Indice de comorbilidad específico para trasplante alogénico de células progenitoras hematopoyéticas: cohorte retrospectiva de niños y adolescentes con enfermedad maligna / Specific comorbidity index for allogeneic hematopoietic stem cell transplantation: a retrospective cohort of children and adolescents with malignancies

Introducción: Entre las variables que afectan el riesgo de mortalidad relacionada (MRT) al trasplante alogénico de células progenitoras hematopoyéticas (TACPH) se incluyen las comorbilidades previas. Los índices de comorbilidad (IC) buscan mejorar la predicción de eventos combinando factores de riesgo independientes. Objetivos: 1) evaluar el uso de la versión breve y adaptada para niños, adolescentes y adultos jóvenes con enfermedad maligna del índice de comorbilidad específico para trasplante alogénico de células progenitoras hematopoyéticas (smyHCT-CI ); 2) evaluar el uso de los biomarcadores ferritina y albúmina en un índice de comorbilidad ampliado (smyHCT-CIa). Población y métodos: Diseño: cohorte retrospectiva. Periodo 2017- 2022. A cada p se le asignó nuevos puntajes utilizando el smyHCT-CI y el smyHCT-CIa. Los p se clasificaron en grupos de riesgo (GR) bajo (puntaje 0), intermedio (1-2) y alto (>3) con cada índice. Se comparó el n° de p asignado a cada GR grupo de riesgo y la MRT en cada grupo al usar el HCT-CI, el smyHCTCI y el smyHCT-CIa. Resultados: n 75. Frecuencia de p por GR según cada indicador (IC95): HCT-CI bajo 36 (25-47), intermedio 57 (56-69), alto 7 (1-12); smyHCT-CI: bajo 48 (37-59), intermedio 33 (23-44), alto 19 (10-27); smyHCT-CIa: bajo 43 (31-54), intermedio 36 (25-47), alto 21 (12-31). MRT por GR según indicador (IC95): HCT-CI: bajo 6,8 (14-28), intermedio 20,9 (9-33), alto 17,9 (0-55); smyHCT-CIa bajo 12,5 (1-24), intermedio 18,5 (4-33), alto 31,2 (9-54). Conclusión: El smyHCT-CI permitió identificar mejor los pacientes con mayor comorbilidad y riesgo de MRT. La ferritina resultó un biomarcador útil en la estimación del riesgo de MRT (AU)

Introduction: Variables affecting allogeneic hematopoietic stem cell transplantation (HCT) related mortality risk (TMR) include prior comorbidities. Comorbidity indices (CI) aim to improve event prediction by combining independent risk factors. Objectives: 1) to evaluate the use of the brief and adapted version of the HCT-specific comorbidity index for children, adolescents and young adults with malignancies (ymHCT-CI); 2) to evaluate the use of the biomarkers ferritin and albumin in an expanded comorbidity index (expanded ymHCT-CI). Population and methods: Design: retrospective cohort. Period 2017- 2022. Each patient was assigned new scores using the ymHCTCI and expanded ymHCT-CI. The p were classified into low (score 0), intermediate (1-2) and high (>3) risk groups (RG) with each index. The number of patients assigned to each RG and the TMR in each group were compared using the HCTCI, the ymHCT-CI, and the expanded ymHCT-CI. Results: n 75. Frequency of patients per RG according to each indicator (95%CI): HCT-CI low 36 (25-47), intermediate 57 (56-69), high 7 (1-12); ymHCT-CI: low 48 (37-59), intermediate 33 (23-44), high 19 (10-27); expanded ymHCT-CI: low 43 (31-54), intermediate 36 (25-47), high 21 (12-31). TMR by RG according to indicator (95%CI): HCT-CI: low 6.8 (14-28), intermediate 20.9 (9-33), high 17.9 (0-55); expanded ymHCT-CI low 12.5 (1-24), intermediate 18.5 (4-33), high 31.2 (9-54). Conclusion: ymHCT-CI allowed better identification of patients with higher comorbidity and risk of TMR. Ferritin proved to be a useful biomarker to estimate TMR risk (AU)

Comprehensive Evaluation of the Ability of Comorbidity and Health Status Indices to Improve the Prediction of Perioperative Morbidity and Long-Term Survival Outcomes After Radical Cystectomy.

