Introdução: Diversas condições clínicas podem modificar a resposta ao tratamento trombolítico no acidente vascular isquêmico agudo. O grau de comorbidade dos pacientes medido pelo Índice de Charlson, um índice que mede o grau de comorbidades clínicas em AVC, tem valor prognóstico na incapacidade pós-AVC tanto em populações com acidente vascular do tipo hemorrágico como isquêmico. Objetivo: Avaliar o efeito do grau de comorbidade aferido pelo índice de Charlson na resposta ao tratamento trombolítico no acidente vascular isquêmico e a incapacidade na alta hospitalar. Métodos: Estudo de coorte prospectivo de 96 pacientes tratados com trombólise para o acidente vascular isquêmico, avaliando o impacto das comorbidades clínicas na resposta ao tratamento trombolítico no AVC isquêmico. Os pacientes foram divididos em dois grupos, aqueles com alto ou baixo grau de comorbidades clínicas, conforme o índice de Charlson. A evolução após o tratamento foi aferida pelo escore de gravidade dos sintomas de acordo com a escala do NIHSS medido antes da infusão, imediatamente após o tratamento, 24horas e 7 dias após a trombólise. A incapacidade na alta foi avaliada pela escala modificada de Rankin sendo, considerada boa resposta a pontuação 0-1 e sua frequência comparada entre os dois grupos de pacientes. Resultados: A comparação dos escores médios do NIHSS mostraram diferenças significativas nos diferentes momentos entre os grupos de alta e baixa comorbidade (Wilk's Lambda test F (1,92) = 24.293; p< 0.001). Pacientes com índice de comorbidade baixo apresentaram redução do escore do NIHSS de 10.13 para 2.9, enquanto que no grupo com alta comorbidade, o tratamento trombolítico demostrou pouco efeito. Uma boa evolução, definida como incapacidade 0 e 1 na escala modificada de Rankin, foi observada em (73%) dos pacientes com baixo índice de comorbidade, enquanto somente (15%) dos pacientes com alto índice de comorbidade apresentaram essa evolução favorável, uma diferença clinicamente muito significativa (RR 5.62; 95% CI = 2.97 a 10.65; p< 0.001). Conclusão: A presença de comorbidades clínicas medida peloíndice de Charlson foi associada a uma menor resposta neurológica no tratamento trombolítico do AVC isquêmico e a um maior grau de incapacidade funcional na alta. / Background and purpose: Clinical comorbidities modify prognosis in haemorrhagic and ischaemic stroke. Charlson Comorbidity index is a validated and useful tool for evaluating comorbidity in stroke. In this study we evaluated the effect of clinical comorbidities as measured by Charlson Comorbidity Index in the in ischaemic stroke thrombolysis. Methods: Prospective cohort study of 96 thrombolysis treated ischaemic stroke patients. The cohort population was divided in two groups according with severity of Charlson Comorbidity Index. During study, NIHSS score was evaluated four times (pre, post, 24 hours and 7 days after thrombolysis) and lower or higher comorbidities groups were compared using repeated measures ANOVA. Response to thrombolysis in both groups was also analysed with disability modified Rankin scale. Results: We observed differences in evolution of mean NIHSS scores between higher and lower clinical comorbidity groups. Patients with low clinical comorbidities experiencing a significant reduction of NIHSS score that ranged from 10.13 to 2.9 points, while patients in the HIC group had initial NIHSS score of 14.75 and final NIHSS score of 13.78 (Wilk's Lambda test F (1,92) = 24.293; p< 0.001). Lack of response to thrombolysis had direct relation with disability at hospital discharge. Better clinical outcome, as evaluated by modified Rankin scale of 0 and 1, was markedly different between groups, with 23 (73%) versus 9 (15%) in low and high clinical comorbidities patients respectively (RR=5.62; 95%CI=2.97 to 10.65; p< 0.001). Conclusion: High level of clinical comorbidities negatively influences response to thrombolysis, attenuating treatment related reduction of stroke symptoms severity and increasing the frequency of disabled patients at discharge.

