. Movement complexity, which was quantified using the entropy of room transitions, was significantly higher in the 10 min preceding falls compared with other 10-min time segments not preceding falls (1.15 ± 0.47 vs. 0.96 ± 0.24, P = 0.02). Path length was significantly longer (151.3 ± 156.1 m vs. 95.0 ± 157.2 m, P = 0.003) in the ten minutes preceding a fall compared with non-fall periods. Fall risk also varied among rooms but not consistently across participants. CONCLUSIONS: Movement metrics derived from wearable sensors and smart-home tracking systems are associated with fall risk in PwMS. More pauses-while-walking, and more complex, longer movement trajectories are associated with increased fall risk. FUNDING: Department of Veterans Affairs (RX001831-01A1). National Science Foundation (#2030859).
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Esclerosis Múltiple , Dispositivos Electrónicos Vestibles , Humanos , Calidad de Vida , Movimiento , Marcha , CaminataRESUMEN
The transition from pregnancy into parturition is physiologically directed by maternal, fetal and placental tissues. We hypothesize that these processes may be reflected in maternal physiological metrics. We enrolled pregnant participants in the third-trimester (n = 118) to study continuously worn smart ring devices monitoring heart rate, heart rate variability, skin temperature, sleep and physical activity from negative temperature coefficient, 3-D accelerometer and infrared photoplethysmography sensors. Weekly surveys assessed labor symptoms, pain, fatigue and mood. We estimated the association between each metric, gestational age, and the likelihood of a participant's labor beginning prior to (versus after) the clinical estimated delivery date (EDD) of 40.0 weeks with mixed effects regression. A boosted random forest was trained on the physiological metrics to predict pregnancies that naturally passed the EDD versus undergoing onset of labor prior to the EDD. Here we report that many raw sleep, activity, pain, fatigue and labor symptom metrics are correlated with gestational age. As gestational age advances, pregnant individuals have lower resting heart rate 0.357 beats/minute/week, 0.84 higher heart rate variability (milliseconds) and shorter durations of physical activity and sleep. Further, random forest predictions determine pregnancies that would pass the EDD with accuracy of 0.71 (area under the receiver operating curve). Self-reported symptoms of labor correlate with increased gestational age and not with the timing of labor (relative to EDD) or onset of spontaneous labor. The use of maternal smart ring-derived physiological data in the third-trimester may improve prediction of the natural duration of pregnancy relative to the EDD.
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Infants might be exposed to pain during their admissions in the neonatal intensive care unit [NICU], both from their underlying conditions and several invasive procedures required during their stay. Considering the particularities of this population, recognition and adequate management of pain continues to be a challenge for neonatologists and investigators. Diverse therapies are available for treatment, including non-pharmacological pain management measures and pharmacological agents (sucrose, opioids, midazolam, acetaminophen, topical agents ) and research continues. In recent years one of the most promising drugs for analgesia has been dexmedetomidine, an alpha-2 adrenergic receptor agonist. It has shown a promising efficacy and safety profile as it produces anxiolysis, sedation and analgesia without respiratory depression. Moreover, studies have shown a neuroprotective role in animal models which could be beneficial to neonatal population, especially in preterm newborns. Side effects of this therapy are mainly cardiovascular, but in most studies published, those were not severe and did not require specific therapeutic measures for their resolution. The main objective of this article is to summarize the existing literature on neonatal pain management strategies available and review the efficacy of dexmedetomidine as a new therapy with increasing use in the NICU.
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We present a robust insulin delivery system that includes automated meal detection and carbohydrate content estimation using machine learning for meal insulin dosing called robust artificial pancreas (RAP). We conducted a randomized, single-center crossover trial to compare postprandial glucose control in the four hours following unannounced meals using a hybrid model predictive control (MPC) algorithm and the RAP system. The RAP system includes a neural network model to automatically detect meals and deliver a recommended meal insulin dose. The meal detection algorithm has a sensitivity of 83.3%, false discovery rate of 16.6%, and mean detection time of 25.9 minutes. While there is no significant difference in incremental area under the curve of glucose, RAP significantly reduces time above range (glucose >180 mg/dL) by 10.8% (P = 0.04) and trends toward increasing time in range (70-180 mg/dL) by 9.1% compared with MPC. Time below range (glucose <70 mg/dL) is not significantly different between RAP and MPC.
