Search Results (21)

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. Full article

Background/Objectives: Multimorbidity, where patients have ≥2 comorbidities, is recognized as a major challenge for health systems worldwide, driving up morbidity and cost. The differences in multimorbidity burden between those with and without type-2 diabetes mellitus (T2DM) in the Veteran population are not well studied. This large retrospective cohort study fills the existing gap. Methods: Using a retrospective cohort of adult Veterans with and without T2DM, we examined 29 comorbidities defined by Elixhauser criteria for 10,499,394 Veterans from 1 January 2008 to 31 December 2009. We then ascertained diabetes status for 10 years of follow-up from 1 January 2010 to 31 December 2019. Multimorbidity status was categorized using the Elixhauser comorbidity index (0, 1, ≥2) and logistic regression was used to estimate the odds ratio (OR) for its association with risk of diabetes, adjusting for covariates. Results: Compared to those with zero comorbidities, the odds of having diabetes were more than doubled (2.53, CI: 2.51–2.54) for those with ≥2 comorbidities. Conclusions: The doubling of the odds of T2DM among those with more than one comorbidity is typical of Veterans with T2DM. In addition, the odds were significantly higher for Hispanics compared to other groups when adjusting for covariates. This calls for more attention to reduce the risk of T2DM through improved management and effective use of treatments informed by disparities that exist in the VHA. Full article

Invasive pneumococcal disease (IPD) is a serious infection caused by the bacterium Streptococcus pneumoniae (pneumococcus) that can produce a wide spectrum of clinical manifestations. The aim of this study was to analyze the comorbidity factors that influenced the mortality in patients with diabetes (D) according to IPD. A retrospective study to analyze patients with D and IPD was carried out. Based on the discharge reports from the Spanish Minimum Basic Data Set (MBDS) from 1997 to 2022, the Elixhauser Comorbidity Index (ECI) and the Charlson Comorbidity Index (CCI) were calculated to predict in-hospital mortality (IHM) in Spain. A total of 12,994,304 patients with D were included, and 84,601 cases of IPD were identified. The average age for men was 70.23 years and for women 73.94 years. In all years, ECI and CCI were larger for type 2 D than for type 1 D, with men having a higher mean than women. An association was found between risk factors ECI, age, type 1 D, COVID-19, IPD (OR = 1.31; 95% CI: 1.29–1.35; p < 0.001); CCI, age, type 1 D, COVID-19, IPD (OR = 1.45; 95% CI: 1.42–1.49; p < 0.001), and increased mortality. The IHM increased steadily with the number of comorbidities and index scores from 1997 to 2022. D remains a relevant cause of hospitalization in Spain. Comorbidities reflected a great impact on patients with D and IPD, which would mean a higher risk of mortality. Predicting mortality events and length of stay by comparing indices showed that CCI outperforms ECI in predicting inpatient death after IPD. Full article

Background/Objectives: Despite advances, large vessel occlusion strokes (LVO) remain associated with significant morbidity. Recent studies have suggested that blood transfusions may help manage critically ill LVO patients. We sought to evaluate the patient characteristics, complications, and clinical outcomes associated with blood transfusions in acute ischemic stroke (AIS) patients undergoing endovascular thrombectomy. Methods: A query of the 2016–2019 National Inpatient Sample was conducted to identify AIS patients who underwent endovascular thrombectomy, using International Classification of Disease 10th Revision diagnostic codes. Demographic, clinical characteristics, severity of presentation, complications, and outcomes were analyzed. Multivariate binary logistic regression was used to assess complications, length of stay (LOS), discharge disposition, and inpatient mortality. Results: A total of 47,835 AIS patients undergoing endovascular thrombectomy were identified. Of these patients, 1215 (2.5%) received blood transfusions. After controlling for age, gender, National Institutes of Health Stroke Scale scores, Elixhauser Comorbidity Index, and location of stroke, blood transfusions were significant positive predictors for higher rates of inpatient death (OR: 1.96; 95% CI: 1.681, 2.286; p < 0.001), lower rates of routine discharge (OR: 0.425; 95% CI: 0.342, 0.527; p < 0.001), and prolonged LOS (OR: 2.928; 95% CI: 2.572, 3.333; p < 0.001). Conclusions: Blood transfusions in AIS patients receiving endovascular thrombectomy are associated with elevated complication rates, extended hospital stays, and increased mortality, even after for controlling for predictors of poor outcome. Understanding the broader effects of blood transfusions in AIS patients is essential to ensure that the balance between potential benefits and risks upholds best care practice for all patients. Full article