Introdução: A doença pulmonar obstrutiva crônica (DPOC) é um importante problema de saúde pública, que apresenta morbimortalidade considerável. Objetivos: Identificar as principais comorbidades e causas de morte e estudar os fatores preditores de mortalidade na DPOC. Métodos: Estudo de coorte com inclusão de pacientes ambulatoriais com DPOC. Foram coletados dados antropométricos, clínicos e funcionais. As comorbidades foram avaliadas através de um índice elaborado somando-se um ponto para cada comorbidade que o paciente apresentasse e através do índice de Charlson. O método de regressão de Cox foi utilizado para estudar os fatores associados à mortalidade. Resultados: Dos 520 pacientes 303 (58,3%) eram homens, a idade foi de 65,1±9,6 anos e o volume expiratório forçado no primeiro segundo (VEF1) foi de 1,18±0,57 l, 44,6±17,9% do previsto. Dezesseis pacientes (3,1%) não apresentavam comorbidades e 354 (68,1%) tinham três ou mais comorbidades, sendo a média de 3,63±1,95. O índice de Charlson foi 4,26±2,52. As principais comorbidades foram hipertensão arterial sistêmica (HAS; 46,5%), seguida por doença cardíaca (31,2%), dislipidemia (24,4%), diabetes mellitus (23,3%), obesidade (21,3%), desnutrição (21,3%), osteopenia/osteoporose (21,2%) e câncer (17,3%). Durante o tempo de seguimento de 38,3±20,8 meses 116 pacientes (22,3%) morreram. As principais causas de óbito foram respiratória (52,3%), câncer (22,4%), cardiovascular (10,3%) e abdominal (9,5%). Os fatores associados com a mortalidade na análise univariada foram idade, número de comorbidades, índice de Charlson, intensidade da dispneia, escore BODE (Body mass index, airway Obstruction, Dyspnea, and Exercise capacity), história de câncer, VEF1 (% do previsto) e distância percorrida no teste da caminhada de seis minutos (p<0,05). Na análise multivariada apenas o escore BODE e o índice de comorbidades de Charlson permaneceram significativos. Um escore de BODE de 5 apresentou uma hazard ratio (HR) de 2,96 (intervalo de confiança - IC 95% 1,54-5,68; p=0,0001) e um índice de Charlson de 4 uma HR de 1,78 (IC 95% 1,04-3,04; p=0,01). Conclusões: Comorbidades foram frequentes em pacientes com DPOC e a principal causa de morte foi respiratória. Tanto o escore de BODE como o índice de Charlson foram fatores preditores independentes de mortalidade. / Introduction: Chronic obstructive pulmonary disease (COPD) is a major public health problem involving considerable morbidity and mortality. Objectives: To identify major comorbidities and causes of death and to study the predictors of mortality in COPD. Methods: Cohort study including outpatients with COPD. Anthropometric, clinical and functional data were collected. Comorbidities were assessed through an index calculated by adding one point for each comorbidity the patient presented and using the Charlson index. The Cox regression method was used to study the factors associated with mortality. Results: Of the 520 patients 303 (58.3 %) were men, age was 65.1 ± 9.6 years and forced expiratory volume in one second (FEV1), was 1.18 ± 0.57 L, 44.6 ± 17.9 % of predicted. Sixteen patients (3.1 %) had no comorbidities and 354 (68.1 %) had three or more comorbidities, with an average of 3.63 ± 1.95. The Charlson index was 4.26 ± 2.52. The most common comorbidities were systemic arterial hypertension (46.5 %), followed by heart disease (31.2 %), dyslipidemia (24.4%), diabetes mellitus (23.3 %), obesity (21.3 %), low body weight (21.3%), osteopenia/osteoporosis (21.2 %) and cancer (17.3%). During the follow-up time of 38.3 ± 20.8 months 116 patients (22.3 %) died. The main causes of death were respiratory (52.3 %), cancer (22.4 %), cardiovascular (10.3%) and abdominal (9.5%). Factors associated with mortality in the univariate analysis were age, number of comorbidities, Charlson index, intensity of dyspnea, BODE score, history of cancer, FEV1 (% predicted) and distance on the six-minute walk test (p<0.05). In the multivariate analysis only the BODE score (Body mass index, airway Obstruction, Dyspnea, and Exercise capacity) and Charlson comorbidity index remained significant. A BODE score of 5 was associated with an hazard ratio (HR) of 2.96 (95% CI 1.54 to 5.68, p=0.0001) and a Charlson index of 4 with an HR of 1.78 (95% CI 1, 04 to 3.04, p=0.01). Conclusions: Comorbidities were common in patients with COPD and the main cause of death was respiratory. Both the BODE score and the Charlson index were independent predictors of mortality.

