Neutrophil–lymphocyte ratio as a predictor of adverse outcome in patients with community‐acquired pneumonia: A systematic review

Utility of pneumonia severity assessment tools for mortality prediction in healthcare-associated pneumonia: a systematic review and meta-analysis

Accurate prognostic tools for mortality in patients with healthcare-associated pneumonia (HCAP) are needed to provide appropriate medical care, but the efficacy for mortality prediction of tools like PSI, A-DROP, I-ROAD, and CURB-65, widely used for predicting mortality in community-acquired and hospital-acquired pneumonia cases, remains controversial. In this study, we conducted a systematic review and meta-analysis using PubMed, Cochrane Library (trials), and Ichushi web database (accessed on August 22, 2022). We identified articles evaluating either PSI, A-DROP, I-ROAD, or CURB-65 and the mortality outcome in patients with HCAP, and calculated the pooled sensitivities, specificities, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the summary area under the curves (AUCs) for mortality prediction. Additionally, the differences in predicting prognosis among these four assessment tools were evaluated using overall AUCs pooled from AUC values reported in included studies. Eventually, 21 articles were included and these quality assessments were evaluated by QUADAS-2. Using a cut-off value of moderate in patients with HCAP, the range of pooled sensitivity, specificity, PLR, NLR, and DOR were found to be 0.91-0.97, 0.15-0.44, 1.14-1.66, 0.18-0.33, and 3.86-9.32, respectively. Upon using a cut-off value of severe in those patients, the range of pooled sensitivity, specificity, PLR, NLR, and DOR were 0.63-0.70, 0.54-0.66, 1.50-2.03, 0.47-0.58, and 2.66-4.32, respectively. Overall AUCs were 0.70 (0.68-0.72), 0.70 (0.63-0.76), 0.68 (0.64-0.73), and 0.67 (0.63-0.71), respectively, for PSI, A-DROP, I-ROAD, and CURB-65 (p = 0.66). In conclusion, these severity assessment tools do not have enough ability to predict mortality in HCAP patients. Furthermore, there are no significant differences in predictive performance among these four severity assessment tools.

Enhancing pneumonia prognosis in the emergency department: a novel machine learning approach using complete blood count and differential leukocyte count combined with CURB-65 score

BACKGROUND

Pneumonia poses a major global health challenge, necessitating accurate severity assessment tools. However, conventional scoring systems such as CURB-65 have inherent limitations. Machine learning (ML) offers a promising approach for prediction. We previously introduced the Blood Culture Prediction Index (BCPI) model, leveraging solely on complete blood count (CBC) and differential leukocyte count (DC), demonstrating its effectiveness in predicting bacteremia. Nevertheless, its potential in assessing pneumonia remains unexplored. Therefore, this study aims to compare the effectiveness of BCPI and CURB-65 in assessing pneumonia severity in an emergency department (ED) setting and develop an integrated ML model to enhance efficiency.

METHODS

This retrospective study was conducted at a 3400-bed tertiary medical center in Taiwan. Data from 9,352 patients with pneumonia in the ED between 2019 and 2021 were analyzed in this study. We utilized the BCPI model, which was trained on CBC/DC data, and computed CURB-65 scores for each patient to compare their prognosis prediction capabilities. Subsequently, we developed a novel Cox regression model to predict in-hospital mortality, integrating the BCPI model and CURB-65 scores, aiming to assess whether this integration enhances predictive performance.

RESULTS

The predictive performance of the BCPI model and CURB-65 score for the 30-day mortality rate in ED patients and the in-hospital mortality rate among admitted patients was comparable across all risk categories. However, the Cox regression model demonstrated an improved area under the ROC curve (AUC) of 0.713 than that of CURB-65 (0.668) for in-hospital mortality (p<0.001). In the lowest risk group (CURB-65=0), the Cox regression model outperformed CURB-65, with a significantly lower mortality rate (2.9% vs. 7.7%, p<0.001).

