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Background/Aim: Current evidence regarding the optimal management of older colorectal cancer patients, is conflicting. Functional deficits impact long-term survival prognosis, while frailty often results to optimal treatment postponement. Thus, the characteristics of this subgroup combined with treatment deviations further perplex optimal oncological management. The study aim was to compare survival and optimal surgery rates between older and younger colorectal cancer patients. Patients and Methods: This study was designed as a prospective cohort. All adult (318 years) colorectal cancer patients operated, during the 2016-2020 period, in the Department of Surgery, University Hospital of Larissa, were considered as eligible. The primary endpoint of the study was the difference in terms of the overall survival between older (>70 year) and younger (<70 years) colorectal cancer patients. Results: Overall, 166 patients (60 younger and 106 older) were enrolled. Although the older subgroup displayed a higher rate (p=0.007) of ASA II and ASA III patients, mean CCI scores were comparable (p=0.384). The two subgroups were similar in terms of performed operations (p=0.140). No delay in surgery was noted. Most operations were performed using an open approach (open: 57.8% vs. laparoscopic: 42.2%), under an elective status (elective: 91% vs. emergency: 1.8%). There was no difference in terms of overall complications rate (p=0.859). Overall survival was similar (p=0.227) between the older and younger subgroups (25.68 vs. 28.48 months). Conclusion: Older operated patients did not differ from their younger counterparts with regard to their overall survival. Due to several study limitations, further trials are required to confirm these findings. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) is the most common type of acute leukemia in adults and patients older than 65 years have a poor prognosis. Patient-related factors, such as comorbid conditions that affect performance status, and insufficient organ functions, explain why elderly patients have a worse prognosis. The Charlson Comorbidity Index (CCI), is used to predict prognosis according to comorbidities. This retrospective study was conducted on patients diagnosed with AML between 2010 and 2019. Patients >60 years were included. Demographic information, comorbidities, CCI, ECOG (Eastern Cooperative Oncology Group) score, cytogenetic characteristics, treatment regimens, treatment response, follow-up periods were recorded for all patients. Evaluation was made of a total of 82 patients with a mean age of 71.18 ± 7.67. The median follow-up was 6.7 months. The median number of comorbidities was 1 [0.0-4.0] with the median CCI score of 3 [2.0-6.0]. Median overall survival (OS) was 7.0 months [3.1-10.8] and PFS was 6.8 months [3.6-10.0]. As the median CCI score was 3, patients were divided into two groups as CCI > 3 and CCI = 3. Age, gender, ECOG, cytogenetic risk profile, first-line treatment and CR1 achievement status were all similar in both groups (p > 0.05). Patients with CCI > 3 had significantly shorter OS than patients with CCI = 3 (3.6 months [0.3-29.3] vs 8.6 months [0.2-60.2], p= 0.049). The results of the current study demonstrated that CCI, can be used as a prognostic index in elderly patients with AML independently of other patient and disease-related characteristics. [ABSTRACT FROM AUTHOR]

Shoulder arthroplasty (SA) procedures are increasingly common. The Charlson and Elixhauser indices are ICD-10 based measures used in large databases to describe the patient case mix in terms of secondary medical conditions. There is a paucity of data on the relationship between these indices and patient-reported outcome measures (PROMs) after shoulder arthroplasty. Patients undergoing SA from 2016-2018 were identified in the electronic medical records. Charlson and Elixhauser comorbidities were used to calculate comorbidity scores according to established algorithms (eg Elixhauser-Walraven). Patient shoulder-specific (American Shoulder and Elbow Surgeons (ASES) score and Shoulder Activity Scale (SAS)) and general health scales (SF-12 Mental Component Score (MCS) and Physical Component Score (PCS) and Patient-Reported Outcomes Measurement Information System-Pain Interference (PROMIS-PI)) PROMs were obtained from our institution's shoulder registry. Linear regression models adjusting for age and sex evaluated associations between comorbidity scores and PROMs. Receiver operating characteristic (ROC) curves determined optimal cutoffs, maximizing sensitivity and specificity to identify patients likely to fail to meet minimal clinically important difference (MCID) values. A total of 1817 SA procedures were identified. Higher Charlson and Elixhauser-Walraven scores were significantly associated with lower baseline SAS and SF-12 PCS. Patients with higher Charlson scores had lower baseline ASES (P =.003) and lower baseline (P =.0002) and 2-year (P =.02) SF-12 MCS. No significant associations were found for PROMIS-PI with either index. The Charlson score better predicted the failure to meet MCID for SF-12 PCS with an AUC of 0.64, compared to 0.55 for Elixhauser-Walraven. Conversely, Elixhauser-Walraven better predicted PROMIS-PI with an AUC of 0.66, compared to 0.53 for Charlson. Moderate AUCs were observed for the remaining PROMs, ranging from 0.57-0.64, with little difference between index scores. Higher Charlson and Elixhauser-Walraven scores were associated with lower baseline scores on most PROMs. Generally, the Charlson score performed better than the Elixhauser-Walraven score in predicting worse outcomes at 2 years. Comorbidity indices may be useful as a decision aid to provide appropriate expectations of outcomes for patients undergoing SA. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to test whether a newly designed polypharmacy‐based scale would perform better than Charlson's Comorbidity Index (CCI) to predict outcomes in chronic complex adult patients after a reference Emergency Department (ED) visit. Methods: We built a polypharmacy‐based scale with prespecified drug families. The primary outcome was 6‐month mortality after the reference ED visit. Predefined secondary outcomes were need for hospital admission, 30‐day readmission, and 30‐day and 90‐day mortality. We evaluated the ability of the CCI and the polypharmacy‐based scale to independently predict 6‐month mortality using logistic regression, receiver operating characteristic (ROC) curves, and cumulative survival curves using Kaplan–Meier estimates and the log‐rank test for three‐category distributions of the polypharmacy‐based scale and the CCI. Finally, we sought to replicate our results in two different external validation cohorts. Results: We included 201 patients (53.7% women, mean age = 81.4 years), 162 of whom were admitted to the hospital at the reference ED visit. In separate multivariable analyses accounting for gender, age and main diagnosis at discharge, both the polypharmacy‐based scale (P <.001) and the CCI (P =.005) independently predicted 6‐month mortality. The polypharmacy‐based scale performed better in the ROC analyses (area under the curve [AUC] = 0.838, 95% confidence interval [CI] = 0.780–0.896) than the CCI (AUC = 0.628, 95% CI = 0.548–0.707). In the 6‐month cumulative survival analysis, the polypharmacy‐based scale showed statistical significance (P <.001), whereas the CCI did not (P =.484). We replicated our results in the validation cohorts. Conclusions: Our polypharmacy‐based scale performed significantly better than the CCI to predict 6‐month mortality in chronic complex patients after a reference ED visit. [ABSTRACT FROM AUTHOR]

