The documentation of deep infection rates in joint replacement is fraught with multiple difficulties. Deep infections acquired in theatre may present late, but some later presenting deep infections are clearly haematogenous, and not related to surgical management. The effect of Ultra Clean Air on infection rates was published by Charnley in 1972 (CORR,87:167–187). The data is valuable because large numbers of THRs were performed in standard and Ultra Clean theatres, and detailed microbiology of the air was also recorded. No IV antibiotics were used, so only the effect of air quality was studied. We extracted the data on theatre type and numbers from Table 3, and numbers and intervals from surgery of deep infections from Table 7. Theatre types with 300 air changes per hour and 3.5 CFU/M. 3. were classified as Ultra Clean. A logistic regression model was used to examine the effect of theatre type and time elapsed after procedure on the probability of becoming infected. The model suggests that, controlling for time period, Ultra Clean Air is associated with a significantly lower probability of infection, with an OR of 0.30, p = 2.74 × 10. −6. The effect is larger earlier post-surgery, but it does persist. The results are best reviewed as a graphic, which shows that Ultra Clean Air clearly affects the deep infection rate for up to four years post-surgery. Ultra Clean Air reduces infection rates for up to four years post-surgery, so it is safe to assume that infections presenting after this are haematogenous. Ultra Clean Air does not eliminate early deep infection, so some early infections are not related to air quality. It is not practical to undertake widespread detailed retrospective analyses of cases. When monitoring infection rates there needs to be a balance between failing to record infections related to surgical technique and waiting many years to record low numbers of very late presenting problems. We suggest that registries should regard infections documented within three years of surgery as treatment complications. For any figures or tables, please contact the authors directly

Introduction. Operating theatre airflow can be measured using pulsed lasers (particle image velocimetry) but the process is difficult to do in 3D. Cup, vane or hot wire anemometers provide only 2D information. 3D measurements enable better understanding of airflow. Patients/Materials & Methods. We used a Windmaster ultrasound 3D anemometer (Skyview systems), which uses three ultrasound transmitters to measure velocity in XYZ planes, with a sampling rate of 32 Hz. Post processing was done using MATLAB. An operating theatre with an Howorth Exflow canopy was studied. Equipment, including lights, was moved. A 50 cm grid was marked, and measurements were made at intervals up to the ceiling. Door opening was observed within the clean zone and the peripheral zone, next to the door and on the opposite side of the room. Anaesthetic screens were studied during operating. Airflow was visualised initially using video of smoke puffs and subsequently measured using the aeronometer. Results. In the upper part of the ultraclean canopy air velocity was 0.34 m/s with a standard deviation of 0.02 m/s, indicating an almost constant velocity. In the periphery there was more turbulence and horizontal air movement. Door opening had no effect on air movements in the clean zone. In the periphery there was an increase in horizontal airflow when the doors are closed. There is a pattern of upward airflow against an anaesthetic screen. This is unlikely to be caused by warming blankets. If the partial wall of the enclosure is lowered this results in a fast washout of air towards the anaesthetist. Discussion. Traditional anaesthetic screens may interfere with airflow. Door opening is a lesser effect. Conclusion. The 3D anemometer enables detailed mapping of airflow within an ultra clean air operating theatre. The data obtained will enable the construction of more accurate computational fluid dynamic models of operating theatres