Incidencia de diabetes mellitus tipo 1 en niños: resultados del registro poblacional de la Comunidad de Madrid, 1997–2005

Torrás, Belén Zorrilla; Real, José Luis Cantero; Castellanos, Raquel Barrios; Fernández, Joaquín Ramírez; Oliver, José Luis Tejera; Vergaz, A. González

doi:10.1016/j.medcli.2008.05.020

Cited by 20 publications

(9 citation statements)

References 7 publications

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“…There was no consistency in previous works that analyzed it separately. In our study, IR presents an intermediate value with respect to other European countries and slightly higher than other Spanish regions. An increasing trend during the period of analysis can be observed, although it was not statistically significant.…”

Section: Discussioncontrasting

confidence: 54%

“…The 0–4‐year age group presented lower IR than 5–9 and 10–14‐year age groups. IR in boys was higher than in girls, although this result was not statistically significant . It was also observed that, in boys, the DM1 IR presented a clear geographical pattern, decreasing from north to south, with the highest smoothed SIRs in the north of the region.…”

Section: Discussionmentioning

confidence: 81%

“…An increasing trend during the period of analysis can be observed, although it was not statistically significant. In other studies, trends remain stable, as in the Autonomous Community of Madrid (Spain) for the period 1997–2005 as well as in other countries, mainly in northern Europe , but there are studies that show that the IR is increasing .…”

Section: Discussionmentioning

confidence: 96%

“…The highest rates are seen in Finland and Sardinia (Italy) with 40.0 and 37.8 cases/10 5 inhabitants, respectively, and the lowest in Venezuela and China with 0.1 cases/10 5 inhabitants . The IR varies even within the same country; thus, for example, in Spain, in the Castilla León region, the IR was 22.2/10 5 inhabitants in the period 2003–2004 , in Madrid, 15.9 cases/10 5 inhabitants in the period 1997–2005 , and in Catalonia, 14.4 cases/10 5 inhabitants during the period 1989–1998 .…”

mentioning

confidence: 98%

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Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009

Compés

Feja²,

Guzmán³

et al. 2012

Pediatr Diabetes

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Section: Discussioncontrasting

confidence: 54%

Section: Discussionmentioning

confidence: 81%

Section: Discussionmentioning

confidence: 96%

mentioning

confidence: 98%

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Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009

Compés

Feja²,

Guzmán³

et al. 2012

Pediatr Diabetes

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“…In Spain, we cannot conclude that this decrease in LEA rates among type 1 diabetic patients is associated with changes in the prevalence of type 1 diabetes. Zorrilla Torras et al (19) indicated that incidence data showed no significant changes during 1997–2005 for type 1 diabetes, and other studies (4,19) in Spain reach similar conclusions. We agree with Jonasson et al (20), who suggested that in Sweden the reduction in the risk of nontraumatic LEAs among patients with type 1 diabetes might be attributed to the introduction of a program for prevention and treatment of ulceration in patients with diabetes.…”

Section: Discussionmentioning

confidence: 65%

Trends in Lower-Extremity Amputations in People With and Without Diabetes in Spain, 2001–2008

et al. 2011

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OBJECTIVETo examine trends in nontraumatic lower-extremity amputations (LEAs) over an 8-year period in patients with and without diabetes in Spain.RESEARCH DESIGN AND METHODSWe identified all patients who underwent an LEA using national hospital discharge data. Discharges were grouped by diabetes status: type 1 diabetes, type 2 diabetes, and no diabetes. The incidence of discharges attributed to amputations were calculated overall and stratified by diabetes status and year. We calculated length of stay and in-hospital fatality stratified by diabetes status and type of LEA.RESULTSFrom 2001 to 2008, 46,536 minor LEAs and 43,528 major LEAs were performed. In patients with type 1 diabetes, the incidence of minor and major amputations decreased significantly from 2001 to 2008 (0.88–0.43 per 100,000 inhabitants and 0.59–0.22 per 100,000 inhabitants, respectively). In patients with type 2 diabetes, the incidence of minor and major LEAs increased significantly (9.23–10.9 per 100,000 inhabitants and 7.12–7.47 per 100,000 inhabitants). Hospital stay was similar among type 1 diabetic and type 2 diabetic subjects, according to the type of LEA. Only in-hospital mortality for minor LEAs among type 1 diabetic subjects decreased significantly (4.0% in 2001 vs. 1.6% in 2008).CONCLUSIONSOur national data show a decrease in the incidence of major and minor LEAs in patients with type 1 diabetes and an increase among patients with type 2 diabetes. Further improvement is necessary in the preventive care and early treatment of patients with diabetes. The management of foot lesions, especially among type 2 diabetic patients, is particularly urgent.

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Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol

et al. 2023

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Purpose Paediatric Type 1 Diabetes (T1D) patients are at greater risk for developing severe hypo and hyperglycaemic events due to poor glycaemic control. To reduce the risk of adverse events, patients need to achieve the best possible glycaemic management through frequent blood glucose monitoring with finger prick or Continuous Glucose Monitoring (CGM) systems. However, several non-invasive techniques have been proposed aiming at exploiting changes in physiological parameters based on glucose levels. The overall objective of this study is to validate an artificial intelligence (AI) based algorithm to detect glycaemic events using ECG signals collected through non-invasive device. Methods This study will enrol T1D paediatric participants who already use CGM. Participants will wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glycaemic measurements driven through ECG variables are the main outcomes. Data collected will be used to design, develop and validate the personalised and generalized classifiers based on a deep learning (DL) AI algorithm, able to automatically detect hypoglycaemic events by using few ECG heartbeats recorded with wearable devices. Results Data collection is expected to be completed approximately by June 2023. It is expected that sufficient data will be collected to develop and validate the AI algorithm. Conclusion This is a validation study that will perform additional tests on a larger diabetes sample population to validate the previous pilot results that were based on four healthy adults, providing evidence on the reliability of the AI algorithm in detecting glycaemic events in paediatric diabetic patients in free-living conditions. Trial registration ClinicalTrials.gov identifier: NCT03936634. Registered on 11 March 2022, retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT05278143?titles=AI+for+Glycemic+Events+Detection+Via+ECG+in+a+Pediatric+Population&draw=2&rank=1.

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Incidencia de diabetes mellitus tipo 1 en niños: resultados del registro poblacional de la Comunidad de Madrid, 1997–2005

Cited by 20 publications

References 7 publications

Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009

Bayesian analysis of the geographical variation of type 1 diabetes mellitus in under 15 yr olds in northeast Spain, 1991-2009

Trends in Lower-Extremity Amputations in People With and Without Diabetes in Spain, 2001–2008

Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol

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