Large scale 3-Phase Clinical Trial
This section describes a large 3-phase clinical trial conducted simultaneously in 3 different hospitals in the US, each with different types of patient populations. Funding for this trial was provided by the U.S. Army Medical Research and Materiel Command.
This large ground breaking clinical trial was conducted in the US to evaluate the the impact of introducing copper alloys surfaces into the Medical Intensive Care Units (ICUs) in three hospitals:
Medical University of South Carolina, Charleston, South Carolina, with a general patient population
Memorial Sloan Kettering Cancer Center, New York City, with an immune-compromised patient population
Ralph H. Johnson Veterans Administration Medical Center, also in Charleston, with an elderly, mostly male patient population
The clinical trial was performed in three phases illustrated below.
Phase 1: Measuring baseline amount of bacteria on standard components in the medical ICU rooms
Phase 2: Introducing copper components into random medical ICU rooms and comparing the amount of bacteria found on the copper versus the standard components**
Phase 3: Measuring and comparing the rates at which patients acquire infections in the rooms with copper and standard components***
The bacterial contamination levels on various standard components made of polymers, stainless steel, aluminum, etc., can be seen image of the standard room shown below:
The built environment is a source of pathogens
Total bacteria count per 100 cm sq (n = 668 rooms)
The following components were selected to be fabricated from copper, based upon the observation that they had the highest levels of contamination in phase 1:
Rails of the Patient Bed
Nurse's Call button used by the patient
Arms of the Visitor's Chair
Over-the-Bed patient tray table
Data Input Device-varied by hospital (computer mouse, bezel on touch screen, or where palm of hand rests on a laptop computer)
IV Pole (intravenous pole)
Antimicrobial Copper Components for Medical ICU Patient Rooms
Antimicrobial copper components shown in a Memorial Sloan Kettering Cancer Center Medical ICU Room
The measured levels of bacterial contamination are show in the bar graph shown below. The gray bars indicate the the contamination found on the standard components and the red bars are from the copper components. It is clear that the standard component surfaces have much higher levels of bacteria than the copper surfaces, except for the Data Input Device, which is has the lowest level of bacteria. One explanation is that patients do not touch the Data Input Device. Note that contamination was also low on the copper version but was slightly higher than that found on the standard device.
The average level of contamination is 2647 CFU/sq cm on the standard components versus 465 CFU/sq cm on the copper components. The standard components have over five times more contamination than the copper components. Most noteworthy, the standard bed rail is, by far, the most contaminated surface. This is the key point of interaction between the patient, healthcare worker and visitors. The items in the standard room, listed in decreasing order of their level of contamination, are: the Bed Rail, Call Button, Chair Arms, Tray Table, IV Pole and Data Input Device. In marked contrast, the bacterial level is much lower on each copper component, except for the Data Input Device, as previously mentioned.
It is clear that copper surfaces significantly reduced bacterial levels, but will that impact infection rates?
Number of Bacteria Found on Antimicrobial Copper and Standard Components
As shown below, the infection rates lower by 58% in the copper rooms when compared to the standard rooms. The results are also highly statistically significant, as indicated by its low p value of 0.013. This means that, if this finding were random and unrelated to the copper components, there is only a 1.3% chance of getting this result if the trial were repeated.
Patients treated in ICU with antimicrobial copper surfaces had significantly fewer infections
This positive result raises an interesting question. If I install copper components in my hospital, how long does it take to to get my investment back, and start making a return on my investment? Based upon the cost to treat an infection and the number of infections prevented, it is estimate to take less than two months, or specifically 29.2 to 43.3 days, as shown below.
Basic ROI calculation from US clinical trials
Do higher levels of contamination result in higher rates of infection? YES! The plot shown below includes all the data from both the copper rooms and ordinary rooms and is statistically significant (p=0.038). It shows a correlation between infection rates and contamination levels. In summary, it confirms that higher levels of bacterial contamination result in higher infection rates.
Amount of Bacteria Found on Components in All Room Correlates with Infection Rate
Take Away Message
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** Michael G. Schmidt, Hubert H. Attaway, Peter A. Sharpe, Joseph John Jr., Kent A. Sepkowitz, Andrew Morgan, Sarah E. Fairey, Susan Singh, LisaL. Steed, J. Robert Cantey, Katherine D. Freeman, Harold T. Michels and Cassandra D. Salgado, Sustained Reduction of Microbial Burden on Common Hospital Surfaces through Introduction of Copper, Journal; of Clinical Microbiology, Vol. 50, N0. 7, pp. 2217-2223, July 2012
***Cassandra D. Salgado, Kent A. Sepkowitz, Joseph F. John, J. Robert Cantey, Hubert H. Attaway, Katherine D. Freeman, Peter A. Sharpe, Harold T. Michels, Michael G. Schmidt, Copper Surfaces Reduce the Rate of Healthcare-Acquired Infections in the Intensive Care Unit, Infection Control and Hospital Epidemiology, Vol. 34, No. 5, Special Topics Issue: The Role of the Environment in Infection Prevention, pp. 479-486, May 2013
Other clinical trials have been carried out in the US, Chile, Japan, and South Africa but on a smaller scale. Michels and Michels (2017) is a comprehensive review these clinical trials. PDF links to a few of the journal articles reporting these studies are listed below. The country in which the study was carried out is indicated. Open the file to see the full reference.
Hinsa-Leasure et al. 2016
Ibrahim et al. 2018
Pineta et al. 2017
Casey et al. 2010
Steinhauer et al. 2018
Marais et al. 2010
Michels and Michels