Miao Cai,1 Echu Liu,2 Ruihua Zhang,3 Xiaojun Lin,4,5 Steven E Rigdon,1 Zhengmin Qian,1 Rhonda Belue,2 Jen-Jen Chang1 1Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA; 2Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA; 3School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu 610075, Sichuan, People’s Republic of China; 4West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, Sichuan, People’s Republic of China; 5West China Research Center for Rural Health Development, Sichuan University, Chengdu 610041, Sichuan, People’s Republic of ChinaCorrespondence: Ruihua ZhangSchool of Management, Chengdu University of Traditional Chinese Medicine, 1166 Liutaidadao, Chengdu 610075, Sichuan, People’s Republic of ChinaEmail zhangruihua@cdutcm.edu.cnObjective: Earlier comorbidity measures have been developed or validated using the North American population. This study aims to compare five Charlson or Elixhauser comorbidity indices to predict in-hospital mortality using a large electronic medical record database from Shanxi, China.Methods: Using the primary diagnosis code and surgery procedure codes, we identified four hospitalized patient cohorts, hospitalized between 2013 and 2017, in Shanxi, China, as follows: congestive heart failure (CHF, n=41,577), chronic renal failure (CRF, n=40,419), diabetes (n=171,355), and percutaneous coronary intervention (PCI, n=39,097). We used logistic regression models and c-statistics to evaluate the in-hospital mortality predictive performance of two multiple comorbidity indicator variables developed by Charlson in 1987 and Elixhauser in 1998 and three single numeric scores by Quan in 2011, van Walraven in 2009, and Moore 2017.Results: Elixhauser comorbidity indicator variables had consistently higher c-statistics (0.824, 0.843, 0.904, 0.853) than all other four comorbidity measures, across all four disease cohorts. Moore’s comorbidity score outperformed the other two score systems in CHF, CRF, and diabetes cohorts (c-statistics: 0.776, 0.832, 0.869), while van Walraven’s score outperformed all others among PCI patients (c-statistics: 0.827).Conclusion: Elixhauser comorbidity indicator variables are recommended, when applied to large Chinese electronic medical record databases, while Moore’s score system is appropriate for relatively small databases.Keywords: comorbidity, Charlson, Elixhauser, administrative data, China

Objectives: Comorbidity along with tumor and patient characteristics is taken into account when deciding for the surgical treatment of renal cell carcinoma (RCC). Comorbidity has also been used as an independent predictive factor for postoperative complications of several major urological procedures including radical nephrectomy for RCC. The aim of the present study was to objectively evaluate the association between comorbidity and postoperative complications after radical nephrectomy for RCC, using standardized systems to grade both comorbidity and severity of postoperative complications. Materials and methods: Clinicopathological data of 171 patients undergoing open radical nephrectomy for lesions suspected of RCC were prospectively recorded for a period of 3 years. Comorbidity was scored using the Charlson Comorbidity Index (CCI) while postoperative complications were graded according to the Clavien-Dindo system. Results: Patients were predominantly males (59.1%); their age ranged from 35 to 88 years (mean ± SD: 63.6 ± 11.9 yrs) with 50.8% of them being ≤ 65 yrs. CCI ranged from 0 to 8 with the majority (85.3%) scoring ≤ 2. The procedure was uncomplicated in 57.3% cases; 10 patients suffered major (grade III/IV) complications and 4 patients died within the 40 days postoperative period. CCI correlated with the manifestation of any postoperative complication, Clavien ≥ 1, OR (95% CI): 1.47 (1.09-1.96), p = 0.011 and the occurrence of severe complications, Clavien > 2. OR (95% CI): 1.29 (1.01-1.63), p = 0.038. Conclusions: The present prospective study showed that considerable complications occur in patients with major comorbidities. CCI is easily calculated and should be incorporated in preoperative consultation especially in cases of elder patients with severe comorbidity and favorable tumor characteristics where less invasive interventions or even active surveillance could be applied.

Abstract Background Comorbidity measures, such as the Charlson Comorbidity Index (CCI) and Elixhauser Method (EM), are frequently used for risk-adjustment by healthcare researchers. This study sought to create CCI and EM lists of Read codes, which are standard terminology used in some large primary care databases. It also aimed to describe and compare the predictive properties of the CCI and EM amongst patients with hip fracture (and matched controls) in a large primary care administrative dataset. Methods Two researchers independently screened 111,929 individual Read codes to populate the 17 CCI and 31 EM comorbidity categories. Patients with hip fractures were identified (together with age- and sex-matched controls) from UK primary care practices participating in the Clinical Practice Research Datalink (CPRD). The predictive properties of both comorbidity measures were explored in hip fracture and control populations using logistic regression models fitted with 30- and 365-day mortality as the dependent variables together with tests of equality for Receiver Operating Characteristic (ROC) curves. Results There were 5832 CCI and 7156 EM comorbidity codes. The EM improved the ability of a logistic regression model (using age and sex as covariables) to predict 30-day mortality (AUROC 0.744 versus 0.686). The EM alone also outperformed the CCI (0.696 versus 0.601). Capturing comorbidities over a prolonged period only modestly improved the predictive value of either index: EM 1-year look-back 0.645 versus 5-year 0.676 versus complete record 0.695 and CCI 0.574 versus 0.591 versus 0.605. Conclusions The comorbidity code lists may be used by future researchers to calculate CCI and EM using records from Read coded databases. The EM is preferable to the CCI but only marginal gains should be expected from incorporating comorbidities over a period longer than 1 year.

Background This study’s aim was to investigate an association between outcome from in-hospital cardiopulmonary resuscitation (CPR) and increasing burden of comorbidities and frailty. Methods Retrospective analysis of prospectively collected data from contemporaneous patient notes and electronic records of all patients who suffered an in-hospital cardiac arrest between 1 April 2017 and 31 March 2018 in a hospital that includes a tertiary cardiology department. Results A total of 113 patient records were assessed. Patient frailty was assessed based on calculation of Rockwood clinical frailty score (CFS) and comorbidity assessment based on Charlson comorbidity index (CCI). A linear correlation has been identified between increasing CCI and reduced survival (ANOVA = p<0.001) and rates of return of spontaneous circulation (ROSC) (ANOVA = 0.013). No patients with a CFS above 6 survived to 1 year. A linear correlation was identified between increasing CFS and reduced probability of ROSC (ANOVA p=0.002), survival to discharge (ANOVA p=0.003) and 1 year (ANOVA p=0.001). Conclusion Our findings suggest an association between increasing patient multimorbidity and frailty and poorer outcome post cardiac arrest. [ABSTRACT FROM AUTHOR]

