scholarly journals Five risk factors and their interactions of probability for a sow in breeding herds having a piglet death during days 0–1, 2–8 and 9–28 days of lactation

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Yuzo Koketsu ◽  
Ryosuke Iida ◽  
Carlos Piñeiro
Keyword(s):  
Regression Models ◽  
Management Practices ◽  
Gestation Length ◽  
Early Lactation ◽  
Logistic Regression Models ◽  
Five Factors ◽  
More Care ◽  
Parity Number ◽  
Multi Level ◽  
Piglet Mortality

Abstract Background Increasing preweaning piglet mortality is a concern for veterinarians and producers in relation to sow performance and piglet welfare. Our objectives were (1) to characterize pre-weaning piglet mortality risk for sows (PWM) during early (0–1 days), mid- (2–8 days) and late (9–28 days) lactation and (2) to quantify the following five factors and their interactions, parity, number of piglets born alive (PBA), number of stillborn piglets (SB), gestation length (GL) and season for PWM during the three lactation phases. Methods Data obtained from 264,333 parity records of 55,635 sows farrowed in 2015 and 2016 from 74 Spanish herds. Three multi-level mixed-effects logistic regression models were separately applied for PWM during three lactation phases, which was analyzed as whether or not a sow had a piglet death (i.e. probability of a sow having a piglet death) in each phase. Results PWM during early, mid- and late lactation were 36.9, 27.0 and 15.4%, respectively. As PBA increased from 11 or less to 16 or more pigs, PWM during early and mid-lactation increased by 15.8 and 6.0%, respectively, but there was no increase during late lactation. Also, as GL decreased from 117–120 to 110–113 days, PWM during early, mid- and late lactation increased by 7.5, 6.8 and 1.5%, respectively. Additionally, PWM during the respective lactation phases increased by 8.3, 5.2 and 1.0%, as SB increased from 0 to 3 or more pigs. During early lactation, parity 1 sows had 2.1% lower PWM than parity 5 or higher sows, but during mid- and late lactation they had 4.2% higher PWM (P < 0.05). However, there was no difference between summer and winter for PWM during early lactation (P = 0.26). Conclusion Management practices to reduce PWM need to take account of these factors, and be modified for different phases. For example, during early lactation special care should be given to piglets born to parity 5 or higher sows farrowing 16 or more PBA, having 3 or more SB or GL 110–113 days, whereas during mid- and late lactation more care should be given to piglets born to parity 1 sows with the same PBA, GL and SB conditions.

scholarly journals Physician-Related Variability in the Outcomes of an Invasive Treatment for Neck and Back Pain: A Multi-Level Analysis of Data Gathered in Routine Clinical Practice

2021 ◽  
Vol 18 (8) ◽  
pp. 3855
Author(s):  
Ana Royuela Vicente ◽  
Francisco M. Kovacs ◽  
Jesús Seco-Calvo ◽  
Borja M. Fernández-Félix ◽  
Víctor Abraira ◽  
...  
Keyword(s):  
Back Pain ◽  
Regression Models ◽  
Intraclass Correlation ◽  
Spinal Pain ◽  
Routine Clinical Practice ◽  
Invasive Treatment ◽  
Logistic Regression Models ◽  
Training Standards ◽  
Multi Level ◽  
Level Analysis

Neuro-reflexotherapy (NRT) is a proven effective, invasive treatment for neck and back pain. To assess physician-related variability in results, data from post-implementation surveillance of 9023 patients treated within the Spanish National Health Service by 12 physicians were analyzed. Separate multi-level logistic regression models were developed for spinal pain (SP), referred pain (RP), and disability. The models included all patient-related variables predicting response to NRT and physician-related variables. The Intraclass Correlation Coefficient (ICC) and the Median Odds Ratio (MOR) were calculated. Adjusted MOR (95% CI) was 1.70 (1.47; 2.09) for SP, 1.60 (1.38; 1.99) for RP, and 1.65 (1.42; 2.03) for disability. Adjusted ICC (95%CI) values were 0.08 (0.05; 0.15) for SP, 0.07 (0.03; 0.14) for RP, and 0.08 (0.04; 0.14) for disability. In the sensitivity analysis, in which the 6920 patients treated during the physicians’ training period were excluded, adjusted MOR was 1.38 (1.17; 1.98) for SP, 1.37 (1.12; 2.31) for RP, and 1.25 (1.09; 1.79) for disability, while ICCs were 0.03 (0.01; 0.14) for SP, 0.03 (0.00; 0.19) for RP, and 0.02 (0.00; 0.10) for disability. In conclusion, the variability in results obtained by different NRT-certified specialists is reasonable. This suggests that current training standards are appropriate.

