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Roberts MH, Mannino DM, Mapel DW, Lunacsek O, Amin S, Farrelly E, Feigler N, Pollack MF. Disease Burden and Health-Related Quality of Life (HRQoL) of Chronic Obstructive Pulmonary Disease (COPD) in the US - Evidence from the Medical Expenditure Panel Survey (MEPS) from 2016-2019. Int J Chron Obstruct Pulmon Dis 2024; 19:1033-1046. [PMID: 38765766 PMCID: PMC11100519 DOI: 10.2147/copd.s446696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 03/25/2024] [Indexed: 05/22/2024] Open
Abstract
Purpose Chronic obstructive pulmonary disease (COPD) is a progressive disease associated with reduced life expectancy, increased morbidity, mortality, and cost. This study characterized the US COPD burden, including socioeconomic and health-related quality of life (HRQoL) outcomes. Study Design and Methods In this retrospective, cross-sectional study using nationally representative estimates from Medical Expenditures Survey (MEPS) data (2016-2019), adults (≥18 years) living with and without COPD were identified. Adults living without COPD (control cohort) and with COPD were matched 5:1 on age, sex, geographic region, and entry year. Demographics, clinical characteristics, socioeconomic, and generic HRQoL measures were examined to include a race-stratified analysis of people living with COPD. Results A total of 4,135 people living with COPD were identified; the matched dataset represented a weighted non-institutionalized population of 11.3 million with and 54.2 million people without COPD. Among people living with COPD, 66.3% had ≥1 COPD-related condition; 62.7% had ≥1 cardiovascular condition, compared to 33.5% and 50.5% without COPD. More people living with COPD were unemployed (56.2% vs 45.3%), unable to work due to illness/disability (30.1% vs 12.1%), had problems paying bills (16.1% vs 8.8%), reported poorer perceived health (fair/poor: 36.2% vs 14.4%), missed more working days due to illness/injury per year (median, 2.5 days vs 0.0 days), and had limitations in physical functioning (40.1% vs 19.4%) (all P<0.0001). In race-stratified analyses for people living with COPD, people self-reporting as Black had higher prevalence of cardiovascular-risk conditions, poorer socioeconomic and HRQoL outcomes, and higher healthcare expenses than White or Other races. Conclusion Adults living with COPD had higher clinical disease burden, lower socioeconomic status, and reduced HRQoL than those without, with greater disparities among Black people living with COPD compared to White and other races. Understanding the characteristics of patients helps address care disparities and access challenges.
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Affiliation(s)
| | - David M Mannino
- College of Medicine, University of Kentucky, Lexington, KY, USA
- COPD Foundation, Miami, FL, USA
| | | | | | - Shahla Amin
- Global Consulting, Cencora, Conshohocken, PA, USA
| | | | - Norbert Feigler
- BioPharmaceuticals, US Medical, AstraZeneca, Wilmington, DE, USA
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Womack JA, Murphy TE, Leo-Summers L, Bates J, Jarad S, Gill TM, Hsieh E, Rodriguez-Barradas MC, Tien PC, Yin MT, Brandt CA, Justice AC. Assessing the contributions of modifiable risk factors to serious falls and fragility fractures among older persons living with HIV. J Am Geriatr Soc 2023; 71:1891-1901. [PMID: 36912153 PMCID: PMC10258163 DOI: 10.1111/jgs.18304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 01/14/2023] [Accepted: 01/25/2023] [Indexed: 03/14/2023]
Abstract
BACKGROUND Although 50 years represents middle age among uninfected individuals, studies have shown that persons living with HIV (PWH) begin to demonstrate elevated risk for serious falls and fragility fractures in the sixth decade; the proportions of these outcomes attributable to modifiable factors are unknown. METHODS We analyzed 21,041 older PWH on antiretroviral therapy (ART) from the Veterans Aging Cohort Study from 01/01/2010 through 09/30/2015. Serious falls were identified by Ecodes and a machine-learning algorithm applied to radiology reports. Fragility fractures (hip, vertebral, and upper arm) were identified using ICD9 codes. Predictors for both models included a serious fall within the past 12 months, body mass index, physiologic frailty (VACS Index 2.0), illicit substance and alcohol use disorders, and measures of multimorbidity and polypharmacy. We separately fit multivariable logistic models to each outcome using generalized estimating equations. From these models, the longitudinal extensions of average attributable fraction (LE-AAF) for modifiable risk factors were estimated. RESULTS Key risk factors for both outcomes included physiologic frailty (VACS Index 2.0) (serious falls [15%; 95% CI 14%-15%]; fractures [13%; 95% CI 12%-14%]), a serious fall in the past year (serious falls [7%; 95% CI 7%-7%]; fractures [5%; 95% CI 4%-5%]), polypharmacy (serious falls [5%; 95% CI 4%-5%]; fractures [5%; 95% CI 4%-5%]), an opioid prescription in the past month (serious falls [7%; 95% CI 6%-7%]; fractures [9%; 95% CI 8%-9%]), and diagnosis of alcohol use disorder (serious falls [4%; 95% CI 4%-5%]; fractures [8%; 95% CI 7%-8%]). CONCLUSIONS This study confirms the contributions of risk factors important in the general population to both serious falls and fragility fractures among older PWH. Successful prevention programs for these outcomes should build on existing prevention efforts while including risk factors specific to PWH.
