Evidence map›Paper›PMID 37987862›Full record

ArticleTropical animal health and production2023

The survival analysis of some environmental factors associated with lamb mortality in Awassi sheep.

Ayhan Ceyhan, Özge Kozaklı

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Article in Tropical animal health and production, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Ayhan CeyhanDepartment of Animal Production and Technologies, Faculty of Agricultural Sciences and Technologies, Niğde Ömer Halisdemir University, 51240, Niğde, Turkey. aceyhan@ohu.edu.tr.ORCID http://orcid.org/0000-0003-2862-7369
Özge KozaklıDepartment of Animal Production and Technologies, Faculty of Agricultural Sciences and Technologies, Niğde Ömer Halisdemir University, 51240, Niğde, Turkey.ORCID http://orcid.org/0000-0003-4201-1157
Niğde Ömer Halisdemir Üniversitesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most of the economic losses in the Turkish sheep industry are due to lamb deaths between birth and weaning period. Survival analysis is an essential step in the understanding of the lamb's survival function and the hazards that have an impact on mortality. The lamb records were accessed from 2013 to 2019, with the information of 11,523 lambs from birth to weaning at 90 days of age. The Kaplan-Meier method was used for the estimation of the survival function of the lambs. The Cox proportional hazards survival analysis was performed to evaluate the factors influencing Awassi lamb mortality in the central Anatolian region of Türkiye. A multivariable Cox regression was fitted to the data after checking the assumptions of the regression. Year of birth, lambing season, lamb sex, method of birth, and birth weight groups were used as explanatory variables. The overall survival of the lambs to weaning was 75.7%, and the Kaplan-Meier estimate of the average survival time to weaning was 62.25 days. Cox proportional hazards modeling showed that the hazard rate of death before weaning was higher in male lambs (1.205 and 95% CI, 1.119-1.300) compared to female lambs. It was also noted that the hazard rate of death (HR = 0.956 and 95% CI, 0.937-0.974) had significant years. The single-born lambs had a lower risk of death among the lambs. The summer and autumn seasons had a very highly advanced effect on the survival rate of the lambs. The hazard rate for the categorical birth weight group was 0.703 (95% CI, 0.667-0.741). This indicates that the risk of pre-weaning mortality decreased with increasing birth weight > 3.5 kg. The results of this study showed that lamb survival can be increased by paying more attention to winter born lambs, male sex, twin births, and lambs about birth weight (< 3.5 kg).

Indexed as

Red MeatAnimalsBirth WeightFemaleKaplan-Meier EstimateMaleSeasonsSheepSurvival AnalysisWeight GainAwassi sheepCox regressionHazardMortalitySeasonWeaning

Identifiers

PMID37987862
OpenAlexW4388866264

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.