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Record W2582161515 · doi:10.1111/apa.13690

Admission hypo‐ and hyperthermia are associated with increased mortality and morbidity in very preterm infants

2017· letter· en· W2582161515 on OpenAlexaboutno aff
Julia Maletzki, Stephanie Adzikah, Christoph M. Rüegger, Dirk Bassler

Bibliographic record

VenueActa Paediatrica · 2017
Typeletter
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHyperthermiaRectal temperatureHypothermiaPediatricsGestationGestational agePregnancyAnesthesiaInternal medicine

Abstract

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Commentary on: Lyu Y, Sha PS, Ye XY, Waree R, Piedboeuf B, Deshpandey A, Dunn M, Lee SK, for the Canadian Neonatal Network. Association between admission temperature and mortality and major morbidity in preterm infants born at fewer than 33 weeks′ gestation. JAMA Pediatr 2015; 169: e150277. Even though the pathophysiologic mechanisms of hypo- and hyperthermia and their impact on infants’ outcome have been known for a long time, most previous research merely covers one end of the temperature scale, namely hypothermia. In this Canadian Neonatal Network study, Lyu et al. retrospectively investigated the effect of admission body temperature (low and high) on adverse outcomes of preterm infants. The nationwide participation resulted in an impressive number of included infants with only very few dropouts. Nevertheless, there are a few comments to make. The authors define the admission temperature as the temperature taken with the first vital signs within the first hour of the infant's admission to the NICU. Information about the infant's chronological age when admission temperature was measured is missing. There is no standard protocol to measure the admission temperature. Not only does the location of temperature acquisition vary (rectal vs. axillary) but also the temperature detecting device. The authors cite Craig et al. 1 who concluded that there is a pooled mean temperature difference of 0.17°C between axillary and rectal temperatures. This indicates only a small – probably not significant – difference between the two measurement locations. They forgot to mention that the range of temperature difference was wide and that the temperature measurement device (mercury vs. electronic) plays an important role. Mercury thermometers had narrower limits of agreement when comparing axillary vs. rectal temperatures. Other studies also come to the conclusion that axillary and rectal temperatures are not interchangeable in preterm infants 2. Important, but not documented, are possible confounders such as the mother's temperature at birth and the time needed to transport the baby from the delivery room to the NICU. Other confounders such as ventilation with a dry circuit and the use of fluids for resuscitation are not mentioned, as well. The authors included factors like these in their infants’ characteristics (Apgar score <7 with five minutes, SNAP II >20, resuscitation needed) and applied a univariate analysis, which showed that these factors were associated with admission temperature. In addition, the primary composite outcome may contain too many individual components. Schmidt et al. 3 presented a count of three major neonatal morbidities, namely bronchopulmonary dysplasia, brain injury and severe retinopathy of prematurity, as the most important prognostic factors for neurodevelopmental outcome at 18 months. Bassler et al. 4 showed that necrotising enterocolitis and sepsis (except meningitis) are weaker predictors of a poor long-term outcome. Late-onset sepsis, on the other hand, has been shown to be inversely correlated with hypothermia 5, which might have been the reason for adding sepsis to the composite primary outcome. For the secondary outcome, the authors calculated the admission temperature at which each single adverse outcome was at its lowest rate. This is interesting on a theoretical basis, but not applicable for clinical everyday life. In conclusion, the authors found an association between hypo- and hyperthermia and an adverse neonatal outcome, which calls for continuous monitoring of body temperature in extremely preterm infants as part of routine resuscitation. https://ebneo.org/2016/11/admission-hypo-and-hyperthermia-are-associated-with-increased-mortality-and-morbidity-in-very-preterm-infants None. None.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0050.001
Research integrity0.0130.010
Insufficient payload (model declined to judge)0.0110.004

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 head0.067
GPT teacher head0.347
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2017
Admission routes1
Has abstractyes

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