ICM document update: Russian translation completed

ICM document Russian translation is completed. It is available online at the following link.


2018 ICM book updates

Dear Delegates many of you are still waiting to receive a hard copy of the ICM book. The 5000 copies we had are all accounted for at this point. We are planning to have 300-400 copies of the book for distribution at the AAOS either in some of our industry partners’ booth or during off-site activities like the ICM symposium that will be held on Thursday evening at Venetian. In addition, some copies will be distributed in European meetings this month. We hope you will be able to get your hands on a copy soon.

Very sorry if we were unable to get you a copy. We distributed the books on first come first served basis and have ran out of the hard copies at this point. We may consider a second print run in the future.

Please note that the entire document (and the soon to come translations) are available on the App (ICMPhilly) and also the website (www.icmphilly.com).


Paper of the week: Reconsidering Strategies for Managing Chronic Periprosthetic Joint Infection in Total Knee Arthroplasty: Using Decision Analytics to Find the Optimal Strategy Between One-Stage and Two-Stage Total Knee Revision

Paper of the Week: Reconsidering Strategies for Managing Chronic Periprosthetic Joint Infection in Total Knee Arthroplasty: Using Decision Analytics to Find the Optimal Strategy Between One-Stage and Two-Stage Total Knee Revision. Srivastava K, Bozic KJ, Silverton C, Nelson AJ, Makhni EC, Davis JJ.J Bone Joint Surg Am. 2019 Jan 2;101(1):14-24. doi: 10.2106/JBJS.17.00874.

Summary and Editorial by Sreeram Penna

In this study, researchers used decision analysis to determine the optimal decision for the management of chronic periprosthetic infection (PJI) following total knee arthroplasty (TKA). Researchers constructed an expected-value decision tree to estimate the quality-adjusted-life-years (QALYs) and costs associated with 1-stage and 2-stage revision. Two decision trees were created one was for all pathogens, a second decision tree was constructed for difficult to treat organisms including methicillin-resistant. A Markov model was used to calculate the QALYs over a 15-year period. The model input was based on values such as mortality rates and reinfection rates published in original studies since 2000. Cost data were obtained from Medicare data.

Results showed that 1-stage revision was the optimal decision in producing greater health utility in both decision trees in the analysis. Some of the issues with research are that there is limited data on infection eradication 1-stage revisions for PJI. Seven studies included in the above simulation for 1-stage revision showed reinfection rates of 7% compared to 15% for 2-stage revision. Researchers contend that even if we assume reinfection rate for 2-stage revision to be around 10% infection rates of 1-stage be more than 30% to be considered non-optimal strategy compared to 2-stage revision as decision model captures significant morbidity and mortality associated with a 2-stage procedure. The simulation also captures cost savings of around $19,000 to $27,000 per infection (depending on pathogen) for 1-stage revision.

Normally in PJI treatment 2 stage revision procedure is considered the gold standard for infection eradication. However, it is known that such strategy place significant morbidity on the patient. In addition, a significant number of patients does not complete the reimplantation procedure in 2-stage operation.[1] This study gives an opportunity for orthopaedic community to rethink options in managing patients with PJI and further research is required.

[1] Gomez MM, Tan TL, Manrique J, Deirmengian GK, Parvizi J. The Fate of Spacers in the Treatment of Periprosthetic Joint Infection. J Bone Joint Surg Am 2015;97:1495–502. doi:10.2106/JBJS.N.00958.


Paper of the week: Humidity a potential risk factor for prosthetic joint infection in a tropical Australian hospital.

Paper of the week: Humidity a potential risk factor for prosthetic joint infection in a tropical Australian hospital. Armit D, Vickers M, Parr A, Van Rosendal S, Trott N, Gunasena R, Parkinson B. ANZ J Surg. 2018 Dec;88(12):1298-1301. doi: 10.1111/ans.14916. Epub 2018 Oct 24.

Summary and Editorial by Sreeram Penna and Javad Parvizi

This study aims to determine the role of humidity as a risk factor for the development of prosthetic joint infection (PJI) in total knee replacement patients. In this single-center retrospective study researchers looked at the incidence of deep PJI and correlated with daily weather data. Deep PJI was diagnosed using the Australian Commission on Safety and Quality in Health Care criteria for deep incisional organ space infection. Weather variables used for analysis was relative humidity and apparent temperature on the day of the primary procedure. Results showed humidity more than 60% (OR 1.4) and apparent temperature more than 30-degree centigrade (OR 2.4) are possible potential risk factors for the development of deep PJI. However, these variables were not statistically significant.