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Affiliation(s)
- Julie A. Womack
- VA Connecticut Healthcare System, West Haven, CT
- Yale School of Nursing, West Haven, CT
| | | | | | - Jonathan Bates
- VA Connecticut Healthcare System, West Haven, CT
- Yale School of Medicine, New Haven, CT
| | | | | | - Evelyn Hsieh
- VA Connecticut Healthcare System, West Haven, CT
- Yale School of Medicine, New Haven, CT
| | - Maria C. Rodriguez-Barradas
- Infectious Diseases Section, Michael E DeBakey VA Medical Center, and Department of Medicine, Baylor College of Medicine, Houston, TX
| | - Phyllis C. Tien
- University of California, San Francisco, and Department of Veterans Affairs, San Francisco, CA
| | | | - Cynthia A. Brandt
- VA Connecticut Healthcare System, West Haven, CT
- Yale School of Medicine, New Haven, CT
| | - Amy C. Justice
- VA Connecticut Healthcare System, West Haven, CT
- Yale School of Medicine, New Haven, CT
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Zsichla L, Müller V. Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors. Viruses 2023; 15:175. [PMID: 36680215 PMCID: PMC9863423 DOI: 10.3390/v15010175] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/04/2023] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.
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Affiliation(s)
- Levente Zsichla
- Institute of Biology, Eötvös Loránd University, 1117 Budapest, Hungary
- National Laboratory for Health Security, Eötvös Loránd University, 1117 Budapest, Hungary
| | - Viktor Müller
- Institute of Biology, Eötvös Loránd University, 1117 Budapest, Hungary
- National Laboratory for Health Security, Eötvös Loránd University, 1117 Budapest, Hungary
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Kaur D, Agrawal KC, Deep A, Choudhary H, Soni L, Saran R, Sankhla V. Post-COVID-19 manifestations: A study of analyzing symptoms, complications following hospitalization. J Family Med Prim Care 2022; 11:6015-6022. [PMID: 36618168 PMCID: PMC9810890 DOI: 10.4103/jfmpc.jfmpc_219_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/04/2022] [Accepted: 04/11/2022] [Indexed: 11/11/2022] Open
Abstract
Background Post-COVID-19 symptoms and diseases appeared on recovered from COVID-19. Hence, the study aims to investigate and characterize the manifestations which appear after recovery from the corona virus infection. Objectives To investigate the post-COVID-19 Manifestation, to demonstrate different symptoms or signs that appeared during COVID and after recovery from the disease and to see association of independent factors (like age, sex, BMI, Comorbidities) with Post-COVID complication. Methods The study was conducted using cross-sectional study among COVID positive patients admitted and then recovered in Bangur Hospital, Pali, Rajasthan, including ICU and Isolation wards from March to December 2020. Sample size calculated was 423 with simple random sampling. Findings In our study of these 421 COVID-19 cases, median age was 36 year (Interquartile Range: 26-55 years). Post-COVID manifestation (at least one symptom) significantly associated with age of subjects (p = 0.001), subjects who were in ICU during COVID-19 positive (p = 0.003), symptomatic subjects (p = 0.009) during COVID positive and SPO2 level at the time of admission during COVID positive (p = 0.01). Conclusion The recovered subjects should be highly vigilant in maintaining and monitoring their health status as there is a risk of future complications after recovery.
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Affiliation(s)
- Daljeet Kaur
- Department of Community Medicine, Government Medical College and Bangur Hospital, Pali, Rajasthan, India
| | - Kailash Chandra Agrawal
- Department of Respiratory Medicine, Government Medical College and Bangur Hospital, Pali, Rajasthan, India
| | - Aman Deep
- Department of Community Medicine, Government Medical College and Bangur Hospital, Pali, Rajasthan, India
| | - Hazarimal Choudhary
- Department of General Medicine, Government Medical College and Bangur Hospital, Pali, Rajasthan, India
| | - Laxman Soni
- Department of Respiratory Medicine, Government Medical College and Bangur Hospital, Pali, Rajasthan, India,Address for correspondence: Dr. Laxman Soni, Department of Respiratory Medicine, Government Medical College & Bangur Hospital, Pali, Rajasthan, India. E-mail:
| | - Rajendra Saran
- Department of Community Medicine, Government Medical College and Bangur Hospital, Pali, Rajasthan, India
| | - Vasudev Sankhla
- Department of Biochemistry, Government Medical College and Bangur Hospital, Pali, Rajasthan, India
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Dinesh KS, Nazeema PK, Archana M, Jayakrishnan K, Santhi Krishna AS, Swapna CS, Sujitha VK, Anju S, Girish BM, Geethu B, Krishnendu C. Application Of A Non-Linear Multi-Model Ayurveda Intervention In Elderly COVID-19 Patients- A Retrospective Case Series. J Ayurveda Integr Med 2021; 13:100476. [PMID: 34230788 PMCID: PMC8249719 DOI: 10.1016/j.jaim.2021.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 06/19/2021] [Accepted: 06/21/2021] [Indexed: 10/30/2022] Open
