Prophylactic Antibiotic Therapy for Preventing Poststroke Infection

A Machine Learning Model Based on CT Imaging Metrics and Clinical Features to Predict the Risk of Hospital-Acquired Pneumonia After Traumatic Brain Injury

Objective

To develop a validated machine learning (ML) algorithm for predicting the risk of hospital-acquired pneumonia (HAP) in patients with traumatic brain injury (TBI).

Materials and Methods

We employed the Least Absolute Shrinkage and Selection Operator (LASSO) to identify critical features related to pneumonia. Five ML models-Logistic Regression (LR), Extreme Gradient Boosting (XGB), Random Forest (RF), Naive Bayes Classifier (NB), and Support Vector Machine (SVC)-were developed and assessed using the training and validation datasets. The optimal model was selected based on its performance metrics and used to create a dynamic web-based nomogram.

Results

In a cohort of 858 TBI patients, the HAP incidence was 41.02%. LR was determined to be the optimal model with superior performance metrics including AUC, accuracy, and F1-score. Key predictive factors included Age, Glasgow Coma Score, Rotterdam Score, D-dimer, and the Systemic Immune Response to Inflammation Index (SIRI). The nomogram developed based on these predictors demonstrated high predictive accuracy, with AUCs of 0.818 and 0.819 for the training and validation datasets, respectively. Decision curve analysis (DCA) and calibration curves validated the model's clinical utility and accuracy.

Conclusion

We successfully developed and validated a high-performance ML algorithm to assess the risk of HAP in TBI patients. The dynamic nomogram provides a practical tool for real-time risk assessment, potentially improving clinical outcomes by aiding in early intervention and personalized patient management.

Construction and validation of a predictive model of pneumonia for ICU patients with traumatic brain injury (TBI)

The incidence of pneumonia in ICU patients with TBI is very high, seriously affecting the prognosis. This study aims to construct a predictive model for pneumonia in ICU patients with TBI and provide help for the prevention of TBI-related pneumonia.Clinical data of ICU patients with TBI were collected from the Medical Information Mart for Intensive Care (MIMIC)-IV database and hospital data. Variables were screened by lasso and multivariate logistic regression to construct a predictive nomogram model, verified in internal validation cohort and external validation cohort by receiver operator characteristic (ROC) curve, calibration curve and decision curve analysis (DCA).A total of 1850 ICU patients with TBI were enrolled in the study from the MIMIC-IV database, including 1298 in the training cohort and 552 in internal validation cohort. The external validation cohort included 240 ICU patients with TBI from hospital data. Nine variables were selected from the training cohort by lasso regression and multivariate logistic regression, and a pneumonia prediction nomogram was constructed. This nomogram has a high discrimination in training, internal validation and external validation cohorts (AUC = 0.857, 0.877, 0.836). The calibration curve and DCA showed that this nomogram had a high calibration and better clinical decision-making efficiency.The nomogram showed excellent discrimination and clinical utility to predict pneumonia, and could identify pneumonia high-risk patients early, thus providing personalised treatment strategies for ICU patients with TBI.

Post-Stroke Pneumonia in Real-World Practice: Background, Microbiological Examination, and Treatment

Post-stroke pneumonia (PSP) has an impact on acute ischemic stroke (AIS). Although predictive scores for PSP have been developed, it is occasionally difficult to predict. Clarifying how PSP was treated after its onset in clinical practice is important. Admitted patients with AIS over a 2-year period were retrospectively reviewed. Of 281 patients with AIS, 24 (8.5%) developed PSP. The integer-based pneumonia risk score was higher in patients with PSP. The onset of PSP was frequently seen up to the 4th day of hospitalization. Of patients with PSP, sputum examination yielded Geckler 4 or 5 in only 8.3%. Angiotensin-converting enzyme inhibitor (ACE-I) was more frequently administered to patients with PSP; however, all these cases were started with ACE-I following PSP onset. Nasogastric tubes (NGTs) were inserted in 16 of the patients with PSP, of whom 11 were inserted following PSP onset. Multivariate analysis showed that PSP onset was a poor prognostic factor independent of the female sex, urinary tract infection, and National Institutes of Health Stroke Scale. PSP treatment would benefit from the administration of antimicrobials and ACE-I, as well as NGT insertion. To select effective agents for PSP and evaluate the indications for NGT insertion, further case studies are needed.

