Background: Penicillin allergy is a common problem in the management of infectious diseases. The aim of this study was to determine the impact of penicillin allergy on length of hospital stay (LOHS) among hospitalized adult patients and on in-hospital mortality at a national level. Methods: A retrospective cohort study of adult patients discharged from the Spanish Hospital System between 2006 and 2015 was conducted using the Minimum Basic Data Set (MBDS). We compared LOHS and in-hospital mortality of adult patients whose records contained penicillin allergy code V14.0 (International Classification of Diseases, Ninth Revision, Clinical Modification) as a secondary diagnosis, with a random sample without such a code. Results: We identified 981,291 admissions with code V14.0, which corresponded to 2.63% of all hospitalizations. Adults patients with a penicillin allergy label were significantly older than patients without such a label, with a median of 70 years (interquartile range [IQR]: 51–80) versus 63 years (IQR: 40–77). The proportion of women and the prevalence of infectious diseases were higher in the group with a penicillin allergy label (61.40% vs. 53.84%; 34.04% vs. 30.01%; respectively). We found a higher median Elixhauser-Van Walraven score in hospitalized patients with an allergy label. The median LOHS for hospitalizations with a penicillin allergy label (5 [IQR: 2–9]) was significantly longer than that in those without such a label (4 [IQR: 2–9]). Multivariate analysis showed an increase in LOHS due to the penicillin allergy label (odds ratio [OR] [95% confidence interval [CI]: 1.061 [1.057–1.065]) and a decrease in mortality in penicillin allergy records (OR [95% CI]: 0.834 [0.825–0.844]). Conclusion: In our study, the prevalence of a penicillin allergy label in hospitalized patients, using the MBDS, is low. Hospitalizations with an allergy label was associated with a longer LOHS. However, penicillin-allergic patients did not show higher mortality rates. Inaccurate reporting of penicillin allergies may have an impact on healthcare resources.

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.

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.

Introduction: Hospital pharmacists are increasingly playing a critical role in the care of patients with multiple sclerosis (MS). However, little is known about their preferences and perspectives towards different attributes of disease-modifying therapies (DMTs). The objective of this research was to assess pharmacists´ preferences for DMT efficacy attributes. Methods: A multicenter, non-interventional, cross-sectional, web-based study was conducted. Preventing relapses, delaying disease progression, controlling radiological activity, and preserving health-related quality of life (HRQoL) and cognition were the attributes selected based on a literature review and a focus group with six hospital pharmacists. Conjoint analysis was used to determine preferences in eight hypothetical treatment scenarios, combining different levels of each attribute and ranking them from most to least preferred. Results: Sixty-five hospital pharmacists completed the study (mean age: 43.5 ± 7.8 years, 63.1% female, mean years of professional experience: 16.1 ± 7.4 years). Participants placed the greatest preference on delaying disease progression (35.7%) and preserving HRQoL (21.6%) and cognition (21.6%). Importance was consistent in all groups of pharmacists stratified according to demographic characteristics, experience, research background, and volume of patients seen per year. Conclusions: Understanding which treatment characteristics are meaningful to hospital pharmacists may help to enhance their synergistic role in the multidisciplinary management of patients with MS.

Drugs of various classes are prescribed for intermittent claudication. However, there is some discrepancy between medical practice and the scientific basis for drug selection. We have developed a quantitative criteria-based decision analysis to evaluate all implications of drug treatment choices for intermittent claudication. Pentoxifylline, buflomedil, naftidrofuryl and ticlopidine were the drugs selected for analysis. The evaluation criteria were 1) therapeutic efficacy, 2) safety, 3) patient acceptance and 4) cost. A review panel of experts determined the relative importance of each criterion by assigning points (or utility values) to each one. The points were 48, 20, 14 and 18, respectively, for criteria 1, 2, 3 and 4. A probability value, or numerical estimate of how well a drug meets a criterion, was assigned to each drug for each of the 4 criteria. The probability value was multiplied by the utility value to determine the score for each drug and criterion. The criteria points for each drug were added for a total score for the drug. The drug with the highest overall score was pentoxifylline, with 69 points out of an ideal score of 100. The rank order for the other drugs was buflomedil, ticlopidine and naftidrofuryl. A sensitive analysis showed that the relative ranking of the drugs remained unchanged over a series of data modifications.

Hospital-wide SARS-CoV-2 seroprevalence is rarely explored and can identify areas of unexpected risk. We determined the seroprevalence against SARS-CoV-2 in all health care workers (HCW) at a hospital. Cross-sectional study (14-27/04/2020). We determined SARS-CoV-2 IgG by ELISA in all HCW including external workers of a teaching hospital in Madrid. They were classified by professional category, working area, and risk for SARS-CoV-2 exposure. Among 2919 HCW, 2590 (88,7%) were evaluated. The mean age was 43.8 years (SD 11.1), and 73.9% were females. Globally, 818 (31.6%) workers were IgG positive with no differences for age, sex or previous diseases. Of these, 48.5% did not report previous symptoms. Seropositivity was more frequent in high- (33.1%) and medium- (33.8%) than in low-risk areas (25.8%, p = 0.007), but not for hospitalization areas attending COVID-19 and non-COVID-19 patients (35.5 vs 38.3% p > 0.05). HWC with a previous SARS-CoV2 PCR-positive test were IgG seropositive in 90.8%. By multivariate logistic regression analysis seropositivity was significantly associated with being physicians (OR 2.37, CI95% 1.61–3.49), nurses (OR 1.67, CI95% 1.14–2.46), nurse assistants (OR 1.84, CI95% 1.24–2.73), HCW working at COVID-19 hospitalization areas (OR 1.71, CI95% 1.22–2.40), non-COVID-19 hospitalization areas (OR 1.88, CI95% 1.30–2.73), and at the Emergency Room (OR 1.51, CI95% 1.01–2.27). Seroprevalence uncovered a high rate of infection previously unnoticed among HCW. Patients not suspected of having COVID-19 as well as asymptomatic HCW may be a relevant source for nosocomial SARS-CoV-2 transmission.