Abstract
Background and Aim With over 155 million infections, nearly 32 lakh deaths, and an economic toll accounting to trillions, the COVID-19 pandemic is ravaging the world. The mainstream medical system is being handicapped with the challenge of patient management with no proven treatment at one end and the use of vaccine at the other with prevailing ambiguity in developing herd immunity and safety concerns of mass vaccinations amidst pandemic. Though vaccination is the only hope, fool proof evidences are absent on its efficacy. Also, adults of above 65 are of greater risk in terms of complications and death. China has already documented the use of traditional Chinese medicine against the pandemic with national participation rate of 90%. In this regard, the use of complementary and alternative medicine (CAM) against COVID-19 is relevant, especially in a country like India where it is widely practised as Ayurveda. Experimental procedure The current report is a retrospective case series of 64 Non-Resident Indians (NRIs) above the age of 60 years tested positive through Reverse Transcription-Polymerase Chain Reaction (RT-PCR) through a Non-Linear multi-modal Ayurveda Intervention (NLMAI) for 21 days consulted through online media. The NLMAI is a combination of herbal and herbo-mineral drug interventions, lifestyle modifications, and psychological support done in 2 phases. Results and conclusions The management revealed a mean duration of symptoms assessed through survival function of 11 symptoms of COVID-19 as 0.577 days [SE=0.39] with a CI 95% [lower bound=0.500, upper bound 0.653] which was considerably low when compared to global statistics. Moreover, none of the cases advanced to complications or death. The holistic, non-linear, multi-modal approach of Ayurveda may be used to counter the gravity of the COVID-19 pandemic through easy symptomatic recovery, co-morbidity managements and deaths.
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Key Words
- AYUSH, Ayurveda, yoga and naturopathy, Unani, Siddha and homoeopathy
- Alternative medicine
- Ayurveda
- CAM, Complementary and alternative medicine
- COVID-19
- COVID-19, Corona Virus Disease- 2019
- Co-morbidity
- NLMAI, Non-Linear multi-modal Ayurveda Intervention
- NRIs, Non-Resident Indians
- RT-PCR, Reverse Transcription-Polymerase Chain Reaction
- SARS-CoV-2, Severe Acute Respiratory Syndrome Corona Virus-2
- Traditional medicine
- elderly patients
- survival function
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Affiliation(s)
- K S Dinesh
- Department of Kaumarabhritya, Vaidyaratnam P S Varier Ayurveda College, Kottakkal. Edarikode (P.O), Pincode:676501, Malappuram district, Kerala, India, Contact No: 9447698085
| | - P K Nazeema
- Department of Kaumarabhritya, Vaidyaratnam P S Varier Ayurveda College, Kottakkal. Edarikode (P.O), Pincode:676501, Malappuram district, Kerala, India, Contact No: 9495511081
| | - Madhavi Archana
- AYUSH Public Health Initiative, Department of Kaumarabhritya, Vaidyaratnam P S Varier Ayurveda College, Kottakkal Edarikode (P.O), Pincode:676501, Malappuram district, Kerala, India, Contact No.7022928745
| | - K Jayakrishnan
- Department of Swasthavritha, All India Institute of Ayurveda, Mathura Rd, Gautampuri Awas, Sarita Vihar, New Delhi, Pincode:110076, India, Contact No: 9496349829
| | - A S Santhi Krishna
- Surya, katampazhipuram, Palakkad, Pincode: 678633 Kerala, India, Contact No: 9447785271
| | - Chitra S Swapna
- Department of Kaumarabhritya, Santhigiri Ayurveda Medical college, Olassery, Kodumba, Palakkad, Pincode: 67855, Kerala, India, Contact No: 9495608309
| | - V K Sujitha
- Department of Kaumarabhritya, Vaidyaratnam P S Varier Ayurveda College, Kottakkal, Edarikode (P.O), Pincode:676501, Malappuram district, Kerala, India, Contact No: 9744872345
| | - Sathian Anju
- AYUSH Public Health Initiative, Department of Kaumarabhritya, Vaidyaratnam P S Varier Ayurveda College, Kottakkal, Edarikode (P.O), Pincode:676501, Malappuram district, Kerala, India, Contact No: 9946424009
| | - Babu M Girish
- Department of Statistics, CHMKM Government Arts and Science College, Koduvally, pin code: 673572 Kozhikode, Contact No: 9447395825
| | - Balakrishnan Geethu
- AYUSH Extra Mural Research, Department of Kaumarabhritya, Vaidyaratnam P S Varier Ayurveda College, Kottakkal, Edarikode (P.O), Pincode:676501, Malappuram district, Kerala, India
| | - C Krishnendu
- AYUSH Extra Mural Research, Department of Kaumarabhritya, Vaidyaratnam P S Varier Ayurveda College, Kottakkal, Edarikode (P.O), Pincode:676501, Malappuram district, Kerala, India
