Epidemiological retrospective analysis in major burn patients: single centre medical records from 2009 to 2019

A 10-year mono-center study on patients with burns ≥70% TBSA: prediction model construction and multicenter validation - retrospective cohort

BACKGROUND

Burn injuries with ≥70% total body surface area (TBSA) are especially acute and life-threatening, leading to severe complications and terrible prognosis, while a powerful model for the prediction of overall survival (OS) is lacking. The objective of this study is to identify prognostic factors for the OS of patients with burn injury ≥70% TBSA and construct and validate a feasible predictive model.

MATERIALS AND METHODS

Patients diagnosed with burns ≥70% TBSA admitted and treated between 2010 and 2020 in our hospital were included. A cohort of the patients from the Kunshan explosion were assigned as the validation set. The χ2 test and K-M survival analysis were conducted to identify potential predictors for OS. Then, multivariate Cox regression analysis was performed to identify the independent factors. Afterward, we constructed a nomogram to predict OS probability. Finally, the Kunshan cohort was applied as an external validation set.

RESULTS

Sex, the percentage of third-degree and fourth-degree burns as well as organ dysfunction were identified as significant independent factors. A nomogram only based on the factors of the individuals was built and evidenced to have promising predictive accuracy, accordance, and discrimination by both internal and external validation.

CONCLUSIONS

This study recognized significant influencing factors for the OS of patients with burns ≥70% TBSA. Furthermore, our nomogram proved to be an effective tool for doctors to quickly evaluate patients' outcomes and make appropriate clinical decisions at an early stage of treatment.

Evolution of two metabolic genes involved in nucleotide and amino acid metabolism in Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic human pathogen causing various severe infections. Understanding genetic mechanisms of its metabolic versatility aids in developing novel antibacterial drugs and therapeutic strategies to address multidrug-resistant P. aeruginosa infections. The metabolism of nucleotides and amino acids contributes to the cycle of two key biological macromolecules in the genetic central dogma. Guanine deaminase (GuaD) catalyzes the deamination of guanine to produce xanthine to maintain the homeostasis of the nucleotide pool, and transporters specific to BCAAs (termed as BraT) import BCAAs to keep its intracellular availability level. However, little is known about the evolution of GuaD and BraT in P. aeruginosa population. Here, two copies turned out to be widespread in P. aeruginosa population for each of GuaD and BraT. The phylogenic analysis demonstrated that GuaD1 and BraB were inherited from the ancestor of Pseudomonas, while GuaD2 and BraZ were additionally acquired via evolutionary events in the ancestors of P. aeruginosa. The functional divergence of two copies was supported by different distribution patterns of dN/dS ratios, divergent expression levels, differentially co-expressed genes, and their functional enrichment modules with few intersections. Besides, some co-expressed genes with known functions are involved in infecting hosts, forming biofilm and resisting antibiotic treatment. Taken together, functional divergence following copy number increase and differentiation of co-expression networks might confer greater metabolic potential to P. aeruginosa, especially in response to host immune responses and antibiotic treatments in clinical settings.

Automatic wound closure system: closure of large wounds by stretching the skin around the wound

Large-wound treatment often requires autologous skin grafting or skin flap transfer, causing iatrogenic secondary injuries. Thus, we have developed an automatic wound closure system that consists of a stretch module, microcontroller, and touch screen. Full-thickness wounds (8 × 14 cm) on Bama miniature pigs were manually closed by direct suture in control animals and with three different tension levels performed by the automatic device in the experimental animals. Wound-closure conditions, post-closure healing, and scars were evaluated. Post-operative microscopic changes in collagen fibers, local cell apoptosis, and changes in vascular density were compared between the two wound-closure techniques. In the control group and the first experimental group, which used a traction force of 15 N, primary wound closure could not be achieved. The other two experimental groups used a traction force of 30 N and 60 N and all wounds achieved primary closure. Collagen-fiber stretching was observed histologically in all groups and collagen-fiber breakdown occurred in some wounds when the traction force was 60 N. Scar hyperplasia was significantly reduced in the automatic wound closure system groups. The collagen content decreased, cell apoptosis increased, and vascular density decreased in local tissues in the early post-closure stage, but eventually recovered to normal-skin levels. In summary, we developed an automatic wound closure system that effectively and safely stretches dermal-collagen fibers under an appropriate traction force (30 N) and stretch wound-peripheral skin to cover the wound, achieve primary closure, and reduce scar hyperplasia.

Identification of cuproptosis-related gene clusters and immune cell infiltration in major burns based on machine learning models and experimental validation

Introduction

Burns are a global public health problem. Major burns can stimulate the body to enter a stress state, thereby increasing the risk of infection and adversely affecting the patient's prognosis. Recently, it has been discovered that cuproptosis, a form of cell death, is associated with various diseases. Our research aims to explore the molecular clusters associated with cuproptosis in major burns and construct predictive models.

Methods

We analyzed the expression and immune infiltration characteristics of cuproptosis-related factors in major burn based on the GSE37069 dataset. Using 553 samples from major burn patients, we explored the molecular clusters based on cuproptosis-related genes and their associated immune cell infiltrates. The WGCNA was utilized to identify cluster-specific genes. Subsequently, the performance of different machine learning models was compared to select the optimal model. The effectiveness of the predictive model was validated using Nomogram, calibration curves, decision curves, and an external dataset. Finally, five core genes related to cuproptosis and major burn have been was validated using RT-qPCR.

