Prognostic value of lymphocyte count for in-hospital mortality in patients with severe AECOPD

Clinical relevance of blood urea nitrogen to serum albumin ratio for predicting bacteremia in very young children with febrile urinary tract infection

BACKGROUND

Urinary tract infections (UTIs) are one of the most common bacterial infections in febrile children and a common cause of hospitalization, especially in very young children. We examined the clinical characteristics and predictive factors of concomitant bacteremia in pediatric patients with febrile UTI aged ≤24 months.

METHODS

This retrospective multicenter study reviewed medical data from 2,141 patients from three centers from January 2000 to December 2019. Enrolled cases were classified into the bacteremic UTI and non-bacteremic UTI groups according to the presence of blood culture pathogens.

RESULTS

Among 2,141 patients with febrile UTI, 40 (1.9%) had concomitant bacteremia. All patients in the bacterial group were aged ≤6 months. Multivariate analysis revealed that younger age, lower blood lymphocyte counts and serum albumin levels, higher C-reactive protein (CRP) levels, blood urea nitrogen (BUN) levels, and BUN/serum albumin ratio were independent risk factors of concomitant bacteremia. The area under the receiver-operating characteristic curves predicting bacteremia were 0.668 for CRP, 0.673 for lymphocytes, and 0.759 for the BUN/albumin ratio.

CONCLUSION

The present study identified the BUN/albumin ratio and lower blood lymphocyte counts as novel predictive factors for bacteremia in young infants with febrile UTI in addition to the previously identified factors of younger age and higher CRP levels. Our findings could help to identify patients at high risk of bacteremia and benefit decision-making in the management of infants with febrile UTI.

A predictive model for frequent exacerbator phenotype of acute exacerbations of chronic obstructive pulmonary disease

Background

The frequent exacerbator phenotype of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is characterized by experiencing at least two exacerbations per year, leading to a significant economic burden on healthcare systems worldwide. Although several biomarkers have been shown to be effective in assessing AECOPD severity in recent years, there is a lack of studies on markers to predict the frequent exacerbator phenotype of AECOPD. The current study aimed to develop a new predictive model for the frequent exacerbator phenotype of AECOPD based on rapid, inexpensive, and easily obtained routine markers.

Methods

This was a single-center, retrospective study that enrolled a total of 2,236 AECOPD patients. The participants were divided into two groups based on the frequency of exacerbations: infrequent group (n=1,827) and frequent group (n=409). They underwent a complete blood count, as well as blood biochemistry, blood lipid and coagulation testing, and general characteristics were also recorded. Univariate analysis and binary multivariate logistic regression analyses were used to explore independent risk factors for the frequent exacerbator phenotype of AECOPD, which could be used as components of a new predictive model. The receiver operator characteristic (ROC) curve was used to assess the predictive value of the new model, which consisted of all significant risk factors predicting the primary outcome. The nomogram risk prediction model was established using R software.

Results

Age, gender, length of stay (LOS), neutrophils, monocytes, eosinophils, direct bilirubin (DBil), gamma-glutamyl transferase (GGT), and the glucose-to-lymphocyte ratio (GLR) were independent risk factors for the frequent exacerbator phenotype of AECOPD. The area under the curve (AUC) of the new predictive model was 0.681 [95% confidence interval (CI): 0.653-0.708], and the sensitivity was 63.6% (95% CI: 58.9-68.2%) and the specificity was 65.0% (95% CI: 60.3-69.6%).

Conclusions

A new predictive model based on demographic characteristics and blood parameters can be used to predict the frequency of acute exacerbations in the management of chronic obstructive pulmonary disease (COPD).

Using complete blood count, serum immunoglobulins G/A/M and complement C3/C4 levels to predict the risk of COPD acute exacerbation: 2-year follow-up in a single-center prospective cohort study

Autoimmunity is present in patients with stable chronic obstructive pulmonary disease (COPD), playing a role in indirect and direct ways. We aimed to explore whether autoimmunity could play a role in COPD exacerbations and construct autoimmunity-related prediction models. This prospective, longitudinal, observational cohort study enrolled 155 patients with acute COPD exacerbations (AECOPD) followed for at least two years. The laboratory parameters, including complete blood count, serum immunoglobulins G/A/M and complement C3/C4 levels, were collected at enrollment. We studied the demographic characteristics, clinical characteristics and laboratory parameters to identify independent risk factors and build predictive models. The results showed that lower lymphocyte count was associated with noninvasive ventilation (NIV) in patients with AECOPD (the odds ratio [OR] 0.25, the 95% confidence interval [CI]: 0.08-0.81, P = 0.02). Lymphocyte count performed well with an area under the curves (AUC) of 0.75 (P < 0.0001, sensitivity: 78.1%, specificity: 62.3%, cutoff value [Cov] ≤ 1.1). The C index, calibration plot, decision curve analysis (DCA) and bootstrap repetitions indicated that this clinical prediction model based on lymphocyte count for NIV in patients with AECOPD performed well. Having prior home oxygen therapy (OR: 2.82, 95% CI: 1.25-6.36, P = 0.013) and higher COPD Assessment Test (CAT) scores (OR: 1.14, 95% CI: 1.03-1.25, P = 0.011) were associated with the increased risk for respiratory failure. For predicting respiratory failure, CAT scores and home oxygen therapy combined had an AUC-ROC of 0.73 (P < 0.0001). This clinical prediction model based on lymphocyte count may help to assist in treatment decisions for NIV in patients with AECOPD. Lower complement C3 seems to be associated with worse outcomes in patients with AECOPD.

