A computerized indicator for surgical site infection (SSI) assessment after total hip or total knee replacement: The French ISO-ORTHO indicator

Automated surveillance for surgical site infections (SSI) in hospitals and surveillance networks-expert perspectives for implementation

BACKGROUND

This work aims at providing practical recommendations for implementing automated surveillance (AS) of surgical site infections (SSI) in hospitals and surveillance networks. It also provides an overview of the steps, choices, and obstacles that need to be taken into consideration when implementing such surveillance. Hands-on experience with existing automated surveillance systems of SSI (AS SSI systems) in Denmark, France, the Netherlands and Spain is described regarding trend monitoring, benchmarking, quality control, and research for surveillance purposes.

METHODS

Between April and October 2023, specific aspects/options of various surveillance purposes for AS SSI were identified during regular meetings of the SSI working group in the PRAISE (Providing a Roadmap for Automated Infection Surveillance in Europe) network. Expert discussions provided the basis for this perspective article.

RESULTS

Decisions for implementation of AS SSI systems highly depend on the purpose of the surveillance. AS SSI systems presented here differ according to study population, setting, central or local implementation; the level of automation, design, and the data sources used. However, similarities were found for the rationales of automation, design principles and obstacles that were identified. There was consensus among all the experts that shortcomings in interoperability of databases, limited time, a want of commitment on the part of stakeholders, and a shortage of resources for information technology (IT) specialists represent the main obstacles for implementing AS SSI. To overcome obstacles, various solutions were reported, including training in the development of AS systems and the interpretation of AS SSI results, early consultation of end-users, and regular exchanges between management levels, IT departments, infection prevention and control (IPC) teams, and clinicians.

CONCLUSION

Clarity on the intended application (e.g. purpose of surveillance) and information on the availability of electronic and structured data are crucial first steps necessary for guiding decisions on the design of AS systems. Adequate resources for IT specialists and regular communication between management, IT departments, IPC teams, and clinicians were identified as essential for successful implementation. This perspective article may be helpful for a wider implementation of more homogeneous AS SSI systems in Europe.

Feasibility of automated surveillance of implantable devices in orthopaedics via clinical data warehouse: the Studio study

BACKGROUND

Total hip, knee and shoulder arthroplasties (THKSA) are increasing due to expanding demands in ageing population. Material surveillance is important to prevent severe complications involving implantable medical devices (IMD) by taking appropriate preventive measures. Automating the analysis of patient and IMD features could benefit physicians and public health policies, allowing early issue detection and decision support. The study aimed to demonstrate the feasibility of automated cohorting of patients with a first arthroplasty in two hospital data warehouses (HDW) in France.

METHODS

The study included adult patients with an arthroplasty between 2010 and 2019 identified by 2 data sources: hospital discharge and pharmacy. Selection was based on the health insurance thesaurus of IMDs in the pharmacy database: 1,523 distinct IMD references for primary THSKA. In the hospital discharge database, 22 distinct procedures for native joint replacement allowing a matching between IMD and surgical procedure of each patient selected. A program to automate information extraction was implemented in the 1st hospital data warehouse using natural language processing (NLP) on pharmacy labels, then it was then applied to the 2nd hospital.

RESULTS

The e-cohort was built with a first arthroplasty for THKSA performed in 7,587 patients with a mean age of 67.4 years, and a sex ratio of 0.75. The cohort involved 4,113 hip, 2,630 knee and 844 shoulder surgical patients. Obesity, cardio-vascular diseases and hypertension were the most frequent medical conditions.

DISCUSSION

The implementation of an e-cohort for material surveillance will be easily workable over HDWs France wild. Using NLP as no international IMD mapping exists to study IMD, our approach aims to close the gap between conventional epidemiological cohorting tools and bigdata approach.

CONCLUSION

This pilot study demonstrated the feasibility of an e-cohort of orthopaedic devices using clinical data warehouses. The IMD and patient features could be studied with intra-hospital follow-up and will help analysing the infectious and unsealing complications.

Prophylactic use of vancomycin powder on postoperative infection after total joint arthroplasty

OBJECTIVE

By reviewing the literature analyzing vancomycin powder for preventive surgery, the effect of this method on reducing the infection rate after TJA was systematically evaluated to provide a basis for future clinical work.