Background/Objectives: The demographic change raises concerns about the provision of adequate, long-term healthcare. Our study was driven by the decision to test other studies’ findings about how patients’ age and comorbidities are significantly increasing in German intensive care units (ICUs) over time. The goal of this study was to analyze the age and age-related characteristics, e.g., comorbidities and frailty, in ICU populations from 86 hospitals in the German Helios Group over a period of 6 years. Methods: For this retrospective observational study, we derived two different definitions of ICU cases, with (i) CodeBased ICU cases being defined by typical ICU procedures (e.g., OPS 8-980, 8-98f and/or duration of ventilation > 0 h) derived from the German administrative dataset of claims data according to the German Hospital Remuneration Act and (ii) BedBased ICU cases being based on the actual presence of a patient on a designated ICU bed; this was taken from the Helios hospital bed classification system. For each ICU definition, the size of the respective ICU population, age, Elixhauser Comorbidity Index (ECI) and Hospital Frailty Risk Score (HFR) were analyzed. Further patient characteristics, treatments and outcomes are reported. Trends in cases with and without COVID-19 were analyzed separately. Results: We analyzed a total of 6,204,093 hospital cases, of which 281,537 met the criteria for the CodeBased ICU definition and 457,717 for the BedBased ICU definition. A key finding of our study is that a change in age in absolute and relative terms is observable and statistically significant: the mean age of CodeBased ICU cases, 68.7 (14.4/−0.06), is marginally decreasing, and that of BedBased ICU cases, 69.1 (15.9/0.07) (both with a p-value of <0.001), is marginally increasing. Age analysis excluding COVID-19 cases does not change this key finding. A longitudinal analysis shows a continuously decreasing number of ICU admissions and a marginally positive trend of patients who are 60–69 and ≥80 years old: CodeBased ICU, 1.04/1.02; BedBased ICU, 1.03/1.03, all with a p-value of <0.001. A severity analysis based on the ECI and HFS shows that both are higher in CodeBased ICU cases (2021 ECI:18.0 (12.9); HFS: 10.7 (7.3); both p-values < 0.001) than in BedBased ICU cases (2021 ECI: 12.3 (12.4); HFS: 7.4 (7.1); p-values of 0.3 and 0.12). Further testing results per definition are reported. Conclusions: The observed age-related trends suggest that there has been a further increase in demand for intensive care from a frailer population. We recommend further studies to critically evaluate the increasing frailty within the ICU population and to test the associated presumed need for increased ICU capacities. Full article

Introduction: Vertebral compression fractures (VCFs) pose a considerable healthcare burden and are linked to elevated morbidity and mortality. Despite available anti-osteoporotic treatments (AOTs), guideline adherence is lacking. This study aims to evaluate subsequent hip fracture incidence after index VCF and to elucidate AOT prescribing patterns in VCF patients, further assessing the impact of surgical interventions on these patterns. Materials and Methods: Patients with index VCFs between 2010 and 2021 were identified using the PearlDiver database. Diagnostic and procedural data were recorded using International Classification of Diseases (ICD-9, ICD-10) and Current Procedural Terminology (CPT) codes. Patients under age 50 and follow-up <one year following index VCF were excluded. Patients were categorized based on whether they received AOT within one year, preceding and after index VCF, and were subsequently propensity-matched 1:3 based on age, sex, and Elixhauser Comorbidity Index (ECI) score to compare hip fracture incidence following index VCF. Sub-analysis was performed for operatively managed VCFs (kyphoplasty/vertebroplasty). Statistical tests included Chi-squared for categorical outcomes, and Kruskal–Wallis for continuous measures. Results: Of 637,701 patients, 72.6% were female. The overall subsequent hip fracture incidence was 2.6% at one year and 12.9% for all-time follow-up. Propensity-matched analysis indicated higher subsequent hip fracture rates in patients initiated on AOT post-index VCF (one year: 3.8% vs. 3.5%, p = 0.0013; all-time: 14.3% vs. 13.0%, p < 0.0001). Conclusions: The study reveals an unexpected increase in subsequent hip fractures among patients initiated on AOT post-index VCF, likely due to selection bias. These findings highlight the need for refined osteoporosis-management strategies to improve guideline adherence, thereby mitigating patient morbidity and mortality. Full article