scholarly journals A Longitudinal Study of Lameness Incidence and Association with Animal-Based Welfare Measures in Dairy Cows

2021 ◽  
Vol 44 (1) ◽  
Author(s):  
Mohammed Babatunde Sadiq ◽  
Siti Zubaidah Ramanoon ◽  
Wan Mastura Shaik Mossadeq ◽  
Rozaihan Mansor ◽  
Sharifah Salmah Syed-Hussain
Keyword(s):  
Dairy Cows ◽  
Body Condition ◽  
Regression Models ◽  
Management Practices ◽  
Cox Regression ◽  
Body Condition Score ◽  
Logistic Regression Models ◽  
Condition Score ◽  
Claw Lesions ◽  
Welfare Measures

The objective of this study was to investigate time to lameness event, prevalence of claw lesions, and their associations with animal-based welfare measures (ABWMs) in dairy cows. A total of 120 non-lame lactating cows (n = 30 each from four intensive dairy farms) having no claw lesion were enrolled in the study. The cow-level enrollment criteria included good body condition score (BCS), normal hock condition score, absence of body injuries, and normal claw length. Information on cows’ parity, milk yield, and previous lameness event (PLE) were recorded. The cows were observed twice monthly (every 2 weeks) for locomotion scores (LS), and ABWMs, whereas claw lesions were recorded upon onset of lameness and at the end of the observation period. Cows were considered lame when 2 consecutive LS = 3, or any assessment with score 4. Cox regression models were used to investigate lameness incidence and the association with ABWMs, while association between the latter and claw horn lesions (CHL) prevalence were analyzed using logistic regression models. Twenty-four percent (29/120) of the cows were lame during the study period. Lameness risk was associated with PLE (Hazard ratio; HR = 7.4; 95% CI 2.4-23.0), presence of overgrown claw (HR = 3.7; 95% CI 1.1-12.6) and low BCS pre-lame (HR = 4.5; 95% CI 1.3-16.6). Amongst the cows affected with claw lesions, 68.4% (37/44) were lame and CHL were predominant (75.4%) compared to infectious claw lesions (24.7%). Cows with lower BCS (< 3.0) (OR = 5.7; 95% CI 1.6- 20.4) and those with PLE (OR = 7.2; 95% CI = 2.1-24.7) were more likely to have CHL. Management practices such as maintaining cows’ body condition, improved care for those with history of lameness, and proper claw trimming could assist farmers to reduce lameness incidence in the studied herds.

scholarly journals Risk factors associated with stillbirth of piglets born from oxytocin-assisted parturitions

2020 ◽  
Vol 13 (10) ◽  
pp. 2172-2177
Author(s):  
Nguyen Hoai Nam ◽  
Peerapol Sukon
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Models ◽  
Significant Risk ◽  
Gestation Length ◽  
Stillbirth Rate ◽  
Multivariate Logistic Regression ◽  
Crown Rump Length ◽  
Logistic Regression Models ◽  
Factors Associated

Aim: The present study aimed to investigate the effects of different risk factors on stillbirth of piglets born from oxytocin-assisted parturitions. Materials and Methods: Data were collected from a total of 1121 piglets born from 74 Landrace x Yorkshire crossbred sows from a herd. Logistic regression models were used to determine the associations between stillbirth and different risk factors including parity (1, 2, 3-5, and 6-10), gestation length (GL) (112-113, 114-116, and 117-119 days), litter size, birth order (BO), sex, birth interval (BI), cumulative farrowing duration, birth weight (BW), crown rump length, BW deviation, body mass index, ponderal index (PI), and the use of oxytocin during expulsive stage of farrowing. Results: The incidence of stillbirth at litter level and stillbirth rate was 59.5% (44/74) and 8.1% (89/1094), respectively. The final multivariate logistic regression selected BO, BI, PI, GL, and parity as the five most significant risk factors for stillbirth. Increased BO and BI, GL <114 and >116 days, parity 6-10, and low PI increased the stillbirth rate in piglets. Conclusion: Several factors previously determined as risks for stillbirth in exogenous oxytocin-free parturitions also existed in exogenous oxytocin-assisted parturitions. One dose of oxytocin at fairly high BO did not increase stillbirth, whereas two doses of oxytocin were potentially associated with increased values.