METHODS

Using PubMed, Medline, Elsevier, and CNKI, with the following mesh words: "vancomycin", "local / intraoperative / topical / intrawound", "TJA", "TKA", "THA", "total joint arthroplasty", "total knee arthroplasty", "total hip arthroplasty", "infection", and "SSI", to search for case-control research papers on the impact of prophylactic application of vancomycin powder on the incidence of postoperative infection, we compared the overall infection rate in the literature by using RevMan 5.3 meta-analysis software and analyzed the impact of vancomycin on the infection rate of different parts and types of TJA according to different subgroups.

RESULTS

A total of 22 qualified studies were selected; twenty-five studies compared the effect of prophylactic use of vancomycin powder on infection rates after TJA. There were 23,363 cases in total, including 9545 cases in the vancomycin group and 13,818 cases in the control group. The results of the meta-analysis showed that the possibility of postoperative infection after prophylactic use of vancomycin powder was significantly lower than that without vancomycin risk ratio: 0.38 [0.23,0.59], P < 0.01). However, a meta-analysis of randomized controlled trials (RCTs) showed no significant effect of vancomycin on postoperative infection (P = 0.52).

CONCLUSION

Based on the retrospective studies, local prophylactic use of vancomycin powder in TJA can significantly reduce the incidence of postoperative infection. High-quality RCTs should be carried out to further evaluate these results.

Comorbidities directly extracted from the hospital database for adjusting SSI risk in the new national semiautomated surveillance system in France: The SPICMI network

OBJECTIVE

To evaluate the performance of a comorbidity-based risk-adjustment model for surgical-site infection (SSI) reporting and benchmarking using a panel of variables extracted from the hospital discharge database (HDD), including comorbidities, compared to other models that use variables from different data sources.

METHODS

The French national surveillance program for SSI (SPICMI) has collected data from voluntary hospitals in the first 6 months of 2020 and 2021, for 16 selected surgery procedures, using a semiautomated algorithm for detection. Four risk-adjustment models were selected with logistic regression analysis, combining the different patterns of variables: National Nosocomial Infections Surveillance System (NNIS) risk-index components, individual operative data, and 6 individual comorbidities according to International Classification of Disease, Tenth Revision (ICD-10) diagnosis: obesity, diabetes, malnutrition, hypertension, cancer, or immunosuppression. Areas under the curve (AUCs) were calculated and compared.

RESULTS

Overall, 294 SSI were detected among 11,975 procedures included. All 6 comorbidities were related to SSI in the univariate analysis. The AUC of the selected model including comorbidities (0.675; 95% confidence interval [CI], 0.642-0.707), was significantly higher than the AUC of the model without comorbidities (0.641; 95% CI, 0.609-0.672; P = .016) or the AUC using the NNIS-index components (0.598; 95% CI, 0.564-0.630; P < .001). The HDD-based model AUC (0.659; 95% CI, 0.625-0.692) did not differ significantly from the selected model without comorbidities (P = .23).

CONCLUSION

Including HDD-based comorbidities as patient case-mix variables instead of NNIS risk index factors could be an effective approach for risk-adjustment of automated SSI surveillance more widely accessible to hospitals.

Using artificial intelligence to reduce orthopedic surgical site infection surveillance workload: Algorithm design, validation, and implementation in 4 Spanish hospitals

BACKGROUND

Surgical site infection (SSI) surveillance is a labor-intensive endeavor. We present the design and validation of an algorithm for SSI detection after hip replacement surgery, and a report of its successful implementation in 4 public hospitals in Madrid, Spain.

METHODS

We designed a multivariable algorithm, AI-HPRO, using natural language processing (NLP) and extreme gradient boosting to screen for SSI in patients undergoing hip replacement surgery. The development and validation cohorts included data from 19,661 health care episodes from 4 hospitals in Madrid, Spain.

RESULTS

Positive microbiological cultures, the text variable "infection", and prescription of clindamycin were strong markers of SSI. Statistical analysis of the final model indicated high sensitivity (99.18%) and specificity (91.01%) with an F1-score of 0.32, AUC of 0.989, accuracy of 91.27%, and negative predictive value of 99.98%.

DISCUSSION

Implementation of the AI-HPRO algorithm reduced the surveillance time from 975 person/hours to 63.5 person/hours and permitted an 88.95% reduction in the total volume of clinical records to be reviewed manually. The model presents a higher negative predictive value (99.98%) than algorithms relying on NLP alone (94%) or NLP and logistic regression (97%).