Results

In both major burn and normal samples, we determined the cuproptosis-related genes associated with major burns through WGCNA analysis. Through immune infiltrate profiling analysis, we found significant immune differences between different clusters. When K=2, the clustering number is the most stable. GSVA analysis shows that specific genes in cluster 2 are closely associated with various functions. After identifying the cross-core genes, machine learning models indicate that generalized linear models have better accuracy. Ultimately, a generalized linear model for five highly correlated genes was constructed, and validation with an external dataset showed an AUC of 0.982. The accuracy of the model was further verified through calibration curves, decision curves, and modal graphs. Further analysis of clinical relevance revealed that these correlated genes were closely related to time of injury.

Conclusion

This study has revealed the intricate relationship between cuproptosis and major burns. Research has identified 15 cuproptosis-related genes that are associated with major burn. Through a machine learning model, five core genes related to cuproptosis and major burn have been selected and validated.

Outbreak of Pseudomonas aeruginosa High-Risk Clone ST309 Serotype O11 Featuring blaPER-1 and qnrVC6

Pseudomonas aeruginosa is a leading cause of hospital-acquired infections worldwide. Biofilm production, antibiotic resistance, and a wide range of virulence factors contribute to their persistence in nosocomial environments. We describe an outbreak caused by a multidrug-resistant P. aeruginosa strain in an ICU. Antibiotic susceptibility was determined and blaPER-1 and qnrVC were amplified via PCR. Clonality was determined using PFGE and biofilm formation was studied with a static model. A combination of antibiotics was assessed on both planktonic cells and biofilms. WGS was performed on five isolates. All isolates were clonally related, resistant to ceftazidime, cefepime, amikacin, and ceftolozane-tazobactam, and harbored blaPER-1; 11/19 possessed qnrVC. Meropenem and ciprofloxacin reduced the biofilm biomass; however, the response to antibiotic combinations with rifampicin was different between planktonic cells and biofilms. WGS revealed that the isolates belonged to ST309 and serotype O11. blaPER-1 and qnrVC6 were associated with a tandem of ISCR1 as part of a complex class one integron, with aac(6')-Il and ltrA as gene cassettes. The structure was associated upstream and downstream with Tn4662 and flanked by direct repeats, suggesting its horizontal mobilization capability as a composite transposon. ST309 is considered an emerging high-risk clone that should be monitored in the Americas.

Deficiencies of Rule-Based Technology-Generated Antibiograms for Specialized Care Units

The objective of this study was to compare the pathogens and susceptibilities of the current automated, rule-based technology (RBT) antibiogram with one manually collected through chart review with additional rules applied. This study was a two-year, retrospective cohort study and included all bacterial cultures within the first 30 days from patients admitted to a single Burn Center. The current RBT antibiogram served as the control, and new antibiogram versions were created using additional rules and compared to the control. Six-hundred fifty-seven patients were admitted (61% excluded for lack of cultures). 59% had at least one hospital-acquired risk factor, with over one-third having recent illicit drug use and one-third having a recent hospitalization. Of the 410 cultures included, 57% were Gram-negative, and half were from wound infections. Sensitivities were significantly different when comparing the manual and the RBT version after including factors such as days since admission, presence of hospital-acquired risk factors, or previous antibiotic courses. Recommended empiric Gram-negative antibiotics changed from double coverage to a single β-lactam with >90% susceptibility. The susceptibilities between the first and subsequent courses were dramatically different. Before developing an antibiogram or interpreting the output, it is important to consider which automated criteria are utilized, especially for units with extended lengths of stay.

Novel Resistance Regions Carrying TnaphA6, blaVIM-2, and blaPER-1, Embedded in an ISPa40-Derived Transposon from Two Multi-Resistant Pseudomonas aeruginosa Clinical Isolates

Antibiotic resistance is an alarming problem throughout the world and carbapenem-resistant Pseudomonas aeruginosa has been cataloged as critical in the World Health Organization list of microorganisms in urgent need for the development of new antimicrobials. In this work, we describe two novel resistance regions responsible for conferring a multidrug resistance phenotype to two clinical isolates of P. aeruginosa (Pa873 and Pa6415) obtained from patients hospitalized in the ICU of University Hospital of Uruguay. Bacterial identification and antibiotic susceptibility tests were performed using MALDI-TOF and the Vitek 2 system, respectively. WGS was performed for both isolates using Oxford Nanopore Technologies and Illumina and processed by means of hybrid assembly. Both isolates were resistant to ceftazidime, cefepime, piperacillin-tazobactam, aztreonam, and imipenem. Strain Pa6415 also showed resistance to ciprofloxacin. Both strains displayed MICs below the susceptibility breakpoint for CAZ-AVI plus 4 mg/L of aztreonam as well as cefiderocol. Both resistance regions are flanked by the left and right inverted repeats of ISPa40 in two small regions spanning 39.3 and 35.6 kb, for Pa6415 and Pa873, respectively. The resistance region of Pa6415 includes TnaphA6, and the new Tn7516 consists of IRi, In899, qacEΔ1-sul1-ISCR1, qnrVC6-ISCR1-bla_PER-1-qacEΔ1-sul1, araJ-like, IS481-like tnpA, ISPa17, and IRR. On the other hand, the resistance region of Pa873 includes Tnaph6 and the new Tn7517 (IRi, In899, qacEΔ1-sul1, ISCR1-bla_PER-1-qacEΔ1-sul1, araJ-like, IS481-like tnpA, ISPa17, and IRR). It is necessary to monitor the emergence of genetic structures that threaten to invalidate the available therapeutic resources.