Impact of patient comorbidities on surgical site infection within 90 days of primary and revision joint (hip and knee) replacement

Edmiston, Charles E.; Chitnis, A.S.; Lerner, Jason; Folly, E.; Holy, Chantal E.; Leaper, David

doi:10.1016/j.ajic.2019.03.030

Cited by 19 publications

(23 citation statements)

References 41 publications

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“…The infections are further complicated by a lack of clinical signs and the absence of inflammatory markers [10][11][12][13]. Assessment of patients with previous complications or increased risk factors (Table 1) [9,[14][15][16][17][18], including altered microbiota or impaired immune response, is important as these aspects are associated with possibility of SSI [19].…”

Section: Surgical Site Infectionsmentioning

confidence: 99%

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Dynamics of skin microbiota in shoulder surgery infections

Fatima

Bjarnsholt

Bay

2021

APMIS

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Post-surgical infections arise due to various contributing factors. Most important is the presence of potential pathogenic microorganisms in the skin complemented by the patient´s health status. Cutibacterium acnes is commonly present in the pilosebaceous glands and hair follicle funnels in human skin. After surgical intervention, these highly prevalent, slow-growing bacteria can be found in the deeper tissues and in proximity of implants. C. acnes is frequently implicated in post-surgical infections, often resulting in the need for revision surgery. This review summarizes the current understanding of microbial dynamics in shoulder surgical infections. In particular, we shed light on the contribution of C. acnes to post-surgical shoulder infections as well as their colonization and immune-modulatory potential. Despite being persistently found in post-surgical tissues, C. acnes is often underestimated as a causative organism due to its slow growth and the inefficient detection methods. We discuss the role of the skin environment constituted by microbial composition and host cellular status in influencing C. acnes recolonization potential. Future mapping of the individual skin microbiome in shoulder surgery patients using advanced molecular methods would be a useful approach for determining the risk of post-operative infections.

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Section: Surgical Site Infectionsmentioning

confidence: 99%

“…is not only the first colonizer but also the most consistent and most abundant cutaneous genus [45,46]. Its ability to colonize is regulated by the presence of a sebum-rich environment, microbial interactions and host immune status [15,47,48]. It is notable that the increase of Cutibacterium spp.…”

Section: Pathogens In Shoulder Surgical Infectionsmentioning

confidence: 99%

Dynamics of skin microbiota in shoulder surgery infections

Fatima

Bjarnsholt

Bay

2021

APMIS

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“…The number of TKA procedures is predicted to grow to 1.26 million in the US by 2030 [ 1 ]. Surgical site infection (SSI), with an incidence rate ranging from 1.1% to 4.8%, is a serious complication following TKA, causing considerable morbidity and increasing the economic burden of patients [ 2 , 3 , 4 , 5 , 6 ]. Preoperative evaluation of risk factors, such as patient characteristics and comorbid conditions, allows physicians to provide specific clinical intervention that can reduce the risk of infection following TKA [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…Preoperative evaluation of risk factors, such as patient characteristics and comorbid conditions, allows physicians to provide specific clinical intervention that can reduce the risk of infection following TKA [ 7 , 8 ]. Consequently, investigation of risk factors associated with infection after TKA using registry [ 9 , 10 , 11 , 12 ], government health claims [ 4 , 13 , 14 , 15 ], and hospital databases [ 5 , 6 , 16 , 17 , 18 ] has gained growing interest [ 6 ]. However, there are two important issues that remain to be addressed: First, the various preferred comorbid conditions potentially associated with infection after TKA were evaluated in previous studies.…”

Section: Introductionmentioning

confidence: 99%

“…However, there are two important issues that remain to be addressed: First, the various preferred comorbid conditions potentially associated with infection after TKA were evaluated in previous studies. This limitation may be caused by the lack of information available on comorbid conditions in the databases [ 5 , 6 , 9 , 10 , 11 , 12 , 16 , 17 , 18 ], or by the excessive numbers of International Classification of Diseases (ICD) diagnostic codes that could be used to identify patients’ comorbid conditions [ 4 , 13 , 14 , 15 ]. A more comprehensive evaluation of comorbid conditions associated with SSI after TKA is still lacking.…”

Section: Introductionmentioning

confidence: 99%

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Using the Phecode System to Identify the Preoperative Clinical Phenotypes Associated with Surgical Site Infection in Patients Undergoing Primary Total Knee Arthroplasty: The Sex Differences