In the United States, racial disparities have been observed in complications following total joint arthroplasty (TJA), including readmissions and mortality. It is unclear whether such disparities also exist for periprosthetic joint infection (PJI). The clinical data registry of a large New England hospital system was used to identify patients who underwent TJA between January 2018 and December 2021. The comorbidities were evaluated using the Elixhauser Comorbidity Index (ECI). We used Poisson regression to assess the relationship between PJI and race by estimating cumulative incidence ratios (cIRs) and 95% confidence intervals (CIs). We adjusted for age and sex and examined whether ECI was a mediator using structural equation modeling. The final analytic dataset included 10,018 TJAs in 9681 individuals [mean age (SD) 69 (10)]. The majority (96.5%) of the TJAs were performed in non-Hispanic (NH) White individuals. The incidence of PJI was higher among NH Black individuals (3.1%) compared with NH White individuals (1.6%) [adjusted cIR = 2.12, 95%CI = 1.16–3.89; p = 0.015]. Comorbidities significantly mediated the association between race and PJI, accounting for 26% of the total effect of race on PJI incidence. Interventions that increase access to high-quality treatments for comorbidities before and after TJA may reduce racial disparities in PJI. Full article

Background: In acute myocardial infarction (AMI), acute hepatic injury is an independent risk factor for prognosis and is associated with complex coagulation dynamics. This study aims to determine the interaction between acute hepatic injury and coagulation dysfunction on outcomes in AMI patients. Methods: The Medical Information Mart for Intensive Care (MIMIC-III) database was used to identify AMI patients who underwent liver function testing within 24 h of admission. After ruling out previous hepatic injury, patients were divided into the hepatic injury group and the nonhepatic injury group based on whether the alanine transaminase (ALT) level at admission was >3 times the upper limit of normal (ULN). The primary outcome was intensive care unit (ICU) mortality. Results: Among 703 AMI patients (67.994% male, median age 65.139 years (55.757–76.859)), acute hepatic injury occurred in 15.220% (n = 107). Compared with the nonhepatic injury group, patients with hepatic injury had a higher Elixhauser comorbidity index (ECI) score (12 (6–18) vs. 7 (1–12), p < 0.001) and more severe coagulation dysfunction (85.047% vs. 68.960%, p < 0.001). In addition, acute hepatic injury was associated with increased in-hospital mortality (odds ratio (OR) = 3.906; 95% CI: 2.053–7.433; p < 0.001), ICU mortality (OR = 4.866; 95% CI: 2.489–9.514; p < 0.001), 28-day mortality (OR = 4.129; 95% CI: 2.215–7.695; p < 0.001) and 90-day mortality (OR = 3.407; 95% CI: 1.883–6.165; p < 0.001) only in patients with coagulation disorder but not with normal coagulation. Unlike patients with coagulation disorder and normal liver, patients with both coagulation disorder and acute hepatic injury had greater odds of ICU mortality (OR = 8.565; 95% CI: 3.467–21.160; p < 0.001) than those with normal coagulation. Conclusions: The effects of acute hepatic injury on prognosis are likely to be modulated by early coagulation disorder in AMI patients. Full article

With the increase in the elderly population, surgery in aged patients is seeing an exponential increase. In this population, sepsis is a major concern for perioperative care, especially in older and frail patients. We aim to investigate the incidence of sepsis in elderly patients receiving diverse types of surgical procedures and explore the predictive capacity of the Hospital Frailty Risk Score (HFRS) to identify patients at high risk of incidence of postoperative sepsis. This study relies on information from the Spanish Minimum Basic Data Set, including data from nearly 300 hospitals in Spain. We extracted records of 254,836 patients aged 76 years and older who underwent a series of surgical interventions within three consecutive years (2016–2018). The HFRS and Elixhauser comorbidity index were computed to determine the independent effect on the incidence of sepsis. Overall, the incidence of postoperative sepsis was 2645 (1.04%). The higher risk of sepsis was in major stomach, esophageal, and duodenal (7.62%), followed by major intestinal procedures (5.65%). Frail patients are at high risk of sepsis. HFRS demonstrated a high predictive capacity to identify patients with a risk of postoperative sepsis and can be a valid instrument for risk stratification and vigilant perioperative monitoring for the early identification of patients at high risk of sepsis. Full article

