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Record W7027831175

The effects of standardised parturition care and animal-bound factors on stillbirth: a retrospective study of canine parturitions in a homogeneous population

2019· dissertation· en· W7027831175 on OpenAlexaboutno aff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2019
Typedissertation
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsRetrospective cohort studyLogistic regressionIncidence (geometry)PopulationObservational studyHomogeneousPopulation study
DOInot available

Abstract

fetched live from OpenAlex

Background: Veterinarians are routinely confronted with phone calls and inquiries regarding canine parturition. However, since few veterinarians use a standard specific parturition protocol, various actions are undertaken. Neonatal mortality, both during parturition and in the neonatal period, is a significant problem in the canine population. It has been previously reported that the overall incidence of stillbirth varies between 3.5% – 10.9%. Previous studies are either based upon a small number of dogs and/or diverse breeds. Possible causes of high stillbirth numbers and animal-bound factors have been described in the literature, but often it is not clear on what type of investigation this information is based or whether different parturition protocols have been used. The aim of this large-scale observational retrospective study was to evaluate a standardised parturition care and determine animal-bound factors that might influence the stillbirth rate in puppies in a homogenous canine population of mainly Labrador Retrievers. 
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\nMethods: Data was collected from a guide dog facility. A total of 2585 puppies from 331 parturitions - occurring from 1998 to 2019 - were included in this study. Qualitative analysis was carried out by conducting interviews with four experienced staff members of the guide dog facility. Quantitative data was analysed using Chi-square tests and logistic regression models.
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\nResults: The experienced staff members of the guide dog facility use a short and structured parturition protocol which they do not always strictly follow. 142 (5.5%) of the 2585 puppies were stillborn. A borderline significance between maternal age and stillbirth was detected. Digital vaginal exploration, use of oxytocin, and manual obstetric assistance were significantly associated with increased stillbirth rates. Pups in posterior presentation at expulsion, or pups of which the placenta was expulsed immediately following delivery, were also significantly more likely to be stillborn. The last pup of a litter had the highest stillbirth rate. Stillbirth rate increased as inter-pup interval increased. No effect on stillbirth was found for maternal parity, litter size, caesarean section, time between first passage of foetal fluids via the vulva and first pup, presentation of the first pup, the pup’s gender, or the pup’s birthweight. 
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\nConclusion: Univariable analyses revealed that stillbirth was significantly influenced by digital vaginal exploration, use of oxytocin, manual obstetric assistance, a pup’s presentation, a pup’s placenta attachment, a pup’s place in the sequence of births, and/or inter-pup interval. This information is valuable to gaining a more detailed understanding of parturitions in dogs and to make informed decisions during a parturition. The results of this study can also be used to establish a better adapted parturition protocol. To reduce the number of stillbirths, the results of the present study indicate that: 1) good parturition care at individual puppy level is important; 2) the age of the bitch may be correlated with stillbirth rate; 3) more research is needed on oxytocin therapy in bitches; 4) extra close monitoring is required for pups born with posterior presentation, pups born with the placenta attached, and the final pup in a litter, as these puppies showed a higher risk on stillbirth; 5) the interval between the birth of a pup and a intervention needs to be reconsidered.

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 score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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