Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset

[EN] Objective: The lack of representative coronavirus disease 2019 (COVID-19) data is a bottleneck for reliable and generalizable machine learning. Data sharing is insufficient without data quality, in which source variability plays an important role. We showcase and discuss potential biases from data source variability for COVID-19 machine learning. Materials and Methods: We used the publicly available nCov2019 dataset, including patient-level data from several countries. We aimed to the discovery and classification of severity subgroups using symptoms and comorbidities. Results: Cases from the 2 countries with the highest prevalence were divided into separate subgroups with distinct severity manifestations. This variability can reduce the representativeness of training data with respect the model target populations and increase model complexity at risk of overfitting. Conclusions: Data source variability is a potential contributor to bias in distributed research networks. We call for systematic assessment and reporting of data source variability and data quality in COVID-19 data sharing, as key information for reliable and generalizable machine learning.This work was supported by Universitat Politecnica de Valencia contract no. UPV-SUB.2-1302 and FONDO SUPERA COVID-19 by CRUE-Santander Bank grant "Severity Subgroup Discovery and Classification on COVID-19 Real World Data through Machine Learning and Data Quality assessment (SUBCOVERWD-19)."Sáez Silvestre, C.; Romero, N.; Conejero, JA.; Garcia-Gomez, JM. (2021). Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset. Journal of the American Medical Informatics Association. 28(2):360-364. https://doi.org/10.1093/jamia/ocaa25836036428

Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique

[EN] Background: The COVID-19 pandemic has led to an unprecedented global health care challenge for both medical institutions and researchers. Recognizing different COVID-19 subphenotypes-the division of populations of patients into more meaningful subgroups driven by clinical features-and their severity characterization may assist clinicians during the clinical course, the vaccination process, research efforts, the surveillance system, and the allocation of limited resources. Objective: We aimed to discover age-sex unbiased COVID-19 patient subphenotypes based on easily available phenotypical data before admission, such as pre-existing comorbidities, lifestyle habits, and demographic features, to study the potential early severity stratification capabilities of the discovered subgroups through characterizing their severity patterns, including prognostic, intensive care unit (ICU), and morbimortality outcomes. Methods: We used the Mexican Government COVID-19 open data, including 778,692 SARS-CoV-2 population-based patient-level data as of September 2020. We applied a meta-clustering technique that consists of a 2-stage clustering approach combining dimensionality reduction (ie, principal components analysis and multiple correspondence analysis) and hierarchical clustering using the Ward minimum variance method with Euclidean squared distance. Results: In the independent age-sex clustering analyses, 56 clusters supported 11 clinically distinguishable meta-clusters (MCs). MCs 1-3 showed high recovery rates (90.27%-95.22%), including healthy patients of all ages, children with comorbidities and priority in receiving medical resources (ie, higher rates of hospitalization, intubation, and ICU admission) compared with other adult subgroups that have similar conditions, and young obese smokers. MCs 4-5 showed moderate recovery rates (81.30%-82.81%), including patients with hypertension or diabetes of all ages and obese patients with pneumonia, hypertension, and diabetes. MCs 6-11 showed low recovery rates (53.96%-66.94%), including immunosuppressed patients with high comorbidity rates, patients with chronic kidney disease with a poor survival length and probability of recovery, older smokers with chronic obstructive pulmonary disease, older adults with severe diabetes and hypertension, and the oldest obese smokers with chronic obstructive pulmonary disease and mild cardiovascular disease. Group outcomes conformed to the recent literature on dedicated age-sex groups. Mexican states and several types of clinical institutions showed relevant heterogeneity regarding severity, potentially linked to socioeconomic or health inequalities. Conclusions: The proposed 2-stage cluster analysis methodology produced a discriminative characterization of the sample and explainability over age and sex. These results can potentially help in understanding the clinical patient and their stratification for automated early triage before further tests and laboratory results are available and even in locations where additional tests are not available or to help decide resource allocation among vulnerable subgroups such as to prioritize vaccination or treatments.We sincerely thank the different types of clinical institutions and the Mexican government, which made a huge effort to make these data publicly available. We also thank the clinicians and epidemiologists from the Servicios de Salud de Nayarit for the useful discussions on specific aspects of the medical attention to hospitalized patients and the reporting of epidemiological data processes related to COVID-19. Furthermore, we would also like to thank Francisco Tomas Garcia Ruiz for his valuable help in data visualization design. This work was supported by Universitat Politecnica de Valencia contract no. UPV-SUB.2-1302 and FONDO SUPERA COVID-19 by CRUE-Santander Bank grant: "Severity Subgroup Discovery and Classification on COVID-19 Real World Data through Machine Learning and Data Quality assessment (SUBCOVERWD-19) ." The authors thank the Institute for Information and Communication Technologies (ITACA) at the Universitat Politecnica de Valencia for its support in the publication of this manuscript.Zhou, L.; Romero-Garcia, N.; Martínez-Miranda, J.; Conejero, JA.; Garcia-Gomez, JM.; Sáez Silvestre, C. (2022). Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique. JMIR Public Health and Surveillance. 8(3):1-21. https://doi.org/10.2196/300321218