Introdução: Diversas condições clínicas podem modificar a resposta ao tratamento trombolítico no acidente vascular isquêmico agudo. O grau de comorbidade dos pacientes medido pelo Índice de Charlson, um índice que mede o grau de comorbidades clínicas em AVC, tem valor prognóstico na incapacidade pós-AVC tanto em populações com acidente vascular do tipo hemorrágico como isquêmico. Objetivo: Avaliar o efeito do grau de comorbidade aferido pelo índice de Charlson na resposta ao tratamento trombolítico no acidente vascular isquêmico e a incapacidade na alta hospitalar. Métodos: Estudo de coorte prospectivo de 96 pacientes tratados com trombólise para o acidente vascular isquêmico, avaliando o impacto das comorbidades clínicas na resposta ao tratamento trombolítico no AVC isquêmico. Os pacientes foram divididos em dois grupos, aqueles com alto ou baixo grau de comorbidades clínicas, conforme o índice de Charlson. A evolução após o tratamento foi aferida pelo escore de gravidade dos sintomas de acordo com a escala do NIHSS medido antes da infusão, imediatamente após o tratamento, 24horas e 7 dias após a trombólise. A incapacidade na alta foi avaliada pela escala modificada de Rankin sendo, considerada boa resposta a pontuação 0-1 e sua frequência comparada entre os dois grupos de pacientes. Resultados: A comparação dos escores médios do NIHSS mostraram diferenças significativas nos diferentes momentos entre os grupos de alta e baixa comorbidade (Wilk's Lambda test F (1,92) = 24.293; p< 0.001). Pacientes com índice de comorbidade baixo apresentaram redução do escore do NIHSS de 10.13 para 2.9, enquanto que no grupo com alta comorbidade, o tratamento trombolítico demostrou pouco efeito. Uma boa evolução, definida como incapacidade 0 e 1 na escala modificada de Rankin, foi observada em (73%) dos pacientes com baixo índice de comorbidade, enquanto somente (15%) dos pacientes com alto índice de comorbidade apresentaram essa evolução favorável, uma diferença clinicamente muito significativa (RR 5.62; 95% CI = 2.97 a 10.65; p< 0.001). Conclusão: A presença de comorbidades clínicas medida peloíndice de Charlson foi associada a uma menor resposta neurológica no tratamento trombolítico do AVC isquêmico e a um maior grau de incapacidade funcional na alta. / Background and purpose: Clinical comorbidities modify prognosis in haemorrhagic and ischaemic stroke. Charlson Comorbidity index is a validated and useful tool for evaluating comorbidity in stroke. In this study we evaluated the effect of clinical comorbidities as measured by Charlson Comorbidity Index in the in ischaemic stroke thrombolysis. Methods: Prospective cohort study of 96 thrombolysis treated ischaemic stroke patients. The cohort population was divided in two groups according with severity of Charlson Comorbidity Index. During study, NIHSS score was evaluated four times (pre, post, 24 hours and 7 days after thrombolysis) and lower or higher comorbidities groups were compared using repeated measures ANOVA. Response to thrombolysis in both groups was also analysed with disability modified Rankin scale. Results: We observed differences in evolution of mean NIHSS scores between higher and lower clinical comorbidity groups. Patients with low clinical comorbidities experiencing a significant reduction of NIHSS score that ranged from 10.13 to 2.9 points, while patients in the HIC group had initial NIHSS score of 14.75 and final NIHSS score of 13.78 (Wilk's Lambda test F (1,92) = 24.293; p< 0.001). Lack of response to thrombolysis had direct relation with disability at hospital discharge. Better clinical outcome, as evaluated by modified Rankin scale of 0 and 1, was markedly different between groups, with 23 (73%) versus 9 (15%) in low and high clinical comorbidities patients respectively (RR=5.62; 95%CI=2.97 to 10.65; p< 0.001). Conclusion: High level of clinical comorbidities negatively influences response to thrombolysis, attenuating treatment related reduction of stroke symptoms severity and increasing the frequency of disabled patients at discharge.