Objectives: Comorbidity along with tumor and patient characteristics is taken into account when deciding for the surgical treatment of renal cell carcinoma (RCC). Comorbidity has also been used as an independent predictive factor for postoperative complications of several major urological procedures including radical nephrectomy for RCC. The aim of the present study was to objectively evaluate the association between comorbidity and postoperative complications after radical nephrectomy for RCC, using standardized systems to grade both comorbidity and severity of postoperative complications. Materials and methods: Clinicopathological data of 171 patients undergoing open radical nephrectomy for lesions suspected of RCC were prospectively recorded for a period of 3 years. Comorbidity was scored using the Charlson Comorbidity Index (CCI) while postoperative complications were graded according to the Clavien-Dindo system. Results: Patients were predominantly males (59.1%); their age ranged from 35 to 88 years (mean ± SD: 63.6 ± 11.9 yrs) with 50.8% of them being ≤ 65 yrs. CCI ranged from 0 to 8 with the majority (85.3%) scoring ≤ 2. The procedure was uncomplicated in 57.3% cases; 10 patients suffered major (grade III/IV) complications and 4 patients died within the 40 days postoperative period. CCI correlated with the manifestation of any postoperative complication, Clavien ≥ 1, OR (95% CI): 1.47 (1.09-1.96), p = 0.011 and the occurrence of severe complications, Clavien > 2. OR (95% CI): 1.29 (1.01-1.63), p = 0.038. Conclusions: The present prospective study showed that considerable complications occur in patients with major comorbidities. CCI is easily calculated and should be incorporated in preopera-tive consultation especially in cases of elder patients with severe comorbidity and favorable tumor characteristics where less invasive interventions or even active surveillance could be applied. [ABSTRACT FROM AUTHOR]

Background: Open radical cystectomy (ORC) with pelvic lymph-node dissection (PLND) for bladder cancer (BCa) and urinary diversion is a morbid procedure, and advanced age has been associated with a higher incidence of Clavien–Dindo ≥ 3 complications. Aim: To investigate the association between chronological age, survival outcomes, incidence of perioperative complications, and quality parameters in patients undergoing ORC. Methods: We reviewed 413 patients who underwent ORC and PLND at a single academic centre between December 2009 and June 2018 for cT2-T4N0M0 BCa. Complete clinical, demographic, and pathological data were collected in the preoperative, preoperative, and postoperative setting. Patients were categorized as ≥ 75 years or < 75 years and statistical analysis was performed accordingly. Besides descriptive statistics, Kaplan–Meier log-rank test was used. Cox regression univariate and multivariate analyses were used to assess any potential predictor of OS and CSS. Results: There were 285 (69%) patients < 75 years and 128 (31%) patients ≥ 75 years old. There was no significant difference between the two age groups neither in terms of distribution of pathological stage nor in terms of overall incidence of postoperative complications. Chronological age was not significantly associated with survival outcomes on multivariate analysis. Finally, the comorbidity index was the only significant risk factor for the incidence of any complications (OR = 0.83, p = 0.002) at multivariate binary logistic regression. Conclusion: Open radical cystectomy (ORC) is a feasible and safe procedure in patients with high-risk non-metastatic bladder cancer. Uro-oncologists should consider evaluating elderly patients for surgery according to a thorough geriatric assessment despite chronological age. [ABSTRACT FROM AUTHOR]

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Objectives: Few studies have evaluated the impact of risk factors and comorbidity on overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDAC). The aim was to investigate the prognostic importance of Charlson's age‐comorbidity index (CACI) and other risk factors on prognosis in a clinical real‐world cohort of PDAC patients. Methods: A total of 1,159 patients with PDAC who had received at least one cycle of adjuvant or palliative chemotherapy were included from the Danish BIOPAC study. We analysed OS according to CACI, tobacco smoking, alcohol intake, performance status (PS), BMI and diabetes. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for OS using Cox proportional hazards regression. Results: At the end of follow‐up, 994 (86%) patients had died. The median OS was 298 days for all patients (range 3–3010) and shortest in patients with stage IV. No association with short OS was seen for CACI > 2, diabetes, alcohol abuse, tobacco smoking, hypertension, and high BMI. Multivariate analysis showed that stage (IV vs. I: HR = 9.05, 95% CI 5.17–15.84), PS (2 vs. 0: HR = 3.67, 2.92–4.61) and treatment with angiotensin‐converting enzyme inhibitors (yes vs. no: HR = 1.31, 1.06–1.61) were independent negative prognostic factors. Conclusions: We found that CACI, diabetes, tobacco smoking, alcohol abuse, hypertension, and high BMI were not associated with OS in a real‐world cohort of patients with PDAC treated with chemotherapy. Only stage and PS were prognostic parameters. [ABSTRACT FROM AUTHOR]

The objective of this study was to determine the ability of the Elixhauser Comorbidity Index (ECI) and Charlson Comorbidity Index (CCI) to predict postoperative complications after anterior cervical discectomy and fusion (ACDF). This was a retrospective study of ACDF hospitalizations in the National Inpatient Sample from 2013 to 2014. The ECI and CCI were calculated, and patients who experienced postoperative complications were identified. The ability of these indexes to predict complications was compared using the c statistic (area under the receiver operating characteristic curve [AUC]). In addition, the CCI and ECI were compared with a base model that included age, sex, race, and primary payer. A total of 261,780 patients were included. Patients who experienced a complication were more often male (P < 0.0001) and older (P < 0.0001). They also had a higher comorbidity burden as assessed by both the ECI (P < 0.0001) and the CCI (P < 0.0001). The ECI was superior in predicting airway complications (AUC, 0.81 vs. 0.75; P < 0.0001), hemorrhagic anemia (AUC, 0.67 vs. 0.63; P = 0.0015), pulmonary embolism (AUC, 0.91 vs. 0.77; P < 0.0001), wound dehiscence (AUC, 0.80 vs. 0.55; P = 0.0080), sepsis (AUC, 0.87 vs. 0.82; P = 0.0001), and septic shock (AUC, 0.94 vs. 0.83; P < 0.0001). The CCI was not found to be superior to the ECI for predicting any complications. Both were excellent for predicting mortality (ECI AUC, 0.87; CCI AUC, 0.90). The ECI was superior to the CCI in predicting 6 of 15 complications in this study. Both are excellent tools for predicting mortality after ACDF. [ABSTRACT FROM AUTHOR]

Purpose: Survival difference between socioeconomic groups with ovarian cancer has persisted in the United Kingdom despite efforts to reduce disparities in care. Our aim was to delineate critical episodes in the patient journey, where deprivation has most impact on survival.Methods: A retrospective review of 834 patients with advanced ovarian cancer (AOC) between 16/8/07-16/2/17 at a large cancer centre serving one of the most deprived areas of the UK. Using the Index of Multiple Deprivation (IMD), patients were categorised into five groups.Results: Surgery was more common in less deprived patients (p < 0.00001). Across IMD groups, there were no differences in complete (R0) cytoreduction rate (r = 0.18, p > 0.05), age, or comorbidity. The R0/total cohort rate increased with increasing IMD group (p < 0.0001). Patients refusing any intervention belonged exclusively to the three most deprived groups; 5/7 patients who refused surgery belonged to the most deprived IMD group. Overall survival in the total patient group was less in IMD group 1-2 compared to 9-10 (p = 0.002). On multivariate analysis, IMD group was not an independent predictor of survival (p > 0.05).Conclusions: Socioeconomic differences in survival manifest in patients not receiving surgical treatment for AOC and are not purely explained by comorbidity, age, stage, or histological factors. [ABSTRACT FROM AUTHOR]