Risk factors for and impact of poststroke pneumonia in patients with acute ischemic stroke

Poststroke pneumonia (PSP) is a common complication of stroke and an important cause of death following stroke. However, the treatment of PSP remains inadequate due to severe impairment to the respiratory system by PSP. Thus, it is crucial to focus on preventing PSP to improve the prognosis of patients with stroke.This prospective single-center Cohort study aimed to investigate the risk factors for pulmonary infection following an ischemic stroke and identify whether PSP significantly influences the prognosis of patients after stroke.Altogether, 451 patients who were treated for acute ischemic stroke in the First Affiliated Hospital of Chongqing Medical University in China between April 2017 and April 2018 were enrolled. Clinical data from the patients from admission to 3 months after discharge were collected. PSP was the primary outcome and poor prognosis or death at 3 months following discharge was the secondary outcome observed in this study. We performed logistic regression analyses to identify the risk factors for PSP and test an association between pneumonia and poor prognosis or death after stroke.Our findings revealed the following risk factors for PSP: atrial fibrillation odds ratio (OR) = 2.884, 95% confidence intervals (CI) = 1.316-6.322), being bedridden (OR = 2.797, 95%CI = 1.322-5.921), subject to an invasive procedure (OR = 12.838, 95%CI = 6.296-26.178), massive cerebral infarction (OR = 3.994, 95%CI = 1.496-10.666), and dysphagia (OR = 2.441, 95%CI = 1.114-5.351). Pneumonia was a risk factor for poor prognosis (OR = 2.967, 95%CI = 1.273-6.915) and death (OR = 5.493, 95%CI = 1.825-16.53) after stroke.Hence, since pneumonia increases the risk of poor prognosis and death following acute ischemic stroke, preventing, and managing the risk factors for PSP may improve the prognosis and reduce the mortality after stroke.

High Monocyte-To-Lymphocyte Ratio Is Associated With Stroke-Associated Pneumonia

Purpose: Stroke-associated pneumonia (SAP), a common complication in acute ischemic stroke (AIS) patients, is associated with poor prognosis after AIS. Inflammation plays an important role in the development of SAP. In this study, we aimed to explore the association between the monocyte-to-lymphocyte ratio (MLR) and SAP in AIS patients.

Methods: We continuously enrolled 972 AIS patients. SAP was diagnosed by two trained neurologists and confirmed by radiography, meeting the modified Centers for Disease Control and Prevention criteria. MLR values were measured for all participants, and all patients were evenly classified into three tertiles according to the MLR levels. We used the values that Youden's index max points corresponded to represent the optimal cutoffs, which represented the balance in sensitivity and specificity.

Results: 104 (10.7%) patients were diagnosed with SAP. SAP patients showed a significant increased (P < 0.001) MLR when compared with non-SAP. The optimal cutoff points of MLR were (T1) <0.2513, (T2) 0.2513–0.3843, and (T3) > 0.3843. The incidence of SAP was significantly higher in the third MLR tertile than the first and second MLR tertiles (21.7 vs. 4 vs. 6.5%, respectively, P < 0.001). After adjusting for confounding and risk factors, multivariate regression analysis showed that the third MLR tertile was an independent variable predicting the occurrence of SAP (odds ratio = 3.503, 95%CI = 1.066–11.515, P = 0.039).

Conclusions: Our study showed that higher MLR was significantly associated with SAP in AIS patients. MLR is beneficial for clinicians to recognize patients with a high risk of SAP at an early stage and is an effective way to improve clinical care of SAP patients. Higher MLR could be a helpful and valid biomarker for predicting SAP in clinical practice.

Role of Prophylactic Antibiotics in Critical Care of Stroke Patients - A Preventive Approach to Post-stroke Infections?

