Association of COVID-19 with risks of all-cause and cause-specific mortality post-infection: A UK Biobank cohort study

Association of COVID-19 with risks of all-cause and cause-specific mortality post-infection: A UK Biobank cohort study | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Association of COVID-19 with risks of all-cause and cause-specific mortality post-infection: A UK Biobank cohort study View ORCID Profile Ruoyu Zhang , View ORCID Profile Yong Xiang , Jinghong Qiu , View ORCID Profile Hon-Cheong So doi: https://doi.org/10.1101/2025.08.01.25332496 Ruoyu Zhang 1 School of Biomedical Sciences, The Chinese University of Hong Kong , Shatin, Hong Kong Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ruoyu Zhang Yong Xiang 1 School of Biomedical Sciences, The Chinese University of Hong Kong , Shatin, Hong Kong Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yong Xiang Jinghong Qiu 1 School of Biomedical Sciences, The Chinese University of Hong Kong , Shatin, Hong Kong Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hon-Cheong So 1 School of Biomedical Sciences, The Chinese University of Hong Kong , Shatin, Hong Kong 2 KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Institute of Zoology and The Chinese University of Hong Kong , China 3 CUHK Shenzhen Research Institute , Shenzhen, China 4 Department of Psychiatry, The Chinese University of Hong Kong , Shatin, Hong Kong 5 Margaret K.L. Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong , Shatin, Hong Kong 6 Brain and Mind Institute, The Chinese University of Hong Kong , Shatin, Hong Kong 7 Hong Kong Branch of the Chinese Academy of Sciences Center for Excellence in Animal Evolution and Genetics, The Chinese University of Hong Kong , Hong Kong SAR, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hon-Cheong So For correspondence: hcso{at}cuhk.edu.hk Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Background SARS-CoV-2 infection can lead to fatal multi-organ complications extending beyond the acute phase. However, a comprehensive assessment of relatively long-term mortality risks across various organ systems following COVID-19 is lacking. This study aimed to evaluate the impact of COVID-19 on all-cause and cause-specific mortality across a broad range of body systems and disease categories. Methods This prospective cohort study followed UK biobank (UKBB) participants (N=467,522; age: 50-87) from 31 Jan 2020 to 19 Dec 2022. COVID-19 exposure was classified as overall, hospitalized and non-hospitalized infections, with median follow-up durations of 274, 305 and 268 days, respectively. Prespecified outcomes included mortality from 12 organ systems and 47 individual diseases, categorized using the Clinical Classifications Software Refined (CCSR) system. Adjusted Cox models were used to assess mortality risks. Sensitivity analyses were conducted based on COVID-19 severity. Stratification by comorbidity and demographic variables were further performed. Results All-cause mortality was significantly elevated across all COVID-19 exposure groups: overall (HR: 2.39, 95% CI: 2.29-2.50), hospitalized (HR: 6.29, 95% CI: 5.99-6.61), and non-hospitalized (HR: 1.23, 95% CI: 1.15-1.32). For cause-specific mortality, COVID-19 infection was associated with increased risks from circulatory (HR: 1.45, 95% CI: 1.26-1.66; subsequent values are presented in the same format), digestive (1.98, 1.45-2.70), genitourinary (2.54, 1.58-4.09), neurological (2.20, 1.85-2.62) and respiratory (1.39, 1.12-1.72) diseases, as well as external causes (3.42, 1.89-6.21) and neoplasms (1.53, 1.41-1.67). Hospitalized COVID-19 cases notably exhibited a greater proportion of outcomes with significantly elevated risks (11 out of 12 organ systems; 36 out of 42 individual diseases). Increased risks for external causes and neurological outcomes were also observed in non-hospitalized cases. Subgroup analyses revealed that advanced age, chronic kidney disease (CKD) and hypertension (HTN) exacerbated the risk of all-cause mortality following COVID-19, whereas atrial fibrillation (AF) was specifically associated with amplified respiratory and neurological mortality risks. Conclusion This study demonstrates elevated risks of all-cause and cause-specific post-COVID mortality across multiple organ systems, with hospitalized cases exhibiting increased mortality risks across a broader spectrum of outcomes. These findings highlight the need for comprehensive strategies to mitigate COVID-19 severity and manage post-infection complications, particularly in survivors with older age and pre-existing high-risk comorbidities. Introduction The COVID-19 pandemic, caused by coronavirus SARS-CoV-2 infection, has posed an unprecedented challenge to global health since December 2019. As of 5 Jan 2025, the World Health Organization (WHO) reported more than 777 million confirmed cases and over 7 million deaths worldwide attributed to COVID-19[ 1 ]. Emerging evidence indicates that SARS-CoV-2 infection can trigger complications in respiratory[ 2 ], cardiovascular[ 3 ], neurological[ 4 ], renal[ 5 ], gastrointestinal[ 6 ] and other systems[ 7 , 8 ], leading to diverse multi-system disorders. While the increased morbidity and mortality during the acute phase of COVID-19 are well-characterized[ 9 ], with recent data suggesting that acute mortality may still cause a huge health burden in early 2025[ 10 ], the post-acute risks across various organs remain incompletely understood. Evaluating the long-term impacts of COVID-19 sequelae is thus essential for guiding patient care strategies and optimizing healthcare resources allocation. Current research has mainly focused on the prevalence of persistent symptoms and hospitalizations due to post-COVID-19 disorders. It was reported that COVID-19, especially severe case requiring hospitalization, confers a greater risk of downstream symptoms and hospitalizations compared to COVID-19-negative individuals or those with non-hospitalized infections[ 11 – 14 ]. In parallel, population-level analyses have documented substantial excess mortality during the pandemic that exceeds the expected incidence based on historical trends[ 15 – 20 ]. However, by relying on aggregated data, these excess-death estimates cannot fully adjust for individual-level confounders nor accurately attribute deaths from non-COVID conditions to SARS-CoV-2 infection. Although two studies led by Al-Aly[ 11 , 12 ] employed survival models to quantify mortality risks in COVID-19 patients, their work primarily focused on overall mortality rather than specific causes of death. While some studies have explored post-COVID-19 mortality risks for neurological[ 21 ], respiratory, and cardiovascular outcomes[ 22 ], the associations between COVID-19 infection and mortality rates spanning a broader spectrum of sequelae remain unclear. Therefore, a systematic and comprehensive analysis of the impact of COVID-19 on all-cause and cause-specific mortality across all body systems is urgently needed. To address this knowledge gap, we conducted a longitudinal analysis using data from the UK Biobank (UKBB) by following a large prospective cohort from 31 Jan 2020 to 19 Dec 2022. We leveraged the CCSR to facilitate an inclusive and clinically relevant grouping of all ICD-10 diagnoses, thereby avoiding arbitrary exclusion or preferential selection of specific disease categories. This allowed us to systemically classify causes of post-COVID-19 deaths into 12 composite organ systems and 47 individual disease outcomes. We then estimated the associations between COVID-19 (considering overall, hospitalized and non-hospitalized infection status) and mortality due to these post-infection disorders. For each single outcome, deaths were further stratified by the presence or absence of a prior history of the same condition. Additionally, we performed subgroup analyses stratified by various characteristics to explore potential differences in the mortality risks of certain COVID-19 sequelae across these subgroups. To our knowledge, this study is the first to comprehensively examine post-COVID-19 mortality across a wide range of diseases spanning all organ systems, and to assess mortality stratified by patients’ clinical characteristics. Methods Study design and setting This prospective cohort study was conducted using data from the UKBB (project #28732), which continuously tracks the electronic health records of approximately 500,000 UK participants aged 50-87 years[ 23 ]. To evaluate the hazard ratios (HRs) for all-cause and cause-specific post-COVID-19 deaths, the follow-up for the UKBB sample spanned from 31 Jan 2020 (the date of the first confirmed COVID-19 case in the UK) to 19 Dec 2022 (the last date for available mortality records during analysis). Totally 467,522 individuals with available linked health records and alive at the start of the follow-up period (31 Jan 2020) were included for subsequent analysis. Data Sources Participants’ baseline demographic characteristics and clinical information were accessed from UKBB. As the primary study outcome, mortality records linked to UKBB participants were obtained from national death registries. This mortality data incorporates the corresponding date and causes of death. Primary causes of death were considered as outcomes to prevent confounding from secondary conditions that might obscure the true COVID-19-mortality relationship. Pre-existing (ICD-10 coded) comorbidities, were extracted from multiple sources within the UKBB, including baseline assessments, follow-up questionnaires, Hospital Episode Statistics (HES) data, and General Practitioner (GP) records. Exposure to SARS-CoV-2 infection was defined using COVID-19 testing data from the UKBB portal: specifically, any positive PCR test result or any hospital inpatient record associated with diagnosis code U07.1 during the study follow-up period. Any COVID-19 tests, clinical events or deaths occurring after the study end date were excluded from the analysis. Cohort The COVID-19 exposure cohort comprised individuals with a single, confirmed episode of SARS-CoV-2 infection. Participants