BACKGROUND: In the era of standardized outcome reporting, it remains unclear if widely used comorbidity and health status indices can enhance predictive accuracy for morbidity and long-term survival outcomes after radical cystectomy (RC). PATIENTS AND METHODS: In this monocentric study, we included 468 patients undergoing open RC with pelvic lymph node dissection for bladder cancer between January 2009 and December 2017. Postoperative complications were meticulously assessed according to the EAU guideline criteria for standardized outcome reporting. Multivariable regression models were fitted to evaluate the ability of ASA physical status (ASA PS), Charlson comorbidity index (± age-adjustment) and the combination of both to improve prediction of (A) 30-day morbidity key estimates (major complications, readmission, and cumulative morbidity as measured by the Comprehensive Complication index [CCI]) and (B) secondary mortality endpoints (overall [OM], cancer-specific [CSM], and other-cause mortality [OCM]). RESULTS: Overall, 465 (99%) and 52 (11%) patients experienced 30-day complications and major complications (Clavien-Dindo grade ≥IIIb), respectively. Thirty-seven (7.9%) were readmitted within 30 days after discharge. Comorbidity and health status indices did not improve the predictive accuracy for 30-day major complications and 30-day readmission of a reference model but were associated with 30-day CCI (all P < .05). When ASA PS and age-adjusted Charlson index were combined, ASA PS was no longer associated with 30-day CCI (P = .1). At a median follow-up of 56 months (IQR 37-86), OM, CSM, and 90-day mortality were 37%, 24%, and 2.9%, respectively. Both Charlson and age-adjusted Charlson index accurately predicted OCM (all P < .001) and OM (all P ≤ .002) but not CSM (all P ≥ .4) and 90-day mortality (all P > .05). ASA PS was not associated with oncologic outcomes (all P ≥ .05). CONCLUSION: While comorbidity and health status indices have a role in predicting OCM and OM after RC, their importance in predicting postoperative morbidity is limited. Especially ASA PS performed poorly. This highlights the need for procedure-specific comorbidity assessment rather than generic indices.

Which comorbidity index is more appropriate for geriatric patients from the frailty perspective?

OBJECTIVES: This study examined the relationship between comorbidity indices and physical, psychologic and social frailty and 1-year mortality. METHODS: A cross-sectional analysis was conducted with 136 community-dwelling older adults. The relationship of 4 comorbidity indices (CIRS-G, ACCI, GIC, ICED) with 3 different frailty scales (FRAIL, CFS, TFI) was examined. RESULTS: The participants' median age was 72 years (65-90); 62% of the participants were female. Overall, 15.4% of the participants were living with frailty according to the FRAIL scale, 27.9% of them according to the CFS, 58.8% of them according to the TFI, 47.7% of them living with psychological frailty, and 28.6% of them living with social frailty. There were significant and moderate correlations between CIRS-G and FRAIL, CFS and TFI total scores, TFI-Psychological scores and TFI-Social scores (respectively; p < 0.001, r = 0.530; p < 0.001, r = 0.471; p < 0.001, r = 0.535; p < 0.001, r = 0.402; p = 0.016 r = 0.206). AUC for CIRS-G was calculated as 0.716 among comorbidity indices in predicting the presence of frailty according to the FRAIL scale (p = 0.002, 95%CI [0.60-0.82]), 0.765 according to the CFS (p < 0.001, 95%CI [0.66-0.86]), 0.746 according to the TFI (p < 0.001, 95%CI [0.66-0.82]). CONCLUSION: The CIRS-G index was found to be superior to other indices in predicting the presence of frailty of comorbidity indices, and only GIC scores showed significant results in predicting mortality. However, it would not be the right approach to recommend a single comorbidity index when evaluating older adults.

