Influence Of Multimorbidity And Comorbidity Index On Severity And Treatment Outcomes Of COVID-19 Patients

BackgroundAlthough Coronavirus disease 2019(COVID-19)has entered a new phase,previous studies have shown that COVID-19 patients with chronic disease have higher fatality rate,and a portion of those patients have more than one chronic disease.According to the World health organization(WHO),the condition of co-exists with two or more diseases belongs to "multimorbidity".The multimorbidity condition of COVID-19 patients was complex.Previous studies have shown that among severe COVID-19 patients,the major multimorbiditiy included hypertension,diabetes,cardiovascular disease,cancer,chronic kidney disease,and chronic obstructive pulmonary disease.A fair number of researches suggested that multimorbidity may increase the risk of COVID-19 infection and death.Previous studies on the relationship between multimorbidity and the severity or prognosis of COVID-19 were mostly conducted from two dimensions of multimorbidity:single disease and the number of co-existed diseases.However,the results were still controversial.Some foreign studies used Charlson comorbidity index(CCI)or age-adjusted Charlson comorbidity index(aCCI)to describe and evaluate the condition of COVID-19 patients with multimorbidity.Several studies also discussed the association between CCI/aCCI and the COVID-19 patients’ risk of severity and death.Other studies further established prediction models including aCCI for practical application of COVID-19 control.However,there was little domestic research on multimorbidity and risk of COVID-19 severity or prognosis.ObjectiveThis study aims to describe the multimorbidity condition of COVID-19 patients,explore the influence of number of co-existed diseases,multimorbidity types(including single disease and combination of diseases)and aCCI on COVID-19 severity and treatment outcomes.On this basis,evaluated the prediction ability of multimorbidity on COVID-19 severity and treatment outcomes.Provide a scientific basis to formulate and implement preventive measures,and reduce the mortality of COVID-19 in high-risk groups.MethodsThis retrospective cohort study included 1160 COVID-19 patients from 53 hospitals in 9 provinces or cities(Anhui,Fujian,Guangxi,Hebei,Heilongjiang,Shaanxi,Sichuan,Shanxi,and Chongqing)during January 13 to April 13,2020.The diagnosis of diseases was collected from hospital case systems.First,we descripted the basic information and characteristics of COVID-19 patients and their multimorbidity conditions.Second,we made a multimorbidity pattern analysis and constructed comorbidity index.Third,Logistic regression analysis was used to investigate the impact of three multimorbidity dimensions(number,type and comorbidity index)on COVID-19 severity and treatment outcomess.Fourth,subgroup analysis with types of diseases,sex and age stratified were used to explore sex and age differences in the impact of multimorbidity on COVID-19 severity and treatment outcomes.COVID-19 patients younger than 18 years of age were excluded for sensitivity analysis.Fifth,restricted cubic spline(RCS)was used to analyze the nonlinear relationship between the number of co-existed diseases,aCCI and the risk of severity and adverse outcomes of COVID-19.Last,receiver operating characteristic curve(ROC)was used to evaluate the prediction ability of multimorbidity factors to predict the risk of severity and adverse outcome of COVID-19.Epidata 3.0 software was used for data entry.SAS 9.4,and R 4.1.2 were maninly used for data analysis.Results1.Basic characteristics of COVID-19 patientsA total of 606 male patients and 554 female patients were included in this study,the average age of COVID-19 patients was 46.46 years,and the average age of female patients was higher than male.The incidence rate of severity,adverse outcome and multimorbidity in COVID-19 patients was 13.62%,2.76%and 32.33%,respectively.We did not find sex difference in the incidence of severity and adverse outcome(P>0.05),while the sex difference of multimorbidity rate was statistically significant:the rate was higher in men than women(P=0.005).The mean age,BMI and multimorbidity rate of severe patients were higher than those non-severe patients(P<0.01),meanwhile,the mean age and multimorbidity rate of patients with