Association between the prognostic nutritional index (PNI) and all-cause mortality in patients with chronic kidney disease

BACKGROUND

Nutrition and immunity play an important role in many chronic diseases. The prognostic nutritional index (PNI) has been proposed as a comprehensive indicator of an individual's immune and nutritional status. However, there is a lack of evidence regarding the association between the PNI and mortality in patients with chronic kidney disease (CKD).

METHODS

We used National Health and Nutrition Examination Survey (NHANES) data from 2001-2014 for participants with CKD. Mortality data were obtained from the National Death Index and matched to NHANES participants. Cox proportional hazards models were used to estimate hazard ratios for all-cause mortality.Results: The patients were 72.5 ± 9.8 years old, and 47.57% were male. The median follow-up was 58 months, and the mortality rate in patients with CKD was 30.27%. A higher PNI protected against all-cause mortality in patients with CKD, with an adjusted hazard ratio (aHR) of 0.98 (95% confidence interval (CI): 0.97-0.99). After grouping according to PNI quartiles, statistically significant between-group differences were observed in survival probabilities. The aHR for the lowest PNI quartile compared to the highest PNI quartile was 1.64 (95% CI: 1.26-2.14). Sensitivity analysis further supported this association. Restricted cubic spline analysis revealed an L-shaped association between the PNI and all-cause mortality in patients with CKD, with a critical value of 50.5.

CONCLUSIONS

The PNI is a protective factor in patients with CKD, with an L-shaped decrease in all-cause mortality with an increasing PNI.

Serum YKL-40 Levels, Leukocyte Profiles, and Acute Exacerbations of Advanced COPD

Little information exists on YKL-40-a key protein in tissue remodeling-and complete blood count (CBC) parameters during acute exacerbations of advanced chronic obstructive pulmonary disease (COPD). This pilot exploratory study (August 2020-January 2021) investigated the connection between serum YKL-40 levels and CBC profile in sex- and age-matched individuals with severe COPD (GOLD stage III, n = 23, median age = 66 years, 65.21% males) and very severe COPD (GOLD stage IV, n = 24, median age = 66.5 years, 74.81% males). The measured parameters were serum YKL-40, absolute leukocyte count (ALLC), absolute neutrophil count (ANC), neutrophil percentage, absolute lymphocyte count (ALC), lymphocyte percentage, neutrophil-to-lymphocyte ratio (NLR), absolute eosinophil count (AEC), eosinophil percentage, absolute monocyte count (AMC), monocyte percentage, absolute basophil count (ABC), basophil percentage, hemoglobin levels, and hematocrit concentrations. No significant inter-group differences were observed. However, high YKL-40 subjects (n = 23)-as stratified via median YKL-40 (3934.5 pg/mL)-showed significantly increased neutrophil percentage and NLR but significantly lower lymphocyte-, eosinophil-, and basophil-related parameters compared to low YKL-40 patients (n = 24). These results reveal multidimensional, YKL-40-associated changes in leukocyte profile of patients with advanced COPD during acute exacerbations, with potential implications for personalized treatment.

Controlling Nutritional Status (CONUT) Score as a Potential Prognostic Indicator of In-Hospital Mortality, Sepsis and Length of Stay in an Internal Medicine Department

The controlling nutritional status (CONUT) score represents poor nutritional status and has been identified as an indicator of adverse outcomes. Our aim was to evaluate the prognostic role of the CONUT score on in-hospital outcomes in an Internal Medicine Department. This is a retrospective study analyzing data from 369 patients, divided into four groups based on the CONUT score: normal (0-1), mild-high (2-4), moderate-high (5-8), and marked high (9-12). In-hospital all-cause mortality increased from normal to marked high CONUT score group (2.2% vs. 3.6% vs. 13.4% vs. 15.3%, p < 0.009). Furthermore, a higher CONUT score was linked to a longer length of hospital stay (LOS) (9.48 ± 6.22 vs. 11.09 ± 7.11 vs. 12.45 ± 7.88 vs. 13.10 ± 8.12, p < 0.013) and an increased prevalence of sepsis. The excess risk of a high CONUT score relative to a low CONUT score remained significant after adjusting for confounders (all-cause mortality: OR: 3.3, 95% CI: 1.1-9.7, p < 0.02; sepsis: OR: 2.7, 95% CI: 1.5-4.9, p < 0.01; LOS: OR: 2.1, 95% CI: 1.2-3.9, p < 0.007). The present study demonstrated that an increased CONUT score is related to a higher risk of short-term in-hospital death and complications.