Predictive Ability of Comorbidity Indices for Surgical Morbidity and Mortality: a Systematic Review and Meta-analysis.

BACKGROUND: Several contemporary risk stratification tools are now being used since the development of the Charlson Comorbidity Index (CCI) in 1987. The purpose of this systematic review and meta-analysis was to compare the utility of commonly used co-morbidity indices in predicting surgical outcomes. METHODS: A comprehensive review was performed to identify studies reporting an association between a pre-operative co-morbidity measurement and an outcome (30-day/in-hospital morbidity/mortality, 90-day morbidity/mortality, and severe complications). Meta-analysis was performed on the pooled data. RESULTS: A total of 111 included studies were included with a total cohort size 25,011,834 patients. The studies reporting the 5-item Modified Frailty Index (mFI-5) demonstrated a statistical association with an increase in the odds of in-hospital/30-day mortality (OR:1.97,95%CI: 1.55-2.49, p < 0.01). The pooled CCI results demonstrated an increase in the odds for in-hospital/30-day mortality (OR:1.44,95%CI: 1.27-1.64, p < 0.01). Pooled results for co-morbidity indices utilizing a scale-based continuous predictor were significantly associated with an increase in the odds of in-hospital/30-day morbidity (OR:1.32, 95% CI: 1.20-1.46, p < 0.01). On pooled analysis, the categorical results showed a higher odd for in-hospital/30-day morbidity (OR:1.74,95% CI: 1.50-2.02, p < 0.01). The mFI-5 was significantly associated with severe complications (Clavien-Dindo ≥ III) (OR:3.31,95% CI:1.13-9.67, p < 0.04). Pooled results for CCI showed a positive trend toward severe complications but were not significant. CONCLUSION: The contemporary frailty-based index, mFI-5, outperformed the CCI in predicting short-term mortality and severe complications post-surgically. Risk stratification instruments that include a measure of frailty may be more predictive of surgical outcomes compared to traditional indices like the CCI.

The role of comorbidity indices and histochemical markers in surgically resected and non-resected primary central nervous system lymphoma.

The role of surgical resection in primary central nervous system lymphoma (PCNSL) was not recognized until recently. However, prognostic factors for surgically treated PCNSL remain unclear. In the present study, we aimed to identify and compare the prognostic value of comorbidity indices and immunohistochemical markers in patients with surgically and non-surgically treated PCNSL. This retrospective single-center study analyzed patients who underwent either surgical resection or stereotactic biopsy for newly diagnosed PCNSL between January 2012 and December 2021. Clinical demographics, comorbidity indices, and immunohistochemical markers were analyzed. We included 23 and 18 patients who underwent stereotactic biopsy and surgical resection, respectively. The median overall survival (OS) was 11.05 months. Using multivariate Cox regression, we identified pretreatment prognostic nutritional index (PNI) (p = 0.009), positive BCL2 staining (p = 0.026), and infratentorial involvement (p = 0.004) as independent prognostic factors of OS. Predictors of progression-free survival (PFS) included PNI (p = 0.040), infratentorial involvement (p = 0.021), and surgical resection for PCNSL (p = 0.048). Subgroup analyses revealed that positive BCL2 (p = 0.048) and PD-L1 (p = 0.037) staining were associated with worse OS in the biopsy group. PNI and infratentorial involvement could significantly impact both OS and PFS in patients with PCNSL. Surgical resection could predict favorable PFS but not OS. Moreover, BCL2 and PD-L1 expression can be employed as prognostic markers in these patients.

Age and BMI equal Modified Frailty Index, Modified Charlson Comorbidity Index and ASA in predicting adverse events in spinal surgery for cervical degenerative diseases.