CONCLUSIONS

The BCPI model, constructed using CBC/DC data and ML techniques, performs comparably to the widely utilized CURB-65 in predicting outcomes for patients with pneumonia in the ED. Furthermore, by integrating the CURB-65 score and BCPI model into a Cox regression model, we demonstrated improved prediction capabilities, particularly for low-risk patients. Given its simple parameters and easy training process, the Cox regression model may be a more effective prediction tool for classifying patients with pneumonia in the emergency room.

The Clinical Value of Systemic Immune Inflammation Index (SII) in Predicting the Severity of Hospitalized Children with Mycoplasma Pneumoniae Pneumonia: A Retrospective Study

Objective

The Systemic Immune Inflammation Index (SII), as a novel inflammation biomarker that comprehensively reflects the inflammatory and immune status of the body, has not been reported in studies on Mycoplasma pneumoniae pneumonia (MPP) in children. This study aims to investigate whether SII can serve as an effective indicator for evaluating the condition of MPP.

Methods

This study recruited a total of 304 hospitalized patients with mycoplasma pneumoniae pneumonia (MPP), including 78 patients with severe MPP (SMPP) and 226 patients with non-SMPP. Univariate analysis using chi-square test, t-test, and Mann-Whitney U-test was conducted to analyze the clinical data of the patients. Logistic regression analysis was employed to identify the main risk factors for SMPP. Receiver operating characteristic curves were plotted to evaluate the potential of using neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic immune response index (SIRI) to predict the severity of MPP.

Results

The ROC curve results show that patients with SII values ≥ 699.00 are more likely to develop severe MPP (sensitivity=0.876, specificity=0.987, AUC=0.940), and the predictive value of SII is significantly better than that of NLR, PLR, and SIRI. The results of multivariate logistic regression analysis indicate that SII can serve as a major risk factor for distinguishing non-SMPP from SMPP.

Conclusion

This study suggests that SII may be an effective indicator for predicting the severity of MPP in children. SII is more sensitive and specific than NLR, PLR, and SIRI in evaluating the condition of MPP.

The Neutrophil/Lymphocyte Ratio and Outcomes in Hospitalized Patients with Community-Acquired Pneumonia: A Retrospective Cohort Study

We aimed to assess the prognostic role of the neutrophil/lymphocyte ratio (NLR) in community-acquired pneumonia (CAP) via a single-center retrospective cohort of hospitalized adult patients from 1/2009 to 12/2019. Patients were dichotomized into lower NLR (≤12) and higher NLR (>12). The primary outcome was mortality. ICU admission and hospital- and ICU-free days were secondary outcomes. The pneumonia severity index (PSI) and the NLR's ability to predict outcomes was also tested. An NLR ≤12 was observed in 2513 (62.2%) patients and >12 in 1526 (37.8%). After adjusting for PSI, the NLR was not associated with hospital mortality (odds ratio [OR] 1.115; 95% confidence interval [CI] 0.774, 1.606; p = 0.559), but it was associated with a higher risk of ICU admission (OR 1.405; 95% CI 1.216, 1.624; p < 0.001). The PSI demonstrated acceptable discrimination for mortality (area under the receiver operating characteristic curve [AUC] 0.78; 95% CI 0.75, 0.82) which was not improved by adding the NLR (AUC 0.78; 95% CI 0.75, 0.82, p = 0.4476). The PSI's performance in predicting ICU admission was also acceptable (AUC 0.75; 95% CI 0.74, 0.77) and improved by including the NLR (AUC 0.76, 95% CI 0.74, 0.77, p = 0.008), although with limited clinical significance. The NLR was not superior to the PSI for predicting mortality in hospitalized CAP patients.

Can inflammatory indexes predict the spontaneous passage of common bile duct stones?

OBJECTIVES

We aimed to determine whether inflammatory indexes (II), including the neutrophil-lymphocyte ratio (NLR), the C-reactive protein (CRP) to albumin ratio (CAR), the CRP-lymphocyte ratio (CLR), and the systemic immune-inflammation index (SIII) can be diagnostic for common bile duct stones (CBDSs) excretion before endoscopic retrograde cholangiopancreatography (ERCP).