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. Full article

(1) Background: Clostridioides difficile infection (CDI) is associated with a high recurrence rate, and a significant proportion of patients with CDI are readmitted following discharge. We aimed to identify the risk factors for CDI-related readmission within 90 days following an index hospital stay for CDI. (2) Methods: We analyzed the electronic medical data of admitted patients in our health system over a two-year period. A multivariate logistic regression model, supplemented with bias-corrected and accelerated confidence intervals (BCa-CI), was implemented to assess the risk factors. (3) Results: A total of 1253 adult CDI index cases were included in the analysis. The readmission rate for CDI within 90 days of discharge was 11% (140/1253). The risk factors for CDI-related readmission were fluoroquinolone exposure within 90 days before the day of index CDI diagnosis (aOR: 1.58, 95% CI: 1.05–2.37), higher Elixhauser comorbidity score (aOR: 1.05, 95% CI: 1.02–1.07), and being discharged home (aOR: 1.64, 95% CI: 1.06–2.54). In contrast, a longer length of index stay (aOR: 0.97, 95% BCa-CI: 0.95–0.99) was associated with reduced odds of readmission for CDI. (4) Conclusion: More than 1 out of 10 patients were readmitted for CDI following an index hospital stay for CDI. Patients with recent previous fluoroquinolone exposure, greater overall comorbidity burden, and those discharged home are at higher risk of readmission for CDI. Full article

Background: A prognostic assessment is crucial for making cancer treatment decisions in older patients. We assessed the prognostic performance (relative to one-year mortality) of eight comorbidity indices in a cohort of older patients with cancer. Methods: We studied patients with cancer aged ≥70 included in the Elderly Cancer Patient (ELCAPA) cohort between 2007 and 2010. We assessed seven nonspecific indices (Charlson Comorbidity Index (CCI), three modified versions of the CCI, the Elixhauser Comorbidity Index, the Gagne index, and the Cumulative Illness Rating Scale for Geriatrics (CIRS-G)) and the National Cancer Institute Comorbidity Index. Results: Overall, 510 patients were included. Among patients with nonmetastatic cancer, all the comorbidity indices were independently associated with 1-year mortality (adjusted hazard ratios (aHRs) of 1.44 to 2.51 for one standard deviation increment; p < 0.05 for all) and had very good discriminant ability (Harrell’s C > 0.8 for the eight indices), but were poorly calibrated. Among patients with metastatic cancer, only the CIRS-G was independently associated with 1-year mortality (aHR (95% confidence interval): 1.26 [1.06–1.50]). Discriminant ability was moderate (0.61 to 0.70) for the subsets of patients with metastatic cancer and colorectal cancer. Conclusion: Comorbidity indices had strong prognostic value and discriminative ability for one-year mortality in older patients with nonmetastatic cancer, although calibration was poor. In older patients with metastatic cancer, only the CIRS-G was predictive of one-year mortality. Full article

Background: COVID-19 is caused by SARS-CoV-2 infection and has reached pandemic proportions. Since then, several clinical characteristics have been associated with poor outcomes. This study aimed to describe the morbidity profile of COVID-19 deaths in Portugal. Methods: A study was performed including deaths certificated in Portugal with “COVID-19” (ICD-10: U07.1 or U07.2) coded as the underlying cause of death from the National e-Death Certificates Information System between 16 March and 31 December 2020. Comorbidities were derived from ICD-10 codes using the Charlson and Elixhauser indexes. The resident Portuguese population estimates for 2020 were used. Results: The study included 6701 deaths (death rate: 65.1 deaths/100,000 inhabitants), predominantly males (72.1). The male-to-female mortality ratio was 1.1. The male-to-female mortality rate ratio was 1.2; however, within age groups, it varied 5.0–11.4-fold. COVID-19 deaths in Portugal during 2020 occurred mainly in individuals aged 80 years or older, predominantly in public healthcare institutions. Uncomplicated hypertension, uncomplicated diabetes mellitus, congestive heart failure, renal failure, cardiac arrhythmias, dementia, and cerebrovascular disease were observed among COVID-19 deceased patients, with prevalences higher than 10%. A high prevalence of zero morbidities was registered using both the Elixhauser and Charlson comorbidities lists (above 40.2%). Nevertheless, high multimorbidity was also identified at the time of COVID-19 death (about 36.5%). Higher multimorbidity levels were observed in men, increasing with age up to 80 years old. Zero-morbidity prevalence and high multimorbidity prevalences varied throughout the year 2020, seemingly more elevated in the mortality waves’ peaks, suggesting variation according to the degree of disease incidence at a given period. Conclusions: This study provides detailed sociodemographic and clinical information on all certificated deaths from COVID-19 in Portugal during 2020, showing complex and extreme levels of morbidity (zero-morbidity vs. high multimorbidity) dynamics during the first year of the pandemic in Portugal. Full article