OBJECTIVE: To compare Modified Frailty Index (mFI), Modified Charlson Comorbidity (mCCI) and ASA with demographic data such as age, BMI and gender in the prediction of AEs obtained using a validated systematic reporting system in a prospective cohort undergoing cervical spine surgery. METHODS: All adult patients undergoing spine surgery for cervical degenerative disease at our academic tertiary referral center from February 1, 2016, to January 31, 2017, were included. Morbidity and mortality were determined according to the predefined adverse event (AE) variables using the Spinal Adverse Events Severity (SAVES) System. Area under the curve (AUC) analyses from receiver operating characteristics (ROC) curves were used to assess the discriminative ability in predicting AEs for the comorbidity indices mFI, mCCI, ASA and for BMI, age and gender. RESULTS: A total of 288 consecutive cervical cases were included. BMI was the most predictive demographic factor for an AE (AUC = 0.58), the most predictive comorbidity index was mCCI (AUC = 0.52). No combination of comorbidity indices or demographic factors reached a threshold of AUC ≥ 0.7 for AEs. As predictor of extended length of stay: age (AUC = 0.77), mFI (AUC = 0.70) and ASA (AUC = 0.70) were similar and fair. CONCLUSION: Age and BMI equal mFI, mCCI and ASA in predicting postoperative AEs, amongst patients operated for cervical degenerative disease. No significant difference was found between mFI, mCCI and ASA in the discriminative abilities in predicting morbidity, based on prospectively collected AEs according to the SAVES grading system.

Adjusting for comorbidity in observational cancer studies: A systematic review to assess alignment between index and study.

Epidemiological and retrospective clinical studies on cancer outcomes frequently adjust for patients' comorbid conditions. Despite the existence of multiple comorbidity indices, the Charlson comorbidity index (CCI) is the most frequently applied. Indices are developed in specific settings and the extent of alignment between the development setting and subsequent study is unclear. The present study provides a contemporaneous snapshot of comorbidity indices used in retrospective observational cancer studies and the extent to which cancer type(s), data source(s) and outcome(s) matched the studies in which the indices were developed. A systematic literature search in PubMed identified retrospective, observational studies on outcomes in patients with cancer published between March 2015 and March 2020. Information including the cancer type, data source and outcome were extracted and compared to those used in the validation study of the comorbidity index used. Of 158 papers reviewed, 79 used the CCI, either alone or in combination with other indices. The cancer type matched to that used in the validation study of the comorbidity index in 16 of the 115 studies using an established index, whilst the data source matched in 27 studies and outcome in only two. Justification was rarely provided for index choice (15 of the 115 studies). It may be concluded that, while the CCI remains the dominant comorbidity index, it may not always align to key elements of the study design in terms of cancer type, data source and outcome. A range of indices exists and identification of the most appropriate measure has the potential to improve adjustment for comorbidity. The present study provided information about the indices used in included studies and encourages future studies to consider which comorbidity index offers the best alignment with the study population, data source and question addressed.

Dactylitis and Early Onset Psoriasis in Psoriatic Arthritis: Are they Markers of Disease Severity? A Clinical Study.

OBJECTIVES: To stratify psoriatic arthritis (PsA) patients based on psoriasis (PsO) onset age: early onset psoriasis (EOP) vs. late onset psoriasis (LOP), and to assess if there are differences in disease characteristics, activity/function/impact of the disease, and comorbidity indices. METHODS: Cross-sectional analysis of a longitudinal PsA cohort. Patients were stratified based on PsO onset age. RESULTS: One hundred and sixty PsA patients were enrolled (84 in EOP and 76 in LOP group) in the study. EOP PsA patients seem to have an increased probability to have dactylitis rather than LOP ones, OR 9.64 (3.77-24.6). Comorbidity indices (Rheumatic Disease Comorbidity Index and Charlson Comorbidity Index) were higher in LOP PsA patients, but these data were not confirmed when adjusted by age and sex. There are also differences in the treatment regimen: EOP PsA patients were more frequently treated with anti-interleukin (IL) 17; instead, LOP patients were more frequently treated with non-steroid anti-inflammatory drugs and conventional synthetic disease-modifying anti-rheumatics drugs. There were no differences in the disease activity, function, or impact of the disease. CONCLUSIONS: There are some clinical and therapeutic differences in PsA patients linked to the PsO onset age, namely dactylitis in EOP. Other characteristics found were: a "comorbidities trend" in LOP patients and a more frequent use of anti-IL17 in EOP.

