Smartphones are often equipped with inertial sensors capable of measuring individuals' physical activities. Their role in monitoring the patients' physical activities in telemedicine, however, needs to be explored. The main objective of this study was to explore the correlation between a participant's daily step counts and the daily step counts reported by their smartphone. This prospective observational study was conducted on patients undergoing lower limb orthopedic surgery and a group of non-patients. The data collection period was from 2 weeks before until four weeks after the surgery for the patients and two weeks for the non-patients. The participants' daily steps were recorded by physical activity trackers employed 24/7, and an application recorded the number of daily steps registered by the participants' smartphones. We compared the cross-correlation between the daily steps time-series taken from the smartphones and physical activity trackers in different groups of participants. We also employed mixed modeling to estimate the total number of steps. Overall, 1067 days of data were collected from 21 patients (11 females) and 10 non-patients (6 females). The cross-correlation coefficient between the smartphone and physical activity tracker was 0.70 [0.53–0.83]. The correlation in the non-patients was slightly higher than in the patients (0.74 [0.60–0.90] and 0.69 [0.52–0.81], respectively). Considering the ubiquity, convenience, and practicality of smartphones, the high correlation between the smartphones and the total daily step time-series highlights the potential usefulness of smartphones in detecting the change in the step counts in remote monitoring of the patient's physical activity.

Culture of multiple intraoperative tissue samples is the standard of microbiological diagnosis of prosthetic joint infections. Recently, improved sensitivity of using prosthesis sonication method and molecular techniques has been reported in the literature. However, collecting the removed prosthesis as well as additional specimens for molecular analysis is not straightforward for the surgeons and assistants in the operation theatre. Our All-in-a-Box concept addresses the need for simple and unambiguous sampling of clinical specimens in the operating theatre, and to overcome the variation in sampling technique within and between surgical teams and across different hospitals.

The All-in-a-Box concept was developed in close cooperation between surgeons, their operating assistants, clinical microbiologists and molecular biologists in order to ensure the concept is easily implemented in the operating theatre, achieving high completeness, and being well preserved all the way to the laboratory.

All needed equipment, vials and forms are collected in a single box, and corresponding items are clearly color coded to further reduce the likelihood of confusion.

Boxes are designed to address the specific needs for either routine diagnosis or special demands as in clinical studies. Their design is based on large experience in connection with diagnosis of joint prosthesis-related infections. Downstream SOPs for sample processing are included in the All-in-a-box concept and specimens can subsequently be analyzed in parallel by culturing and molecular methods.

We have implemented this concept in two large research projects, we received 1508 (89%) of 1685 scheduled samples during the 2-year project period in the first project despite several different surgical teams and hospitals, while the other project is still ongoing.

All-in-a-Box is useful concept to improve the completeness of routine sampling for microbial analysis.

Recent evidence suggests that the microbial community, its spatial distribution and activity play an important role in the prolongation of treatment and healing of chronic infections. Standard bacterial cultures often underestimate the microbial diversity present in chronic infections. This lack of growth is often due to a combination of inadequate growth conditions, prior usage of antibiotics and presence of slow-growing, fastidious, anaerobic or unculturable bacteria living in biofilms. Thus, diagnosis of chronic infections is challenged by lack of appropriate sampling strategies and by limitations in microbiological testing methods. The purpose of this study was to improve sampling and diagnosis of prosthetic joint infections (PJI) and chronic wounds, especially considering the biofilm issue.

Systematic sampling, sonication of prosthesis and extended culture were applied on patients with chronic wounds and patients with suspected PJIs. Optimized DNA extraction, quantitative PCR, cloning, next generation sequencing and PNA FISH were applied on the different types of specimens for optimized diagnosis. For further investigation of the microbial pathogenesis, in situ transcriptomics and metabolomics were applied.

In both chronic wounds and PJIs, molecular techniques detected a larger diversity of microorganisms than culture methods in several patients. Especially in wounds, molecular methods identified more anaerobic pathogens than culture methods. A heterogeneous distribution of bacteria in various specimens from the same patient was evident for both patient groups. In chronic wounds, multiple biopsies from the same ulcer showed large differences in the abundance of S. aureus and P. aeruginosa at different locations. Transcriptomic and metabolomic analyses indicated the important virulence genes and nutrient acquisition mechanisms of Staphylococcus aureus in situ. As an example, diagnosis and treatment of a patient with a chronic biofilm prosthesis infection persisting for 7 years will be presented.