adverse outcomes were higher than those with good outcomess(P<0.001).Hypertension,overweight/obesity,type 2 diabetes(T2DM),heart disease and COPD were most common single diseases;the top five disease combinations with the highest prevalence were hypertension+T2DM,hypertension+overweight/obesity,hypertension+heart disease,hypertension+stroke,and hypertension+T2DM+heart disease.2.Influence of multimorbidity on the severity and treatment outcomes of COVID-19After adjusting for covariates,patients with multimorbidity had an increased risk of both severity and adverse outcomes,with OR values(95%CI)of 3.52(2.37-5.22)and 3.73(1.64-8.50),respectively.In this study,the number of co-existed diseases was 0-4.Compared with patients without multimorbidity,the number of co-existed diseases was 1,2,or≥3,could increase the risk of severity by 3.27 times(95%CI:2.13-5.02),3.50 times(95%CI:1.88-6.54),and 7.15 times(95%CI:2.98-17.15),respectively.The risk of severity increased by 90%for each additional number of co-existed disease,and the trend of severity risk increased with the number of single diseases growing up.When the number of co-existed disease was 1 and 2,the risk of adverse outcomes increased 3.70 times(95%CI:1.52-8.99)and 3.77 times(95%CI:1.21-11.76),respectively.Risk of adverse outcomes increased 67%for each additional number of single diseases,and the risk of adverse outcomes also increased with the number growing.In addition,this study found T2DM and heart disease were both risk factors for severity(OR,95%CI:4.11,1.74-9.71;5.07,1.61-15.95)and adverse outcomes(OR,95%CI:8.14,2.20-30.17;32.05,5.35-192.00)of COVID-19.After subgroup analysis by sex,the effect of cardiometabolic disease on the risk of severity in women remained significant(OR:6.33,95%CI:3.04-13.18).Common combination of diseases was the combination of hypertension and other cardiometabolic diseases.Hypertension+overweight/obesity(OR:8.16,95%CI:2.02-33.03),hypertension+stroke(OR:8.15,95%CI:1.42-46.59)were risk factors of COVID-19 severity,and hypertension+heart disease(OR:10.42,95%CI:1.26-86.15)was a risk factor of adverse outcomes.After stratifing by sex,the combination of hypertension and cardiovascular disease had more significant effect in women on COVID-19 severity and adverse outcomes;after stratifing by age,the effect of combination of hypertension and cardiovascular disease on COVID-19 severity was more pronounced in patients aged 60 years and older.In this study,the aCCI score ranged from 0 to 8 points.After adjusting covariates,the risk of severity and adverse outcomes showed an upward trend within aCCI score increasing.For every one-point increased aCCI,the risk of severity and adverse outcomes separately increased 64%and 55%.3.The ability of multimorbidity to predict the severity and treatment outcomes of COVID-19According to adjusted ROC analysis,hypertension,T2DM,heart disease,stroke,allergic disease,hypertension+overweight/obesity,hypertension+stroke all had good predictive ability on the risk of severity(AUC:0.767-0.795).T2DM,overweight/obesity+heart disease,hypertension+ heart disease were good predictors of risk of adverse outcomes(AUC:0.722-0.783).Both the number of co-existed diseases and aCCI could predict the risk of severity and adverse outcomes well(AUC:0.774-0.799).However,ROC analysis without adjusting for covariates showed that the scores of aCCI remained robust in predicting severe and adverse outcomes of COVID-19.ConclusionCOVID-19 patients with severity and adverse outcomes have higher rates of multimorbidity,and their multimorbidity conditions were complex.Cardiaometabolic disease and its combination was associated with risk of severity and adverse outcomes of COVID-19.In addition,larger number of co-existed diseases and higher aCCI scores were also associated with risk of severity and adverse outcomes.There were sex differences in the impact of multimorbidity on COVID-19 severity and treatment outcomes:women had more significant risk of severity and adverse outcomes influenced by cardiometabolic disease and its multimorbidity.Besides,the risk of severity and adverse outcomes in older patients aged≥60 years was significantly affected by cardiometabolic disease and its combination.In addition,aCCI score have good predictive power for both severity and adverse outcomes of COVID-19.