Predictivity of the comorbidity indices for geriatric syndromes.

BACKGROUND: The aging population and increasing chronic diseases make a tremendous burden on the health care system. The study evaluated the relationship between comorbidity indices and common geriatric syndromes. METHODS: A total of 366 patients who were hospitalized in a university geriatric inpatient service were included in the study. Sociodemographic characteristics, laboratory findings, and comprehensive geriatric assessment(CGA) parameters were recorded. Malnutrition, urinary incontinence, frailty, polypharmacy, falls, orthostatic hypotension, depression, and cognitive performance were evaluated. Comorbidities were ranked using the Charlson Comorbidity Index(CCI), Elixhauser Comorbidity Index(ECM), Geriatric Index of Comorbidity(GIC), and Medicine Comorbidity Index(MCI). Because, the CCI is a valid and reliable tool used in different clinical settings and diseases, patients with CCI score higher than four was accepted as multimorbid. Additionally, the relationship between geriatric syndromes and comorbidity indices was assessed with regression analysis. RESULTS: Patients' mean age was 76.2 ± 7.25 years(67.8% female). The age and sex of multimorbid patients according to the CCI were not different compared to others. The multimorbid group had a higher rate of dementia and polypharmacy among geriatric syndromes. All four indices were associated with frailty and polypharmacy(p < 0.05). CCI and ECM scores were related to dementia, polypharmacy, and frailty. Moreover, CCI was also associated with separately slow walking speed and low muscle strength. On the other hand, unlike CCI, ECM was associated with malnutrition. CONCLUSIONS: In the study comparing the four comorbidity indices, it is revealed that none of the indices is sufficient to use alone in geriatric practice. New indices should be developed considering the complexity of the geriatric cases and the limitations of the existing indices.

Relation between drug therapy-based comorbidity indices, Charlson's comorbidity index, polypharmacy and mortality in three samples of older adults.

BACKGROUND: Comorbidity indexes were designed in order to measure how the disease burden of a patient is related to different clinical outcomes such as mortality, especially in older and intensively treated people. Charlson's Comorbidity Index (CCI) is the most widely used rating system, based on diagnoses, but when this information is not available therapy-based comorbidity indices (TBCI) are an alternative: among them, Drug Derived Complexity Index (DDCI), Medicines Comorbidity Index (MCI), and Chronic Disease Score (CDS) are available. AIMS: This study assessed the predictive power for 1-year mortality of these comorbidity indices and polypharmacy. METHODS: Survival analysis and Receiver Operating Characteristic (ROC) analysis were conducted on three Italian cohorts: 2,389 nursing home residents (Korian), 4,765 and 633 older adults admitted acutely to geriatric or internal medicine wards (REPOSI and ELICADHE). RESULTS: Cox's regression indicated that the highest levels of the CCI are associated with an increment of 1-year mortality risk as compared to null score for all the three samples. DDCI and excessive polypharmacy gave similar results but MCI and CDS were not always statistically significant. The predictive power with the ROC curve of each comorbidity index was poor and similar in all settings. CONCLUSION: On the whole, comorbidity indices did not perform well in our three settings, although the highest level of each index was associated with higher mortality.

The ability of comorbidity indices to predict mortality in an orthopedic setting: a systematic review.

