Background: Various authors have validated scales to measure comorbidity. However, the prognosis capacity variation according to the comorbidity measurement index used needs to be determined in order to identify which is the best predictor. Aims: To quantify the differences between the Charlson (CCI), Elixhauser (ECI) and van Walraven (WCI) comorbidity indices as prognostic factors for in-hospital mortality and to identify the best comorbidity measure predictor. Methods: A retrospective observational study that included all hospitalizations of patients over 18 years of age, discharged between 2017 and 2021 in the hospital, using the Minimum Basic Data Set (MBDS). We calculated CCI, ECI, WCI according to ICD-10 coding algorithms. The correlation and concordance between the three indices were evaluated by Spearman’s rho and Intraclass Correlation Coefficient (ICC), respectively. The logistic regression model for each index was built for predicting in-hospital mortality. Finally, we used the receiver operating characteristic (ROC) curve for comparing the performance of each index in predicting in-hospital mortality, and the Delong method was employed to test the statistical significance of differences. Results: We studied 79,425 admission episodes. The 54.29% were men. The median age was 72 years (interquartile range [IQR]: 56–80) and in-hospital mortality rate was 4.47%. The median of ECI was = 2 (IQR: 1–4), ICW was 4 (IQR: 0–12) and ICC was 1 (IQR: 0–3). The correlation was moderate: ECI vs. WCI rho = 0.645, p < 0.001; ECI vs. CCI rho = 0.721, p < 0.001; and CCI vs. WCI rho = 0.704, p < 0.001; and the concordance was fair to good: ECI vs. WCI Intraclass Correlation Coefficient type A (ICC_A) = 0.675 (CI 95% 0.665–0.684) p < 0.001; ECI vs. CCI ICC_A = 0.797 (CI 95% 0.780–0.812), p < 0.001; and CCI vs. WCI ICC_A = 0.731 (CI 95% 0.667–0.779), p < 0.001. The multivariate regression analysis demonstrated that comorbidity increased the risk of in-hospital mortality, with differences depending on the comorbidity measurement scale: odds ratio [OR] = 2.10 (95% confidence interval [95% CI] 2.00–2.20) p > |z| < 0 using ECI; OR = 2.31 (CI 95% 2.21–2.41) p > |z| < 0 for WCI; and OR = 2.53 (CI 95% 2.40–2.67) p > |z| < 0 employing CCI. The area under the curve [AUC] = 0.714 (CI 95% 0.706–0.721) using as a predictor of in-hospital mortality CCI, AUC = 0.729 (CI 95% 0.721–0.737) for ECI and AUC = 0.750 (CI 95% 0.743–0.758) using WCI, with statistical significance (p < 0.001). Conclusion: Comorbidity plays an important role as a predictor of in-hospital mortality, with differences depending on the measurement scale used, the van Walraven comorbidity index being the best predictor of in-hospital mortality.

Introduction: Autoimmune pulmonary alveolar proteinosis (aPAP) is a disease caused by IgG antibodies against granulocyte‐macrophage colony‐stimulating factor (GM‐CSF). Whole lung lavage (WLL) allows to remove the lipo‐proteinaceous material accumulated by the poor clearance of alveolar surfactant. However, it is a complex technique that is not exempt from complications, and in some cases, the patients are refractory, requiring the performance of several WLLs spaced apart in time.Materials and Methods: We present the clinical, functional, and radiological evolution after 24 months of follow‐up of a patient diagnosis of aPAP refractory to WLL, with performed three therapeutic WLLs spaced 16 and 36 months and serious potentially fatal complications in the last one.Results and Disscusion: After 24 months, no adverse effects have appeared and the great clinical, functional and radiological response is maintained. The patient has been successfully treated with inhaled recombinant human GM‐CSF sargramostim.

Objectives: Antimicrobial resistance is a major global health threat. This study aimed to assess the impact of antimicrobial-resistant bacterial pneumonia on in-hospital mortality and length of hospital stay in Spain using a large, nationally representative cohort. Methods: A retrospective cohort study that used data from Spain’s Registry of Specialized Health Care Activity (RAE-CMBD) between 2017 and 2022. Hospitalized adults with bacterial pneumonia were included. Hospitalization episodes with bacterial antimicrobial resistance, defined according to ICD-10-CM codes for antimicrobial resistance (Z16.1, Z16.2), were analyzed versus hospitalization episodes without these codes. Multivariate logistic regression models, adjusted for potential confounders (e.g., age, comorbidity, intensive care unit admission) and sensitivity analyses (Poisson regression and propensity score matching test), were performed. Results: Of the 116,901 eligible hospitalizations, 6017 (5.15%) involved antimicrobial-resistant bacteria. Patients with antimicrobial-resistant bacterial pneumonia were older (median 75 vs. 72 years), had greater comorbidity (Elixhauser–van Walraven index: 8 vs. 5), and were more frequently admitted to the intensive care unit (22% vs. 14%). Crude in-hospital mortality was higher in the antimicrobial resistance group (18.46% vs. 10.05%, p < 0.0001), with an adjusted odds ratio of 1.47 (95% confidence interval, 1.36–1.58), p < 0.0001. Length of hospital stay was prolonged in antimicrobial resistance patients (median 14 vs. 8 days; adjusted incident rate ratio of 1.46; 95% confidence interval of 1.41 to 1.50). The most prevalent antimicrobial resistant pathogens were Staphylococcus aureus and Gram-negative bacilli (Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli). Conclusions: Antimicrobial resistance is associated with longer hospital stays and an up to 50% higher risk of mortality. Despite the implementation of control policies in place over the past decade, policymakers must strengthen AMR surveillance and ensure adequate resource allocation. Clinicians, in turn, must reinforce antimicrobial stewardship and incorporate rapid diagnostic tools to minimize the impact of antimicrobial resistance on patient outcomes.

