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Presentation_1_A systematic review and meta-analysis of the globally reported International Classification of Diseases to Perinatal Mortality (ICD-PM).pdf

2024· article· en· W6927441579 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMedical Coding and Health Information
Canadian institutionsnot available
Fundersnot available
KeywordsPerinatal mortalityInfant mortalityGestational agePregnancyMortality rateCause of deathLow birth weightPerinatal period

Abstract

fetched live from OpenAlex

Introduction Accurate recording and identification of perinatal mortality causes are crucial to reducing the global burden of perinatal mortality through targeted interventions. However, existing studies on the International Classifications of Diseases to Perinatal Mortality (ICD-PM) are limited by inconsistent results and variations by gestational age. Thus, this review aims to synthesize and document updated data on the causes of death using the ICD-PM classification. Methods Electronic databases such as the PubMed via MEDLINE, SCOPUS, Web of Sciences, EMBASE, Cochrane Library, and PROSPERO were searched to retrieve studies published from 2016 to February 2024. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included studies, and heterogeneity between the studies was assessed using I<sup>2</sup> statistics. ICD-PM coded reported data were extracted to Microsoft Excel, and aggregate data of frequencies and percentages were reported. Results Out of the 23 included studies, 48,596 perinatal mortalities were reported, and approximately 96% (46,816 deaths) were classified according to the ICD-PM. The pooled rate of stillbirths in high-income countries was 23/1,000 births; in low-income countries, it was found to be approximately twice as in high-income countries. Regarding the category of deaths, 25,563 (54.6%) deaths were recorded in the antepartum period, and more than half, 14,887 (58.2%), were classified under unspecified causes (A6). Moreover, 6,148 (13.7%) and 14,835 (31.7%) deaths were coded with intrapartum and neonatal period causes, respectively. The leading causes of perinatal mortality during the intrapartum were acute intrapartum events (I3) 3,712 (57.8%). Furthermore, neonatal death was caused by low birth weight and prematurity (N9) 4,091 (27.6%), congenital malformations, and chromosomal abnormalities (N1) 2,512(16.9%). Conclusion Congenital malformations, and chromosomal abnormalities contribute to 1 in every 10 perinatal deaths and 1 in every 4 neonatal deaths. Other specified antepartum disorders are responsible for over half of antepartum deaths, while acute intrapartum events are the leading cause of intrapartum deaths, with a significant proportion remaining unexplained. Maternal complications related to the placenta, membranes, cord, labor, and delivery play a significant role in antepartum and intrapartum deaths. Targeted interventions and improved monitoring of high-risk pregnancies are crucial to reducing perinatal mortality rates. Further investigation is needed to enhance understanding and address unexplained perinatal deaths. Systematic review registration [https://clinicaltrials.gov/], identifier [CRD4202452549].

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0720.000

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 head0.528
GPT teacher head0.541
Teacher spread0.013 · 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 designSystematic review
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
Published2024
Admission routes1
Has abstractyes

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