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Association of Dietary Fiber on Asthma, Respiratory Symptoms, and Inflammation in the Adult National Health and Nutrition Examination Survey Population. Ann Am Thorac Soc 2021; 17:1062-1068. [PMID: 32369709 DOI: 10.1513/annalsats.201910-776oc] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Rationale: High intake of dietary fiber may have antiinflammatory properties and be protective against respiratory morbidity.Objectives: We examined the relationship between dietary fiber intake and asthma, respiratory symptoms, and inflammation among adults who participated in the 2007 to 2012 NHANES (National Health and Nutrition Examination Survey).Methods: We analyzed data from adults 20 to 79 years of age (n = 13,147) with complete information on fiber intake, total calorie intake, body mass index, smoking status, and poverty level. Fiber intake was categorized into quartiles, with Q1 being lowest quartile of intake and Q4 being the highest quartile. Respiratory morbidities included asthma, wheeze, cough, and phlegm. Self-report questionnaires were used to define asthma, wheeze, cough, and phlegm production. Serum C-reactive protein (CRP) was used as a biomarker of inflammation. Exclusion criteria included current pregnancy and implausible intake of total calories.Results: A total of 69.5% of participants were non-Hispanic white; 54.5% were nonsmokers, and 7.8% had current asthma. After adjusting for covariates, fiber intake was associated with asthma (P = 0.01), with an increased odds of asthma with lower fiber intake (Q1 vs. Q4: odds ratio [OR], 1.4; 95% confidence interval [CI], 1.0-1.8; P = 0.027). There were significant interactions between fiber and sex and fiber and race/ethnicity; stronger associations were seen for women and for non-Hispanic white adults. Low fiber intake (Q1) was associated with increased odds of wheeze (OR, 1.3; 95% CI, 1.0-1.6; P = 0.018), cough (OR, 1.7; 95% CI, 1.2-2.3; P = 0.002), and phlegm (OR, 1.4; 95% CI, 1.1-2.0; P = 0.021) compared with high fiber intake. The odds of having high CRP versus nondetectable CRP were 1.6 times higher in the low-fiber group (Q1) compared with high-fiber group (Q4; OR, 1.6; 95% CI, 1.0-2.5).Conclusions: High-fiber diet may mediate an inflammatory response and decrease odds of having asthma, especially for women and specific racial groups, cough, wheeze, and phlegm production when compared with low-fiber diet.
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Rodríguez-Queraltó O, Guerrero C, Formiga F, Calvo E, Lorente V, Sánchez-Salado JC, Llaó I, Mateus G, Alegre O, Ariza-Solé A. Geriatric Assessment and In-Hospital Economic Cost of Elderly Patients With Acute Coronary Syndromes. Heart Lung Circ 2021; 30:1863-1869. [PMID: 34083151 DOI: 10.1016/j.hlc.2021.05.077] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 03/27/2021] [Accepted: 05/04/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Elderly patients with acute coronary syndromes (ACS) are at higher risk for complications and health care resources expenditure. No previous study has assessed the specific contribution of frailty and other geriatric syndromes to the in-hospital economic cost in this setting. METHOD Unselected patients with ACS aged ≥75 years were prospectively included. A comprehensive geriatric assessment was performed during hospitalisation. Hospitalisation-related cost per patient was calculated with an analytical accountability method, including hospital stay-related expenditures, interventions, and consumption of devices. Expenditure was expressed in Euros (2019). The contribution of geriatric syndromes and clinical factors to the economic cost was assessed with a linear regression method. RESULTS A total of 194 patients (mean age 82.6 years) were included. Mean length of hospital stay was 11.3 days. The admission-related economic cost was €6,892.15 per patient. Most of this cost was attributable to hospital length of stay (77%). The performance of an invasive strategy during the admission was associated with economic cost (p=0.008). Of all the ageing-related variables, comorbidity showed the most significant association with economic cost (p=0.009). Comorbidity, disability, nutritional risk, and frailty were associated with the hospital length of stay-related component of the economic cost. The final predictive model of economic cost included age, previous heart failure, systolic blood pressure, Killip class at admission, left main disease, and Charlson index. CONCLUSIONS Management of ACS in elderly patients is associated with a significant economic cost, mostly due to hospital length of stay. Comorbidity mostly contributes to in-hospital resources expenditure, as well as the severity of the coronary event.
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Affiliation(s)
| | - Carme Guerrero
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Francesc Formiga
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Elena Calvo
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Victòria Lorente
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | | | - Isaac Llaó
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Gemma Mateus
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Oriol Alegre
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Albert Ariza-Solé
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain.