Infective endocarditis (IE) is a severe infection associated with high morbidity and mortality. Although antimicrobial resistance (AMR) is increasingly recognised as a major global public health threat, its impact on outcomes in IE at the population level remains poorly characterised. We aimed to evaluate the association between AMR and in-hospital mortality among adults hospitalised with bacterial IE in a real-world, nationwide setting. We conducted a nationwide, population-based retrospective cohort study using the Spanish RAE-CMBD administrative hospital discharge database. We included adults (≥18 y) hospitalised with bacterial IE and a single identified causative microorganism between 1 January 2017 and 31 December 2022. AMR was defined by the presence of International Classification of Diseases, 10th Revision, Clinical Modification resistance codes (Z16.1 or Z16.2) linked to the causative pathogen. The primary outcome was in-hospital mortality. Time-to-event analyses were performed using Cox proportional hazards models, with adjustment for age, sex, comorbidity burden (Elixhauser-van Walraven index), sepsis (modelled as a time-varying covariate), cardiac surgery, and prosthetic valve endocarditis. Sensitivity analyses included censoring follow-up at 90, 30, and 18 d and alternative logistic regression model. Among 9540 hospitalisations with bacterial IE included in the analysis, 729 (7.64%) were coded as AMR infections. Overall, in-hospital mortality was 18.57% (1722 deaths). Mortality was higher among patients with AMR IE than among those without resistance (29.36% vs. 17.68%; P < 0.0001). Staphylococcus aureus was the most frequently identified resistant pathogen. In univariable analysis, AMR was associated with increased in-hospital mortality (hazard ratio 1.68, 95% confidence interval 1.45-1.93). After multivariable adjustment, AMR remained independently associated with in-hospital mortality (adjusted hazard ratio 1.39, 95% confidence interval 1.19-1.59; P < 0.0001). Increasing age and comorbidity burden were associated with higher mortality, whereas cardiac surgery was associated with improved survival. Prosthetic valve endocarditis was not independently associated with in-hospital mortality. Results were consistent across all sensitivity analyses. In this nationwide cohort, AMR was independently associated with a substantially increased risk of in-hospital mortality among adults with bacterial IE. These findings highlight AMR as an important prognostic factor in IE and underscore the need for early identification of resistant pathogens, optimisation of antimicrobial therapy, and strengthened antimicrobial stewardship strategies.

Background: Antimicrobial resistance (AMR) is a major global health threat with substantial clinical and economic consequences. However, robust national estimates of the economic burden of AMR-related hospitalizations to AMR remain limited. We aimed to quantify the hospitalization costs attributable to AMR in Spain and to assess their variation across infection types. Methods: We conducted a nationwide, retrospective cohort study using the Spanish Specialized Care Activity registry. We included all adult hospitalizations with a diagnosis of bacterial infection between 1 January 2017, and 31 December 2022. Antimicrobial resistance was defined using International Classification of Diseases, 10th Revision, Clinical Modification resistance diagnosis codes. Hospitalization costs were estimated using nationally standardized All Patient Refined Diagnosis-Related Groups cost weights. Generalized linear models were used to estimate the incremental cost associated with AMR after adjustment for demographic and clinical characteristics. Results: Among 2 817 406 hospitalizations with bacterial infection, 175 188 (6.22%) involved AMR. In adjusted analyses, AMR was associated with a 15% increase in hospitalization costs (cost ratio 1.15, 95% confidence interval [CI] 1.15–1.16; P < .0001), corresponding to an incremental cost of euros (EUR) 925 (95% CI 887–962) per hospitalization. The cost of hospitalizations with bacterial AMR infections was EUR 215 million annually (95% CI 213.33–216.67). After adjustment for patient and clinical characteristics, the attributable economic burden of AMR was EUR 27.10 million annually. This economic impact of AMR varied substantially across infection types, with the greatest attributable economic burden intra-abdominal infections, acute pyelonephritis, pneumonia, and lower urinary tract infections. Conclusions: In this nationwide cohort, AMR was independently associated with an increase in hospitalization costs in Spain, contributing meaningfully to national healthcare expenditure.