Person:
Sánchez Luna, Manuel Ramón

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First Name
Manuel Ramón
Last Name
Sánchez Luna
URI
https://hdl.handle.net/20.500.14352/79227
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Medicina
Department
Salud Pública y Materno-Infantil
Area
Pediatría
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2020 - 20222
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Author: Gutiérrez Vélez, Ana ×

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    Lung recruitment in neonatal high‐frequency oscillatory ventilation with volume‐guarantee
    (Pediatric Pulmonology, 2022) Solís García, Gonzalo; González Pacheco, Noelia; Ramos Navarro, Cristina; Vigil Vázquez, Sara; Gutiérrez Vélez, Ana; Merino Hernández, Amaia; Rodríguez Sánchez De la Blanca, Ana; Sánchez Luna, Manuel Ramón
    Background and objectives: The optimal lung volume strategy during high-frequency oscillatory ventilation (HFOV) is reached by performing recruitment maneuvers, usually guided by the response in oxygenation. In animal models, secondary spontaneous change in oscillation pressure amplitude (ΔPhf) associated with a progressive increase in mean airway pressure during HFOV combined with volume guarantee (HFOV-VG) identifies optimal lung recruitment. The aim of this study was to describe recruitment maneuvers in HFOV-VG and analyze whether changes in ΔPhf might be an early predictor for lung recruitment in newborn infants with severe respiratory failure. Design and methods: The prospective observational study was done in a tertiary-level neonatology department. Changes in ΔPhf were analyzed during standardized lung recruitment after initiating early rescue HFOV-VG in preterm infants with severe respiratory failure. Results: Twenty-seven patients were included, with a median gestational age of 24 weeks (interquartile range [IQR]: 23-25). Recruitment maneuvers were performed, median baseline mean airway pressure (mPaw) was 11 cm H2 O (IQR: 10-13), median critical lung opening mPaw during recruitment was 14 cm H2 O (IRQ: 12-16), and median optimal mPaw was 12 cm H2 O (IQR: 10-14, p < 0.01). Recruitment maneuvers were associated with an improvement in oxygenation (FiO2 : 65.0 vs. 45.0, p < 0.01, SpO2/FiO2 ratio: 117 vs. 217, p < 0.01). ΔPhf decreased significantly after lung recruitment (mean amplitude: 23.0 vs. 16.0, p < 0.01). Conclusion: In preterm infants with severe respiratory failure, the lung recruitment process can be effectively guided by ΔPhf on HFOV-VG.
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    Longitudinal Analysis of Continuous Pulse Oximetry as Prognostic Factor in Neonatal Respiratory Distress
    (American Journal of Perinatology, 2020) Solís García, Gonzalo; Maderuelo Rodríguez, Elena; Pérez Pérez, Teresa; Torres Soblechero, Laura; Gutiérrez Vélez, Ana; Ramos Navarro, Cristina; López Martínez, Raúl; Sánchez Luna, Manuel Ramón
    Objective: Analysis of longitudinal data can provide neonatologists with tools that can help predict clinical deterioration and improve outcomes. The aim of this study is to analyze continuous monitoring data in newborns, using vital signs to develop predictive models for intensive care admission and time to discharge. Study design: We conducted a retrospective cohort study, including term and preterm newborns with respiratory distress patients admitted to the neonatal ward. Clinical and epidemiological data, as well as mean heart rate and saturation, at every minute for the first 12 hours of admission were collected. Multivariate mixed, survival and joint models were developed. Results: A total of 56,377 heart rate and 56,412 oxygen saturation data were analyzed from 80 admitted patients. Of them, 73 were discharged home and 7 required transfer to the intensive care unit (ICU). Longitudinal evolution of heart rate (p < 0.01) and oxygen saturation (p = 0.01) were associated with time to discharge, as well as birth weight (p < 0.01) and type of delivery (p < 0.01). Longitudinal heart rate evolution (p < 0.01) and fraction of inspired oxygen at admission at the ward (p < 0.01) predicted neonatal ICU (NICU) admission. Conclusion: Longitudinal evolution of heart rate can help predict time to transfer to intensive care, and both heart rate and oxygen saturation can help predict time to discharge. Analysis of continuous monitoring data in patients admitted to neonatal wards provides useful tools to stratify risks and helps in taking medical decisions. Key points: · Continuous monitoring of vital signs can help predict and prevent clinical deterioration in neonatal patients.. · In our study, longitudinal analysis of heart rate and oxygen saturation predicted time to discharge and intensive care admission.. · More studies are needed to prospectively prove that these models can helpmake clinical decisions and stratify patients' risks..