Post-stroke complications are very common worldwide and the most common complication is infection. This contributes the most to the mortality rate in stroke patients. Among the infections, pneumonia and urinary tract infections are most common. Hyperthermia following stroke is associated with neuronal damage and worse outcomes. Post-stroke immunosuppression and activation of inflammatory mediators also cause infections. Based on the high mortality caused by post-stroke infections, various trials were done to seek the advantage that prophylactic antibiotics can give in the critical care of stroke patients. Antibiotics, including ceftriaxone (cephalosporin), levofloxacin (fluoroquinolone), penicillin, and minocycline (tetracycline), were used and the stroke patients were followed up to analyze the primary and secondary outcomes. It was concluded that early antibiotic therapy (mostly within 24 hours) leads to a reduced rate of post-stroke infections and reduced fever spikes, whereas follow-up for a longer period of time showed no better functional outcome. Furthermore, mortality and morbidity benefits were also not seen with prophylactic antibiotic therapy. This review helped us to put a nail in the coffin to the earlier thoughts that prophylactic antibiotics are necessary for the critical care of stroke patients.

External Validation of the ISAN, A2DS2, and AIS-APS Scores for Predicting Stroke-Associated Pneumonia

BACKGROUND

The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN), Age, Atrial Fibrillation, Dysphagia, male sex, and National Institutes of Health Stroke Scale (A2DS2), and acute ischemic stroke-associated pneumonia score (AIS-APS) scores were created to predict stroke-associated pneumonia (SAP), one of the most important medical stroke complications. External validation of all such scores in an acute stroke population was the aim of our study.

METHODS

Patients with ischemic or hemorrhagic stroke were prospectively enrolled in the multicenter Stroke-Induced Pneumonia in Andalucía project between October 2014 and May 2016. Receiver operating characteristic curves and linear regression analyses were used to determine discrimination ability of the scores. The Hosmer-Lemeshow goodness-of-fit test and the plot of observed versus predicted SAP risk were used to assess model calibration.

RESULTS

Among 201 included patients, SAP rate was 15.5% (31). Higher ISAN, A2DS2, and AIS-APS scores were related to SAP (all P < .001). The C statistic was .83 (95% confidence interval [CI], .76-.91) for the ISAN score, .80 (95% CI, .70-.89) for the A2DS2 score, and .82 (95% CI, .74-.90) for the AIS-APS score, suggesting good discrimination. The ISAN and AIS-APS scores showed good calibration (Cox and Snell R² = .206 and .174, respectively). The A2DS2 score showed the highest sensitivity (87%), and the AIS-APS score showed the highest specificity (92.8%).

CONCLUSIONS

In our cohort, the external validation of ISAN, A2DS2, and AIS-APS scores have demonstrated their accurate prediction of SAP and the ability of these scores as screening tools to better manage SAP. The AIS-APS score would be recommendable for the development of future clinical trials.

Antibiotic prophylaxis for infections in patients with acute stroke: a systematic review and meta-analysis of randomized controlled trials

Objective

Infections are frequent after stroke and lead to increased mortality and neurological disability. Antibiotic prophylaxis has potential of decreasing the risk of infections and mortality and improving poor functional outcome. Several studies evaluated antibiotic prophylaxis for infections in acute stroke patients have generated conflicting results. The systematic review of randomized clinical trials (RCTs) aimed at comprehensively assessing the evidence of antibiotic prophylaxis for the treatment of acute stroke patients.

Materials and Methods

PubMed, EMBASE, the Cochrane library and the reference lists of eligible articles were searched to identify all potential studies. We included the studies that investigated the efficacy and safety of antibiotic prophylaxis for the treatment of acute stroke patients. The primary outcome included mortality and infection rate. The secondary outcomes included poor functional outcome and adverse events.

Results

Seven trials randomizing 4,261 patients were included. Pooled analyses showed that antibiotic prophylaxis did not improve the mortality (risk ratio (RR) = 1.03, 95% confidence interval (CI) 0.84 to 1.26, p = 0.78, I² = 25%) and poor functional outcome (RR = 0.93, 95% CI 0.80 to 1.08, p = 0.32, I² = 80%), but reduced the incidence of infection (RR = 0.67, 95% CI 0.53 to 0.84, p = 0.0007, I² = 49%). No major side effects were reported. Sensitivity analyses confirmed the results of infection rate and poor functional outcome.

Conclusions

Antibiotic prophylaxis can be used to treat the infectious events of acute stroke patients although it has no potential of decreased mortality and improved functional outcome.