京都大学 / 新制・課程博士 / 博士(社会健康医学) / 甲第23118号 / 社医博第114号 / 新制||社医||11(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 佐藤 俊哉, 教授 森田 智視, 教授 黒田 知宏 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

Background. In-hospital mortality is a measure recognized by US Agency for Healthcare Quality to represent quality of care within hospitals, that accounts for mortality based on three indicators: 1. select medical conditions and procedures; 2. procedures linked with questions of use (misuse, over/under use); 3. high volume procedures traditionally associated with lower mortality rates. Understanding how different comorbidity models measure in-hospital mortality is essential not only for determining patient health status in the hospital setting, but also help to regulating mortality risk and mortality risk predictions. One of the most widely used discriminatory models is the Charlson model, which predicts the risk of mortality within one year of hospitalization of patients with various comorbidities using CCSR codes for ICD-10 diagnoses which is quantified by the c-statistics, represented by the area under the curve (AUC). Objectives. To adapt a comorbidity index model to the National Inpatient Sample (NIS) database of 2020 to predict 1-year mortality for patients admitted with select ICD-10 codes of diagnoses. Methods Our study analysis examined mortality with comorbidity using the Charlson model in a sample population of estimated 5,533,477 adult inpatients (individuals ≥18 years of age). A multivariate logistic regression model was constructed with in-hospital mortality as the outcome variable and identifying predictor variables as defined by the Clinical Classifications Software Refined Variables (CCSR) codes for selected ICD-10 diagnoses (Table 3). Descriptive statistics and the base logistic regression analyses were conducted using SAS statistical software version 9.4. To avoid overpowering and avoid variables attaining statistical significance while only marginally changing the outcome, a subsample (n=100,000) was randomly selected from the original data set. Ultimately, 20 CCSR variables with p-values <0.20 from the base simple logistic regression models were included in the subsequent backward stepwise logistic regression analysis. Results Table 1 shows the prevalence of the selected diagnoses for our analysis. Anemia (28.32%), pulmonary disease (asthma, COPD, pneumoconiosis;21.88%), and diabetes without complications (19.47%) were the three most prevalent conditions among hospitalized patients. Table 2 shows the results of the base logistic regression analysis conducted, which excluded connective tissue/rheumatologic disorders, peptic ulcer disease, anemia, diabetes with complications, and human immunodeficiency as predictors of inpatient mortality. Results of the backward stepwise regression analysis revealed that severe liver disease/hepatic failure ([adjusted odds ratio (aOR): 10.50, (CI: 10.40-10.59)], acute myocardial infarction ([2.85, (2.83-2.87)] and malnutrition ([2.15, (2.14-2.16)] were three most important risk factors and had the highest impact on inpatient mortality (p-value <0.0001). However, smoking history, obesity, and liver disease were negatively associated with inpatient mortality. The c-statistic or the area under the curve (AUC) for the final model was 0.752. Conclusion Our findings, based on Charlson modeling procedures, indicate that independent variables representative of comorbidity with the strongest 1-year risk of mortality were among patients with ICD-10 codes relating to: severe liver disease/hepatic failure, acute myocardial infarction, and malnutrition. Hence, relevant stakeholders (patients, family members, and healthcare providers) can utilize this knowledge to advance models of care and prevention strategies that limit disease progression and improve patient outcomes.

