BACKGROUND: Knowledge about impact of age and comorbidities on outcome in patients with leadless pacemakers (LPM) is limited.
OBJECTIVE: To analyse outcome in LPM patients according to age and comorbidities.
METHODS: This Swiss, multi-centre, retrospective analysis includes all patients with LPM implanted between 2015 and 2022. Charlson-Comorbidity-Index (CCI) was determined and patients were divided into a low- (CCI ≤ 5) and high- comorbidity (CCI > 5) group. Peri-procedural complications, in-hospital death, and all-cause mortalities were assessed. Finally, all-cause mortality according to three groups (CCI ≤ 3, 4-5, >5) was compared to age and sex-adjusted mortality in the general Swiss population.
RESULTS: 863 patients (median age 81 years, 65% male, 42% with CCI > 5) were included. Peri-procedural/long-term complication rates did not differ between the low- vs. high-comorbidity groups (2.6% vs. 1.7%, p = 0.48 and 1.2% vs. 2.8%, p = 0.12, respectively). In-hospital (3.6% vs. 0.6%, p = 0.002) and all-cause mortality (HR 2.9, 95%CI 2.2-3.8, p < 0.001) were significantly higher in the high-comorbidity group resulting in a three-year mortality of 58% (95%CI 51-65%) vs. 22% (95%CI 17-27%) in the low-comorbidity group. In patients with a CCI ≤ 3, all-cause mortality was comparable to the age- and sex-adjusted mortality of the general Swiss population.
CONCLUSIONS: In elderly patients with high comorbidity, LPM implantation was not associated with increased peri-procedural/long-term complications. All-cause mortality in LPM patients with a CCI ≤ 3 was comparable to age- and sex-adjusted mortality in the general Swiss population. Despite a relatively high three-year mortality due to competing risk factors, LPM implantation is safe, even in elderly patients with high comorbidity.
CONCLUSIONS: In this Swiss, multi-centre, retrospective cohort analysis, 863 patients implanted with a leadless pacemaker were included and divided into a high-comorbidity (with a CCI > 5) and low-comorbidity (with a CCI ≤ 5) group. There was no between group difference in terms of implantation outcomes and peri-operative or long-term complications. Furthermore, all-cause mortality during follow-up in patients with a CCI ≤ 3 was comparable to age- and sex-adjusted mortality in the general Swiss population. These data indicate that LPM implantation is a safe procedure, even in elderly patients with high comorbidity.

OBJECTIVE: The current knowledge about the role of comorbidities in systemic sclerosis (SSc) is limited. Therefore, the aim of this study was to evaluate the prevalence of comorbidities and their impact on disease activity and prognosis in the Systemic sclerosis PRogression INvestiGation (SPRING) registry.
METHODS: SSc patients from the SPRING registry, fulfilling the ACR/EULAR 2013 classification criteria, with complete data on baseline comorbidities were enrolled. The Charlson comorbidity index (CCI) was used to quantify the overall comorbidity burden. The disease activity was calculated using the revised EUSTAR activity index (AI). The impact of SSc features on CCI, the effect of CCI on SSc disease activity and mortality were tested with multivariable regression models.
RESULTS: Among 1910 SSc patients enrolled, 67.3 % had at least one comorbidity at baseline. The most frequent comorbidities were systemic arterial hypertension (23.7 %), osteoporosis (12.9 %) and dyslipidemia (11 %). The mean value of CCI score was 2.0 ± 1.8. When patients were grouped according to increasing levels of CCI, a clear separation in the distribution of SSc-related clinical features could be observed. Among over 900 patients with available follow-up, no association between baseline CCI and changes in disease activity was observed. Conversely, the risk of death over time was independently predicted by both CCI and AI.
CONCLUSIONS: Comorbidities and disease activity independently impact on the prognosis of SSc patients. This suggests that the management of comorbidities, together with the reduction of disease activity, is fundamental to improve patient survival.

