A nomogram for predicting postoperative urosepsis following retrograde intrarenal surgery in upper urinary calculi patients with negative preoperative urine culture

Yang, Miaomiao; Li, Yongchao; Huang, Fang

doi:10.1038/s41598-023-29352-y

Cited by 6 publications

(2 citation statements)

References 36 publications

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“…The nomogram is a graphical, mathematical model that has been used to predict prognosis by estimating clinical events and integrating relevant prognostic factors in numerous diseases. 7 – 8 The objective of the present study was to validate the prognostic factors of AB-caused HAP and VAP in terms of 90-day mortality among patients in the RICU and to develop a predictive nomogram to individually predict the probability of 90-day mortality among patients with AB-caused HAP and VAP in the RICU.…”

Section: Introductionmentioning

confidence: 99%

Nomogram for predicting 90-day mortality in patients with Acinetobacter baumannii-caused hospital-acquired and ventilator-associated pneumonia in the respiratory intensive care unit

et al. 2023

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Objective We built a prediction model of mortality risk in patients the with Acinetobacter baumannii (AB)-caused hospital-acquired (HAP) and ventilator-associated pneumonia (VAP). Methods In this retrospective study, 164 patients with AB lower respiratory tract infection were admitted to the respiratory intensive care unit (RICU) from January 2019 to August 2021 (29 with HAP, 135 with VAP) and grouped randomly into a training cohort (n = 115) and a validation cohort (n = 49). Least absolute shrinkage and selection operator regression and multivariate Cox regression were used to identify risk factors of 90-day mortality. We built a nomogram prediction model and evaluated model discrimination and calibration using the area under the receiver operating characteristic curve (AUC) and calibration curves, respectively. Results Four predictors (days in intensive care unit, infection with carbapenem-resistant AB, days of carbapenem use within 90 days of isolating AB, and septic shock) were used to build the nomogram. The AUC of the two groups was 0.922 and 0.823, respectively. The predictive model was well-calibrated; decision curve analysis showed the proposed nomogram would obtain a net benefit with threshold probability between 1% and 100%. Conclusions The nomogram model showed good performance, making it useful in managing patients with AB-caused HAP and VAP.

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Section: Introductionmentioning

confidence: 99%

Nomogram for predicting 90-day mortality in patients with Acinetobacter baumannii-caused hospital-acquired and ventilator-associated pneumonia in the respiratory intensive care unit

et al. 2023

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“…Yang et al established a preoperative nomogram to predict postoperative urosepsis for negative preoperative urine culture patients. Unfortunately, there is no postoperative etiological detection to verify urosepsis (Yang et al, 2023). It is not recommended to predict UPB completely out of touch with etiological detection.…”

Section: Introductionmentioning

confidence: 99%

Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria

Jiang

Wei

et al. 2023

Front. Cell. Infect. Microbiol.

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BackgroundThe identification of uropathogens (UPBs) and urinary tract colonizing bacteria (UCB) conduces to guide the antimicrobial therapy to reduce resistant bacterial strains and study urinary microbiota. This study established a nomogram based on the nanopore-targeted sequencing (NTS) and other infectious risk factors to distinguish UPB from UCB.MethodsBasic information, medical history, and multiple urine test results were continuously collected and analyzed by least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression was used to determine the independent predictors and construct nomogram. Receiver operating characteristics, area under the curve, decision curve analysis, and calibration curves were used to evaluate the performance of the nomogram.ResultsIn this study, the UPB detected by NTS accounted for 74.1% (401/541) of all urinary tract microorganisms. The distribution of ln(reads) between UPB and UCB groups showed significant difference (OR = 1.39; 95% CI, 1.246–1.551, p < 0.001); the reads number in NTS reports could be used for the preliminary determination of UPB (AUC=0.668) with corresponding cutoff values being 7.042. Regression analysis was performed to determine independent predictors and construct a nomogram, with variables ranked by importance as ln(reads) and the number of microbial species in the urinary tract of NTS, urine culture, age, urological neoplasms, nitrite, and glycosuria. The calibration curve showed an agreement between the predicted and observed probabilities of the nomogram. The decision curve analysis represented that the nomogram would benefit clinical interventions. The performance of nomogram with ln(reads) (AUC = 0.767; 95% CI, 0.726–0.807) was significantly better (Z = 2.304, p-value = 0.021) than that without ln(reads) (AUC = 0.727; 95% CI, 0.681–0.772). The rate of UPB identification of nomogram was significantly higher than that of ln(reads) only (χ2 = 7.36, p-value = 0.009).ConclusionsNTS is conducive to distinguish uropathogens from colonizing bacteria, and the nomogram based on NTS and multiple independent predictors has better prediction performance of uropathogens.

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The mayo adhesive probability score predicts postoperative fever and sepsis in retrograde intrarenal surgery

Hsieh,

Chang,

Chueh

et al. 2024

Urolithiasis

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Infectious complications are among the most common and potentially life-threatening morbidities of retrograde intrarenal surgery (RIRS). Few predictive tools on these complications include radiological signs. The Mayo adhesive probability (MAP) score is an image-based scoring system that incorporates two radiological signs: perinephric fat stranding and perinephric fat thickness. Previous studies have suggested an association between these signs and febrile urinary tract infection (UTI) following lithotripsy. This study aimed to evaluate the predictive factors, including the MAP score, for post-RIRS fever and sepsis. A total of 260 patients who underwent 306 RIRS between October 2019 to December 2023 due to renal or upper ureteral stones were included in this retrospective study. Patient demographics, perioperative characteristics, stone factors, radiological signs, and MAP scores were recorded. Multivariate logistic regression analysis was used to evaluate the risk factors associated with postoperative fever and sepsis. Postoperative fever and sepsis occurred in 20.8% and 8.5% of the patients, respectively. On multivariate analysis, female gender, history of recurrent UTI, larger maximal stone diameter, and higher MAP score were independent risk factors for postoperative fever and sepsis. Identifying the risk factors for post-RIRS infectious complications is imperative to providing the proper perioperative management. The MAP score is a promising, easily calculated, image-based scoring system that predicts post-RIRS fever and sepsis.

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A nomogram for predicting postoperative urosepsis following retrograde intrarenal surgery in upper urinary calculi patients with negative preoperative urine culture

Cited by 6 publications

References 36 publications

Nomogram for predicting 90-day mortality in patients with Acinetobacter baumannii-caused hospital-acquired and ventilator-associated pneumonia in the respiratory intensive care unit

Nomogram for predicting 90-day mortality in patients with Acinetobacter baumannii-caused hospital-acquired and ventilator-associated pneumonia in the respiratory intensive care unit

Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria

The mayo adhesive probability score predicts postoperative fever and sepsis in retrograde intrarenal surgery

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