with reinfection were censored at the second infection date. Based on the severity of initial COVID-19 infection, the exposure cohort was further divided into hospitalized (severe) and non-hospitalized (mild) case groups. Follow-up for all individuals in this cohort commenced on the date of the first positive SARS-CoV-2 test (index date, T 0 ) and continued until death, the first SARS-CoV-2 reinfection, or 19 Dec 2022, whichever occurred first. Deaths from causes other than the primary outcome of interest were censored in the survival analysis. The reference cohort, serving as the uninfected control group, consisted of subjects with no documented history of SARS-CoV-2 infection. To mitigate potential survival bias from imbalanced follow-up length and ensure comparability with the exposure cohort, each control participant was assigned a pseudo-index date ( T’ 0 ) drawn randomly from the T 0 distribution observed in the COVID-19 exposure cohort[ 24 ]. Reference individuals were then followed from their assigned T’ 0 until death or the study end date. Outcomes Given that other contributory causes of death in UKBB mortality records might reflect complex comorbidities not directly attributable to COVID-19 exposure, our analysis focused solely on the primary cause of death. These ICD-10 primary cause codes were subsequently categorized into clinically relevant groups based on the Healthcare Cost and Utilization Project (HCUP) Clinical Classifications Software Refined (CCSR) for ICD-10-CM, version 2022.1[ 25 ]. The primary study outcomes were: (1) all-cause mortality and (2) cause-specific mortality, grouped by HCUP CCSR body system categories. For each body system, mortality was defined by the presence of at least one contributing sequela within that system. Secondary outcomes included mortality due to individual CCSR-defined disease categories. To ensure adequate statistical power, analyses were restricted to outcomes with ≥ 5 death events in both the COVID-19 exposure and reference cohorts. This filtering step yielded 12 composite (organ system) outcomes and 47 single (CCSR-defined disease) categories for inclusion in the analysis (Table_S1). In addition, each single CCSR outcome was stratified by pre-existing diagnosis of the same condition, based on records before T 0 , creating subgroups of deaths with and without a relevant prior history. Covariates To adjust for baseline differences between the COVID-19 exposure and reference cohorts, a comprehensive set of covariates that may confound the associations between SARS-CoV-2 infection and post-infection outcomes were selected for statistical analysis[ 13 ]. These comprised: sociodemographic characteristics (age, sex, ethnicity and the Townsend Deprivation Index, with higher values indicating greater area-level material deprivation); lifestyle and anthropometric measures (smoking status, Body Mass Index [BMI] and waist circumference); biochemical markers (lipid and glucose levels, haemoglobin A1c [HbA1c]); immunological factors (autoimmune diseases, immunodeficiency, prior immunosuppressant use); pre-existing medical conditions across various systems, including cardiovascular (atrial fibrillation [AF], coronary artery disease [CAD], hypertension [HTN] and stroke), respiratory (chronic obstructive pulmonary disease [COPD] and pneumonia), renal (chronic kidney disease [CKD]), metabolic (type 2 diabetes mellitus [T2DM]), neurological (dementia) and oncologic (cancer); COVID-19 vaccination status; and indicators of overall health status in the prior year (number of non-cancer illnesses, GP-prescribed medications, and hospital admissions). Missing covariate values were imputed using the random forest-based missRanger package in R[ 26 ]. Statistical Analyses Proportional hazards Cox regression was recruited to model the time to develop the death event of interest. Descriptive statistics are presented for both the COVID-19 exposure and reference cohorts. Continuous variables are reported as mean (standard deviation), and categorical variables as frequencies (percentages). To mitigate potential convergence issues due to the large number of covariates, we employed a variable selection procedure based on the method proposed by Zhao et al.[ 27 ]: After including key standard variables (age, sex, number of hospitalizations and medications within the past year), univariate testing was performed on the remaining covariates. Predictors demonstrating a nominally significant association with the outcome (p < 0.05) were then incorporated into the final multivariable Cox regression model. All statistical analyses were performed using R (version 3.6.1). The false discovery rate (FDR)[ 28 ] was used to control for multiple testing, where FDR-adjusted p-values < 0.05 were considered statistically significant. The overall analytic workflow is illustrated in Fig. 1 . Download figure Open in new tab Fig. 1. An Overview of Analytic Workflow Cohort establishment: UKBB participants were classified into overall COVID-19 exposure and reference cohorts. This overall