UNASSIGNED: This study evaluated national trends in cemented and uncemented reverse shoulder arthroplasty (RSA) for proximal humerus fractures using a comprehensive national surgical database. This study aimed to compare RSA used in the treatment of proximal humerus fractures with the literature and to determine the country\'s trend.
UNASSIGNED: A cross-sectional study was conducted using the health records of individuals aged ≥ 18 years who underwent RSA for proximal humerus fractures between 2016 and 2022. Patients were divided into cemented and uncemented groups, and demographic data (age, sex), duration of hospital stay, transfusions, revisions, mortality, and Charlson Comorbidity Index (CCI) scores were analyzed.
UNASSIGNED: A total of 618 cemented RSA and 1,364 uncemented RSA procedures were reviewed. Patients who underwent cemented RSA were significantly older than those who had uncemented RSA (p = 0.002). Transfusion rates were higher in the cemented RSA group (p = 0.006). The frequency of revision surgery was 6.1%. Younger age and male sex were associated with revision (p < 0.001). CCI scores were higher among transfused patients than non-transfused patients (p < 0.001). The incidence of cemented RSA was 11.7% and 49% in 2016 and 2022, respectively. Differences were found among hospital types and geographical regions.
UNASSIGNED: While cemented RSA has been gaining attention and increased application in recent years for proximal humerus fractures, uncemented RSA still predominates. The choice between these 2 methods is largely influenced by regional and hospital-level factors. The type of RSA and high CCI scores were found to have no significant impact on the risk of surgical revision.

BACKGROUND: The Charlson Comorbidity Index (CCI) is widely utilized for risk stratification for non-cardiac surgical patients, yet it has not been broadly validated in patients undergoing cardiac surgery. We aim to assess its ability to predict early and late outcomes of concomitant mitral valve intervention with ascending aortic surgery.
METHODS: Patients who underwent surgery between 1997 and 2022 were reviewed. Age-adjusted CCI scores were calculated based on clinical status at a time of index operation. The primary endpoint was all causes mortality while secondary outcomes were major adverse events (MAE) that included combined perioperative mortality, dialysis, myocardial infarction, and stroke in addition to the individual outcomes and take back for bleeding and tracheostomy. Chi-square test, Logistic and Cox regression analysis, and Kaplan-Meier curves were used. Maximally selected rank statistics were used to identify best cutoff of CCI for late mortality.
RESULTS: 186 patients (median age 65 [interquartile range (IQR): 54-76] and 69% males) were included with a median CCI of 4 [IQR: 3-6]. Five and ten-years overall survival were 95.9% and 67.1% vs 59.7%, and 19.9% in CCI ≤ 5 vs >5 (P < 0.001). On multivariate Cox regression analysis, higher CCI (HR 1.60 [1.17;2.18], P = 0.00), and lower EF (HR 0.89 [0.83;0.96], P = 0.002) were associated with late mortality. There was a trend to lower mortality in recent surgery years (HR 0.91 [0.83;1.01], P = 0.070)). Perioperative MAE was higher in CCI >5 (11.0% vs 2.1%, P = 0.017), and postoperative need for tracheostomy and CVA had a trend to be higher in CCI > 5 (P = 0.055). Logistic regression revealed that higher CCI, as a continuous variable, was associated with significantly higher odds of MAE, postoperative dialysis, and need for tracheostomy.
CONCLUSIONS: The CCI can be a helpful tool in predicting outcomes of patients undergoing concomitant mitral valve intervention with ascending aortic surgery.

Chronic obstructive pulmonary disease (COPD) patients are particularly susceptible to respiratory infections like influenza, which exacerbate symptoms and increase healthcare utilization. While smoking cessation and influenza vaccination are recommended preventive measures, their combined impact on healthcare resource utilization is underexplored. The Charlson Comorbidity Index (CCI) assesses comorbidity burden in COPD patients and may influence healthcare outcomes. We conducted a retrospective analysis of 357 COPD patients, evaluating smoking cessation success over one year and influenza vaccination receipt, stratifying patients by CCI scores. Healthcare utilization outcomes included emergency room visits, hospitalizations, and medical expenses. Results showed that 51.82% of patients quit smoking and 59.66% received influenza vaccination, with higher comorbidity prevalence in advanced COPD stages (p = 0.002). Both smoking cessation and influenza vaccination independently correlated with decreased emergency room visits, hospital admissions, days, and costs. Patients who both quit smoking and received influenza vaccination exhibited the lowest healthcare utilization rates. In conclusion, smoking cessation and influenza vaccination significantly reduce healthcare resource utilization in COPD patients, with the combination yielding synergistic benefits, particularly in those with lower CCI scores. Integrating these interventions and comorbidity management in COPD strategies is essential for optimizing patient outcomes and healthcare efficiency.

