Use of advanced technology to enhance monitoring of dairy cow health

The UK trend of increasing dairy herd size and milk yield per cow has generated challenges for dairy farmers, namely in the realm of cow health and herd management. Technology has the potential to facilitate livestock production, however the uptake of cow monitoring technologies within the UK has not been widely researched. There are key periods within the life of a cow where high levels of cow monitoring are required, for example calving, and technology has the potential to aid farmers with cow management. Calving cows require regular observation as it is a period of high risk for cow and calf; two common issues at calving are calving difficulty (dystocia) and calf mortality. However as average herd size increases, farm staff are under pressure to manage their time effectively and calving presents a management challenge. In the period surrounding calving, cows are susceptible to a range of disorders such as hypocalcaemia – a metabolic disorder which can be fatal. Automated systems could be used to detect calving and clinical hypocalcaemia on commercial dairy farms to help facilitate herd management and improve cow health and welfare. The first study was a survey investigating the prevalence and use of automated cow technologies was completed by 122 UK dairy farmers. The results showed that approximately 3 in 5 dairy farmers utilised automated cow monitoring technology, and the main parameters that were monitored on UK dairy farms were heat detection, daily milk yield, and illness detection. Half of dairy producers that do not have automated cow monitoring technology installed will invest within the next 5 years, and it is therefore expected that the prevalence of automated cow technologies will increase. Results indicated that dairy producers were satisfied with automated cow monitoring technology on their farms. The main barrier to adoption of technology was initial investment cost. The second study investigated the behavioural changes of eutocic and dystocic dairy cows in late gestation and on the day of calving. An accelerometer was attached to the hind leg of dairy cattle to collect lying and activity behavioural data. Data were collected from 32 multiparous and 12 primiparous Holstein dairy cattle to describe normal calving behavior and parity differences. To quantify behaviour related to calving difficulty, the data from 14 animals that had dystocia at calving were matched to cows that had an eutocic calving based on parity, locomotion score, calf breed, calf sex, month, and year of calving. Retrospective analysis was conducted on lying and activity data in the period before calving (d -4 to d -1) and on the day of calving (d 0). Findings suggest that cow behaviour on the day of calving was significantly different when compared to a non-calving control period (d -4). Important differences were found in the behaviour of primiparous and multiparous cows during the period prior to calving. In addition, the days relative to calving were found to affect activity behaviours. Three different types of machine learning methods (random forest, decision tree, and neural network) were unable to successfully use behavioural changes to classify the day before calving or the 2h period before calving. There was no difference in the behaviour between 14 cows with assisted calvings (dystocic) and 14 cows with non-assisted calvings (eutocic). The third study was designed to describe and quantify any behavioural differences between cows diagnosed with normocalcaemia, subclinical hypocalcaemia, and clinical hypocalcaemia at calving. A total of 51 multiparous cows and 21 primiparous cows were categorised as having either clinical hypocalcaemia, subclinical hypocalcaemia, or normocalcaemia at calving. Lying and activity behaviours of multiparous and primiparous cows within each blood calcium category was assessed for differences. In the 14 d before calving, multiparous cows with normocalcaemia had fewer lying and standing bouts compared to multiparous cows with subclinical hypocalcaemia and clinical hypocalcaemia. In addition, the step count of primiparous cows with normocalcaemia decreased across the period. These results suggested behaviour could be used to categorise cows into blood calcium group categories prior to calving. Cows that had clinical hypocalcaemia at calving were less active and lay down more in the 21 d post-calving. This finding suggests that the effect of hypocalcaemia on cow behaviour was long lasting. Overall, this thesis has shown that the use of remote sensing technology can be used to detect behavioural changes associated with calving and hypocalcaemia. These findings could be used to develop automated detection systems for calving and hypocalcaemia which could aid dairy producers in herd and cow health management. In addition, a survey of UK dairy farmers has shown that farmers are willing to invest in cow monitoring technology and 68% surveyed farmers would invest in the next 5 years. Return on investment was considered the most important criteria when selecting a technology for purchase. Therefore, it is important that technology companies can prove the monetary and non-monetary benefits of technologies

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine

Critical care admission following elective surgery was not associated with survival benefit: prospective analysis of data from 27 countries

This was an investigator initiated study funded by Nestle Health Sciences through an unrestricted research grant, and by a National Institute for Health Research (UK) Professorship held by RP. The study was sponsored by Queen Mary University of London