scholarly journals When Europe hits the subnational authorities: the transposition of EU directives in Germany between 1990 and 2018

2020 ◽  
pp. 1-20
Author(s):  
Jana Paasch ◽  
Christian Stecker
Keyword(s):  
European Union ◽  
Policy Implementation ◽  
Regression Models ◽  
Black Box ◽  
Veto Power ◽  
Data Set ◽  
Logistic Regression Models ◽  
Eu Policies ◽  
Eu Directives ◽  
Multi Level

Abstract Federalism and the associated multi-level polity-structure have been frequently blamed for delaying the implementation of European Union (EU) directives. However, this verdict is incomplete as only a few studies open the “black box” of federalism to analyse the involvement of subnational parliaments and executives or second chambers in policy implementation. This article fills this gap and explains the transposition delay on the level of each individual implementation measure. Our novel data set covers about 850 directives and the corresponding 1,950 implementation measures between 1990 and 2018 in Germany. Using logistic regression models, we find that involving the subnational authorities substantially delays transposition. Subnational measures are three times more likely to be delayed than national ones. The effect of the veto power of a second chamber remains inconclusive. Our findings highlight the challenges federalism poses for the multi-level implementation of EU policies and have implications for the broader literature on compliance with public policies.

Asymmetry in Protest Control? Comparing Protest Policing Patterns in Montreal, Toronto, And Vancouver, 1998-2004

2010 ◽  
Vol 15 (4) ◽  
pp. 489-509 ◽  
Author(s):  
Patrick Rafail
Keyword(s):  
Regression Models ◽  
Management Practices ◽  
National Level ◽  
Management Model ◽  
Logistic Regression Models ◽  
Cooperative Relationships ◽  
Protest Policing ◽  
The 1960S ◽  
Bayesian Logistic Regression ◽  
Western Democracies

Scholars have argued that since the 1960s, protest policing in Western democracies has moved toward emphasizing cooperative relationships with challenging groups. This evolution is referred to as the negotiated management model of protest control. Much of the literature that informs this perspective is based on either analyses of a limited subset of demonstrations or from national-level observation. Few studies have examined whether negotiated management practices hold at city levels. This research examines city-level protest policing using 1,152 demonstrations occurring between 1998 and 2004 in Montreal, Toronto, and Vancouver, Canada. Bayesian logistic regression models are estimated using arrests as the response variable. The main findings suggest that only protestor premobilization and the police use of force are uniformly related to arrests; that there is considerable variation across cities; and that the larger pattern of results is not consistent with negotiated management practices.

Evaluation of speech misattribution bias in schizophrenia

2009 ◽  
Vol 40 (5) ◽  
pp. 741-748 ◽  
Author(s):  
M. Stephane ◽  
M. Kuskowski ◽  
K. McClannahan ◽  
C. Surerus ◽  
K. Nelson
Keyword(s):  
Regression Models ◽  
Group Differences ◽  
Response Accuracy ◽  
Cognitive Demands ◽  
Logistic Regression Models ◽  
Recognition Ability ◽  
Third Person ◽  
General Recognition ◽  
Multi Level ◽  
And Gender