Purpose: Accounting for comorbidity in predicting outcomes for patients is vital in clinical care, epidemiological research, and health service planning. The aim of this study was to review published literature to compare the performance of existing comorbidity indices and their use in injury populations.Methods: A thematic literature search for comorbidity indices and/or injury outcomes was conducted. Methods, results, and recommendations from selected articles were abstracted, documented, and compared; comparisons of results were made in terms of the indices' ability to predict outcomes, using the C-statistic, R2, and odds ratios.Results: Fifty-two articles relating to the derivation and/or validation of comorbidity measures were found. The most commonly used measures were the Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Measure (ECM). The ECM was found to outperform the CCI in terms of predictive ability, although the CCI was more widely used. Derivation of study-specific weights to the CCI added more predictive power to the index.Conclusions: Existing literature that compared the predictive abilities of the ECM and CCI favors the ECM. This literature review did not identify a measure specifically designed for general injury populations. Development of an injury-specific comorbidity measure will be timely and assist future research in injury epidemiology. [ABSTRACT FROM AUTHOR]

Abstract Background To assess the use of updated comorbidity information over time on ability to predict mortality among adults with newly diagnosed hypertension. Methods We studied adults 18 years and older with an incident diagnosis of hypertension from Alberta, Canada. We compared the prognostic performance of Cox regression models using Charlson comorbidities as time-invariant covariates at baseline (TIC) versus models including Charlson comorbidities as time-varying covariates (TVC) using Akaike Information Criterion (AIC) for testing goodness of fit. Results The strength of the association between important prognostic clinical variables and mortality varied by modeling technique; for example, myocardial infarction was less strongly associated with mortality in the TIC model (Hazard Ratio 1.07; 95% Confidence Interval (CI): 1.05 to 1.1) than in the TVC model (HR 1.20; 95% CI: 1.18 to 1.22). All TVC models slightly outperformed TIC models, regardless of the method used to adjust for comorbid conditions (individual Charlson Comorbidities, count of comorbidities or indices). The TVC model including all 17 Charlson comorbidities as individual independent variables showed the best fit and performance. Conclusion Accounting for changes in patient comorbidity status over time more accurately captures a patient’s health risk and slightly improves predictive model fit and performance than traditional methods using TIC assessment.

Background: The Deyo/Charlson co-morbidity index (CCI) and Klabunde co-morbidity index (KCI) co-morbidity indexes represent outdated indexes when the endpoint of complications after radical prostatectomy (RP) is considered. A novel group of co-morbidities derived from International Classification of Diseases-9 diagnostic codes in a contemporary RP database could provide better accuracy. Research Design, Subjects and Measures: We relied on 20,484 patients with clinically localized non-metastatic prostate cancer treated with RP between 2000 and 2009 in the Surveillance, Epidemiology, and End Results-Medicare linked database. We examined 2 endpoints, namely, 90-day medical complication rate and 90-day surgical complication rate after RP. Simulated annealing (SA) was used to develop a novel co-morbidity index. Finally, the newly identified groups of co-morbid conditions were compared with the CCI and Klabunde indexes. Results: Our SA identified 10 and 7 individual co-morbid conditions able to predict 90-day medical and surgical complications respectively. This novel model showed improved predictive accuracy over CCI and KCI for the 2 endpoints considered (respectively: 59.4 vs. 58.1 and 58.0% for medical complications, 58.0 vs. 56.8 and 56.7% for surgical complications). Conclusions: The newly defined groupings of co-morbid conditions resulted in better ability to predict the 2 endpoints of interest compared to CCI and KCI. However, the gain was marginal. This implies that better tools should be defined to more accurately predict these outcomes. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the 90 days and 1 year mortality predictive ability of the RxRisk-V, Charlson, and Elixhauser co-morbidity measures in total hip arthroplasty (THA) and total knee arthroplasty (TKA) patients.Method: A retrospective study of 11,848 THAs and 18,972 TKAs (2001-2002) was conducted. Death within 90 days and 1 year of the surgery were the main endpoints. Co-morbidity measures were calculated using either medication or hospitalisation history. Logistic regression models were employed and discrimination and calibration were assessed. Specifically, models with unweighted and weighted measure scores, models with the specific conditions, and a model combining conditions identified by all measures were assessed.Results: In THAs, the best performing prediction models included co-morbidities from all three measures (90 days: c = 0.84, P = 0.284, 1 year: c = 0.79, P = 0.158). Individually, the model with Charlson conditions performed best at 90 days mortality (c = 0.80, P = 0.777) and the Charlson and Elixhauser performed similarly at 1 year (both c = 0.77, P > 0.05). In TKAs, the best performing prediction model included co-morbidities from all measures (90 days: c = 0.82, P = 0.349, 1 year: c = 0.78, P = 0.873). Individually, the model with Elixhauser conditions performed best with 90 days mortality (c = 0.79, P = 0.435) and all performed similarly at 1 year (c = 0.74-0.75, all P > 0.05).Conclusions: A combined model with co-morbidities identified by the Elixhauser, Charlson, and RxRisk-V was the best mortality prediction model. The RxRisk-V did not perform as well as the others. Because of the Elixhauser and Charlson's similar performance we suggest basing the choice of measurement use on factors such as the need of specific conditions and modelling limitations. [ABSTRACT FROM AUTHOR]

Background: Many aspects of co-morbidity burden in Parkinson's disease (PD) are unclear, but it may be an important predictor of prognosis or confounder of associations in epidemiological studies.Objectives: To determine how best to assess co-morbidity burden in PD, to compare with matched controls, and investigate its association with prognostic outcomes.Methods: Data from an incident, community-based cohort with prospective follow-up (the PINE study) were used (198 patients with PD and 151 controls). The reliability of three co-morbidity scales (the Charlson co-morbidity index (CCI), the Cumulative Illness Rating scale and a simple disease count) were evaluated. The association with mortality and development of dependency was assessed with Cox regression. The co-morbidity burden in PD and controls was compared at baseline and over 5 years of follow-up using linear mixed modelling.Results: The CCI was more reliable and was an independent predictor of mortality with a time-dependent effect (hazard ratio = 1.27 [1.08-1.49] in first four years of follow-up; no significant association after four years). Associations between the other scales and mortality and between each scale and development of dependency were non-significant once adjusted for confounders. Co-morbidity burden was similar between cases and controls at baseline and there was no evidence of differential accrual of co-morbidity between patients and controls (p = 0.94).Conclusions: The CCI is probably the better scale for measuring co-morbidity burden in PD. There were no differences between PD and controls. Co-morbidity burden at diagnosis was associated with mortality in the early part of the disease course, but not later. [ABSTRACT FROM AUTHOR]