Our studies show that diagnosis of chronic biofilm related infections required multiple specimen types, standardized sampling, extended culture and molecular analysis. Our results are useful for improvement of sampling, analysis and treatment in the clinic. It is our ambition to translate studies on bacterial activity into clinical practice in the future.

Optimal sampling for culture-based or molecular diagnosis remains highly contested for patients suspected of prosthetic joint infection (PJI). Most existing studies have a retrospective design without a standardized sampling strategy. Therefore, the results are difficult to translate into guidelines. We have conducted a 2-year prospective study with a sampling strategy adaptable to the specific procedure in patients with either hip or knee alloplasty. Thus, comparisons of results obtained with different specimen types and diagnostic methods are possible.

The study enrolled patients with a painful hip or knee alloplasty. The sampling strategy for microbiological diagnosis included multiple specimens of each type (joint fluid, tissue biopsies, bone biopsies, and swabs taken from the prosthesis in situ), and prosthetic components (if removed). Prepacked boxes with containers and accessories for sampling, transport and storage were provided. Microbial culture and bacterial 16S rDNA screening were carried out for all specimen types. Whenever positive upon 16S rDNA screening, samples were analyzed further by sequencing. Peptide nucleic acid-fluorescence in situ hybridization (optimized using filtrations; Filter-PNA-FISH) was limited to a subset thereof.

An overall completeness of ∼90% was obtained by the sampling strategy in 164 procedures (‘cases’) in 131 patients. In 58 cases PJI was suspected, and a revision was carried out. 42 cases were culture-positive, and 16 were culture-negative; one culture-negative case was positive by 16S rDNA sequencing of a corresponding specimen. The contribution to a microbiological diagnosis was high for periprosthetic tissue biopsies (≥ 3 positive out of 5) 90%, prosthetic component(s) 90%, and joint fluid 94%. Conversely, the contribution was sparse for prosthetic swabs 50% and bone biopsies 40%, respectively. Filter-PNA-FISH was used to confirm findings by culture and to demonstrate biofilm formation.

With the described sampling strategy we reached high completeness of complex specimen sets. The sampling strategy may be adapted to other clinical settings with microbiological sampling of similar complexity. We found multiple periprosthetic tissue biopsies, prosthetic component(s) and joint fluid to form the optimal specimen set for culture-based diagnosis. The contribution by 16S rDNA sequencing is still under investigations but the contributions seems moderate probably because of a low rate of antibiotic therapy before the procedure, use of effective culture methods and prolonged incubation (14 days).

Prosthetic joint infection is one of the most challenging complications of joint alloplasty and the diagnosis remains difficult. The aim of the study was to investigate the bacterial flora in surgical samples from 22 prosthetic patients using a panel of culture-independent molecular methods including broad range 16S rRNA gene PCR, cloning, sequencing, phylogeny, quantitative PCR (qPCR), and fluorescence in situ hybridization (FISH). Concomitant samples were cultured by standard methods.

Molecular methods detected presence of bacteria in samples from 12 of 22 patients. Using clone libraries a total of 40 different bacterial species were identified including known pathogens and species not previously described in association with prosthetic joint infections. The predominant species were Propionibacterium acnes and Staphylococcus epidermidis; polymicrobial infections were found in 9 patients. Culture-based methods showed bacterial growth in 8 cases with the predominant species being S. epidermidis. Neither anaerobic bacteria (including P. acnes) nor any of the species not previously described in implant infections were isolated. Additionally, 7 of the 8 culture positive cases were monomicrobial. Overall, the results of culture-based and molecular methods showed concordance in 11 cases (hereof 9 negative by both methods) and discrepancy in 6 cases. In the remaining 5 cases, culture-based methods identified only one species or a group of bacteria (e.g., coagulase negative staphylococci or coryneform rods), while culture-independent molecular methods were able to detect several distinct bacterial species including a species within the group identified by culture. A qPCR assay was developed to assess the abundance of Propionibacterium while S. aureus was quantified by a published S. aureus qPCR assay. These quantifications confirmed the findings from the clone library approach and showed the potential of qPCR for fast detection of bacteria in orthopedic samples. Additionally, both single cells and microcolonies were visualized using FISH and confocal scanning laser microscopy.

In conclusion, the molecular methods detected a more diverse bacterial flora in prosthetic joint infections than revealed by standard culture-based methods, and polymicrobial infections were more frequently observed. The pathogenesis of these microorganisms and their role in implant-associated infections needs to be determined.