Integration of a Canine Agent in a Wireless Sensor Network for Information Gathering in Search and Rescue Missions

Search and rescue operations in the context of emergency response to human or natural disasters have the major goal of finding potential victims in the shortest possible time. Multi-agent teams, which can include specialized human respondents, robots and canine units, complement the strengths and weaknesses of each agent, like all-terrain mobility or capability to locate human beings. However, efficient coordination of heterogeneous agents requires specific means to locate the agents, and to provide them with the information they require to complete their mission. The major contribution of this work is an application of Wireless Sensor Networks (WSN) to gather information from a multi-agent team and to make it available to the rest of the agents while keeping coverage. In particular, a canine agent has been equipped with a mobile node installed on a harness, providing information about the dog’s location as well as gas levels. The configuration of the mobile node allows for flexible arrangement of the system, being able to integrate static as well as mobile nodes. The gathered information is available at an external database, so that the rest of the agents and the control center can use it in real time. The proposed scheme has been tested in realistic scenarios during search and rescue exercises

Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years

[EN] Objective To evaluate the effects of Process-Reengineering interventions on the Electronic Health Records (EHR) of a hospital over 7 years. Materials and methods Temporal Variability Assessment (TVA) based on probabilistic data quality assessment was applied to the historic monthly-batched admission data of Hospital La Fe Valencia, Spain from 2010 to 2016. Routine healthcare data with a complete EHR was expanded by processed variables such as the Charlson Comorbidity Index. Results Four Process-Reengineering interventions were detected by quantifiable effects on the EHR: (1) the hospital relocation in 2011 involved progressive reduction of admissions during the next four months, (2) the hospital services re-configuration incremented the number of inter-services transfers, (3) the care-services re-distribution led to transfers between facilities (4) the assignment to the hospital of a new area with 80,000 patients in 2015 inspired the discharge to home for follow up and the update of the pre-surgery planned admissions protocol that produced a significant decrease of the patient length of stay. Discussion TVA provides an indicator of the effect of process re-engineering interventions on healthcare practice. Evaluating the effect of facilities¿ relocation and increment of citizens (findings 1, 3¿4), the impact of strategies (findings 2¿3), and gradual changes in protocols (finding 4) may help on the hospital management by optimizing interventions based on their effect on EHRs or on data reuse. Conclusions The effects on hospitals EHR due to process re-engineering interventions can be evaluated using the TVA methodology. Being aware of conditioned variations in EHR is of the utmost importance for the reliable reuse of routine hospitalization data.F.J.P.B, C.S., J.M.G.G. and J.A.C. were funded Universitat Politecnica de Valencia, project "ANALISIS DE LA CALIDAD Y VARIABILIDAD DE DATOS MEDICOS". www.upv.es. J.M.G.G.is also partially supported by: Ministerio de Economia y Competitividad of Spain through MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R); and European Commission projects H2020-SC1-2016-CNECT Project (No. 727560) and H2020-SC1-BHC-2018-2020 (No. 825750). The funders did not play any role in the study design, data collection and analysis, decision to publish, nor preparation of the manuscript.Perez-Benito, FJ.; Sáez Silvestre, C.; Conejero, JA.; Tortajada, S.; Valdivieso, B.; Garcia-Gomez, JM. (2019). Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years. PLoS ONE. 14(8):1-19. https://doi.org/10.1371/journal.pone.0220369S119148Aguilar-Savén, R. S. (2004). Business process modelling: Review and framework. International Journal of Production Economics, 90(2), 129-149. doi:10.1016/s0925-5273(03)00102-6Poulymenopoulou, M. 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Cancer Reporting: Timeliness Analysis and Process. 2016; Available: https://search.proquest.com/openview/4ecf737c5ef6d2d503e948df8031fe54/1?pq-origsite=gscholar&cbl=18750&diss=yHewitt M, Simone J V. Enhancing Data Systems to Improve the Quality of Cancer Care [Internet]. National Academy Press; 2000. Available: http://www.nap.edu/catalog/9970.htmlWeiskopf, N. G., & Weng, C. (2013). Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. Journal of the American Medical Informatics Association, 20(1), 144-151. doi:10.1136/amiajnl-2011-000681Saez C, Robles M, Garcia-Gomez JM. Comparative study of probability distribution distances to define a metric for the stability of multi-source biomedical research data. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. IEEE; 2013. pp. 3226–3229. doi: https://doi.org/10.1109/EMBC.2013.6610228Sáez, C., Rodrigues, P. P., Gama, J., Robles, M., & García-Gómez, J. M. (2014). Probabilistic change detection and visualization methods for the assessment of temporal stability in biomedical data quality. Data Mining and Knowledge Discovery, 29(4), 950-975. doi:10.1007/s10618-014-0378-6Sáez, C., Zurriaga, O., Pérez-Panadés, J., Melchor, I., Robles, M., & García-Gómez, J. M. (2016). Applying probabilistic temporal and multisite data quality control methods to a public health mortality registry in Spain: a systematic approach to quality control of repositories. Journal of the American Medical Informatics Association, 23(6), 1085-1095. doi:10.1093/jamia/ocw010International Ethical Guidelines for Epidemiological Studies [Internet]. Geneva: Council for International Organizations of Medical Sciences (CIOMS) in collaboration with the World Health Organization; 2009. 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Available: http://books.google.fr/books?id=VWq5GG6ycxMC&printsec=frontcover&dq=intitle:Elements+of+Information+Theory&hl=&cd=1&source=gbs_api%5Cnpapers2://publication/uuid/BAF426F8-5A4F-44A4-8333-FA8187160D9BBrandes, U., & Pich, C. (s. f.). Eigensolver Methods for Progressive Multidimensional Scaling of Large Data. Lecture Notes in Computer Science, 42-53. doi:10.1007/978-3-540-70904-6_6Liaw, S. T., Rahimi, A., Ray, P., Taggart, J., Dennis, S., de Lusignan, S., … Talaei-Khoei, A. (2013). Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature. International Journal of Medical Informatics, 82(1), 10-24. doi:10.1016/j.ijmedinf.2012.10.001Arts, D. G. T. (2002). Defining and Improving Data Quality in Medical Registries: A Literature Review, Case Study, and Generic Framework. Journal of the American Medical Informatics Association, 9(6), 600-611. doi:10.1197/jamia.m1087Bray, F., & Parkin, D. M. (2009). 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Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects

[EN] Quality of life (QoL) indicators are now being adopted as clinical outcomes in clinical trials on cancer treatments. Technology-free daily monitoring of patients is complicated, time-consuming and expensive due to the need for vast amounts of resources and personnel. The alternative method of using the patients¿ own phones could reduce the burden of continuous monitoring of cancer patients in clinical trials. This paper proposes monitoring the patients¿ QoL by gathering data from their own phones. We considered that the continuous multiparametric acquisition of movement, location, phone calls, conversations and data use could be employed to simultaneously monitor their physical, psychological, social and environmental aspects. An open access phone app was developed (Human Dynamics Reporting Service (HDRS)) to implement this approach. We here propose a novel mapping between the standardized QoL items for these patients, the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and define HDRS monitoring indicators. A pilot study with university volunteers verified the plausibility of detecting human activity indicators directly related to QoL.Funding for this study was provided by the authors' various departments, and partially by the CrowdHealth Project (Collective Wisdom Driving Public Health Policies (727560)) and the MTS4up project (DPI2016-80054-R).Asensio Cuesta, S.; Sánchez-García, Á.; Conejero, JA.; Sáez Silvestre, C.; Rivero-Rodriguez, A.; Garcia-Gomez, JM. (2019). Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects. International Journal of Environmental research and Public Health. 16(3):1-18. https://doi.org/10.3390/ijerph16030461S118163Number of Smartphone Users Worldwide from 2014 to 2020 (in Billions)https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/Mirkovic, J., Kaufman, D. R., & Ruland, C. M. (2014). Supporting Cancer Patients in Illness Management: Usability Evaluation of a Mobile App. JMIR mHealth and uHealth, 2(3), e33. doi:10.2196/mhealth.3359Xing Su, Hanghang Tong, & Ping Ji. (2014). Activity recognition with smartphone sensors. Tsinghua Science and Technology, 19(3), 235-249. doi:10.1109/tst.2014.6838194Schmitz Weiss, A. (2013). Exploring News Apps and Location-Based Services on the Smartphone. Journalism & Mass Communication Quarterly, 90(3), 435-456. doi:10.1177/1077699013493788Higgins, J. P. (2016). Smartphone Applications for Patients’ Health and Fitness. The American Journal of Medicine, 129(1), 11-19. doi:10.1016/j.amjmed.2015.05.038Rivenson, Y., Ceylan Koydemir, H., Wang, H., Wei, Z., Ren, Z., Günaydın, H., … Ozcan, A. (2018). Deep Learning Enhanced Mobile-Phone Microscopy. ACS Photonics, 5(6), 2354-2364. doi:10.1021/acsphotonics.8b00146Priye, A., Ball, C. S., & Meagher, R. J. (2018). Colorimetric-Luminance Readout for Quantitative Analysis of Fluorescence Signals with a Smartphone CMOS Sensor. Analytical Chemistry, 90(21), 12385-12389. doi:10.1021/acs.analchem.8b03521Measuring Quality of Life for Cancer Patients: Where Are We Today and Where Are We Headed Tomorrow?http://blog.mdsol.com/measuring-quality-of-life-for-cancer-patients-where-are-we-today-and-where-are-we-headed-tomorrow/Zulueta, J., Piscitello, A., Rasic, M., Easter, R., Babu, P., Langenecker, S. A., … Leow, A. (2018). Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study. Journal of Medical Internet Research, 20(7), e241. doi:10.2196/jmir.9775Caruso, R., GiuliaNanni, M., Riba, M. B., Sabato, S., & Grassi, L. (2017). Depressive Spectrum Disorders in Cancer: Diagnostic Issues and Intervention. A Critical Review. Current Psychiatry Reports, 19(6). doi:10.1007/s11920-017-0785-7THE WHOQOL GROUP. (1998). Development of the World Health Organization WHOQOL-BREF Quality of Life Assessment. Psychological Medicine, 28(3), 551-558. doi:10.1017/s0033291798006667Basic Issues Concerning Health-Related Quality of Life. (2017). Central European Journal of Urology, 70(2). doi:10.5173/ceju.2017.923Sloan, J. A. (2011). Metrics to Assess Quality of Life After Management of Early-Stage Lung Cancer. The Cancer Journal, 17(1), 63-67. doi:10.1097/ppo.0b013e31820e15dcBordoni, R., Ciardiello, F., von Pawel, J., Cortinovis, D., Karagiannis, T., Ballinger, M., … Rittmeyer, A. (2018). Patient-Reported Outcomes in OAK: A Phase III Study of Atezolizumab Versus Docetaxel in Advanced Non–Small-cell Lung Cancer. Clinical Lung Cancer, 19(5), 441-449.e4. doi:10.1016/j.cllc.2018.05.011Hartkopf, A. D., Graf, J., Simoes, E., Keilmann, L., Sickenberger, N., Gass, P., … Wallwiener, M. (2017). Electronic-Based Patient-Reported Outcomes: Willingness, Needs, and Barriers in Adjuvant and Metastatic Breast Cancer Patients. JMIR Cancer, 3(2), e11. doi:10.2196/cancer.6996Wallwiener, M., Matthies, L., Simoes, E., Keilmann, L., Hartkopf, A. D., Sokolov, A. N., … Brucker, S. Y. (2017). Reliability of an e-PRO Tool of EORTC QLQ-C30 for Measurement of Health-Related Quality of Life in Patients With Breast Cancer: Prospective Randomized Trial. Journal of Medical Internet Research, 19(9), e322. doi:10.2196/jmir.8210Gresham, G., Hendifar, A. E., Spiegel, B., Neeman, E., Tuli, R., Rimel, B. J., … Shinde, A. M. (2018). Wearable activity monitors to assess performance status and predict clinical outcomes in advanced cancer patients. npj Digital Medicine, 1(1). doi:10.1038/s41746-018-0032-6BOHANNON, R. W. (1997). Comfortable and maximum walking speed of adults aged 20—79 years: reference values and determinants. Age and Ageing, 26(1), 15-19. doi:10.1093/ageing/26.1.15Pérez-García, V. M., Fitzpatrick, S., Pérez-Romasanta, L. A., Pesic, M., Schucht, P., Arana, E., & Sánchez-Gómez, P. (2016). Applied mathematics and nonlinear sciences in the war on cancer. Applied Mathematics and Nonlinear Sciences, 1(2), 423-436. doi:10.21042/amns.2016.2.00036Shin, W., Song, S., Jung, S.-Y., Lee, E., Kim, Z., Moon, H.-G., … Lee, J. E. (2017). The association between physical activity and health-related quality of life among breast cancer survivors. Health and Quality of Life Outcomes, 15(1). doi:10.1186/s12955-017-0706-9Wearable Fitness Monitors Useful in Cancer Treatment, Study Findswww.sciencedaily.com/releases/2018/05/180501130856.htmBade, B. C., Brooks, M. C., Nietert, S. B., Ulmer, A., Thomas, D. D., Nietert, P. J., … Silvestri, G. A. (2016). Assessing the Correlation Between Physical Activity and Quality of Life in Advanced Lung Cancer. Integrative Cancer Therapies, 17(1), 73-79. doi:10.1177/1534735416684016Fortner, B. V., Stepanski, E. J., Wang, S. C., Kasprowicz, S., & Durrence, H. H. (2002). Sleep and Quality of Life in Breast Cancer Patients. Journal of Pain and Symptom Management, 24(5), 471-480. doi:10.1016/s0885-3924(02)00500-6Mishra, S. I., Scherer, R. W., Snyder, C., Geigle, P., & Gotay, C. (2014). Are Exercise Programs Effective for Improving Health-Related Quality of Life Among Cancer Survivors? A Systematic Review and Meta-Analysis. 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Cantabrian capercaillie through time: a further comment