Pulmonary embolism (PE) is the third most common vascular disease in the US, a frequently underdiagnosed and potentially fatal condition where embolic material blocks one or more pulmonary arteries impairing blood flow. In this study, we aim to describe the prevalence, outcomes, and predictors of mortality of PE patients treated with mechanical (MT) and surgical thrombectomy (ST). This is a retrospective study using the Agency for Healthcare Research and Quality’s HCUP NIS data from 2010–2018. We used the ninth and tenth revisions of the International Classification of Diseases clinical modification codes (ICD-9-CM and ICD-10-CM) to identify patients admitted with a primary diagnosis of PE (ICD-10-CM codes I26.02, I26.09, I26.92, I26.93, I26.94, and I26.99; ICD-9-CM codes 415.11, 415.13, and 415.19). We extracted demographics, hospital-level, and patient-level characteristics, and defined the severity of comorbid conditions using Deyo modification of the Elixhauser Comorbidity Index. The primary outcomes of interest were the utilization trends of PE (treated with MT and ST); the secondary outcomes were mortality, discharge to facility, peri-procedural complications, and length of hospital (LOS) stay; the tertiary outcome was to identify the predictors of in-hospital mortality. From 2010–2018, there were 1,627,718 hospitalizations for PE, of which 6531 (0.39%) underwent MT and 3465 (0.21%) underwent ST. The utilization trend of MT increased from 336 (0.20%) in 2010 to 1655 (0.87%) in 2018; the utilization trend of ST was 260 (0.15%) in 2010 and 430 (0.23%) in 2018. The unadjusted in-hospital mortality for MT was 9.1% with the mean LOS being 7(±0.3) days; for ST, mortality was 13.9% with a mean LOS of 13(±0.4) days. The occurrences of periprocedural complications for MT and ST were as follows: invasive mechanical ventilation was 13.8% and 32%; cardiopulmonary bypass was 3.3% and 68.3%; pulmonary embolectomy surgery was 1.7%; and bleeding complications were 1.4% and 3.4%. Predictors associated with in-hospital mortality for MT were: increasing age (OR 1.2, 95% CI 1.0–1.3, p < 0.026), female sex (OR 1.9, 95% CI 1.2–2.8, p < 0.004), large hospitals (OR 2.2, 95% 1.4–3.5, p < 0.001), and teaching hospitals (OR 1.8, 95% CI 1.1–3.1, p < 0.023). The predictor of in-hospital mortality for ST was increasing age (OR 1.2, 95% CI 1.0–1.4, p < 0.046). The number of MT procedures performed has rapidly increased over the past decade. Further studies are warranted to determine their rise and therapeutic use. Full article

Objectives: To examine the comorbidity burden in patients with rheumatoid arthritis (RA) patients using a nationwide population-based cohort by assessing the Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), Multimorbidity Index (MMI), and Rheumatic Disease Comorbidity Index (RDCI) scores and to investigate their predictive ability for all-cause mortality. Methods: We identified 24,767 RA patients diagnosed from 1998 to 2008 in Taiwan and followed up until 31 December 2013. The incidence of comorbidities was estimated in three periods (before, during, and after the diagnostic period). The incidence rate ratios were calculated by comparing during vs. before and after vs. before the diagnostic period. One- and 5-year mortality rates were calculated and discriminated by low and high-score groups and modified models for each index. Results: The mean score at diagnosis was 0.8 in CCI, 2.8 in ECI, 0.7 in MMI, and 1.3 in RDCI, and annual percentage changes are 11.0%, 11.3%, 9.7%, and 6.8%, respectively. The incidence of any increase in the comorbidity index was significantly higher in the periods of “during” and “after” the RA diagnosis (incidence rate ratios for different indexes: 1.33–2.77). The mortality rate significantly differed between the high and low-score groups measured by each index (adjusted hazard ratios: 2.5–4.3 for different indexes). CCI was slightly better in the prediction of 1- and 5-year mortality rates. Conclusions: Comorbidities are common before and after RA diagnosis, and the rate of accumulation accelerates after RA diagnosis. All four comorbidity indexes are useful to measure the temporal changes and to predict mortality. Full article