A Study by Parkinson et al. based on Australian Orthopaedic Association National Joint Replacement Registry, have shown higher PJI incidence in tropical regions (0.73%) compared to the non-tropical areas (0.37%). [1] Their results also showed seasonal variation in the tropical areas with a higher incidence in summer/fall (0.98%) compared to winter/spring (0.51%). Hot and humid weather increases sweating and provide conditions to bacterial growth which might explain the reason behind the increase in infection. One issue with the above study is that weather variables were recorded on the day of surgery, where the patient is indoors, and air conditioning would provide a constant stable environment inside the hospital.


[1] Parkinson B, Armit D, McEwen P, Lorimer M, Harris IA. Is Climate Associated With Revision for Prosthetic Joint Infection After Primary TKA? Clin Orthop Relat Res 2018;476:1200–4. doi:10.1007/s11999.0000000000000144.


Paper of the week: Cutibacterium acnes and the shoulder microbiome.

Paper of the week: Cutibacterium acnes and the shoulder microbiome. Qiu B, Al K, Pena-Diaz AM, Athwal GS, Drosdowech D, Faber KJ, Burton JP, O’Gorman DB. J Shoulder Elbow Surg. 2018 Oct;27(10):1734-1739. doi: http://dx.doi.org/10.1016/j.jse.2018.04.019.

Summary and Editorial by Dr. Sreeram Penna and Dr. Surena Namdari

The aim of this study is to determine if there is a microbiome in the native shoulder joint and whether Cutibacterium acnes (previously known as Propionibacterium acnes), the most common cause of shoulder infections, is part of this microbiome. The indolent nature of Cutibacerium acnes (C. acne) along with lack of significant biomarker response makes it a difficult bacteria to manage. Also, its presence in culture samples in cases with negative joint infection leads to a theory that this bacterium could be commensal in the native joint.

In this study, researchers collected tissue samples from patients undergoing primary open shoulder arthroplasty with no history of previous infection. Twenty-three patients were included in the study. Researchers collected tissue samples from skin, subcutaneous fat, anterior edge of the supraspinatus tendon, middle glenohumeral ligament, and humeral head. A total of 136 samples were collected. Samples were then analyzed using 16s RNA sequencing to identify operational taxonomic units. After careful removal of contamination, results showed that 53 samples showed positive for microbial genome and most abundant bacterial type was Acinetobacter and Oxalobacteraceae. C. acnes was only identified in one skin sample. Anatomical structure wise 74% of supraspinatus tendon samples and 49% of joint capsule samples were positive for a microbial genome.

This study shows that the native shoulder joint is not completely sterile, and bacteria are present. Interestingly C. acnes is not present in the native shoulder joint. Advances in the genomic analysis are making it easier to identify bacterial species and to characterize the microbial genome. Studies of 16s RNA sequencing remain limited by both the risk of contamination and the risk of identifying dead bacteria [1,2]. Further research is needed on the impact of oral and gut microbial load on tissue microbiome as it is well known that transient bacteremia can occur following activities like oral brushing and can lead to tissue seeding.[3,4]


[1]    Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biology 2014;12:87. doi:10.1186/s12915-014-0087-z.

[2]    Weiss S, Amir A, Hyde ER, Metcalf JL, Song SJ, Knight R. Tracking down the sources of experimental contamination in microbiome studies. Genome Biology 2014;15:564. doi:10.1186/s13059-014-0564-2.

[3]    Maharaj B, Coovadia Y, Vayej AC. An investigation of the frequency of bacteraemia following dental extraction, tooth brushing and chewing. Cardiovasc J Afr 2012;23:340–4. doi:10.5830/CVJA-2012-016.

[4]    Lockhart Peter B., Brennan Michael T., Sasser Howell C., Fox Philip C., Paster Bruce J., Bahrani-Mougeot Farah K. Bacteremia Associated With Toothbrushing and Dental Extraction. Circulation 2008;117:3118–25. doi:10.1161/CIRCULATIONAHA.107.758524.