CONCLUSIONS

This is the first report of an algorithm combining NLP and extreme gradient-boosting to permit accurate, real-time orthopedic SSI surveillance.

Validation of the first computerized indicator for orthopaedic surgical site infections in France: ISO-ORTHO

BACKGROUND

The French national authority for health (HAS) develops in-hospital indicators for improving quality of care, safety and patient outcome. Since 2017, it has developed a measurement of surgical site infections (SSI) after total hip or knee arthroplasty (TH/KA) by using a computerized indicator, called ISO-ORTHO, based on a hospital discharge database (HDD) algorithm. The aim of the study was to assess the performance of this new indicator .

METHODS

The ISO-ORTHO performance was estimated via its positive predictive value (PPV) among adult patients having undergone a TH/KA between January 1st and September 30th 2018, based on the orthopaedic procedure codes. Patients at very high risk of SSI and/or with SSI not related to the in-hospital care were excluded. SSI were detected from the date of admission up to 90 days after the TH/KA using the ISO-ORTHO algorithm, based on 15 combinations of ICD-10 and procedure codes. Its PPV was estimated by a chart review in volunteer healthcare organisations (HCO).

RESULTS

Over the study period, 777 HCO including 143,227 TH/KA stays were selected, providing 1,279 SSI according to the ISO-ORTHO indicator. The 90-day SSI rate was 0.89 per 100 TH/KA stays (0.98% for THA and 0.80% for TKA). Among the 448 HCO with at least 1 SSI, 250 HCO participated in reviewing 725 SSI charts; 665 were confirmed, giving a PPV of 90.3% [88.2-92.5%], 89.9% [87.1-92.8%] in THA and 90.9% [87.7-94.2%] in TKA.

CONCLUSIONS

The PPV of ISO-ORTHO over 90% confirms its validity for any use according to the HAS method. ISO-ORTHO and detailed information were provided in 2020 to HCO and used for quality assessment and in-hospital risk management.

Fatty acid metabolism-related genes are associated with flavor-presenting aldehydes in Chinese local chicken

Aldehydes are primary volatile organic compounds (VOCs) in local Chinese chicken meat and contribute green grass, fatty, citrus, and bitter almond aromas to chicken meat. To understand the genetic basis of these aldehyde VOC aromas, we used approximately 500 Chinese Jingxing Yellow (JXY) chickens to conduct genome-wide association studies (GWAS) on the flavor traits with the data of single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs). In total, 501 association variants (253 SNPs and 248 INDELs) were found to be suggestively (SNPs: p-value < 2.77e-06 and INDELs: p-value < 3.78e-05) associated with total aldehydes (the sum of nine aldehydes), hexanal, heptanal, benzaldehyde, (E,E)-2,4-nonadienal, octanal, (E)-2-decenal, nonanal, decanal, and octadecanal. Of them, six SNPs and 23 INDELs reached a genome-wide significance level (SNPs: p-value < 1.38e-07 and INDELs: p-value < 1.89e-06). Potential candidate aldehyde genes were functionally annotated for lipid metabolism, especially fatty acid-related pathways and phospholipid-related gene ontology (GO) terms. Moreover, the GWAS analysis of total aldehydes, hexanal, and nonanal generated the most significant signals, and phenotypic content differed between different genotypes at candidate gene-related loci. For total aldehydes and hexanal traits, candidate genes were annotated based on the significant and suggestive variants on chromosomes 3 and 8 with highly polymorphic linkage blocks. The following candidate genes were also identified: GALM, MAP4K3, GPCPD1, RPS6KA2, CRLS1, ASAP1, TRMT6, SDC1, PUM2, ALDH9A1, MGST3, GMEB1, MECR, LDLRAP1, GPAM and ACSL5. We also found that polyunsaturated fatty acids (PUFAs) (C18:2n6c linoleic acid and C18:3n3 linolenic acid) were significantly correlated with total aldehydes and hexanal contents. PUFAs are important aldehyde precursors, and consistently, our results suggested that candidate genes involved in fatty acid pathways and phospholipid GO terms were identified in association loci. This work provides an understanding of the genetic basis of aldehyde formation, which is a key flavor-forming compound.