The objective of this study was to investigate the utilization of the diagnose-based Charlson Comorbidity Index (CCI) and the medication-based Rx-Risk Comorbidity Index on Swedish administrative data. Data was collected over a ten-year period from the National Patient Register and the National Prescribed Medication Register on 3609 respondents from the national public health survey 2018, aged 16-84 and registered in Stockholm County. The overall aim was to identify comorbid conditions in the study population; and to examine if the identified comorbidities differ between indices, based on subject characteristics such as age and gender. Moreover, the specific aim was to quantify correlation between the indices, as well as within indices over look-back periods of up to ten years. Among the study population, 13 % were identified with at least one comorbid condition through CCI, and 87 % had medications indicative of at least one condition covered by Rx-Risk. Both the original Charlson weights and updated weights by Quan were used to compute the comorbidity scores for CCI. Results showed that when CCI and Quan may have scored low, the Rx-Risk picked up more conditions. The Spearman rank correlation between CCI and Quan scores resulted in relatively high correlation with a coefficient of 0.82 (p-value &lt; 0.05) over look-back periods of 2, 5 and 10 years. Moreover, the correlation between CCI and Rx-Risk was fairly low over all look-back periods with a correlation coefficient of 0.34 (p-value &lt; 0.05) at most. The within-correlation showed that CCI identified much of the comorbidity between the one- and two-year look-back periods, whilst Rx-Risk identified much comorbidity within the one-year look-back period. The overall implications of the presented results are that a utilization of Charlson index and Rx-Risk is likely to capture comorbid conditions in different health care settings, and thus expected correlation is to be of modest level between the two indices. The research question of interest should therefore determine which index is favorable when assessment of comorbidity is desired.

Objective: The objective of this study was to compare the use of different comorbidity measures to predict future healthcare utilization and expenditures for diabetic patients. Methods: This was a retrospective study that included 8,704 diabetic patients enrolled continuously for three years in the Department of Defense TRICARE program. Administrative claims data were used to calculate six comorbidity measures: number of distinct medications, index-year healthcare expenditures, two versions of the Charlson Comorbidity Index (CCI), and two versions of the Chronic Disease Score (CDS). Linear regression models were used to estimate three health outcomes for one- and two-year post-index periods: healthcare expenditures (COST), number of hospitalizations (HOS), and number of emergency department visits (ED). Logistic regression models were used to estimate binary outcomes (above or below the 90th percentile of COST; [greater than or equal to] 1 HOS or none; [greater than or equal to] 1 ED or none). Comparisons were based on adjusted R², areas under the receiver-operator-curve (c statistics), and the Hosmer-Lemeshow goodness-of-fit tests. Results: The study population had a mean age of 51.0 years (SD = 10.5), and 46.3 percent were male. After adjusting for age and sex, the updated CCI was the best predictor of one-year and two-year HOS (adjusted R² = 8.1%, 9.3%), the number of distinct medications was superior in predicting one-year and two-year ED (adjusted R² = 9.9%, 12.4%), and the index-year healthcare expenditures explained the most variance in one-year and two-year COST (adjusted R² = 35.6%, 31.6%). In logistic regressions, the number of distinct medications was the best predictor of one-year and two-year risks of emergency department use (c = 0.653, 0.654), but the index-year healthcare expenditures performed the best in predicting one-year and two-year risks of hospitalizations (c = 0.684, 0.676) and high-expenditure cases (c = 0.810, 0.823). The updated CCI consistently outperformed the original CCI in predicting the outcomes of interest. Conclusions: In a diabetic population under age 65, the number of distinct medications and baseline healthcare expenditures appeared to have superior or similar powers compared to the CCI or CDS for the prediction of future healthcare utilization and expenditures. The updated CCI was a better predictor than the original CCI in this population. / text

No description available.

