Analysis of the Ribonuclease A Superfamily of Antimicrobial Peptides in Patients Undergoing Chronic Peritoneal Dialysis

Pottanat, Neha; Brook, Amy C.; Bartošová, Mária; Cortado, Hanna; Gupta, Shivani; Li, Birong; Jackson, A Reeves; Vonau, Martin; Cohen, Sanford; Ferrara, Maria; Ching, Christina B.; Spencer, John David; Brauner, Annelie; Fraser, Donald; Schmitt, Claus Peter; Eberl, Matthias; Ayoob, Rose; Becknell, Brian

doi:10.1038/s41598-019-44219-x

Cited by 4 publications

(3 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, given the retrospective nature of this study, there might be potential selection bias. Second, we did not consider new biomarkers such as IL-6, COX-2, RNase 3, and RNase 7 ( 27 , 28 ). Future studies should develop or update the prediction model to include new biomarkers.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Prediction Model for the Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Observational Study

et al. 2022

View full text Add to dashboard Cite

AimPeritoneal dialysis (PD)-associated peritonitis (PDAP) is a severe complication of PD. It is an important issue about whether it can be cured. At present, there is no available prediction model for peritonitis cure. Therefore, this study aimed to develop and validate a prediction model for peritonitis cure in patients with PDAP.MethodsPatients with PD who developed PDAP from four dialysis centers in Northeast China were followed up. According to the region of PD, data were divided into training and validation datasets. Initially, a nomogram for peritonitis cure was established based on the training dataset. Later, the nomogram performance was assessed by discrimination (C-statistic), calibration, and decision curves.ResultsTotally, 1,011 episodes of peritonitis were included in the final analysis containing 765 in the training dataset and 246 in the validation dataset. During the follow-up period, peritonitis cure was reported in 615 cases from the training dataset and 198 from the validation dataset. Predictors incorporated in the final nomogram included PD duration, serum albumin, antibiotics prior to admission, white cell count in peritoneal dialysate on day 5 (/μl) ≥ 100/μl, and type of causative organisms. The C-statistic values were 0.756 (95% CI: 0.713–0.799) in the training dataset and 0.756 (95% CI: 0.681–0.831) in the validation dataset. The nomogram exhibited favorable performance in terms of calibration in both the training and validation datasets.ConclusionThis study develops a practical and convenient nomogram for the prediction of peritonitis cure in patients with PDAP, which assists in clinical decision-making.

show abstract

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Prediction Model for the Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Observational Study

et al. 2022

View full text Add to dashboard Cite

show abstract

“…First, given the retrospective nature of this study, there might be potential selection bias. Second, we did not take into account new biomarkers such as IL-6, COX-2, RNase 3 and RNase 7 31,32 . Future studies should develop or update the prediction model to include new biomarkers.…”

Section: Discussionmentioning

confidence: 99%

A Prediction Model for Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Study

Meng

Yang

Zhu

et al. 2021

Preprint

View full text Add to dashboard Cite

AimPeritoneal dialysis (PD)-associated peritonitis (PDAP) is a severe complation of PD. And it is an important issue about whether it can be cured. At present, there is no available prediction model for peritonitis cure. Therefore, the present work aimed to develop and validate a risk prediction model for peritonitis cure in PDAP patients.MethodsPD patients who developed PDAP from four dialysis centers in Northeast China were followed up. According to the region of PD, data were divided into training and validation datasets. First of all, a nomogram for peritonitis cure was established based on the training dataset. Later, performance of the nomogram model was assessed by discrimination (C-statistic), calibration and decision curves. ResultsIn total, 1063 episodes of peritonitis were included in the final analysis, including 806 in the training dataset and 257 in the validation dataset. During the follow-up period, 621 and 199 cases in the training and validation datasets, respectively, reported peritonitis cure. Predictors incorporated in the final nomogram model included PD duration, serum albumin, antibiotics prior to admission, and type of causative organisms. The C-statistic values were 0.76 (95% CI: 0.72–0.80) in the training dataset and 0.77 (95% CI: 0.70–0.84) in the validation dataset. The nomogram exhibited favorable performance in terms of calibration in both the training and validation datasets.ConclusionThis study develops a practical and convenient nomogram for the prediction of peritonitis cure in PDAP patients, which assists in the clinical decision-making.

show abstract

“…Recent studies showed antimicrobial peptides can potentially serve as novel antimicrobial agents. Different AMPs can be utilized by innate immune cells and proteins to counterbalance microbial infections, and contribute more to other cellular and/or biomolecular pathways 64 . Table 4 summarizes the antibacterial activities of AMPs with molecular weight ranging from 1.55 to 41.44 kDa.…”

Section: Antimicrobial Peptidesmentioning

confidence: 99%

Highlights on the alternatives to antibiotic therapy against bacterial infection

Sircar

Mandal

2021

J. Drug Delivery Ther.

View full text Add to dashboard Cite

The antibiotic resistance among gram-positive and gram-negative pathogenic bacteria is of global health concern. This has prompted the development of new effective drugs. But the discovery and development of new drugs is slow, and the emergence of resistance to such new drugs, on the other hand, is rapid as well as continuous among the bacteria. Therefore, in tackling the emergence of antibiotic resistant pathogenic bacteria finding alternative ways is vital. This communication, based on the published scientific data, summarizes the antibacterial capacity of some naturally derived agents such as honey, phytocomponents, probiotics, and antimicrobial peptides that might bring new essence in biomedicine. Keywords: Bacterial resistance, alternative therapeutics, honey, phytomedicine, probiotics, antimicrobial peptides.

show abstract

Analysis of the Ribonuclease A Superfamily of Antimicrobial Peptides in Patients Undergoing Chronic Peritoneal Dialysis

Cited by 4 publications

References 52 publications

Development and Validation of a Prediction Model for the Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Observational Study

Development and Validation of a Prediction Model for the Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Observational Study

A Prediction Model for Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Study

Highlights on the alternatives to antibiotic therapy against bacterial infection

Contact Info

Product

Resources

About