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Ma J, Shen L, Bao L, Yuan H, Wang Y, Liu H, Wang Q. A novel prognosis prediction model, including cytotoxic T lymphocyte-associated antigen-4, ischemia-modified albumin, lipoprotein-associated phospholipase A2, glial fibrillary acidic protein, and homocysteine, for ischemic stroke in the Chinese hypertensive population. J Clin Lab Anal 2021; 35:e23756. [PMID: 33734490 PMCID: PMC8128308 DOI: 10.1002/jcla.23756] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Revised: 02/18/2021] [Accepted: 02/23/2021] [Indexed: 12/15/2022] Open
Abstract
Background There is still a lack of tools to assess the prognosis of ischemic stroke patients induced by hypertension. In this study, we built a novel prognostic assessment model for ischemic stroke in the Chinese hypertensive population. Methods Mass spectrometry technique was used to analyze the changes in serum protein profiles of hypertensive patients with ischemic stroke. A total of 314 hypertensive patients were divided into the testing group (206 patients) and the validation group (108 patients). Results Compared with hypertensive patients without ischemic stroke, serum cytotoxic T lymphocyte‐associated antigen‐4 (CTLA‐4), ischemia‐modified albumin (IMA), lipoprotein‐associated phospholipase A2 (Lp‐PLA2), glial fibrillary acidic protein (GFAP), and homocysteine (HCY) levels were significantly increased among hypertensive patients with ischemic stroke (p < 0.05). Then, we built a novel prognostic assessment model for hypertensive patients with ischemic stroke [Logit(P) = 29.172–1.088*CTLA‐4–0.952*IMA‐0.537*Lp‐PLA2 −0.066*GFAP −0.149*HCY]. It showed higher efficiency (AUC = 0.981, sensitivity = 95.5%, specificity = 93.8%) than any single marker. The estimated probability was 0.739, which means if higher than 0.739, it was classified into poor prognosis. Compared with the estimated probability ≤0.739 group, the survival rate of hypertensive patients with ischemic stroke in the estimated probability >0.739 group was significantly decreased (χ2 = 40.001, p < 0.001). In the validation group, our novel prognostic assessment model still showed good efficiency (AUC = 0.969, sensitivity = 89.4%, specificity = 92.5%; χ2 = 47.551, p < 0.001). Conclusion Current novel prognostic assessment model we have built is of great value in the prognostic evaluation for ischemic stroke in the Chinese hypertensive population.
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Affiliation(s)
- Jin Ma
- Department of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, P.R. China
| | - Likui Shen
- Department of Neurosurgery, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, P.R. China
| | - Lei Bao
- Department of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, P.R. China
| | - Hua Yuan
- Department of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, P.R. China
| | - Yingxin Wang
- Department of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, P.R. China
| | - Hua Liu
- Department of Neurosurgery, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, P.R. China
| | - Qiang Wang
- Department of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, P.R. China
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Hussain M, Iltaf S, Salman S, Ghuman F, Abbas S, Fatima M. Frequency of Comorbidities in Admitting COVID-19 Pneumonia Patients in a Tertiary Care Setup: An Observational Study. Cureus 2021; 13:e13546. [PMID: 33815969 PMCID: PMC8007124 DOI: 10.7759/cureus.13546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Background The novel coronavirus disease 2019 (COVID-19) is a highly infectious and pandemic disease with a variable mode of action. Patients with underlying illnesses such as diabetes, hypertension, and other diseases are more prone to infection. An understanding of the different comorbidities that place patients at the highest risk of COVID-19 pneumonia and other fatal complications associated with COVID-19 is necessary for healthcare professionals. This study aimed to determine the frequency of different comorbid illnesses among COVID-19 patients admitted to a tertiary care hospital in Karachi, Pakistan. Methodology All patients diagnosed with COVID-19 who required admission for the care of their symptoms were included in this observational, cross-sectional study conducted from May 1 to July 30, 2020. The patients were treated at a specialized COVID-19 isolation ward built at the Dow University of Health Sciences at the Ojha campus. The patients were referred from the emergency department, medical and allied wards, and COVID-19 screening units. A detailed history and clinical examination were performed, and comorbidities were evaluated. Results A total of 212 patients were admitted during the study with a mean age of 52 ± 16 years. The study population consisted of 120 (56.6%) males and 92 (43.39%) females, and the most common comorbidities were uncontrolled diabetes with hypertension (n = 56; 26.4%), controlled diabetes (n = 22; 10.37%), obstructive airway disease (n = 16; 7.5%), and interstitial lung disease (n = 14; 6.6%). A total of 48 (22.64%) patients had no comorbidities. Conclusions Most COVID-19-positive patients with pneumonia were male, and common comorbidities included uncontrolled diabetes, hypertension, and obstructive and restrictive lung disease. The presence of comorbidities was associated with a marked increase in the risk of morbidity and mortality. Further studies are warranted to confirm these findings.
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Affiliation(s)
- Muneer Hussain
- Medicine, Dow University of Health Sciences, Karachi, PAK
| | - Samar Iltaf
- Neurology, Dow University of Health Sciences, Karachi, PAK
| | - Salma Salman
- Medicine, Dow University of Health Sciences, Karachi, PAK
| | - Faiza Ghuman
- Medicine, Dow University of Health Sciences, Karachi, PAK
| | - Saira Abbas
- Neurology, Dow University of Health Sciences, Karachi, PAK
| | - Meraj Fatima
- Neurology, Dow University of Health Sciences, Karachi, PAK
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Zhou X, Cheng Z, Shu D, Lin W, Ming Z, Chen W, Hu Y. Characteristics of mortal COVID-19 cases compared to the survivors. Aging (Albany NY) 2020; 12:24579-24595. [PMID: 33234724 PMCID: PMC7803528 DOI: 10.18632/aging.202216] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 10/01/2020] [Indexed: 12/17/2022]
Abstract
The outbreak of coronavirus disease 2019 (COVID-19) initially occurred in December 2019 and triggered a public health emergency. The increasing number of deaths due to this disease was of great concern. Therefore, our study aimed to explore risk factors associated with COVID-19 deaths. After having searched the PubMed, EMBASE, and CNKI for studies published as of August 10, 2020, we selected articles and extracted data. The meta-analysis was performed using Stata 16.0 software. Nineteen studies were used in our meta-analysis. The proportions of comorbidities such as diabetes, hypertension, malignancies, chronic obstructive pulmonary disease, cardio-cerebrovascular disease, and chronic liver disease were statistically significantly higher in mortal COVID-19 cases. Coagulation and inflammatory markers, such as platelet count, D-dimer, prothrombin time, C-reactive protein, procalcitonin, and interleukin 6, predicted the deterioration of the disease. In addition, extracorporeal membrane oxygenation and mechanical ventilation predicted the poor prognosis during its progression. The COVID-19 pandemic is still evolving, placing a huge burden on healthcare facilities. Certain coagulation indicators, inflammatory indicators, and comorbidities contribute to the prognosis of patients. Our study results may help clinicians optimize the treatment and ultimately reduce the mortality rate.
