Adverse Events and Associated Factors During Intrahospital Transport of Newborn Infants

Delacrétaz, Romaine; Fumeaux, Céline J. Fischer; Stadelmann, Corinne; Trejo, Adriana Rodriguez; Destaillats, Alice; Giannoni, Éric

doi:10.1016/j.jpeds.2021.08.074

Cited by 16 publications

(8 citation statements)

References 34 publications

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“…To compare neonatal transport outcomes, we selected several previously published quality metrics; dislodgement of therapeutic devices, temperature control, hypoglycemia, and hypothermia (15-18). In our study, NS and NNS teams were noted to have a difference in total unintended clinical and endotracheal tube events.…”

Section: Discussionmentioning

confidence: 99%

Unintended events in long-distance neonatal interhospital transport in Western Australia: A comparison of neonatal specialist and non-neonatal specialist transport teams

Gardiner,

McDonald,

Blacker

et al. 2023

Preprint

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ObjectiveTo compare unintended events in transport performed by neonatal specialist (NS) and non-neonatal specialist (NNS) teams in Western Australia (WA).Study design: Retrospective comparison of neonatal transports from the Kimberley and Pilbara regions (WA) to tertiary services, King Edward Memorial (perinatal) and Perth Children’s Hospital NICU, in Perth (state capital, distance up to 2200km) between January 2018 - June 2021. NS teams travelled from the tertiary to the referring center and back. NNS travelled from the referring to the tertiary center. Transport time, team composition, total unintended clinical, endotracheal tube (ETT), and logistic events were compared. Categorial data are expressed as numbers (%) and compared by chi-squared test; continuous data are expressed as median (interquartile range) and compared by Mann-Whitney U test.ResultsDuring the study period, 3,709 infants were transported in WA to tertiary services for escalation of care: 119(3.2%) from the Kimberley and Pilbara, 49 with NS and 70 with NNS teams. NNS had shorter transport times than NS teams (508(435 – 609) vs 871(615 – 735) min; p<0.00001). Neonatal nurses were on NS more than NNS teams (36/49(73.5%) vs 6/70(9%); p<0.001). Total unintended clinical and ETT events were less in NS vs. NSS teams (28/49(57%) vs. 54/70(77%); p=0.02) and (0/26(0%) vs. 7/23(30%); p=0.004). Unintended logistic events were greater involving NS than NNS teams (31/49 (63%) vs. 33/70 (47%); p=0.05).ConclusionAlthough NS teams had longer transport times and more unintended logistic events, there were fewer unintended clinical and ETT events. NS teams should be considered as the first choice to undertake neonatal transport.

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Section: Discussionmentioning

confidence: 99%

Unintended events in long-distance neonatal interhospital transport in Western Australia: A comparison of neonatal specialist and non-neonatal specialist transport teams

Gardiner,

McDonald,

Blacker

et al. 2023

Preprint

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“…The minimum sample size was calculated using an unpaired categorical groups sample size formula. 7 The sample size was calculated using the following formula: A total of 30 samples were obtained. The subjects were selected based on total sampling.…”

Section: Methodsmentioning

confidence: 99%

Analysis of the Relationship between Neonatal Risk Factors and Adverse Events in the Transfer of Operational Patients to the Neonatology Unit at RSCM

Tamba,

Rinaldy,

Putra

2024

Preprint

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Introduction: Transport of neonates from the neonatology unit to the operating room and vice versa carries a high risk of adverse events (KTD). However, there have been no detailed studies studying this. This study aims to determine the risk factors that play a role in the occurrence of adverse events during perioperative transfer of neonates. Methods: We conducted a retrospective cohort study at RSUPN dr. Cipto Mangunkusumo. Neonates who met the inclusion criteria and the exclusion criteria were included in this study. Risk factors and adverse event profiles were collected from the study subjects. Analysis was carried out using univariate, bivariate and multivariate analyses. This study was approved by RSUPN dr. Cipto Mangunkusumo. Results: A total of 87 adverse events were recorded in the 56 neonates who were subjects in this study. Fifty one point seventy nine percent of the subjects were female, 48.21% of the subjects were premature, 58.93% had low birth weight, with an average birth weight of 2,138 grams. The most common adverse event features were desaturation, covering 71.43% of the study subjects. There is a significant association between invasive respiratory support and hypothermia (OR = 0.052; 95% CI = 0.005 – 0.506). There is a significant association between invasive respiratory support and medical device adverse events (OR = 0.175; 95% CI = 0.043 – 0.707). Invasive respiratory support is the factor that plays the most role in medical device adverse events based on multivariate analysis (aOR = 0.023; 95% CI = 0.054–0.995). Conclusion: Prematurity, LBW, and congenital abnormalities were not associated with adverse events. Meanwhile, the use of invasive respiratory support is associated with hypothermia and medical device adverse events in neonatology unit surgery transfer patients.

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“…The data have been further analyzed and interpreted in the article “Adverse events and associated factors during intra-hospital transport of newborn infants” [1] .…”

Section: Data Descriptionmentioning

confidence: 99%

Intra-hospital transport of newborn infants dataset

et al. 2021

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Adverse Events and Associated Factors During Intrahospital Transport of Newborn Infants

Cited by 16 publications

References 34 publications

Unintended events in long-distance neonatal interhospital transport in Western Australia: A comparison of neonatal specialist and non-neonatal specialist transport teams

Unintended events in long-distance neonatal interhospital transport in Western Australia: A comparison of neonatal specialist and non-neonatal specialist transport teams

Analysis of the Relationship between Neonatal Risk Factors and Adverse Events in the Transfer of Operational Patients to the Neonatology Unit at RSCM

Intra-hospital transport of newborn infants dataset

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