Objective. To assess the impact of pre-existing co-morbidities on mortality among patients affected by granulomatosis with polyangiitis (GPA). Methods. By means of the Danish National Hospital Register, we identified a cohort of patients hospita-lized for GPA during 1994-2010 (n = 308). The burden of pre-existing co-morbidities among the patients was quantified according to the Charlson Comorbidity Index (CCI). Each patient was matched with five age- and gender-matched population controls with no pre-existing co-morbidities captured by the CCI (CCI score = 0). The study subjects were followed throughout 2010. Cox regression analyses were used to calculate mortality rate ratios (MRRs). Results. The median duration of follow-up in the GPA cohort was 5.8 years (interquartile range 2.3-10.0). Compared with their matched population controls, the MRR for patients presenting with a CCI score of 0 (n = 246) was 3.9 (95% CI 2.0, 7.5) during years 0-2 and 1.4 (95% CI 0.9, 2.0) from the second year of follow-up onwards. The corresponding MRRs were 13.3 (95% CI 5.8, 31) and 1.9 (95% CI 1.1, 3.6) for patients with a CCI score ≥1 (n = 62). In a direct comparison, GPA patients with a CCI score ≥1 were found to have significantly higher mortality than GPA patients with a CCI score of 0 during years 0-2 [ad-justed MRR 3.4 (95% CI 1.6, 7.0)] but not after >2 years of follow-up [adjusted MRR 1.3 (95% CI 0.7, 2.6)]. Conclusion. During early follow-up periods, the mortality among GPA patients with pre-existing co-morbidities is markedly higher than that among GPA patients with no pre-existing illnesses. Our analyses identify an increased CCI score for pre-existing co-morbidities as an important risk factor for a fatal outcome in GPA. [ABSTRACT FROM AUTHOR]

Purpose: Adequate comorbidity risk adjustment is central for reliable outcome prediction and provider performance evaluation. The two most commonly employed risk-adjustment methods in orthopaedic surgery were not originally validated in this patient population. We sought (1) to develop a single numeric comorbidity score for predicting inpatient mortality in patients undergoing orthopaedic surgery by combining and reweighting the conditions included in the Charlson and Elixhauser measures, and to compare its predictive performance to each of the separate component scores. We also (2) evaluated the new score separately for spine surgery, adult reconstruction, hip fracture, and musculoskeletal oncology admissions. Methods: Data from the National Hospital Discharge Survey for the years 1990 through 2007 were obtained. A comorbidity score for predicting inpatient mortality was developed by combining conditions from the Charlson and Elixhauser measures. Weights were derived from a random sample of 80 % of the cohort ( n = 26,454,972), and the predictive ability of the new score was internally validated on the remaining 20 % ( n = 6,739,169). Performance of scores was assessed and compared using the area under the receiver operating characteristic curve (AUC) derived from multivariable logistic regression models. Results: The new combined comorbidity score (AUC = 0.858, 95 % CI 0.856-0.859) performed 58 % better than the Charlson score (AUC = 0.794, 95 % CI 0.792-0.796) and 12 % better than the Elixhauser score (AUC = 0.845, 95 % CI 0.844-0.847). Of the seven conditions that received the highest weights in the new combined score, only three of them were included in both the Charlson and the Elixhauser indices. The new combined score achieved higher discriminatory power for all orthopaedic admission subgroups. Conclusion: A single numeric comorbidity score combining conditions from the Charlson and Elixhauser models provided better discrimination of inpatient mortality than either of its constituent scores. Future research should test this score in other populations and data settings. [ABSTRACT FROM AUTHOR]

Background The benefit from intervention in elderly patients with symptomatic severe aortic stenosis (AS) and high comorbidity is unknown. Our aims were to establish the correlation between the Charlson comorbidity index and the prognosis of octogenarians with symptomatic sever AS and to identify patients who might not benefit from intervention. Methods We used the data from PEGASO (Pronóstico de la Estenosis Grave Aórtica Sintomática del Octogenario -- Prognosis of symptomatic severe aortic stenosis in octogenarians), a prospective registry that included consecutively 928 patients aged ≥ 80 years with severe symptomatic AS. Results The mean Charlson comorbidity index was 3.0 ± 1.7, a total of 151 patients (16.3%) presented high comorbidity (index ≥ 5). Median survival was lower for patients with high comorbidity than for those without (16.7 ± 1.2 vs. 26.5 ± 0.6 months, p < 0.001). In patients without high comorbidity planned interventional management was clearly associated with prognosis (log rank p < 0.001), which was not the case in patients with high comorbidity (log rank p > 0.10). In multivariate analysis, the only variables that were independently associated with prognosis were planned medical management and Charlson index. Patients with high comorbidity presented non-cardiac death more frequently than those who had not (28.6% vs. 19.5%, p = 0.008). Conclusions One sixth of octogenarians with symptomatic severe AS have very high comorbidity (Charlson index ≥ 5). These patients have a poor prognosis in the short term and do not seem to benefit from interventional treatment. [ABSTRACT FROM AUTHOR]

Study Design. Retrospective analysis of nationally representative data collected for the National Hospital Discharge Survey. Objective. To compare the performance of the Charlson and Elixhauser comorbidity-based measures for predicting in-hospital mortality after cervical spine fractures. Summary of Background Data. Mortality occurring as a consequence of cervical spine fractures is very high in the elderly. The Charlson comorbidity measure has been associated with an increased risk of mortality, but its predictive accuracy has yet to be compared with the more recent and increasingly used Elixhauser measure. Methods. Using the National Hospital Discharge Survey for the years 1990 through 2007, we identified all patients aged 65 years or older hospitalized with a diagnosis of cervical spine fracture. The association of each Charlson and Elixhauser comorbidity with mortality was assessed in bivariate analysis using χ2 tests. Two main multivariable logistic regression models were constructed, with in-hospital mortality as the dependent variable and 1 of the 2 comorbidity-based measures (as well as age, sex, and year of admission) as independent variables. A base model that included only age, sex, and year of admission was also evaluated. The discriminative ability of the models was quantifi ed using the area under the receiver operating characteristic curve (AUC). Results. Among an estimated 111,564 patients admitted for cervical spine fractures, 7.6% died in the hospital. Elixhauser comorbidity adjustment provided better prediction of in-hospital case mortality (AUC = 0.852, 95% confidence interval: 0.848–0.856) than the Charlson model (AUC = 0.823, 95% confidence interval: 0.819–0.828) and the base model with no comorbidities (AUC = 0.785, 95% confidence interval: 0.781–0.790). In terms of relative improvement in predictive ability, the Elixhauser model performed 43% better than the Charlson model. Conclusion. The Elixhauser comorbidity risk adjustment method performed numerically better than the widely used Charlson measure in predicting in-hospital mortality after cervical spine fractures. [ABSTRACT FROM AUTHOR]

Objective Ascertaining comorbid conditions in cancer patients is important for research and clinical quality measurement, and is particularly important for understanding care and outcomes for older patients and those with multi-morbidity. We compared the medical records-based ACE-27 index and the claims-based Charlson index in predicting receipt of therapy and survival for lung and colon cancer patients. Materials and Methods We calculated the Charlson index using administrative data and the ACE-27 score using medical records for Veterans Affairs patients diagnosed with stage I/II non-small cell lung or stage III colon cancer from January 2003 to December 2004. We compared the proportion of patients identified by each index as having any comorbidity. We used multivariable logistic regression to ascertain the predictive power of each index regarding delivery of guideline-recommended therapies and two-year survival, comparing the c-statistic and the Akaike information criterion (AIC). Results Overall, 97.2% of lung and 90.9% of colon cancer patients had any comorbidity according to the ACE-27 index, versus 59.5% and 49.7%, respectively, according to the Charlson. Multivariable models including the ACE-27 index outperformed Charlson-based models when assessing receipt of guideline-recommended therapies, with higher c-statistics and lower AICs. Neither index was clearly superior in prediction of two-year survival. Conclusions The ACE-27 index measured using medical records captured more comorbidity and outperformed the Charlson index measured using administrative data for predicting receipt of guideline-recommended therapies, demonstrating the potential value of more detailed comorbidity data. However, the two indices had relatively similar performance when predicting survival. [ABSTRACT FROM AUTHOR]