exposure cohort was further divided into hospitalized and non-hospitalized exposure cohorts. Outcome definition: The primary (composite) outcomes were: (1) all-cause mortality and (2) cause-specific mortality grouped by 12 organ systems; Secondary (single) outcome included cause-specific mortality grouped by 47 individual CCSR disorders, which were further stratified by the presence or absence of a prior history of the same condition. Statistical analysis: In our primary analysis, adjusted Cox regression models were employed to assess mortality risks of overall COVID-19 exposure compared to the reference. Additional analyses included (1) stratification of the exposure cohort into hospitalized and non-hospitalized cohorts; (2) stratification of single CCSR outcomes by prior history of the same condition; and (3) subgroup comparisons based on the presence or absence of specific risk factors. For further details, please refer to the Method sections in the main text. Risks of death due to composite outcomes within each body system HRs for all-cause mortality and death due to at least one sequela in each body system were calculated for the COVID-19 exposure cohort, compared with non-infected controls. The overall exposure cohort was then divided into two mutually exclusive groups: hospitalized and non-hospitalized COVID-19, to analyze mortality risks associated with each post-infection outcome, respectively. Risks of death due to single diseases To estimate HRs for cause-specific mortality due to each individual CCSR disease outcome, analyses were repeated by comparing the overall, hospitalized, and non-hospitalized COVID-19 cohorts to the reference cohort. Within these COVID-19 cohorts, we also performed stratified analysis to examine each death outcome in patients with and without a prior history of the corresponding CCSR sequela, as described previously in the Outcomes section. Subgroup analysis To assess the heterogeneity of the association between overall COVID-19 infection and mortality (for both composite and single outcomes) across different subgroups, stratified analyses were conducted. We compared individuals with (risk factor present group) and without (risk factor absent group) each of the following demographic or comorbidity characteristics: age (advanced age [> 65] vs. middle age [ 50 –65]), sex (male vs. female), history of AF, CAD, CKD, COPD, dementia, heart failure, HTN, renal failure, stroke, and T2DM. For each characteristic, we calculated the difference in beta coefficients between the risk factor present and absent subgroups ( β diff = β present - β absent ), with a standard error estimated as . We then used z-statistic ( z = β diff / SE diff ) to assess the significance of these differences between subgroups. Analyses were not performed if the subgrouping factor itself was also a component of the primary/secondary outcome of interest. Ethics statement The UK Biobank study has received ethical approval from the NHS National Research Ethics Service North West (16/NW/0274). Individual consents were obtained by the UK Biobank. The current study was conducted under the project number 28732. Only de-identified data was accessed, and no attempts were made to identify any individual participants in this study. Results The COVID-19 exposure cohort included 113,057 participants (61,971 [54.8%] females and 51,086 [45.2%] males), with a median follow-up of 274 days (maximum 969 days). This cohort was further divided into 16,628 individuals in the hospitalized COVID-19 group (8,207 [49.4%] females and 8,421 [50.6%] males; median follow-up 305 days; maximum 969 days) and 96,429 in the non-hospitalized group (53,764 [55.8%] females and 42,665 [44.2%] males; median follow-up 268 days; maximum 921 days). The reference cohort included 354,465 participants without known COVID-19 infection (197,147 [55.6%] females and 157,318 [44.4%] males), with a median follow-up of 365 days (maximum 998 days). Detailed demographic and clinical characteristics for each cohort are presented in Table_1 . View this table: View inline View popup Table 1. Characteristics of the UKBB participants in the COVID-19 Exposure and Reference Cohort. As summarized in Table_2 , total deaths amounted to 3,334 (2.95%) in the overall COVID-19 exposure cohort, 2,750 (16.54%) in the hospitalized COVID-19 group, 584 (0.61%) in the non-hospitalized group and 5,662 (1.60%) in the reference cohort. Notably, neoplasms, circulatory, neurological, and respiratory disorders were consistently identified as the most prevalent causes of death across all cohorts. View this table: View inline View popup Download powerpoint Table 2. Total Number (Percentage) of Death Causes Stratified by Composite Outcomes in the COVID-19 Exposure and Reference Cohort. Mortality risks of composite outcomes within each body system Risks of all-cause and cause-specific mortality stratified by organ system are presented in Fig. 2 and Table_3 . Compared to the reference group without known infection, all-cause mortality was significantly elevated (FDR-adjusted