Hung

Liu

Wen

2022

JCM

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Sex-related differences among comorbid conditions associated with surgical site infection (SSI) after total knee arthroplasty (TKA) are unclear. This population-based cohort study used a novel approach with a Phecode system to evaluate preoperative clinical phenotypes (i.e., comorbid conditions) associated with SSI after TKA and delineate sex-related differences in phenotypes. Using the Taiwan National Health Insurance Research Database (2014–2018), 83,870 patients who underwent TKA were identified. Demographic and SSI data during the 90-day postoperative follow-up were obtained. Comorbidities identified by the International Classification of Diseases within 1 year before TKA were recorded and mapped into Phecodes representing phenotypes. The overall rate of 90-day SSI was 1.3%. In total, 1663 phenotypes were identified among 83,870 patients—1585 and 1458 phenotypes for female (n = 62,018) and male (n = 21,852) patients, respectively. According to multivariate logistic regression analysis, the SSI odds ratio significantly increased with the presence of each of the 16 phenotypes. Subgroup analysis revealed that the presence of 10 and 4 phenotypes significantly increased SSI risk in both sexes; only one phenotype was common to both sexes. Therefore, comorbid conditions and sex should be considered in preoperative SSI risk evaluation in patients undergoing primary TKA. These findings provide new perspectives on susceptibility, prevention, and treatment in these patients.

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Modified Frailty Index Associates With Transoral Robotic Surgery Complications and Survival: A National Database Study

Jain,

Goldberg,

Briggs

et al. 2024

The Laryngoscope

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ObjectiveThe modified frailty index (mFI‐5) is a National Surgical Quality Improvement Program‐derived 5‐factor index that has been proven to reflect frailty and predict morbidity and mortality. We hypothesize that mFI‐5 is a valid predictive measure in the transoral robotic surgery (TORS) population.MethodsRetrospective study utilizing the TriNetX US‐collaborative health records network querying for TORS patients. Cohorts were stratified by mFI‐5 score which uses five ICD‐10 codes: nonindependent functional status, hypertension, obstructive respiratory disease, heart failure, and diabetes mellitus. Cohorts were matched by age using propensity score matching. Outcome measures included survival, infection, pneumonia, tracheostomy dependence, and percutaneous endoscopic gastrostomy dependence. Reported odds ratios were normalized to mFI‐5 = 0.ResultsA total of 9,081 patients were included in the final analysis. Greater mFI‐5 scores predicted decreased survival and increased incidence of postoperative infection and pneumonia. Odds of 5‐year mortality were 1.93 (p = 0.0003) for mFI‐5 = 2 and 1.90 (p = 0.0002) for mFI‐5 = 3. Odds of 2‐year mortality were 1.25 (p = 0.0125) for mFI‐5 = 1, 1.58 (p = 0.0002) for mFI‐5 = 2, and 1.87 (p = 0.003) for mFI‐5 = 3. Odds of postoperative infection were 1.51 (p = 0.02) for mFI‐5 = 2 and 1.78 (p = 0.05) for mFI‐5 = 3. Two‐year odds of developing pneumonia were 1.69 (p = 0.0001) for mFI‐5 = 2 and 2.84 (p < 0.0001) for mFI‐5 = 3. Two‐month odds of pneumonia were 1.50 (p = 0.0259) for mFI‐5 = 2 and 2.55 (p = 0.0037) for mFI‐5 = 3. mFI‐5 = 4 or 5 had too few patients to analyze. Using polynomial regression to model age versus incident 5‐year post‐TORS death (R2 = 0.99), mFI‐5 scores better predicted survival than age alone.ConclusionThis study demonstrates that mFI‐5 predicts mortality, pneumonia, and postoperative infection independently of age.Level of Evidence4 Laryngoscope, 2024

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Impact of patient comorbidities on surgical site infection within 90 days of primary and revision joint (hip and knee) replacement

Cited by 19 publications

References 41 publications

Dynamics of skin microbiota in shoulder surgery infections

Dynamics of skin microbiota in shoulder surgery infections

Using the Phecode System to Identify the Preoperative Clinical Phenotypes Associated with Surgical Site Infection in Patients Undergoing Primary Total Knee Arthroplasty: The Sex Differences

Modified Frailty Index Associates With Transoral Robotic Surgery Complications and Survival: A National Database Study

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