BACKGROUNDS

Because of the spontaneous clearance, it is mandatory to ascertain the presence of CBDSs before ERCP.

METHODS

Retrospectively, we evaluated two groups. Group A included 96 records in which CBDSs existed in magnetic resonance cholangiopancreatography (MRCP) and ERCP. Group B included 36 records in which CBDSs existed in MRCP but not ERCP. IIs were calculated on presentation and before ERCP.

RESULTS

Stone detection in ERCP had a 3.992-fold (95% 1.769-9.007) higher probability with a stone larger than 3.25 mm in MRCP. Before ERCP, CAR, and CLR values were higher in group A than in group B (3.88 [1.25-14.14] and 1.24 [0.50-9.66], p = 0.027 versus 8.79 [2.19-35] and 2.67 [1.02-20.05], p = 0.029, respectively). Higher CRP, CAR, and CLR values were considered significant for detecting a stone in ERCP (AUC: 0.627 [0.519-0.739], 0.625 [0.513-0.737], and 0.624 [0.514-0.734], respectively).

CONCLUSION

Low CRP, CAR, and CLR values might associate with the spontaneous migration of CBDS.

Associations of complete blood cell count-derived inflammatory biomarkers with asthma and mortality in adults: a population-based study

Objective

This study aims to assess the associations of complete blood cell count (CBC)-derived inflammatory biomarkers with the prevalence of asthma and mortality.

Methods

Data was collected from the 1999-2018 National Health and Nutrition Examination Survey (NHANES). Mortality was identified using the National Death Index until December 31, 2019. The study analyzed the relationship between CBC-derived inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic inflammatory response index (SIRI), and systemic immune-inflammation index (SII), and the prevalence of asthma using multiple logistic regressions. To assess the significance of CBC-derived inflammatory biomarkers in predicting all-cause and respiratory disease mortality in asthma patients, Cox proportional regressions and the random survival forest (RSF) analysis were utilized.

Results

A total of 48,305 participants were included, with a mean age of 47.27 ± 0.18 years and 49.44% male. Among them, 6,403 participants had asthma, with a prevalence of 13.28%. The all-cause and respiratory disease deaths at a median follow-up of 8.2 (4.5, 12.8) years were 929 and 137 respectively. After adjusting for confounders, the prevalence of asthma was found to be positively associated with NLR, PLR, MLR, SIRI and SII. Compared to the lowest quartile, the highest quartile of NLR (HR=1.765 [1.378-2.262]), MLR (HR=1.717 [1.316-2.241]), SIRI (HR=1.796 [1.353-2.383]) and SII (HR=1.432 [1.141-1.797]) were associated with an increased risk of all-cause mortality. These associations were more pronounced in respiratory disease mortality of asthma patients. RSF analysis showed that MLR had the highest predictive value for all-cause and respiratory disease mortality in adults with asthma. The sensitivity analysis demonstrated the stability of our results.

Conclusion

The findings suggest that CBC-derived inflammatory biomarkers are associated with a higher risk of all-cause and respiratory disease mortality in adults with asthma.

Variation in infant rhesus monkeys' (Macaca mulatta) neutrophil-to-lymphocyte ratio is associated with environmental conditions, emotionality, and cortisol concentrations, and predicts disease-related outcomes

The neutrophil-to-lymphocyte ratio (NLR) is a predictor of morbidity for a variety of medical conditions, but little is known about how variation in NLR arises. We examined variation in this measure in a sample of 4577 infant rhesus monkeys (54.8 % female), who participated in the BioBehavioral Assessment program at the California National Primate Research Center at 3-4 months of age. Lower values for NLR were seen for animals reared indoors, for animals that were raised to be free of specific pathogens, and for males. In addition lower NLR was associated with higher stress values of cortisol and with greater emotionality in response to an acute stressor. Finally, lower NLR in infancy was associated with greater risk for developing airways hyperresponsiveness (a hallmark of asthma); with display of diarrhea up to 3.97 years later; and with greater viral load when infected with the simian immunodeficiency virus at a mean of 6.1 years of age. Infant NLR was a better predictor of viral load than was a contemporaneously obtained measure of NLR. Infant and adult values of NLR were only modestly correlated; one reason may be that the infant measure was obtained during stressful conditions and the adult measure was obtained under baseline conditions. We propose that NLR is an integrated outcome measure reflecting organization and interaction of stress-response and immune systems. As such, assessment of NLR under conditions of stress may be a particularly useful marker of individual differences in morbidity, especially for conditions in which stress plays an important role, as in asthma, diarrhea/colitis, and AIDS.

