Early mNGS testing for diagnose and prognostic prediction of early onset pneumonia among in-hospital cardiac arrest patients undergoing extracorporeal cardiopulmonary resuscitation.
Metagenomic next-generation sequencing (mNGS) is emerging as a novel diagnostic technology for various infectious diseases; however, limited studies have investigated its application in etiological diagnosis of early onset pneumonia (EOP) among patients undergoing extracorporeal cardiopulmonary resuscitation (ECPR) following in-hospital cardiac arrest (IHCA), The clinical significance of early mNGS in predicting short-term prognosis of IHCA patients after ECPR remains unclear.
This retrospective study included 76 patients with IHCA who underwent ECPR at the First Affiliated Hospital of Zhengzhou University from January 2018 to December 2022. Baseline characteristics and etiological data of all patients during their hospitalization were collected and statistically analyzed. The primary outcome of this study was the diagnosis of EOP, while the secondary outcomes included successful extracorporeal membrane oxygenation (ECMO) weaning and survival at discharge. Additionally, the characteristics of bronchoalveolar lavage fluid (BALF) flora in these patients were compared by analyzing both mNGS results and culture results.
Multivariate logistic regression were employed to analyze the predictors of ECMO weaning failure, mortality at discharge, and the incidence of EOP. Ultimately, patients with lower SOFA scores on admission [OR (95%CI): 1.447 (1.107-1.890), p=0.007] and those who underwent early mNGS testing within 48 hours after ECPR [OR (95%CI): 0.273 (0.086-0.865), p=0.027] demonstrated a higher probability of successful weaning from ECMO. Patients with higher SOFA scores on admission [OR (95%CI): 2.404 (1.422-4.064), p=0.001], and elevated lactate levels [OR (95%CI): 1.176 (1.017-1.361), p=0.029] exhibited an increased likelihood of mortality at discharge. Furthermore, early mNGS detection [OR (95%CI): 0.186 (0.035-0.979), p=0.047], and lower CRP levels (48h-7d after ECMO) [OR (95%CI):1.011 (1.003-1.019), p=0.006] were associated with a reduced incidence of EOP. In addition, the pathogens detected by mNGS within 48 hours after ECPR were mainly oral colonizing bacteria and viruses, and viruses were in the majority, while all BALF cultures were negative. In contrast, between 48 hours and 7 days after ECPR, BALF cultures were positive in all EOP patients.
Early mNGS testing to identify microbial flora facilitates timely adjustment of antibiotic regimens, thereby reducing the incidence of EOP and improving short-term prognosis in patients undergoing ECPR following IHCA.
Guo RM
，Li XX
，Zhou YH
，Liu YJ
，Li J
，Fu GW
，Zhao H
，Zhang X
，Zhao YC
... -
《Frontiers in Cellular and Infection Microbiology》
Effect of metagenomic next-generation sequencing on clinical outcomes in adults with severe pneumonia post-cardiac surgery: a single-center retrospective study.
Reports on the application of metagenomic next-generation sequencing (mNGS) in adult patients with severe pneumonia after cardiac surgery remain limited. This study aimed to evaluate the clinical outcomes of mNGS analysis of bronchoalveolar lavage fluid (BALF) in such patients.A retrospective cohort study was conducted on adult patients with severe pneumonia after cardiac surgery. Samples were collected from patients in the surgical intensive care unit (SICU) of Sichuan Provincial People's Hospital between January 2019 and March 2024. Upon diagnosis of severe pneumonia, bronchoalveolar lavage fluid was obtained via bronchoscopy within 24 h. The mNGS group was composed of patients tested using mNGS and conventional microbiological tests. BALF was detected only by the conventional microbiological test (CMT) method in the CMT group, which involved examining bacterial and fungal smears and cultures at least. We reviewed a total of 4,064 cardiac surgeries, and based on the inclusion criteria, a total of 113 adult patients with severe pneumonia after cardiac surgery were included in this study. The overall positive rate detected by mNGS was significantly higher than that of the culture method (98% vs. 58%, P<0.0001). After receipt of the microbiological results, the mNGS group exhibited a higher incidence of antibiotic adjustments in comparison to the CMT group (P = 0.0021). After adjusting the treatment plan based on microbial testing results, the mNGS group showed an improvement in ventilator-free days within 28 days (P = 0.0475), with a shorter duration of invasive ventilation compared to the CMT group (P = 0.0208). The detection of mNGS can significantly improve the Acute Physiology and Chronic Health Evaluation-II (APACHE II) score (P = 0.0161) and Sequential Organ Failure Assessment (SOFA) score (P = 0.0076) on the 7th day after admission to the SICU. In this study, the mNGS group showed signs of having a positive impact on the length of stay in ICU (median: 9 days, IQR: 7-10 days vs. median: 10 days, IQR: 8-13.75 days, P = 0.0538), length of stay in Hospital (median: 20 days, IQR: 17-28 days vs. median: 25 days, IQR: 18-29 days, P = 0.1558), mortality in 28 days (19% vs. 20%, P = 0.8794), in-hospital mortality (19% vs. 22%, P = 0.7123); however, statistical analysis did not confirm these differences to be significant. mNGS could serve as a valuable complement to conventional diagnostic approaches in adult patients with severe pneumonia after cardiac surgery, potentially improving diagnostic accuracy and leading to more precise and timely interventions, with significant potential to inform clinical decision-making and enhance patient outcomes.
Xiang C
，Wu X
，Li T
，Tang X
，Zhang Y
，Zeng F
，Xiang H
，Chen T
，Kuang Z
，Liu F
，Yang T
，Chen X
，Chen J
，Wu Y
，Huang X
，Wang Y
，Pan C
，Wang Y
... -
《Scientific Reports》
Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
，Chen CW
，Yen HK
，Lin YP
，Lai CY
，Wang JL
，Groot OQ
，Janssen SJ
，Schwab JH
，Hsu FM
，Lin WH
... -
《-》
ResearchGate
(全网免费下载)
钛学术
(全网免费下载)