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Affiliation(s)
- Xianghui Zhou
- Department of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.,Collaborative Innovation Center of Hematology, Huazhong University of Science and Technology, Wuhan 430022, Hubei, China
| | - Zhipeng Cheng
- Department of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.,Collaborative Innovation Center of Hematology, Huazhong University of Science and Technology, Wuhan 430022, Hubei, China
| | - Dan Shu
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430022, China
| | - Wenyi Lin
- Department of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.,Collaborative Innovation Center of Hematology, Huazhong University of Science and Technology, Wuhan 430022, Hubei, China
| | - Zhangyin Ming
- Department of Pharmacology, School of Basic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430022, China.,Tongji-Rongcheng Center for Biomedicine, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Wei Chen
- Laboratory of Vaccine and Antibody Engineering, Beijing Institute of Biotechnology, Beijing 100071, China
| | - Yu Hu
- Department of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.,Collaborative Innovation Center of Hematology, Huazhong University of Science and Technology, Wuhan 430022, Hubei, China.,Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan 430022, Hubei, China
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11
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Bashir S, Moneeba S, Alghamdi A, Alghamdi F, Niaz A, Anan H, Kaleem I. Comorbidities in Patients with COVID-19 and Their Impact on the Severity of the Disease. JOURNAL OF HEALTH AND ALLIED SCIENCES NU 2020. [DOI: 10.1055/s-0040-1718848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
AbstractInfection with COVID-19 is associated with significant morbidity, especially in patients with chronic medical conditions. At least one-fifth of cases require supportive care in intensive care units, which have limited availability in most developing countries. A literature search was conducted on PubMed, Medline, Scopus, Embase, and Google Scholar to find articles published by May 7, 2020 on the role of comorbidities in patients with COVID-19 and the impact of comorbidities on the disease. This review highlighted that patients with comorbidities are more likely to experience severe disease than those with no other conditions; that is, comorbidities correlated with greater disease severity in patients with COVID-19. Proper screening of COVID-19 patients should include careful inquiries into their medical history; this will help healthcare providers identify patients who are more likely to develop serious disease or experience adverse outcomes. Better protection should also be given to patients with COVID-19 and comorbidities upon confirmation of the diagnosis. This literature review showed that the comorbidities most often associated with more severe cases of COVID-19 are hypertension, cardiovascular disease, and diabetes. Individuals with these comorbidities should adopt restrictive measures to prevent exposure to COVID-19, given their higher risk of severe disease.
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Affiliation(s)
- Shahid Bashir
- Neuroscience Center, King Fahad Specialist Hospital Dammam, Dammam, Saudi Arabia
| | - Sadaf Moneeba
- Department of Bioinformatics and Biotechnology, International Islamic University Islamabad, Islamabad, Pakistan
| | - Alaa Alghamdi
- King Fahad University Hospital, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Fouad Alghamdi
- Neuroscience Center, King Fahad Specialist Hospital Dammam, Dammam, Saudi Arabia
| | - Asim Niaz
- Neuroscience Center, King Fahad Specialist Hospital Dammam, Dammam, Saudi Arabia
| | - Hadeel Anan
- Neuroscience Center, King Fahad Specialist Hospital Dammam, Dammam, Saudi Arabia
| | - Imdad Kaleem
- Department of Bioinformatics and Biosciences, COMSATS University (CUI), Islamabad, Pakistan
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12
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Shah CH, Reed RM, Villalonga-Olives E, Slejko JF, Eakin MN, So JY, Zafari Z. Quantifying heterogeneity of physical and mental health-related quality of life in chronic obstructive pulmonary disease patients in the United States. Expert Rev Respir Med 2020; 14:937-947. [PMID: 32500756 DOI: 10.1080/17476348.2020.1776612] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a heterogenous condition. This study aims to quantify the heterogeneity of Health-related Quality of Life (HRQoL), and identify subgroups with the lowest HRQoL, in COPD patients in the United States (US). Methods Data from 2008-2015 Medical Expenditure Panel Survey were used to examine the heterogeneity of HRQoL between different COPD subgroups using mixed-effects modeling and G-computation. The Physical Composite Summary (PCS) and Mental Composite Summary (MCS) scores from the Short-Form-12 questionnaire were utilized. We also compared the heterogeneity of HRQoL in our COPD cohort against that in a matched non-COPD cohort. Results The final sample consisted of 1,866 (weighted = 19,952,143) COPD patients with a mean age of 63.2 years (Standard error (SE):0.38), mean MCS score of 46.84 (SE:0.35), and mean PCS score of 35.65 (SE:0.32). The adjusted MCS and PCS scores ranged from 36.19 to 53.06, and from 25.52 to 48.27, respectively, for COPD subgroups. COPD patients had statistically significantly lower MCS and PCS scores by 4.61, and 5.86 points, respectively, compared to the matched non-COPD cohort, and MCS scores showed a wider variability in the COPD cohort. Conclusion Our study quantifies substantial heterogeneity of HRQoL in COPD in the US and provides evidence for prioritizing COPD subgroups with the lowest HRQoL for targeted interventions.