BACKGROUND: Several comorbidity indices have been created to estimate and adjust for the burden of comorbidity. The objective of this systematic review was to evaluate and compare the ability of different comorbidity indices to predict mortality in an orthopedic setting. METHODS: A systematic search was conducted in Embase, MEDLINE, and Cochrane Library. The search were constructed around two primary focal points: a comorbidity index and orthopedics. The last search were performed on 13 June 2019. Eligibility criteria were participants with orthopedic conditions or who underwent an orthopedic procedure, a comparison between comorbidity indices that used administrative data, and reported mortality as outcome. Two independent reviewers screened the studies using Covidence. The area under the curve (AUC) was chosen as the primary effect estimate. RESULTS: Of the 5338 studies identified, 16 met the eligibility criteria. The predictive ability of the different comorbidity indices ranged from poor (AUC < 0.70) to excellent (AUC ≥ 0.90). The majority of the included studies compared the Elixhauser Comorbidity Index (ECI) and the Charlson Comorbidity Index (CCI). In-hospital mortality was reported in eight studies reporting AUC values ranging from 0.70 to 0.92 for ECI and 0.68 to 0.89 for CCI. AUC values were generally lower for all other time points ranging from 0.67 to 0.78. For 1-year mortality the overall effect size ranging from 0.67 to 0.77 for ECI and 0.69 to 0.77 for CCI. CONCLUSION: The results of this review indicate that the ECI and CCI can equally be used to adjust for comorbidities when analyzing mortality in an orthopedic setting. TRIAL REGISTRATION: The protocol for this systematic review was registered on PROSPERO, the International Prospective Register of Systematic Reviews on 13 June 2019 and can be accessed through record ID 133,871.

Reliability of the ASA Physical Status Classification System in Predicting Surgical Morbidity: a Retrospective Analysis.

The American Society of Anesthesiologists (ASA) Physical Status Classification System has been used to assess pre-anesthesia comorbid conditions for over 60 years. However, the ASA Physical Status Classification System has been criticized for its subjective nature. In this study, we aimed to assess the correlation between the ASA physical status assignment and more objective measures of overall illness. This is a single medical center, retrospective cohort study of adult patients who underwent surgery between November 2, 2017 and April 22, 2020. A multivariable ordinal logistic regression model was developed to examine the relationship between the ASA physical status and Elixhauser comorbidity groups. A secondary analysis was then conducted to evaluate the capability of the model to predict 30-day postoperative mortality. A total of 56,820 cases meeting inclusion criteria were analyzed. Twenty-seven Elixhauser comorbidities were independently associated with ASA physical status. Older patient (adjusted odds ratio, 1.39 [per 10 years of age]; 95% CI 1.37 to 1.41), male patient (adjusted odds ratio, 1.24; 95% CI 1.20 to 1.29), higher body weight (adjusted odds ratio, 1.08 [per 10 kg]; 95% CI 1.07 to 1.09), and ASA emergency status (adjusted odds ratio, 2.11; 95% CI 2.00 to 2.23) were also independently associated with higher ASA physical status assignments. Furthermore, the model derived from the primary analysis was a better predictor of 30-day mortality than the models including either single ASA physical status or comorbidity indices in isolation (p < 0.001). We found significant correlation between ASA physical status and 27 of the 31 Elixhauser comorbidities, as well other demographic characteristics. This demonstrates the reliability of ASA scoring and its potential ability to predict postoperative outcomes. Additionally, compared to ASA physical status and individual comorbidity indices, the derived model offered better predictive power in terms of short-term postoperative mortality.

Evaluation of comorbidity indices in determining the most suitable candidates for uro-oncological surgeries in elderly men.