Background: Several studies have included different co-morbid conditions in prediction models for stroke patients. For subarachnoid haemorrhage (SAH), it is not known whether the Charlson Co-morbidity Index (CCI) is associated with outcome. We evaluated if this index was associated with outcome in patients with ruptured intracerebral aneurysms. Methods: The data of all consecutive aneurysmal SAH (aSAH) patients treated at the Radboudumc, Nijmegen, The Netherlands and entered in the database were retrospectively analysed. Clinical condition at admission was recorded using the WFNS (World Federation of Neurological Surgeons Grading System) grade was collected, as were the age and treatment modality. The burden of co-morbidity was retrospectively registered using the CCI. Outcome was dichotomised on the modified Rankin Scale (mRS; 0-2, favourable outcome; 3-6, unfavourable outcome). A binary logistic regression analysis was performed. Results: Between 6th May 2008 and 31st July 2013, 457 patients were admitted because of non-traumatic SAH (aSAH). Seventy-seven (16.8 %) patients had no aneurysm. Of the 380 patients with aSAH, information on co-morbid conditions was available for 371 patients. Thirty-six of those 371 had no treatment because of: bad clinical condition in 34 (9.2 %), a non-treatable dissecting aneurysm in 1 (0.3 %) and the explicit wishes of another. Co-morbidity was present in 113 (31.5 %) patients. Binary logistic regression analysis revealed no added value of using the CCI in predicting the outcome ( p = 0.91). Conclusions: This study reports that the CCI is not associated with the outcome classified on the mRS at 6 months in patients after aSAH. The CCI has no added value in case-mix correction. [ABSTRACT FROM AUTHOR]

Introduction: Cancer survival is related not only to primary malignancy but also to concomitant nonmalignant diseases. The aim of this study was to investigate the prognostic capacity of four comorbidity indices [the Charlson comorbidity index (CCI), the Elixhauser method, the National Institute on Aging (NIA) and National Cancer Institute (NCI) comorbidity index, and the Adult Comorbidity Evaluation-27 (ACE-27)] for both cancer-related and all-cause mortality among colorectal cancer patients. A modified version of the CCI adapted for colorectal cancer patients was also built. Methods: The study population comprised 468 cases of colorectal cancer diagnosed between 1 January 2000 and 31 December 2010 at a community hospital. Data were prospectively collected and abstracted from patients' clinical records. Kaplan-Meier method and multivariate logistic regression models were performed for survival and risk of death analysis. Results: Only moderate or severe renal disease [hazard ratio (HR) 2.71, 95 % confidence interval (CI) 1.11-6.63] and AIDS (HR 3.27, 95 % CI 1.23-8.68) were independently associated with cancer-specific mortality, with a population attributable risk of 5.18 and 4.36 %, respectively. For each index, the highest comorbidity burden was significantly associated with poorer overall survival (NIA/NCI: HR 2.14, 95 % CI 1.14-4.01; Elixhauser: HR 1.98, 95 % CI 1.09-1.42; ACE-27: HR 1.78, 95 % CI 1.07-1.23; CCI: HR 1.68, 95 % CI 1.05-1.42) and cancer-specific survival. The modified version of the CCI resulted in a higher predictive power compared with other indices studied (cancer-specific mortality HR = 2.37, 95 % CI 1.37-4.08). Conclusions: The comorbidity assessment tools provided better prognostic prevision of prospective outcome of colorectal cancer patients than single comorbid conditions. [ABSTRACT FROM AUTHOR]

Abstract: The majority of hematologic malignancies occur in patients aged more than 65years. Such patients have very variable health status, comorbidity levels, and geriatric syndrome prevalence. It is important to identify who would be a candidate for standard treatment schemes, and who would be a candidate for modified therapeutic approaches. Accurate assessment of patient fitness and comorbidities is key when planning therapy for this group as such factors will affect prognosis. In this paper, we review the published literature on a comprehensive geriatric assessment and comorbidity measurements in patients with hematologic malignancies and their correlation with outcomes. Our review identified the Charlson score and the Cumulative Illness Rating Scale-Geriatric as the most frequently used comorbidity instruments in the general setting, and the Hematopoietic Cell Transplantation-Comorbidity Index in the transplant setting. For the geriatric assessments, the most commonly used scheme combines age, comorbidity, Activities of Daily Living, and the presence of geriatric syndromes. Correlations with overall survival and treatment tolerance are fairly consistently demonstrated. Some tentative thresholds are apparent but remain to be firmly confirmed. Future trials should integrate these assessments as correlates or stratification tools in order to build on the early results already available. [Copyright &y& Elsevier]

Abstract: Objective: The Charlson and Elixhauser indices are the most commonly used comorbidity indices with risk prediction models using administrative data. Our objective was to compare the original Charlson index, a modified set of Charlson codes after advice from clinical coders, and a published modified Elixhauser index in predicting in-hospital mortality. Study Design and Setting: Logistic regression using two separate years of administrative hospital data for all acute nonspecialist public hospitals in England. Results: For all admissions combined, discrimination was similar for the Charlson index using the original codes and weights and the Charlson index using the original codes but England-calibrated weights (c =0.73), although model fit was superior for the latter. The new Charlson codes improved discrimination (c =0.76), model fit, and consistency of recording between admissions. The modified Elixhauser had the best performance (c =0.80). For admissions for acute myocardial infarction and chronic obstructive pulmonary disease, the weights often differed, although the patterns were broadly similar. Conclusion: Recalibration of the original Charlson index yielded only modest benefits overall. The modified Charlson codes and weights offer better fit and discrimination for English data over the original version. The modified Elixhauser performed best of all, but its weights were perhaps less consistent across the different patient groups considered here. [Copyright &y& Elsevier]

This study is a retrospective chart review to determine the association of Charlson Comorbidity Index (CCI), age, body mass index (BMI), and admission glucose with the incidence of postoperative 30-day mortality in older patients undergoing hip fracture surgery from January 1, 2000, to June 30, 2002. A total of 40 (8%) of 485 eligible patients died within 30 days after hip fracture surgery. The factors associated with 30-day mortality were age > 90 years (odds ratio [OR] = 2.74; confidence interval [CI] = 1.27-5.95; P = .012), BMI < 18.5 (OR = 3.98; CI 1.48-10.65; P = .006), and CCI ≥ 6 (OR = 2.6; CI = 1.20-5.65; P = .015). There was no relationship between admission glucose concentration and 30-day mortality. Advanced age, low BMI, and high CCI can be identified prospectively and are independently associated with postoperative 30-day mortality in older, chronically ill patients. [ABSTRACT FROM PUBLISHER]