Radical cystectomy (RC) remains a mainstay surgical treatment for non-metastatic muscle-invasive and BCG-unresponsive bladder cancer. Various perioperative scoring tools assess comorbidity burden, complication risks, and cancer-specific mortality (CSM) risk. We investigated the prognostic value of these scores in patients who underwent RC between 2015 and 2021. Cox proportional hazards were used in survival analyses. Risk models\' accuracy was assessed with the concordance index (C-index) and area under the curve. Among 215 included RC patients, 63 (29.3%) died, including 53 (24.7%) cancer-specific deaths, with a median follow-up of 39 months. The AJCC system, COBRA score, and Charlson comorbidity index (CCI) predicted CSM with low accuracy (C-index: 0.66, 0.65; 0.59, respectively). Multivariable Cox regression identified the AJCC system and CCI > 5 as significant CSM predictors. Additional factors included the extent of lymph node dissection, histology, smoking, presence of concomitant CIS, and neutrophil-to-lymphocyte ratio, and model accuracy was high (C-index: 0.80). The internal validation of the model with bootstrap samples revealed its slight optimism of 0.06. In conclusion, the accuracy of the AJCC staging system in the prediction of CSM is low and can be improved with the inclusion of other pathological data, CCI, smoking history and inflammatory indices.

OBJECTIVE: With new therapies for metastatic prostate cancer, patients are living longer, increasing the need for better understanding of the impact of comorbid disease. Prescription medications may risk-stratify patients independent of established methods, such as the Charlson Comorbidity Index (CCI) and guide treatment selection.
METHODS: In a nationwide retrospective study of US Veterans, we used multivariable logistic regression and Cox proportional hazard modeling to evaluate the association between number and class of prescription medications and overall survival (OS) with age, race, body-mass index, prostate specific antigen (PSA), and Charlson comorbidities as covariates in veterans treated for de novo metastatic hormone sensitive prostate cancer (mHSPC) between 2010-2021.
RESULTS: Among 8,434 Veterans, a median of nine medications and five medication classes were filled in the year prior to initial treatment with abiraterone or enzalutamide for mHSPC. Veterans on 1-4 medications had an average survival of 38 months compared to 5-9 medicines (33 months), 10-14 medicines (27 months), and 15+ medicines (22 months) (p<0.001). After adjusting for age, race, body mass index (BMI), PSA, CCI, and year of diagnosis, both the number of medications and medication classes were associated with increased mortality. The adjusted hazard ratio (aHR) [95% confidence interval (CI)] was 1.03 (1.02-1.03) for the number of medications and 1.05 (1.04-1.07) for medication classes. Medications within ATC B (blood/blood forming organs), ATC C (cardiovascular), and ATC N (nervous) were associated with worse OS, with aHRs of 1.14 (1.07, 1.21), 1.14 (1.06, 1.22), and 1.12 (1.06, 1.19), respectively.
CONCLUSIONS: The number and class of medications were independently associated with overall survival in patients undergoing treatment for mHSPC. With new therapies for advanced prostate cancer, patients are living longer, highlighting the need for a better understanding of the impact of comorbid diseases. Simple methods to assess disease burden and prognosticate survival have the potential to guide treatment decisions.

Care for patients with cancer is more challenging when they have concurrent, complex comorbidities. Risk assessment tools may help to enhance care assessment and predict poor clinical outcomes for these patients. This article.