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Affiliation(s)
- Chintal H Shah
- Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy , Baltimore, MD, USA
| | - Robert M Reed
- Division of Pulmonary and Critical Care Medicine, University of Maryland School of Medicine , Baltimore, MD, USA
| | - Ester Villalonga-Olives
- Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy , Baltimore, MD, USA
| | - Julia F Slejko
- Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy , Baltimore, MD, USA
| | - Michelle N Eakin
- Division of Pulmonary Medicine and Critical Care, Johns Hopkins University , Baltimore, MD, USA
| | - Jennifer Y So
- Division of Pulmonary and Critical Care Medicine, University of Maryland School of Medicine , Baltimore, MD, USA
| | - Zafar Zafari
- Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy , Baltimore, MD, USA
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13
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Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, Liu XQ, Chen RC, Tang CL, Wang T, Ou CQ, Li L, Chen PY, Sang L, Wang W, Li JF, Li CC, Ou LM, Cheng B, Xiong S, Ni ZY, Xiang J, Hu Y, Liu L, Shan H, Lei CL, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Cheng LL, Ye F, Li SY, Zheng JP, Zhang NF, Zhong NS, He JX. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020; 55:13993003.00547-2020. [PMID: 32217650 PMCID: PMC7098485 DOI: 10.1183/13993003.00547-2020] [Citation(s) in RCA: 2096] [Impact Index Per Article: 524.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 03/13/2020] [Indexed: 02/07/2023]
Abstract
Background The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status. Methods We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities. Results The mean age was 48.9 years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424–5.048)), diabetes (1.59 (1.03–2.45)), hypertension (1.58 (1.07–2.32)) and malignancy (3.50 (1.60–7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16–2.77) among patients with at least one comorbidity and 2.59 (1.61–4.17) among patients with two or more comorbidities. Conclusion Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes. The presence and number of comorbidities predict clinical outcomes of COVID-19http://bit.ly/3b9ibw5
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Affiliation(s)
- Wei-Jie Guan
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Wen-Hua Liang
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Yi Zhao
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Heng-Rui Liang
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Zi-Sheng Chen
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,The sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan, China.,These authors are joint first authors
| | - Yi-Min Li
- Dept of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiao-Qing Liu
- Dept of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ru-Chong Chen
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Chun-Li Tang
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Tao Wang
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Dept of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Dept of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ping-Yan Chen
- State Key Laboratory of Organ Failure Research, Dept of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ling Sang
- Dept of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wei Wang
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jian-Fu Li
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Cai-Chen Li
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Li-Min Ou
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Bo Cheng
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shan Xiong
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | | | - Jie Xiang
- Wuhan Jin-yintan Hospital, Wuhan, China
| | - Yu Hu
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Liu
- Shenzhen Third People's Hospital, Shenzhen, China.,The Second Affiliated Hospital of Southern University of Science and Technology, National Clinical Research Center for Infectious Diseases, Shenzhen, China
| | - Hong Shan
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Chun-Liang Lei
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | | | - Li Wei
- Wuhan No. 1 Hospital, Wuhan Hospital of Traditional Chinese and Western Medicine, Wuhan, China
| | - Yong Liu
- Chengdu Public Health Clinical Medical Center, Chengdu, China
| | - Ya-Hua Hu
- Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, Huangshi, China
| | - Peng Peng
- Wuhan Pulmonary Hospital, Wuhan, China
| | - Jian-Ming Wang
- Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Ji-Yang Liu
- The First Hospital of Changsha, Changsha, China
| | - Zhong Chen
- The Third People's Hospital of Hainan Province, Sanya, China
| | - Gang Li
- Huanggang Central Hospital, Huanggang, China
| | | | - Shao-Qin Qiu
- The Third People's Hospital of Yichang, Yichang, China
| | - Jie Luo
- Affiliated Taihe Hospital of Hubei University of Medicine, Shiyan, China
| | | | - Shao-Yong Zhu
- The People's Hospital of Huangpi District, Wuhan, China
| | - Lin-Ling Cheng
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Feng Ye
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Shi-Yue Li
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Jin-Ping Zheng
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Nuo-Fu Zhang
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Nan-Shan Zhong
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Jian-Xing He
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
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14
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Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, Liu XQ, Chen RC, Tang CL, Wang T, Ou CQ, Li L, Chen PY, Sang L, Wang W, Li JF, Li CC, Ou LM, Cheng B, Xiong S, Ni ZY, Xiang J, Hu Y, Liu L, Shan H, Lei CL, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Cheng LL, Ye F, Li SY, Zheng JP, Zhang NF, Zhong NS, He JX. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020. [PMID: 32217650 DOI: 10.1183/13993003.00547‐2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. OBJECTIVE To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status. METHODS We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities. RESULTS The mean age was 48.9 years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424-5.048)), diabetes (1.59 (1.03-2.45)), hypertension (1.58 (1.07-2.32)) and malignancy (3.50 (1.60-7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16-2.77) among patients with at least one comorbidity and 2.59 (1.61-4.17) among patients with two or more comorbidities. CONCLUSION Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.