Abstract: Background: Mean age of patients with lung cancer rises as a result of increasing life expectancy. So, the proportion of patients with serious comorbidity also increases . Lung cancer treatment is characterized by a narrow therapeutic index. When life expectancy is short and therapeutic benefit is limited, it is of paramount importance to know the specific cause of death. Comorbidity is understood as a competing cause of death, and is the main exclusion criterion for lung cancer clinical trials. The aim of this study was to determine the prevalence of comorbidity in elderly lung cancer patients seen in an outpatient oncology department and to determine its correlation with survival. Patients and methods: Between January 2006 and February 2008, 83 untreated lung cancer patients over the age of 70 years were enrolled in the study. Comorbidity was evaluated according to the Charlson comorbidity index (CCI) and the simplified comorbidity score (SCS) . Results: 83 patients (97.6% men, mean age 77 years) were studied. Comorbidities: tobacco consumption (94.6%), cardiovascular diseases (65%), and chronic obstructive pulmonary disease (COPD) (59%). Mean CCI was 3 (range 0–9). Mean SCS was 9 (range 4–19), and 47% of patients had an SCS>9. Comorbidity was fairly well correlated with age, ADL, IADL, and stage. Neither the CCI nor the SCS was related to survival (p: 0.47 and p: 0.24, log rank, respectively). Median survival was 326 days (95% CI, 259–393 days; or 10.8 months, 95% CI 8.6–13.1 months). Main cause of death was lung cancer disease progression (69.5%, 57 patients), with 20 patients (25%) dying of other non-neoplastic causes. Stage was significantly associated with survival (log rank: p <0.001). Conclusions: Although there was a high prevalence of comorbidity in our population, comorbidity was not related to survival. Comorbidity is one of the main reasons for undertreatment of elderly lung cancer patients, but this study indicates that this undertreatment may not be warranted given that those comorbidities may not cause a patient''s death. Our data generated more of a hypothesis than a conclusion. Comorbidity should be an impetus for treatment design instead of an exclusion criterion for oncologic treatment. [Copyright &y& Elsevier]

Summary: We evaluated risk factors for death among hospitalised patients with healthcare-associated infections (HCAIs) using the McCabe classification and Charlson index to predict mortality. The study consisted of a cohort of 703 patients with HCAIs and 7531 patients without HCAI in acute care hospitals participating in the Finnish national prevalence survey in 2005. We used Centers for Disease Control and Prevention definitions for HCAIs and recorded the McCabe classification for comorbidity. We used the date from the prevalence survey and the patient''s national identity code in order to retrieve data from the National Hospital Discharge Registry on discharge diagnoses (International Classification of Diseases-10 codes) for the Charlson index and the dates of death from the National Population Information System. Of all inpatients, 425 (5.2%) died within 28 days from the prevalence survey date; the death rate was higher in HCAI patients than in those without HCAI (9.8% vs 4.7%, P <0.001). In the multivariate regression analysis age >65 years, intensive care, McCabe classification and Charlson index, gastrointestinal system infection and pneumonia/other lower respiratory tract infections were independent predictors for death. The survival analysis, when adjusted by McCabe class or Charlson index, showed that HCAI reduced survival only among patients without severe underlying diseases. Certain types of HCAI increased the risk of death. The McCabe classification had advantages over the Charlson index as a predictor of death, because it was easier to collect from a prevalence survey. [Copyright &y& Elsevier]

Abstract: Objectives: The objectives of this study were (1) to ascertain the level of agreement between the Charlson Comorbidity Index (CCI) based on self-report vs. administrative records, and factors affecting agreement and (2) to compare the predictive validity of the two indices in a sample of older emergency department (ED) patients. Study Design and Setting: The study was a secondary analysis of data from a randomized trial of an ED-based intervention. The self-report and administrative CCI were compared using the intraclass correlation coefficient (ICC). Factors examined for effect on agreement included health service utilization, age, and sex. The predictive validity of the indices was compared using subsequent health services utilization and functional decline as outcomes. Participants (n =520) were recruited at four university-affiliated Montreal hospitals. Eligibility criteria included 65 years of age or older, able to speak English or French, and discharged to the community. Results: Agreement between the two sources was poor to fair (overall weighted ICC 0.43 [95% confidence interval [CI]: 0.40, 0.47]). The predictive validity was similar for the two indices (area under the receiver-operating characteristic curve 0.51–0.66, depending on the outcomes). Conclusion: Agreement between self-report and administrative comorbidity data is only poor to fair but both have comparable predictive validity. [Copyright &y& Elsevier]

Abstract: Background and objective: The ICD-9-CM adaptation of the Charlson comorbidity score has been a valuable resource for health services researchers. With the transition into ICD-10 coding worldwide, an ICD-10 version of the Deyo adaptation was developed and validated using population-based hospital data from Victoria, Australia. Methods: The algorithm was translated from ICD-9-CM into ICD-10-AM (Australian modification) in a multistep process. After a mapping algorithm was used to develop an initial translation, these codes were manually examined by the coding experts and a general physician for face validity. Because the ICD-10 system is country specific, our goal was to keep many of the translated code at the three-digit level for generalizability of the new index. Results: There appears to be little difference in the distribution of the Charlson Index score between the two versions. A strong association between increasing index scores and mortality exists: the area under the ROC curve is 0.865 for the last year using the ICD-9-CM version and remains high, at 0.855, for the ICD-10 version. Conclusion: This work represents the first rigorous adaptation of the Charlson comorbidity index for use with ICD-10 data. In comparison with a well-established ICD-9-CM coding algorithm, it yields closely similar prevalence and prognosis information by comorbidity category. [Copyright &y& Elsevier]

To see if changes in the demographics and illness burden of Medicare patients hospitalized for acute myocardial infarction (AMI) from 1995 through 1999 can explain an observed rise (from 32 percent to 34 percent) in one-year mortality over that period. Utilization data from the Centers for Medicare and Medicaid Services (CMS) fee-for-service claims (MedPAR, Outpatient, and Carrier Standard Analytic Files); patient demographics and date of death from CMS Denominator and Vital Status files. For over 1.5 million AMI discharges in 1995–1999 we retain diagnoses from one year prior, and during, the case-defining admission. We fit logistic regression models to predict one-year mortality for the 1995 cases and apply them to 1996–1999 files. The CORE model uses age, sex, and original reason for Medicare entitlement to predict mortality. Three other models use the CORE variables plus morbidity indicators from well-known morbidity classification methods (Charlson, DCG, and AHRQ's CCS). Regressions were used as is—without pruning to eliminate clinical or statistical anomalies. Each model references the same diagnoses—those recorded during the pre- and index admission periods. We compare each model's ability to predict mortality and use each to calculate risk-adjusted mortality in 1996–1999. The comprehensive morbidity classifications (DCG and CCS) led to more accurate predictions than the Charlson, which dominated the CORE model (validated C-statistics: 0.81, 0.82, 0.74, and 0.66, respectively). Using the CORE model for risk adjustment reduced, but did not eliminate, the mortality increase. In contrast, adjustment using any of the morbidity models produced essentially flat graphs. Prediction models based on claims-derived demographics and morbidity profiles can be extremely accurate. While one-year post-AMI mortality in Medicare may not be worsening, outcomes appear not to have continued to improve as they had in the prior decade. Rich morbidity information is available in claims data, especially when longitudinally tracked across multiple settings of care, and is important in setting performance targets and evaluating trends. [ABSTRACT FROM AUTHOR]