BackgroundThe attribution of self-generated speech to others could explain the experience of verbal hallucinations. To test this hypothesis, we developed a task to simultaneously evaluate (A) operations of self-other distinction and (B) operations that have the same cognitive demands as in A apart from self-other distinction. By adjusting A to B, operations of self-other distinction were specifically evaluated.MethodThirty-nine schizophrenia patients and 26 matched healthy controls were required to distinguish between self-generated, other-generated and non-generated (self or other) sentences. The sentences were in the first, second or third person and were read in a male or female voice in equal proportions. Mixed multi-level logistic regression models were used to investigate the effect of group, sentence source, pronoun and gender of the heard sentences on response accuracy.ResultsPatients differed from controls in the recognition of self-generated and other-generated sentences but not in general recognition ability. Pronoun was a significant predictor of response accuracy but without any significant interaction with group. Differences in the gender of heard sentences were not significant. Misattribution bias differentiated groups only in the self-other direction.ConclusionsThese data support the theory that misattribution of self-generated speech to others could result in verbal hallucinations. The syntactic (pronoun) factor could impact self-other distinction in subtypes of verbal hallucinations that are phenomenologically defined whereas the acoustic factor (gender of heard speech) is unlikely to affect self-other distinction.

Shark Nursery Grounds of the Gulf of Mexico and the East Coast Waters of the United States

2007 ◽  
Keyword(s):  
Logistic Regression ◽  
Chesapeake Bay ◽  
Regression Models ◽  
Management Practices ◽  
Fish Habitat ◽  
Virginia Institute ◽  
Predictive Ability ◽  
The United States ◽  
Carcharhinus Plumbeus ◽  
Logistic Regression Models

<em>Abstract.</em>—The lower Chesapeake Bay is the largest summer nursery for sandbar sharks <em>Carcharhinus plumbeus </em>in the western Atlantic. The objective of this study was to define essential fish habitat for juvenile sandbar sharks in this estuary. The longline survey conducted by the Virginia Institute of Marine Science was expanded from 1990 to 1999 to include ancillary stations throughout the Virginia portion of Chesapeake Bay to delineate this nursery spatially. We analyzed catch per unit of effort data from 83 stations as a function of nine physical and environmental variables using tree-based regression models. The highest abundance of juvenile sandbar sharks was predicted where salinity was greater than 20.5 (practical salinity scale) and depth was greater than 5.5 m. The models also suggested that dissolved oxygen concentration may influence shark distribution. To increase applicability of the models to management practices, we introduced distance to the mouth of the estuary as a surrogate variable for salinity. The models estimated that the highest abundance of sharks was in areas less than 34.5 km from the mouth of the estuary and in depths greater than 5.5 m. The areas of the estuary that met the criteria of the models, based on the threshold values of the variables, were mapped spatially in a geographic information system. The resulting response surfaces were interpreted to represent essential nursery habitat for sandbar sharks in Chesapeake Bay. Both models performed very well using several dependent and independent measures to estimate their classification and predictive ability. We used logistic regression with presence/absence data to validate the tree models. The logistic regression models agreed very well with the tree-based regression models, selecting the same variable combinations to predict sandbar shark presence and absence.

Multi-level analysis of symptoms of poison exposure reported to the Japanese Poison Information Center

2020 ◽  
Vol 35 (3) ◽  
pp. 239-243
Author(s):  
Toshiko Sawaguchi
Keyword(s):  
Odds Ratio ◽  
Regression Models ◽  
Profile Likelihood ◽  
Numerical Data ◽  
Logistic Regression Models ◽  
Information Center ◽  
Causative Agents ◽  
Optimized Model ◽  
Multi Level ◽  
Level Analysis

AbstractTwo types of analytical multi-level approach to analyse symptoms after exposure to poisons were performed using numerical data extracted from reports received by the JAPAN POISON INFORMATION CENTER on the number “Poisoning 110” during 1998–2017. In the first approach, data collected in 2017, 2012, 2007 and 2002 were used, while in the second approach, all data collected during 1999–2017 were used. In the first approach, according to the odds ratio, the order of causative agents was industrial drugs>home drugs>general drugs and in the second approach, it was industrial drugs>foods/natural poisoning>agricultural drugs. However, in the first approach, the order based on the 95% confidence interval (CI) and profile likelihood was general drugs>home drugs>industrial drugs and in the second approach, the order based on 95% CI, profile likelihood and Wald value was agricultural drugs>foods/natural poisoning>industrial drugs. These multi-prospects were developed using a multilevel approach and the most optimized model was selected from the number of numerical data and the adaptability of fit of the multi-level logistic regression models in this report.

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