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Record W2979507772 · doi:10.14740/ijcp349

Outcomes of Newborn Infants With Pulmonary Hypertension Treated With Oral Sildenafil

2019· article· en· W2979507772 on OpenAlexvenueno aff
Manar Al‐lawama, Eman Badran, Abedulrhman S. Abdelfattah, Rama Jaddalla, Hala Ahmad Almahameed, Iyad Al‐Ammouri

Bibliographic record

VenueInternational Journal of Clinical Pediatrics · 2019
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsSildenafilMedicinePulmonary hypertensionPersistent pulmonary hypertensionNitric oxideRespiratory distressShock (circulatory)Incidence (geometry)Mortality rateAnesthesiaPediatricsInternal medicine

Abstract

fetched live from OpenAlex

Background: Persistent pulmonary hypertension of the newborn (PPHN) is a disease with a high mortality rate. The incidence of PPHN is approximately 0.8 per 1,000 live births. Inhaled nitric oxide remains the treatment of choice, but in areas where inhaled nitric oxide is not available, sildenafil citrate is considered the best alternative vasodilator. We conducted this study to investigate the efficacy of oral sildenafil in treating neonatal pulmonary hypertension. Methods: This is a retrospective study of all newborns diagnosed with PPHN who received oral sildenafil over an 8-year period. Results: A total of 27 newborns were included in the study. The most common primary disease was respiratory distress syndrome. The mortality rate was 44.4%; all newborns with cardiovascular shock at presentation died. Conclusions: Oral sildenafil is a promising medication that can help neonates with mild to moderate PPHN in hospital units where inhaled nitric oxide is not available. Development of a treatment protocol to standardize the care of such infants will positively impact outcomes. Int J Clin Pediatr. 2019;8(2):27-31 doi: https://doi.org/10.14740/ijcp349

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.082
GPT teacher head0.439
Teacher spread0.358 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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