The purpose of this work was to further understand nutritional status, especially body weight and composition, during colorectal cancer progression. Population-based studies of colorectal cancer patients were conducted using administrative health data (primary and co-morbid diseases, demographics), and computed tomography (CT) imaging (body composition). In cohort 1, administrative health data was used to study comorbidities and nutritional status in 574 colorectal cancer patients referred for chemotherapy. Multivariate Cox regression revealed several comorbidities, performance status and weight loss 20% predicted survival. In cohort 2, a serial CT image analysis assessed longitudinal body composition changes during the last 12 months preceding death from colorectal cancer (n=34). Body composition changes were typified by exponential increases in liver metastases with concurrent accelerations of muscle and fat loss. These results have the potential to make a difference in how colorectal cancer patients are treated and researched by dietitians, oncologists, and health services researchers. / Nutrition and Metabolism

Background/Objectives: West Nile neuroinvasive disease (WNND) is a severe neurological illness that develops in approximately 1% of individuals infected with West Nile virus (WNV). Manifesting most frequently as encephalitis (WNE), meningitis (WNM), or acute flaccid paralysis (WNP), there is no cure for WNND beyond supportive care and rehabilitation, and death or permanent disability are common outcomes. As the virus arrived in North America less than 20 years ago, determinants of severe disease progression following infection are still being explored. This project is the first to examine comorbid conditions as risk factors of WNND in Ontario using a population-based study design. As prevention is the only avenue of defence against WNND, identifying comorbid risk factors of WNND would allow for public health prevention campaigns targeted to high-risk groups. The main objectives of this thesis were to explore whether pre-existing chronic diseases were associated with the development of WNND, or any of its three manifestations (i.e., encephalitis, meningitis, acute flaccid paralysis). Methods: This was a retrospective, population-based study including all Ontario residents with a confirmed diagnosis of WNV infection between January 1, 2002 and December 31, 2012. A cohort of individuals with WNV was identified from a provincial laboratory database and individually-linked to health administrative databases. In the WNV cohort, individuals with WNND and 13 comorbid conditions were identified using algorithms based on ICD-10-CA diagnostic codes. Incidence of WNND following WNV infection was then compared among individuals with and without comorbid conditions using relative risks estimated by log binomial regression. Additionally, risk ratios were calculated for associations between specific comorbid conditions and WNND neuroinvasive manifestation (i.e., encephalitis, meningitis, acute flaccid paralysis). Finally, associations between Charlson Comorbidity Index (CCI) scoring and development of WNND was examined through calculation of relative risk using log binomial regression. Results/Potential Impact: Risk factors for WNND included male sex (aRR: 1.21; 95% CI: 1.00-1.46) in addition to the combined effect of hypertension and increasing age (5-year intervals) (aRR: 1.16; 95% CI: 1.08-1.24); WNND was also associated with increasing CCI scores; individuals in low, medium, and high categories had increased risk compared to individuals with a score of zero, but the greatest risk was in the high CCI category (aRR: 3.45; 95% CI: 2.25-4.83) Male sex (aRR: 1.32; 95% CI: 1.00-1.76), increasing age (aRR: 1.02; 95% CI: 1.02-1.03), and being immunocompromised (aRR: 2.61; 95% CI: 1.23-4.53) were associated with development of WNE. No risk factors were identified for WNM and WNP. Identification of comorbid risk factors of WNND will allow public health officials to identify high-risk groups and to develop prevention strategies targeted for vulnerable individuals.