In a recent note published in this journal (Rubiales et al. 2009) we discuss the role the long-term environmental history of the Cantabrian Mountains may have played in the dynamics of the Cantabrian capercaillie Tetrao urogallus cantabricus, the only subspecies of capercaillie at risk of extinction worldwide. Three key conclusions, in the light of the available palaeoecological data were that: 1) the vegetation occurring within the range of the Cantabrian capercaillie has heavily changed during the last three millennia, due primarily to anthropogenic activity; 2) the extensive distribution of pinewoods until the historical period is coherent with the pattern of association of capercaillie and conifers occurring in the rest of its range; and 3) in the light of the distinct current patterns of decline and persistence of the capercaillie, it could be expected that the demise of pinewoods (becoming locally extinct at the western part of the Cantabrian mountains) would have had implications in the capercaillie persistence in the long ter

Major Adverse Cardiovascular Events in Coronary Type 2 Diabetic Patients: Identification of Associated Factors Using Electronic Health Records and Natural Language Processing

Diabetes mellitus; Natural language processing; Risk factorsDiabetis mellitus; Processament del llenguatge natural; Factors de riscDiabetes mellitus; Procesamiento del lenguaje natural; Factores de riesgoPatients with Type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) are at high risk of developing major adverse cardiovascular events (MACE). This is a multicenter, retrospective, and observational study performed in Spain aimed to characterize these patients in a real-world setting. Unstructured data from the Electronic Health Records were extracted by EHRead®, a technology based on Natural Language Processing and machine learning. The association between new MACE and the variables of interest were investigated by univariable and multivariable analyses. From a source population of 2,184,662 patients, we identified 4072 adults diagnosed with T2DM and CAD (62.2% male, mean age 70 ± 11). The main comorbidities observed included arterial hypertension, hyperlipidemia, and obesity, with metformin and statins being the treatments most frequently prescribed. MACE development was associated with multivessel (Hazard Ratio (HR) = 2.49) and single coronary vessel disease (HR = 1.71), transient ischemic attack (HR = 2.01), heart failure (HR = 1.32), insulin treatment (HR = 1.40), and percutaneous coronary intervention (PCI) (HR = 2.27), whilst statins (HR = 0.73) were associated with a lower risk of MACE occurrence. In conclusion, we found six risk factors associated with the development of MACE which were related with cardiovascular diseases and T2DM severity, and treatment with statins was identified as a protective factor for new MACE in this study.This study was funded by AstraZeneca Spain (Externally Sponsored Scientific Research, ESR-18-13815) and sponsored by the Spanish Society of Cardiology

Star Formation Under the Outflow: The Discovery of a Non-Thermal Jet from OMC-2 FIR 3 and its Relationship to the Deeply Embedded FIR 4 Protostar

We carried out multiwavelength (0.7-5 cm), multiepoch (1994-2015) Very Large Array (VLA) observations toward the region enclosing the bright far-IR sources FIR 3 (HOPS 370) and FIR 4 (HOPS 108) in OMC-2. We report the detection of 10 radio sources, seven of them identified as young stellar objects. We image a well-collimated radio jet with a thermal free-free core (VLA 11) associated with the Class I intermediate-mass protostar HOPS 370. The jet presents several knots (VLA 12N, 12C, 12S) of non-thermal radio emission (likely synchrotron from shock-accelerated relativistic electrons) at distances of ~7,500-12,500 au from the protostar, in a region where other shock tracers have been previously identified. These knots are moving away from the HOPS 370 protostar at ~ 100 km/s. The Class 0 protostar HOPS 108, which itself is detected as an independent, kinematically decoupled radio source, falls in the path of these non-thermal radio knots. These results favor the previously proposed scenario where the formation of HOPS 108 has been triggered by the impact of the HOPS 370 outflow with a dense clump. However, HOPS 108 presents a large proper motion velocity of ~ 30 km/s, similar to that of other runaway stars in Orion, whose origin would be puzzling within this scenario. Alternatively, an apparent proper motion could result because of changes in the position of the centroid of the source due to blending with nearby extended emission, variations in the source shape, and /or opacity effects.Comment: 16 pages, 4 figures, accepted for publication in The Astrophysical Journa

Influencia del aporte proteico parenteral en las alteraciones electrolíticas en recién nacidos prematuros