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Affiliation(s)
- Wei-Jie Guan
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Wen-Hua Liang
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Yi Zhao
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Heng-Rui Liang
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,These authors are joint first authors
| | - Zi-Sheng Chen
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,The sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan, China.,These authors are joint first authors
| | - Yi-Min Li
- Dept of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiao-Qing Liu
- Dept of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ru-Chong Chen
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Chun-Li Tang
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Tao Wang
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Dept of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Dept of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ping-Yan Chen
- State Key Laboratory of Organ Failure Research, Dept of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ling Sang
- Dept of Pulmonary and Critical Care Medicine, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wei Wang
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jian-Fu Li
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Cai-Chen Li
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Li-Min Ou
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Bo Cheng
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shan Xiong
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | | | - Jie Xiang
- Wuhan Jin-yintan Hospital, Wuhan, China
| | - Yu Hu
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Liu
- Shenzhen Third People's Hospital, Shenzhen, China.,The Second Affiliated Hospital of Southern University of Science and Technology, National Clinical Research Center for Infectious Diseases, Shenzhen, China
| | - Hong Shan
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Chun-Liang Lei
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | | | - Li Wei
- Wuhan No. 1 Hospital, Wuhan Hospital of Traditional Chinese and Western Medicine, Wuhan, China
| | - Yong Liu
- Chengdu Public Health Clinical Medical Center, Chengdu, China
| | - Ya-Hua Hu
- Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, Huangshi, China
| | - Peng Peng
- Wuhan Pulmonary Hospital, Wuhan, China
| | - Jian-Ming Wang
- Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Ji-Yang Liu
- The First Hospital of Changsha, Changsha, China
| | - Zhong Chen
- The Third People's Hospital of Hainan Province, Sanya, China
| | - Gang Li
- Huanggang Central Hospital, Huanggang, China
| | | | - Shao-Qin Qiu
- The Third People's Hospital of Yichang, Yichang, China
| | - Jie Luo
- Affiliated Taihe Hospital of Hubei University of Medicine, Shiyan, China
| | | | - Shao-Yong Zhu
- The People's Hospital of Huangpi District, Wuhan, China
| | - Lin-Ling Cheng
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Feng Ye
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Shi-Yue Li
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Jin-Ping Zheng
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Nuo-Fu Zhang
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Nan-Shan Zhong
- State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Jian-Xing He
- Dept of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
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15
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Murphy TE, McAvay GJ, Agogo GO, Allore HG. Personalized and typical concurrent risk of limitations in social activity and mobility in older persons with multiple chronic conditions and polypharmacy. Ann Epidemiol 2019; 37:24-30. [PMID: 31473124 DOI: 10.1016/j.annepidem.2019.08.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 07/17/2019] [Accepted: 08/05/2019] [Indexed: 12/13/2022]
Abstract
PURPOSE We define personalized concurrent risk (PCR) as the subject-specific probability of an index outcome within a defined interval of time, while currently at risk for a separate outcome, where the outcomes are not mutually exclusive and can be jointly modeled with a shared random intercept. We further define typical concurrent risk as the risk obtained by setting the random intercept to null. METHODS Drawing data from the Medical Expenditure Panel Survey (cohorts 2008-2013), we jointly model limitations in social activity and mobility over two years among older community-dwelling persons with both hypertension and chronic obstructive pulmonary disease. The joint model uses inverse probability of treatment weighting based on each participant's baseline propensity of polypharmacy (≥5 classes of medication). RESULTS Even among participants with the same covariates, older persons with multiple chronic conditions exhibit wide-ranging heterogeneity of the treatment effect from polypharmacy, a risk factor for negative health outcomes among older persons. The magnitude of the PCRs is dominated by the value of the subject-specific random effect. CONCLUSIONS Estimates of PCR and typical concurrent risk can be calculated from national or institutional data sets and may facilitate the practice of personalized care for older patients with multiple chronic conditions.
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Affiliation(s)
- Terrence E Murphy
- Department of Internal Medicine, Section of Geriatrics, Yale School of Medicine, New Haven, CT; Department of Biostatistics, Yale School of Public Health, New Haven, CT
| | - Gail J McAvay
- Department of Internal Medicine, Section of Geriatrics, Yale School of Medicine, New Haven, CT
| | - George O Agogo
- Department of Internal Medicine, Section of Geriatrics, Yale School of Medicine, New Haven, CT
| | - Heather G Allore
- Department of Internal Medicine, Section of Geriatrics, Yale School of Medicine, New Haven, CT; Department of Biostatistics, Yale School of Public Health, New Haven, CT.
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Who Is at Risk? The Role of Airway Imaging in Chronic Lung Disease Risk Assessment. Ann Am Thorac Soc 2018; 15:669-670. [DOI: 10.1513/annalsats.201804-244ed] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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