Page 76 of 201 Table 17: Statistical measures of diagnostic performance for clinical category information as a
test for detecting respiratory disease as a cause of death in cattle. Based on data in Table 16. Se= sensitivity; Sp=specificity; PPV = positive predictive value; NPV = negative predictive
value; App Prev = apparent prevalence; True Prev = true prevalence; CI = Confidence Interval.
Parameter Estimate
95 CI Lower
Upper Se
0.08 0.04
0.15
Sp
0.94 0.88
0.97
PPV
0.6 0.36
0.8
NPV
0.51 0.44
0.58
App Prev
0.07 0.04
0.11
True Prev
0.5 0.43
0.56 The results clearly show that clinical category information alone is not useful for gaining any
reasonable understanding of the extent of respiratory disease as a cause of death on export voyages. The sensitivity in particular is very low indicating that clinical category information
is particularly poor at detecting those animals that truly have died of respiratory disease.
The predictive values appear to be little better than tossing a coin to determine the probability of a disease outcome given the findings of the clinical category information.
The apparent prevalence estimate proportion of all deaths that are due to respiratory disease when based on clinical category information is seriously inaccurate and an under-
representation of the true prevalence.
The results confirm that clinical category information is insufficient to provide a reasonable understanding of the contribution of respiratory disease to mortality on export voyages and
that gross necropsy diagnosis is essential to achieve a good understanding of the contribution of respiratory disease to voyage mortalities.
7.10.3 Musculoskeletal injury detection using gross necropsy
Table 18: Summary of classification of 215 cases of mortality by gold standard test final cause of death and the gross necropsy diagnosis, using musculoskeletal injury as the outcome of
interest. Gross necropsy diagnoses of inflammation of joints, misadventure, anaesthetic complications and neurogenic lameness were combined to represent musculoskeletal injury
conditions.
Musculoskeletal injury Gold standard test
Final cause of death Disease +
Disease - Gross necropsy
diagnosis
Test + 26
11 37
Test - 7
171 178
33 182
215
Page 77 of 201 Table 19: Statistical measures of diagnostic performance for gross necropsy diagnosis as a
test for detecting musculoskeletal injury conditions as a cause of death in cattle. Based on data in Table 18. Se= sensitivity; Sp=specificity; PPV = positive predictive value; NPV =
negative predictive value; App Prev = apparent prevalence; True Prev = true prevalence; CI = Confidence Interval.
Parameter Estimate
95 CI Lower
Upper Se
0.79 0.62
0.89
Sp 0.94
0.9 0.97
PPV 0.7
0.54 0.83
NPV 0.96
0.92 0.98
App Prev 0.17
0.13 0.23
True Prev 0.15
0.11 0.21
A gross necropsy diagnosis of musculoskeletal injury conditions has a very high Sp and a very high NPV. This indicates that when the gross necropsy diagnosis does not record
lameness, there is a very high level of confidence that the animal did not die of musculoskeletal injury conditions 96 based on NPV.
The Se is only moderate 0.68 indicating that 79 of animals that were classified as having musculoskeletal injury conditions as the final cause of death true disease positive were
classified as having musculoskeletal injury conditions as the gross necropsy diagnosis.
7.10.4 Musculoskeletal injury condition detection using clinical category information
Table 20: Summary of classification of 215 cases of mortality by gold standard test final cause of death and the clinical category information outcome, using musculoskeletal injury
conditions as the outcome of interest.
Musculoskeletal injury Gold standard test
Final cause of death Disease +
Disease - Clinical category
Test + 31
8 39
Test -
2 174
176 33
182 215
Page 78 of 201 Table 21: Statistical measures of diagnostic performance for clinical category information as a
test for detecting lameness as a cause of death in cattle. Based on data in Table 22. Se= sensitivity; Sp=specificity; PPV = positive predictive value; NPV = negative predictive value;
App Prev = apparent prevalence; True Prev = true prevalence; CI = Confidence Interval.
Parameter Estimate
95 CI Lower
Upper Se
0.94 0.8
0.98
Sp
0.96 0.92
0.98
PPV
0.79 0.64
0.89
NPV
0.99 0.96
1
App Prev
0.18 0.14
0.24
True Prev
0.15 0.11
0.21 There is a striking difference between these results for clinical category detection of
musculoskeletal injury conditions as a cause of death and the results for clinical category detection of respiratory disease as a cause of death.
Clinical detection of musculoskeletal injury conditions performs well as gross necropsy diagnosis as a test for detection of musculoskeletal injury conditions as a cause of death.
The findings support the suggestion that musculoskeletal injury conditions is a very different type of disease to respiratory disease, mainly because musculoskeletal injury
conditions cases are more likely to have been observed and recorded in clinical category records. Musculoskeletal and injury conditions are more obvious and noticeable both ante-
mortem and post-mortem.
It is interesting to note that musculoskeletal injury conditions has a moderate PPV. The PPV of 0.79 means that once a clinical diagnosis of musculoskeletal injury conditions is
made as a cause of death, there is a 79 probability that musculoskeletal injury conditions truly was the cause of death.
This does not mean that the musculoskeletal injury conditions observation was not accurate. It is likely to reflect the fact that animals that are lame or injured become
increasingly susceptible to other serious diseases that may ultimately cause death or necessitate euthanasia. The role of musculoskeletal injury conditions as a cause of death
has some relatively complex dimensions.
If the ultimate disease or condition that is classified as the cause of death would not have occurred had the animal not been lame or injured, then undoubtedly the lamenessinjury
played an important role in determining the animal’s subsequent mortality, even if it was not
literally the thing that ultimately killed the animal. Extending the counter-factual argument a little further poses the question that if an initial
clinical classification of musculoskeletal injury conditions had been either prevented or successfully treated, would this have prevented the occurrence of other diseases likely to
occur in lameinjured animals and that may result in death. The point of this is that prevention and or treatment of lamenessinjury may reduce mortalities attributed to causes
of death other than lameness. This is not novel and is supported by anecdotal information
Page 79 of 201
from experienced AAVs and exporters. It is pleasing to see the results of statistical analyses supporting well accepted hypotheses and anecdotal opinions since it adds confidence in the
interpretation of the findings and in using these results to inform preventive strategies.
It is also interesting that the apparent prevalence for musculoskeletal injury conditions is much closer to the true prevalence estimate than was observed for respiratory disease. The
apparent prevalence is a little higher than the true prevalence, reflecting the same issue as discussed in the previous paragraph.
When the diagnostic information for musculoskeletal injury conditions is considered, it suggests that musculoskeletal injury conditions can be effectively detected as a cause of
death without requiring necropsy examination for diagnostic classification – in contrast to
respiratory disease. This is not to say that lame animals that die should not be subjected to necropsy. The point
is that necropsy of lameinjured animals that die is of value not only to confirm a necropsy diagnosis of lamenessinjury as a cause of death, but to investigate other causes of death
such as respiratory disease that can only be diagnosed effectively at necropsy and not by clinical category information alone. This information can be used potentially to fine tune the
approach to necropsy to make it more efficient without reducing its diagnostic effectiveness. This will be revisited in more detail in later sections of this report.
7.10.5 Inappetence detection using gross necropsy