BACKGROUND: The Blood Cancer Network Ireland and National Cancer Registry Ireland worked to create an Enhanced Blood Cancer Outcomes Registry (EBCOR). Enhanced data in acute myeloid leukaemia (AML) included an extensive data dictionary, bespoke software and longitudinal follow-up.
OBJECTIVE: To demonstrate the utility of the database, we applied the data to examine a clinically relevant question: Charlson comorbidity index (CCI) usefulness in predicting AML patients\' survival.
METHODS: A software designer and consultant haematologists in Cork University Hospital worked together to standardise a data dictionary, train registrars and populate a database. One hundred and forty-one AML patients underwent enhanced data registration. Comorbidities identified by chart review were used to examine the capability of the CCI and age at diagnosis to predict mortality using Kaplan-Meier curves, Cox regression and receiver operating characteristic curves.
RESULTS: In regression analysis, a dose-response relationship was observed; patients in the highest CCI tertile displayed a greater risk (HR = 4.90; 95% CI 2.79-8.63) of mortality compared to subjects in tertile 2 (HR = 2.74; 95% CI 1.64-4.57) and tertile 1 (reference). This relationship was attenuated in an analysis which adjusted for age at diagnosis. The area under the curve (AUC) for the CCI was 0.76 (95% CI 0.68-0.84) while the AUC for age at diagnosis was 0.84 (95% CI 0.78-0.90).
CONCLUSIONS: Results suggest that the CCI provides no additional prognostic information beyond that obtained from age alone at AML diagnosis and that an EBCOR can provide a rich database for cancer outcomes research, including predictive models and resource allocation.

OBJECTIVE: Head and neck cancer surgery often requires postoperative monitoring in an intensive care unit (ICU) or intermediate care unit (IMC). With a variety of different risk scores, it is incumbent upon the investigator to plan a risk-adapted allocation of resources. Tumor surgery in the head and neck region itself offers a wide range of procedures in terms of resection extent and reconstruction methods, which can be stratified only vaguely by a cross-disciplinary score. Facing a variety of different risk scores we aimed to develop a new Tumor Risk Score (TRS) enabling anterograde preoperative risk evaluation, resource allocation and optimization of cost and outcome measurements in tumor surgery of the head and neck.
METHODS: A collective of 547 patients (2010-2021) with intraoral tumors was studied to develop the TRS by grading the preoperative tumor size and location as well as the invasiveness of the planned surgery by means of statistical modeling. Two postoperative complications were defined: (1) prolonged postoperative stay in IMC/ICU and (2) prolonged total length of stay (LOS). Each parameter was analyzed using TRS and all preoperative patient parameters (age, sex, preoperative hemoglobin, body-mass-index, preexisting medical conditions) using predictive modeling design. Established risk scores (Charlson Comorbidity Index (CCI), American Society of Anesthesiologists risk classification (ASA), Functional Comorbidity Index (FCI)) and Patient Clinical Complexity Level (PCCL) were used as benchmarks for model performance of the TRS.
RESULTS: The TRS is significantly correlated with surgery duration (p < 0.001) and LOS (p = 0.001). With every increase in TRS, LOS rises by 9.3% (95%CI 4.7-13.9; p < 0.001) or 1.9 days (95%CI 1.0-2.8; p < 0.001), respectively. For each increase in TRS, the LOS in IMC/ICU wards increases by 0.33 days (95%CI 0.12-0.54; p = 0.002), and the probability of an overall prolonged IMC/ICU stay increased by 32.3% per TRS class (p < 0.001). Exceeding the planned IMC/ICU LOS, overall LOS increased by 7.7 days (95%CI 5.35-10.08; p < 0.001) and increases the likelihood of also exceeding the upper limit LOS by 70.1% (95%CI 1.02-2.85; p = 0.041). In terms of predictive power of a prolonged IMC/ICU stay, the TRS performs better than previously established risk scores such as ASA or CCI (p = 0.031).
CONCLUSIONS: The lack of a standardized needs assessment can lead to both under- and overutilization of the IMC/ICU and therefore increased costs and losses in total revenue. Our index helps to stratify the risk of a prolonged IMC/ICU stay preoperatively and to adjust resource allocation in major head and neck tumor surgery.