INTRODUCTION: We aimed to evaluate the superiority of different comorbidity indices in determining the most suitable elderly male candidates for uro-oncological operations. While making this assessment, we also aimed to determine the risk factors that may affect surgery-related major complications and overall survival. MATERIAL AND METHODS: Data of 543 male patients, 60 years or older, who underwent uro-oncological surgery (radical cystectomy, radical prostatectomy, radical or partial nephrectomy, transurethral resection of bladder tumor) between September 2009 and January 2019 were retrospectively evaluated. Demographic, clinical and pathological characteristics of the patients, preoperative comorbidity indices, postoperative complications, length of hospitalization, re-admission rates within 90 days and postoperative follow-up outcomes were recorded. Patients in similar tumor stages were divided into different subgroups. All subgroups were divided into two main categories: middle age (60-69 years-old) and elderly age (≥70-years-old). RESULTS: No significant difference was found for all types of surgery in terms of postoperative outcomes in both age groups (p >0.05). Age-adjusted Charlson Comorbidity Index (ACCI), Preoperative Score to Predict Postoperative Mortality (POSPOM), Rockwood Frailty Index (RFI) and tumor characteristics were found to be more significant predictors for postoperative major complications and overall mortality than Eastern Cooperative Oncology Group (ECOG), American Society of Anesthesiologists (ASA) and New York Heart Association (NYHA) functional classification. CONCLUSIONS: Our findings show that patient age alone is not a risk factor for increased postoperative complications and overall mortality. Although many different comorbidity indices have been used in urological practice, ACCI, POSPOM and RFI are more valuable predictors. Uro-oncological surgeries may be performed safely in elderly males after a good clinical decision based on these indices.

Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data.

BACKGROUND: Understanding how comorbidity measures contribute to patient mortality is essential both to describe patient health status and to adjust for risks and potential confounding. The Charlson and Elixhauser comorbidity indices are well-established for risk adjustment and mortality prediction. Still, a different set of comorbidity weights might improve the prediction of in-hospital mortality. The present study, therefore, aimed to derive a set of new Swiss Elixhauser comorbidity weightings, to validate and compare them against those of the Charlson and Elixhauser-based van Walraven weights in an adult in-patient population-based cohort of general hospitals. METHODS: Retrospective analysis was conducted with routine data of 102 Swiss general hospitals (2012-2017) for 6.09 million inpatient cases. To derive the Swiss weightings for the Elixhauser comorbidity index, we randomly halved the inpatient data and validated the results of part 1 alongside the established weighting systems in part 2, to predict in-hospital mortality. Charlson and van Walraven weights were applied to Charlson and Elixhauser comorbidity indices. Derivation and validation of weightings were conducted with generalized additive models adjusted for age, gender and hospital types. RESULTS: Overall, the Elixhauser indices, c-statistic with Swiss weights (0.867, 95% CI, 0.865-0.868) and van Walraven's weights (0.863, 95% CI, 0.862-0.864) had substantial advantage over Charlson's weights (0.850, 95% CI, 0.849-0.851) and in the derivation and validation groups. The net reclassification improvement of new Swiss weights improved the predictive performance by 1.6% on the Elixhauser-van Walraven and 4.9% on the Charlson weights. CONCLUSIONS: All weightings confirmed previous results with the national dataset. The new Swiss weightings model improved slightly the prediction of in-hospital mortality in Swiss hospitals. The newly derive weights support patient population-based analysis of in-hospital mortality and seek country or specific cohort-based weightings.

Comparison between drug therapy-based comorbidity indices and the Charlson Comorbidity Index for the detection of severe multimorbidity in older subjects.

BACKGROUND: To know burden disease of a patient is a key point for clinical practice and research, especially in the elderly. Charlson's Comorbidity Index (CCI) is the most widely used rating system, but when diagnoses are not available therapy-based comorbidity indices (TBCI) are an alternative. However, their performance is debated. This study compares the relations between Drug Derived Complexity Index (DDCI), Medicines Comorbidity Index (MCI), Chronic Disease Score (CDS), and severe multimorbidity, according to the CCI classification, in the elderly. METHODS: Logistic regression and Receiver Operating Characteristic (ROC) analysis were conducted on two samples from Italy: 2579 nursing home residents (Korian sample) and 7505 older adults admitted acutely to geriatric or internal medicine wards (REPOSI sample). RESULTS: The proportion of subjects with severe comorbidity rose with TBCI score increment, but the Area Under the Curve (AUC) for the CDS (Korian: 0.70, REPOSI: 0.79) and MCI (Korian: 0.69, REPOSI: 0.81) were definitely better than the DDCI (Korian: 0.66, REPOSI: 0.74). All TBCIs showed low Positive Predictive Values (maximum: 0.066 in REPOSI and 0.317 in Korian) for the detection of severe multimorbidity. CONCLUSION: CDS and MCI were better predictors of severe multimorbidity in older adults than DDCI, according to the CCI classification. A high CCI score was related to a high TBCI. However, the opposite is not necessarily true probably because of non-evidence-based prescriptions or physicians' prescribing attitudes. TBCIs did not appear selective for detecting of severe multimorbidity, though they could be used as a measure of disease burden, in the absence of other solutions.