Simple Summary: Most oncology patients today are ≥65 years, so we should include in our daily practice tools that facilitate the therapeutic approach for elderly patients. Care overburden makes it difficult to perform comprehensive geriatric assessments (CGAs). The aim of our prospective study was to analyze if frailty screening questionnaires, such as G8 or Charlson, could lead to rapid decision making about treatment change in a radiation oncology service. In a homogeneous population of 161 patients, with a median age of 75 years, we found that 28.7% were frail according to the G8 test, while the estimated survival at 10 years was 2.25% based on the Charlson test. The therapeutic modification increased to 21% after frailty analysis, and the radiotherapy prescribed was 5.8 times more likely to be modified in frail patients. Thus, we postulate that the frailty screening test, easier to integrate into clinical practice, is a reliable and efficient aid for optimal approach. Background: Care overburden makes it difficult to perform comprehensive geriatric assessments (CGAs) in oncology settings. We analyzed if screening tools modified radiotherapy in oncogeriatric patients. Methods: Patients ≥ 65 years, irradiated between December 2020 and March 2021 at the Hospital Provincial de Castellón, completed the frailty G8 and estimated survival Charlson questionnaires. The cohort was stratified between G8 score ≤ 14 (fragile) or >14 (robust); the cutoff point for the Charlson index was established at five. Results: Of 161 patients; 69.4% were male, the median age was 75 years (range 65–91), and the prevailing performance status (PS) was 0–1 (83.1%). Overall, 28.7% of the cohort were frail based on G8 scores, while the estimated survival at 10 years was 2.25% based on the Charlson test. The treatment administered changed up to 21% after frailty analysis. The therapies prescribed were 5.8 times more likely to be modified in frail patients based on the G8 test. In addition, patients ≥ 85 years (p = 0.01), a PS ≥ 2 (p = 0.008), and limited mobility (p = 0.024) were also associated with a potential change. Conclusions: CGAs remain the optimal assessment tool in oncogeriatry. However, we found that the G8 fragility screening test, which is easier to integrate into patient consultations, is a reliable and efficient aid to rapid decision making. [ABSTRACT FROM AUTHOR]

Background: Preliminary study to assess the risk profile and outcomes of patients aged over 90years at the time of percutaneous coronary intervention. Methods: A database search was performed to identify patients 90years or over at the time of percutaneous coronary intervention. Risk profile scores (Charlson Comorbidity Index, SYNTAX, Logistic clinical SYNTAX, New York PTCA score and frailty indices) were evaluated on 24 consecutive patients in order to determine the best predictor for survival. Between both groups (survivors and non-survivors) unpaired Student’s t-test was used to determine statistical significance. Results: The New York PTCA score was significantly higher in those patients that died in hospital (n=5) when compared to those who survived to discharge (n=19) (NY PTCA score of 20.9±5.4 vs. 4.5±0.8, p<0.001) and this was also seen with mortality at 12months. The level of co-morbidity (Charlson index) was similar in patients who died in hospital (n=5) compared with those who survived to discharge (n=19, Charlson comorbidity index of 3.4±0.7 vs.3.9±0.6, p=0.70). This trend was also observed at 1year. The average level of frailty (by the CSHA Clinical Frailty Scale), SYNTAX score and logistic clinical SYNTAX were not significantly different between the two groups both at discharge and at 12months. Choosing an arbitrary New York PTCA score of 9%, nearly two thirds of patients above this level died, whereas no patient below this level of risk died in hospital. Conclusion: This small observational study found that nonagenarians who underwent PCI had relatively low comorbidity and SYNTAX scores. The specific coronary intervention (New York PTCA) risk score appears to have more predictive power in this small group of patients than the other three scores. Crucially, the factors that determine risk by New York PTCA score – haemodynamic instability, shock, pulmonary oedema, renal failure, etc. – are commonly encompassed by an “end-of-bed” assessment of the patient and these patients that pass this test ought not to be denied PCI on the basis of their advanced years. [ABSTRACT FROM AUTHOR]

Objective: To investigate variation in the presence of secondary diagnosis codes in Charlson and Elixhauser comorbidity scores and assess whether including a 1-year lookback period improved prognostic adjustment by these scores individually, and combined, for 30-day mortality., Study Design and Setting: We analyzed inpatient admissions from January 1, 2007 to May 18, 2018 in Oxfordshire, UK. Comorbidity scores were calculated using secondary diagnostic codes in the diagnostic-dominant episode, and primary and secondary codes from the year before. Associations between scores and 30-day mortality were investigated using Cox models with natural cubic splines for nonlinearity, assessing fit using Akaike Information Criteria., Results: The 1-year lookback improved model fit for Charlson and Elixhauser scores vs. using diagnostic-dominant methods. Including both, and allowing nonlinearity, improved model fit further. The diagnosis-dominant Charlson score and Elixhauser score using a 1-year lookback, and their interaction, provided the best comorbidity adjustment (reduction in AIC: 761 from best single score model)., Conclusion: The Charlson and Elixhauser score calculated using primary and secondary diagnostic codes from 1-year lookback with secondary diagnostic codes from the current episode improved individual predictive ability. Ideally, comorbidities should be adjusted for using both the Charlson (diagnostic-dominant) and Elixhauser (1-year lookback) scores, incorporating nonlinearity and interactions for optimal confounding control., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objectives: To determine the most reliable comorbidity measure, we adapted and validated outcome-specific comorbidity scores to predict mortality and hospital charges using the comorbidities composing the Charlson and Elixhauser measures and the combination of these two used in developing Gagne's combined comorbidity scores (CC, EC, and GC, respectively)., Study Design and Setting: We divided cases of patients discharged in 2016-17 from the Diagnosis Procedure Combination database (n = 2,671,749) into two: one to derive weights for the scores, and the other for validation. We further validated them in subgroups, such as that with a selected diagnosis., Results: The c-statistics of the models predicting in-hospital mortality using new mortality scores using the CC, EC, and GC were 0.780, 0.795, and 0.794, respectively. Among them, that using the EC showed the best calibration. To predict hospital charges and the length of hospital stay (LOS), the models using variables indicating the GC performed the best. The performances of the mortality and expenditure scores were considerably different in predicting each outcome., Conclusion: The new score using the EC performed the best in predicting in-hospital mortality for most situations. For hospital charges and the LOS, the binary variables of the GC showed the best results. The outcome-specific comorbidity scores should be considered for different outcomes., (Copyright © 2020 Elsevier Inc. All rights reserved.)