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Focus on Skin and Wounds in Neonates and Children

2020· article· en· W3026464210 on OpenAlexaff
Irene Lara‐Corrales, Cathryn Sibbald, Elizabeth A. Ayello, Gary Sibbald

Bibliographic record

VenueAdvances in Skin & Wound Care · 2020
Typearticle
Languageen
FieldHealth Professions
TopicNeonatal skin health care
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineEpidermolysis bullosaGestational agePopulationIntensive care medicineUmbilical cordPediatricsPregnancyDermatology

Abstract

fetched live from OpenAlex

Managing wounds in neonates is different than in children or adults and deserves special considerations. Neonatal skin is physiologically and developmentally different, and some skin characteristics are dependent on gestational age.1 For example, skin barrier function increases with gestational age; the epidermis is mature by 34 weeks’ gestation, but preterm infants take 2 to 3 weeks longer to reach this maturity.2 The skin of preterm infants has less functionality and thus a higher risk of injury. Not only does skin development affect neonatal outcomes, but the wound causes are also unique. Pediatric specialists should consider several factors when called to assess a newborn with wounds. Evaluate if wounds are the result of skin fragility influenced by genetic disorders including epidermolysis bullosa or some types of ichthyosis. Consider facility-acquired pressure injury incidence and prevalence (as in this issue’s Open Access article on pressure injuries in the pediatric population by Delmore et al) and extrinsic factors such as medical devices.3,4 This evaluation may involve previous surgeries, immobility, sepsis, and other events. Finally, iatrogenic etiologies include chemical burns from antiseptics, access line extravasation injuries, or medical adhesive-related skin injury.5,6 Although institutional protocols for neonatal skin care vary, published guidelines address practices including bathing, moisturizing, umbilical cord handling, sterilization, and diapering7 and often include specific recommendations for preterm infants.8 However, there is limited guidance regarding the use of dressings. In this issue, Keswani et al provide a comprehensive review of wound care products for neonates. Both this CE/CME article and a recently published white paper3 provide important references for neonatal healthcare providers. Because many products exist with varying costs and availability, learn about product categories, know their properties, and anticipate possible scenarios in which a product category might be indicated. Formularies may guide practice, but choosing among products remains an important skill in need of development. Be familiar with atraumatic dressings and tapes, adhesive remover products, and the correct way to remove tape to help prevent injuries. Further, monitor neonates for possible complications including irritant or allergic contact dermatitis. Potential causes of irritant contact dermatitis include leakage of bodily fluids, as well as antiseptics, adhesives, occlusive topical ointments or creams, and some dressings. Another important consideration is the systemic absorption of topical medications.3 Adverse effects include silver-related leukopenia or argyria with silver sulfadiazine cream, aminoglycoside-related ototoxicity from gentamicin or neomycin, and iodine-induced thyroid disorders.9 Prilocaine-related methemoglobinemia from EMLA cream (Astra USA, Inc, Westborough, Massachusetts) can often be prevented; avoid formulation in infants less than 37 weeks’ gestational age and in children younger than 1 year who are on drugs that can induce methemoglobinemia.10 The need for topical medications should be considered carefully; adhere to the minimum required frequency and duration, in addition to limiting the area and amount of product being applied. If significant absorption is suspected, confirm the plasma concentration of the drug and promptly discontinue the offending agent. We hope you enjoy this focused issue supporting best practice care for your vulnerable neonatal and pediatric patients. Irene Lara-Corrales, MD, MSc Cathryn J. Sibbald, MD, MSc, FRCPC Elizabeth A. Ayello, PhD, MS, BSN, RN, CWON, ETN, MAPWCA, FAAN Gary R. Sibbald, MD, DSc (Hons), MEd, BSc, FRCPC (Med Derm), FAAD, MAPWCA, JM

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.361
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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