Predicting adverse events, length of stay, and discharge disposition following shoulder arthroplasty: a comparison of the Elixhauser Comorbidity Measure and Charlson Comorbidity Index.

BACKGROUND: Rising health care expenditures and the adoption of bundled-care initiatives require efficient resource allocation for shoulder arthroplasty. To determine a reliable and accessible metric for implementing perioperative care pathways, we compared the accuracy of the Elixhauser Comorbidity Measure (ECM) and Charlson Comorbidity Index (CCI) for predicting adverse events and postoperative discharge destination after shoulder arthroplasty. MATERIALS AND METHODS: The National Inpatient Sample was queried for patients who underwent total shoulder arthroplasty or reverse total shoulder arthroplasty between 2002 and 2014. Logistic regression models were constructed with basic demographic variables and either the ECM or the CCI to predict inpatient deaths, complications, extended length of stay, and discharge disposition. The predictive discrimination of each model was evaluated using the concordance statistic (C-statistic). RESULTS: We identified a total of 90,491 patients. The model incorporating both basic demographic variables and the complete set of ECM comorbidity variables provided the best predictive model, with a C-statistic of 0.867 for death, 0.752 for extended length of stay, and 0.81 for nonroutine discharge. The model's discrimination for postoperative complications was good, with C-statistics ranging from 0.641 to 0.879. CONCLUSION: A predictive model using the ECM outperforms models using the CCI for anticipating resource utilization following shoulder arthroplasty. Our results may assist value-based reimbursement methods to promote quality of care and reduce health care expenditures.

Prognostic effect of comorbidity indices in elderly patients with multiple myeloma.

BACKGROUND: Consideration of comorbidity, disability, and frailty represents a significant part of the treatment of elderly multiple myeloma (MM) patients. The aim of study was to analyze the effect of the Charlson Comorbidity Index (CCI) and scale of Instrumental Activities of Daily Living (IADL) on the course of disease. PATIENTS AND METHODS: The study included 110 newly diagnosed MM patients older than 65 years of age. According to the CCI most patients had at least 1 comorbidity (CCI score of 1) and most of them (51 of 110 patients; 46.4%) had an age-adjusted CCI (aaCCI) score of 5 to 6. Most of our patients were capable of performing routine daily activities (IADL ≥ 6). Patients were treated with thalidomide- and bortezomib- based combinations, or with conventional chemotherapy. RESULTS: International Staging System (ISS) score 3 correlated with high scores of CCI or aaCCI (R = 0.314, P < .003; R = .317, P < .002, respectively), and lower IADL (R = 0.259, P < .007). The probability of adverse events was 70% greater for CCI score ≥ 2 (odds ratio [OR], 1.72); 28% for aaCCI ≥ 5 (OR, 1.28) and 22% higher for IADL < 3 (OR, 2.25). The patients with a CCI score of 0 to 1 had significantly longer overall survival (OS; log rank, 6.538; P < .011). The patients with aaCCI ≥ 5 had significantly shorter OS (log rank, 4.209; P < .040), and the patients with IADL > 3 had significantly longer OS (log rank, 6.62; P < .001). In the proposed model, aaCCI ≥ 5 and IADL > 3 scores had a major effect on the OS (χ(2), 8.46; P = .037). CONCLUSION: CCI, aaCCI, and IADL scale are clinical parameters of prognostic significance. A proposed model for a personalized treatment approach is based on variables such as scores for aaCCI ≥ 5 and IADL > 3.