Legionella pneumophila Infections during a 7-Year Retrospective Analysis (2016-2022): Epidemiological, Clinical Features and Outcomes in Patients with Legionnaires' Disease

Legionella pneumophila (LP) is one of the main causative agents of community-acquired pneumonia in Europe and its fifth bacterial cause in Italy (4.9%). We conducted a seven year retrospective analysis of LP infection serogroup 1 in Asti, Piedmont, between 2016 and 2022. Patients were included if they tested positive for the Legionella urinary antigen. Clinical, laboratory, and radiologic data were analyzed to describe the risk factors for mortality. Fifty patients with LD were collected, mainly male, with a median age of 69 years. The main comorbidities were cardiovascular diseases (50%), pulmonary diseases (26%), and neurological diseases (12%). The most common clinical presentations were fever, respiratory, gastrointestinal, and neurologic symptoms. Older age (p = 0.004), underlying cardiovascular diseases (p = 0.009), late diagnosis at admission (p = 0.035), and neurological symptoms at diagnosis (p = 0.046) were more common in the non-survivor group. Moreover, a septic-shock presentation or the need for non-invasive ventilation at admission were associated with a higher mortality. No considerable differences in the biochemical data were found between the two groups except for the median neutrophil count, lymphocyte count, neutrophil-to-lymphocyte ratio, and PCT value. We did not find any differences in mortality related to the choice of antibiotic regimen. Differences in outcome were associated with the median duration of treatment (p =< 0.001) but not to the choice of antibiotic regimen (mainly levofloxacin or azithromycin). In conclusion, early individuation of the wide spectrum of clinical characteristics of LP infection such as respiratory, cardiac, and neurological manifestations of the patient's comorbidities, and significant biochemical data should help clinicians flag high risk patients and potentially improve their outcome.

NLR, MLR, PLR and RDW to predict outcome and differentiate between viral and bacterial pneumonia in the intensive care unit

The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and red cell distribution width (RDW) are emerging biomarkers to predict outcomes in general ward patients. However, their role in the prognostication of critically ill patients with pneumonia is unclear. A total of 216 adult patients were enrolled over 2 years. They were classified into viral and bacterial pneumonia groups, as represented by influenza A virus and Streptococcus pneumoniae, respectively. Demographics, outcomes, and laboratory parameters were analysed. The prognostic power of blood parameters was determined by the respective area under the receiver operating characteristic curve (AUROC). Performance was compared using the APACHE IV score. Discriminant ability in differentiating viral and bacterial aetiologies was examined. Viral and bacterial pneumonia were identified in 111 and 105 patients, respectively. In predicting hospital mortality, the APACHE IV score was the best prognostic score compared with all blood parameters studied (AUC 0.769, 95% CI 0.705–0.833). In classification tree analysis, the most significant predictor of hospital mortality was the APACHE IV score (adjusted P = 0.000, χ2 = 35.591). Mechanical ventilation was associated with higher hospital mortality in patients with low APACHE IV scores ≤ 70 (adjusted P = 0.014, χ2 = 5.999). In patients with high APACHE IV scores > 90, age > 78 (adjusted P = 0.007, χ2 = 11.221) and thrombocytopaenia (platelet count ≤ 128, adjusted P = 0.004, χ2 = 12.316) were predictive of higher hospital mortality. The APACHE IV score is superior to all blood parameters studied in predicting hospital mortality. The single inflammatory marker with comparable prognostic performance to the APACHE IV score is platelet count at 48 h. However, there is no ideal biomarker for differentiating between viral and bacterial pneumonia.