Recién nacidos prematuros; Hipercalcemia; Hipofosfatemiapreterm infants; Hypercalcaemia; HypophosphataemiaNounats prematurs; Hipercalcèmia; HipofosfatèmiaIntroduction Aggressive parenteral nutrition with delivery of high amino acid and energy doses is used to improve growth and neurodevelopmental outcomes in very low birth weight (VLBW) preterm infants. Recent findings, however, suggest that this approach may cause electrolyte imbalances. The aim of our study was to compare the prevalence of hypercalcaemia, hypophosphataemia, and hypokalaemia in 2 groups of preterm infants that received parenteral nutrition with different amounts of amino acids and to analyse perinatal and nutritional variables associated with the development of electrolyte imbalances. Methods We conducted a retrospective observational study comparing 2 groups of preterm infants born before 33 weeks’ gestation with birth weights of less than 1500 g managed with parenteral nutrition. One of the groups received less than 3 g/kg/day of amino acids and the other received 3 g/kg//day of amino acids or more. We analysed the prevalence of electrolyte imbalances and possible associations with aggressive parenteral nutrition, adjusting for potential confounders. Results We studied 114 infants: 60 given less than 3 g/kg/day of amino acids (low-intake group) and 54 given at least 3 g/kg/day (high-intake group). The prevalence of electrolyte imbalances was similar in both groups. The prevalence of hypercalcaemia was 1.67% in the low-intake group and 1.85% in the high-intake group (P > .99), the prevalence of severe hypophosphataemia 11.7% vs 9.3%, and the prevalence of hypokalaemia 15.0% vs 11.1% (P > .99). A calcium to phosphorus ratio greater than 1.05 had a protective effect against hypophosphataemia (P = .007). Conclusions We did not find an association between hypercalcaemia, hypophosphataemia, and hypokalaemia and the amino acid dose delivered by PN in the high-intake group of preterm infants.Introducción La nutrición parenteral agresiva con aportes energéticos y proteicos altos se utiliza para mejorar el crecimiento y el neurodesarrollo en recién nacidos prematuros de muy bajo peso. No obstante, hallazgos recientes sugieren que su uso puede ocasionar alteraciones electrolíticas. El objetivo del estudio era comparar la prevalencia de hipercalcemia, hipofosfatemia e hipopotasemia en dos grupos de recién nacidos prematuros que recibieron nutrición parenteral con distintos aportes de aminoácidos, y analizar variables perinatales y nutricionales asociadas a la ocurrencia de alteraciones electrolíticas. Métodos Estudio retrospectivo observacional, con comparación de 2 grupos de recién nacidos prematuros con peso < 1500 g y edad gestacional < 33 semanas manejados con nutrición parenteral. Uno de los grupos recibió < 3 g/kg/d de aminoácidos mientras que el otro recibió ≥3 g/kg/d. Se analizó la prevalencia de distintas alteraciones electrolíticas y su asociación con la nutrición parenteral agresiva, con ajustes para posibles factores de confusión. Resultados El análisis incluyó 114 recién nacidos: 60 que recibieron   0,99). Los respectivos valores para las otras alteraciones fueron 11,7% vs. 9,3% en el caso de la hipofosfatemia grave y 15,0% vs. 11,1% en el caso de la hipopotasemia (p >  0,99). Se observó que una relación calcio:fósforo superior a 1,05 ofrecía un efecto protector frente a la hipofosfatemia (p = 0,007). Conclusiones No se observó asociación entre la hipercalcemia, hipofosfatemia o la hipopotasemia y el aporte de aminoácidos mediante nutrición parenteral en la población de recién nacidos prematuros con ingestas altas de aminoácidos

La tecnología que aprende a elegir tu talla de calzado

Ballester Fernandez, A.; Gil Mora, S.; Valero, J.; Gonzalez Garcia, JC.; Remon Gomez, A. (2019). La tecnología que aprende a elegir tu talla de calzado. Innovación biomecánica en Europa. (8):1-3. http://hdl.handle.net/10251/167979S13