Incidence, Common Pathogens, and Risk Factors for Infection after Primary Anterior Cruciate Ligament Reconstruction: A Systematic Review.

We sought to assess the current literature to present a comprehensive summary of the incidence, common pathogens, and risk factors for infection after anterior cruciate ligament (ACL) reconstruction. PubMed, CINAHL, EMBASE, and Scopus databases were searched for relevant studies reporting on infection after ACL reconstruction. Two reviewers independently screened the extracted studies for adherence to inclusion and exclusion criteria. Studies were selected if they reported on the incidence of infection, pathogens cultured from infected knees, or risk factors for infection after primary ACL reconstruction. Exclusion criteria consisted of studies with fewer than 100 patients or studies that included revision ACL reconstruction. Fifty studies met the inclusion and exclusion criteria, reporting on a total of 316,214 ACL reconstructions. Included studies evaluated between 123 and 104,255 patients. The overall incidence of infection was 0.60% (0.15-2.44%). The most common pathogens were Staphylococcus aureus, S. epidermidis, and coagulase-negative Staphylococci. Five studies reported that the use of hamstring autograft was a statistically significant risk factor for infection after ACL reconstruction, thus making hamstring autograft the most commonly reported risk factor. Other reported risk factors included male sex, use of immuno-suppressive medications or intraarticular steroid injections, prior knee surgery, and diabetes. Systematic review of the literature revealed that infection after ACL reconstruction remains an infrequent event with an incidence of 0.60% (0.15-2.44%). Furthermore, the most common pathogens are from the Staphylococcus genus of bacteria, comprising 84% of all culture-positive infections. Multiple risk factors have been reported for ACL reconstruction; however, statistical significance varied across studies. Together, these findings may help guide physicians in the prevention and treatment of infection after ACL reconstruction.

Patient Perception of Skin Cancer Reduction by Nicotinamide Correlates With Use.

Introduction Nicotinamide (Vitamin B3) has been shown to reduce the rate of non-melanoma skin cancers by 23%, yet most patients do not know that this supplement reduces skin cancer. Understanding patient beliefs about skin cancer reduction attributed to nicotinamide is important to appropriately counsel patients on oral supplement use and ultimately to prevent non-melanoma skin cancers. Objective The objective of this study was to determine the association between nicotinamide use and perceived efficacy in skin cancer reduction. Methods Patients who underwent Mohs surgery in 2019 were sent an online survey assessing nicotinamide use, efficacy compared to sunscreen, and perceived skin cancer risk reduction. Results Data from 50 surveys revealed a perceived risk reduction attributed to nicotinamide of 31.2% for basal cell carcinoma (BCC), 30.2% for squamous cell carcinoma (SCC), and 24.3% for melanoma. In the subset of respondents taking nicotinamide, the perceived risk reduction was significantly higher at 41.2% for BCC and 38.3% for SCC (p<0.05) and positively correlated with reported nicotinamide use (p<0.05). The perceived risk reduction of melanoma was not significantly increased in patients taking nicotinamide (31.6%); however, the perceived risk reduction was correlated with nicotinamide use (p<0.05). In addition, 15.6% of respondents believed that nicotinamide was more effective than sunscreen at preventing skin cancer. Conclusion A larger perceived reduction of non-melanoma skin cancers attributed to nicotinamide is associated with increased oral nicotinamide use. Better patient education regarding the reduction of skin cancers with oral nicotinamide will need to be implemented to change patients' perceptions of the value of nicotinamide.

Diagnosis of Skin Disease in Moderately to Highly Pigmented Skin by Artificial Intelligence.

BACKGROUND: Triage of patients with skin diseases often includes an initial assessment by a nurse or general practitioner, followed by a dermatologist. Artificial intelligence (AI) systems have been reported to improve clinician ability to diagnose and triage skin conditions. Previous studies have also shown that diagnosis in patients with skin of color can be more challenging. PURPOSE: This study seeks to determine the performance of AI in the screening and triage of benign-neoplastic, malignant-neoplastic, and non-neoplastic skin conditions for Fitzpatrick skin types IV-VI. METHODS: A set of 163 non-standardized clinical photographs of skin disease manifestations from patients with Fitzpatrick skin types IV-VI were obtained through a publicly available dataset (Scale AI and MIT Research Lab, “Fitzpatrick 17 Dataset”). All photos were diagnosed by a specialist and categorized into three disease classes: benign-neoplastic, malignant-neoplastic, or non-neoplastic. There were 23, 14, and 122 cases of each disease class, respectively. RESULTS: Overall, the AI was able to classify the disease classes with a high degree of accuracy for the Top 1 diagnosis (86.50%). Based on its first prediction, the AI demonstrated the greatest accuracy when classifying non-neoplastic conditions (90.98%), high accuracy in detecting malignant-neoplastic conditions (77.78%), and moderate accuracy of classifying benign-neoplastic conditions (69.57%). CONCLUSION: The AI had an overall accuracy of 86.50% in diagnosing skin disease in Fitzpatrick skin types IV to VI. This is an improvement over reported clinician diagnostic accuracy of 44.3% in darker skin types. Incorporating AI into front-line screening of skin conditions could thereby assist in patient triage and shorten the time to accurate diagnosis. Schneider LG, Mamelak AJ, Tejani I, et al. Diagnosis of skin disease in moderately to highly pigmented skin by artificial intelligence. J Drugs Dermatol. 2023;22(7):647-652. doi:10.36849/JDD.7581.

Pancreatic cyst fluid glucose: rapid, inexpensive, and accurate diagnosis of mucinous pancreatic cysts.

BACKGROUND: The most widely accepted biochemical test for preoperative differentiation of mucinous from benign, nonmucinous pancreatic cysts is cyst fluid carcinoembryonic antigen. However, the diagnostic accuracy of carcinoembryonic antigen ranges from 70% to 86%. Based on previous work, we hypothesize that pancreatic cyst fluid glucose may be an attractive alternative to carcinoembryonic antigen. METHODS: Pancreatic cyst fluid was collected during endoscopic or operative intervention. Diagnoses were pathologically confirmed. Glucose and carcinoembryonic antigen were measured using a patient glucometer and automated analyzer/enzyme-linked immunosorbent assay. Sensitivity, specificity, accuracy, and receiver operator characteristic analyses were performed. RESULTS: Cyst fluid samples from 153 patients were evaluated (mucinous: 25 mucinous cystic neoplasms, 77 intraductal papillary mucinous neoplasms, 4 ductal adenocarcinomas; nonmucinous: 21 serous cystic neoplasms, 9 cystic neuroendocrine tumors, 14 pseudocysts, 3 solid pseudopapillary neoplasms). Median cyst fluid glucose was lower in mucinous versus nonmucinous cysts (19 vs 96 mg/dL; P < .0001). With a threshold of ≤ 50 mg/dL, cyst fluid glucose was 92% sensitive, 87% specific, and 90% accurate in diagnosing mucinous pancreatic cysts. In comparison, cyst fluid carcinoembryonic antigen with a threshold of >192 ng/mL was 58% sensitive, 96% specific, and 69% accurate. Area under the curve for glucose and CEA were similar at 0.91 and 0.92. CONCLUSION: Cyst fluid glucose has significant advantages over carcinoembryonic antigen and should be considered for use as a routine diagnostic test for pancreatic mucinous cysts.