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OBJECTIVE: Nocturnal hypoglycemia is a known challenge for people with type 1 diabetes, especially for physically active individuals or those on multiple daily injections. We developed an evidential neural network (ENN) to predict at bedtime the probability and timing of nocturnal hypoglycemia (0-4 vs 4-8 h after bedtime) based on several glucose metrics and physical activity patterns. We utilized these predictions in silico to prescribe bedtime carbohydrates with a Smart Snack intervention specific to the predicted minimum nocturnal glucose and timing of nocturnal hypoglycemia. MATERIALS AND METHODS: We leveraged free-living datasets collected from 366 individuals from the T1DEXI Study and Glooko. Inputs to the ENN used to model nocturnal hypoglycemia were derived from demographic information, continuous glucose monitoring, and physical activity data. We assessed the accuracy of the ENN using area under the receiver operating curve, and the clinical impact of the Smart Snack intervention through simulations. RESULTS: The ENN achieved an area under the receiver operating curve of 0.80 and 0.71 to predict nocturnal hypoglycemic events during 0-4 and 4-8 h after bedtime, respectively, outperforming all evaluated baseline methods. Use of the Smart Snack intervention reduced probability of nocturnal hypoglycemia from 23.9 ± 14.1% to 14.0 ± 13.3% and duration from 7.4 ± 7.0% to 2.4 ± 3.3% in silico. DISCUSSION: Our findings indicate that the ENN-based Smart Snack intervention has the potential to significantly reduce the frequency and duration of nocturnal hypoglycemic events. CONCLUSION: A decision support system that combines prediction of minimum nocturnal glucose and proactive recommendations for bedtime carbohydrate intake might effectively prevent nocturnal hypoglycemia and reduce the burden of glycemic self-management.
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Diabetes Mellitus Tipo 1 , Hipoglucemia , Humanos , Diabetes Mellitus Tipo 1/complicaciones , Diabetes Mellitus Tipo 1/tratamiento farmacológico , Bocadillos , Glucemia , Automonitorización de la Glucosa Sanguínea , Incertidumbre , Hipoglucemia/prevención & control , Hipoglucemiantes/uso terapéutico , InsulinaRESUMEN
BACKGROUND: Exercise can rapidly drop glucose in people with type 1 diabetes. Ubiquitous wearable fitness sensors are not integrated into automated insulin delivery (AID) systems. We hypothesised that an AID can automate insulin adjustments using real-time wearable fitness data to reduce hypoglycaemia during exercise and free-living conditions compared with an AID not automating use of fitness data. METHODS: Our study population comprised of individuals (aged 21-50 years) with type 1 diabetes from from the Harold Schnitzer Diabetes Health Center clinic at Oregon Health and Science University, OR, USA, who were enrolled into a 76 h single-centre, two-arm randomised (4-block randomisation), non-blinded crossover study to use (1) an AID that detects exercise, prompts the user, and shuts off insulin during exercise using an exercise-aware adaptive proportional derivative (exAPD) algorithm or (2) an AID that automates insulin adjustments using fitness data in real-time through an exercise-aware model predictive control (exMPC) algorithm. Both algorithms ran on iPancreas comprising commercial glucose sensors, insulin pumps, and smartwatches. Participants executed 1 week run-in on usual therapy followed by exAPD or exMPC for one 12 h primary in-clinic session involving meals, exercise, and activities of daily living, and 2 free-living out-patient days. Primary outcome was time below range (<3·9 mmol/L) during the primary in-clinic session. Secondary outcome measures included mean glucose and time in range (3·9-10 mmol/L). This trial is registered with ClinicalTrials.gov, NCT04771403. FINDINGS: Between April 13, 2021, and Oct 3, 2022, 27 participants (18 females) were enrolled into the study. There was no significant difference between exMPC (n=24) versus exAPD (n=22) in time below range (mean [SD] 1·3% [2·9] vs 2·5% [7·0]) or time in range (63·2% [23·9] vs 59·4% [23·1]) during the primary in-clinic session. In the 2 h period after start of in-clinic exercise, exMPC had significantly lower mean glucose (7·3 [1·6] vs 8·0 [1·7] mmol/L, p=0·023) and comparable time below range (1·4% [4·2] vs 4·9% [14·4]). Across the 76 h study, both algorithms achieved clinical time in range targets (71·2% [16] and 75·5% [11]) and time below range (1·0% [1·2] and 1·3% [2·2]), significantly lower than run-in period (2·4% [2·4], p=0·0004 vs exMPC; p=0·012 vs exAPD). No adverse events occurred. INTERPRETATION: AIDs can integrate exercise data from smartwatches to inform insulin dosing and limit hypoglycaemia while improving glucose outcomes. Future AID systems that integrate exercise metrics from wearable fitness sensors may help people living with type 1 diabetes exercise safely by limiting hypoglycaemia. FUNDING: JDRF Foundation and the Leona M and Harry B Helmsley Charitable Trust, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases.
Asunto(s)
Diabetes Mellitus Tipo 1 , Hipoglucemia , Dispositivos Electrónicos Vestibles , Femenino , Humanos , Actividades Cotidianas , Inteligencia Artificial , Estudios Cruzados , Diabetes Mellitus Tipo 1/tratamiento farmacológico , Glucosa/uso terapéutico , Gastos en Salud , Hipoglucemiantes/uso terapéutico , Insulina , Estados Unidos , MasculinoRESUMEN
A 61-year-old woman presented to the emergency ward complaining of low back pain for a month. She had undergone several spinal surgeries and a right radical nephrectomy 30 years before. A few days earlier she was injected with an intramuscular painkiller in her right buttock. An abdominal CT scan revealed multiple abscesses in the psoas muscle and the right posterior abdominal wall, including cellulitis in the adjacent subcutaneous tissue and the injection site. A diagnosis of pyomyositis from subcutaneous dissemination was made, and intravenous cefazolin was initiated. After five days of favorable progress, treatment was switched to oral cefadroxil to complete four weeks, leading to full recovery.