p < 0.05) in the overall COVID-19 (HR: 2.39, 95% confidence interval (CI): 2.29-2.50), hospitalized COVID-19 (HR: 6.29, 95% CI: 5.99-6.61), and non-hospitalized COVID-19 (HR: 1.23, 95% CI: 1.15-1.32) groups ( Fig. 2a ). View this table: View inline View popup Table 3. Associations Between All-Cause and Cause-Specific Mortality Risks in Different Organ Systems and Overall/Hospitalized/Non-hospitalized COVID-19 Using Cox Regression Model. Download figure Open in new tab Fig. 2. Associations Between All-Cause (2a) and Cause-Specific Mortality Risks in Different Organ Systems (2b) and Overall/Hospitalized/Non-hospitalized COVID-19, Using Cox Regression Model. The vertical red dashed line represents the line of no effect (hazard ratio (HR) = 1). X-axis indicates the HR of mortality post COVID-19. Y-axis indicates each COVID-19 disease severity. Confidence intervals are also shown in the figure. Solid bars indicate significance, and transparent bars indicate non-significant associations. We only present the results if the number of events ≥ 5 for both COVID-19 exposure and reference cohort. For organ system outcomes, all significant associations identified between COVID-19 infection (overall, hospitalized, and non-hospitalized) and death demonstrated increased risks (HR > 1) of cause-specific mortality ( Fig. 2b ). Notably, the hospitalized COVID-19 group exhibited significantly increased mortality risks in the highest proportion of organ systems (11 out of 11 examined). Within the overall COVID-19 exposure cohort, significantly elevated mortality risk was identified in 8 out of 12 (66.7%) organ systems, including: diseases of the blood/blood forming organs (HR: 7.85, 95% CI: 1.80-34.33; subsequent values are presented in the same format), circulatory system (1.45, 1.26-1.66), digestive system (1.98, 1.45-2.70), external causes (3.42, 1.89-6.21), genitourinary system (2.54, 1.58-4.09), neoplasms (1.53, 1.41-1.67), nervous system (2.20, 1.85-2.62) and respiratory system (1.39, 1.12-1.72); While for the non-hospitalized cohort, 2 out of 8 (25%) body systems were found significant, with increased risks of death from external causes (HR: 2.72, 95% CI: 1.35-5.49) and nervous system (1.47, 1.18-1.82). Mortality risks of single CCSR outcomes in the overall COVID-19 cohort Fig. 3 and Table_4a summarize the associations between COVID-19 infection and single CCSR outcomes. Among 47 disorders investigated, COVID-19 infection significantly increased mortality risk for 17 (36.2%) conditions. These significant outcomes, ranked from the largest to smallest HR per system, included: Circulatory: Peripheral/visceral vascular disease (HR: 4.40, 95% CI: 2.40-8.05), endocarditis and endocardial disease (3.12, 1.47-6.62), heart failure (2.23, 1.18-4.22), and coronary atherosclerosis/other heart disease (1.51, 1.12-2.03). Digestive: Biliary tract disease (3.26, 1.36-7.83), and other specified/unspecified gastrointestinal disorders (2.79, 1.36-5.75). Injury due to external causes: Accidental/unintentional intent of injury (4.04, 2.10-7.75), and subsequent encounter of external cause codes (3.59, 1.90-6.79). Genitourinary: Urinary tract infection (UTI) (4.00, 2.04-7.83). Neoplasm: Bile duct cancer (2.45, 1.38-4.35), unspecified malignant neoplasm (2.16, 1.40-3.32), and colorectal cancer (1.55, 1.18-2.03). Neurological: Neurocognitive disorders (2.48, 1.96-3.13), and Parkinson’s disease (2.17, 1.59-2.98). Respiratory: Aspiration pneumonitis (6.56, 1.41-30.51), pneumonia (1.98, 1.26-3.11), and COPD/bronchiectasis (1.53, 1.15-2.04). Download figure Open in new tab Fig. 3. Associations Between Cause-Specific Mortality Risks in Single CCSR Disorders (Any Death records, Death with & without prior history) and Overall COVID-19, Using Cox Regression Model. The 1st, 2nd and 3rd column respectively represent the results for any death records, death with a prior history, and death without a prior history of the same condition. The red dashed line represents the line of no effect (hazard ratio (HR) = 1). X-axis indicates the HR of mortality post COVID-19. Y-axis indicates each CCSR disease category. Solid bars indicate significance, and transparent bars indicate non-significant associations. We only present the results if the number of events ≥ 5 for both COVID-19 exposure and reference cohort. Single CCSR disorders are grouped by organ systems. CIR: circulatory system diseases; DIG: digestive system diseases; END: endocrine, nutritional and metabolic diseases; EXT: external causes of morbidity; GEN: genitourinary system diseases; INF: certain infectious and parasitic diseases; NEO: neoplasms; NVS: nervous system diseases; RSP: respiratory system diseases. View this table: View inline View popup Table 4. Associations Between Cause-Specific Mortality Risks in Single CCSR Disorders and COVID-19 Using Cox Regression Model. When restricting the outcome to death with a prior history of the examined CCSR disease ( Fig.3 , Table_5 and full results in Table_S2), the pattern of significant associations (18 out of 33, 54.5%) was similar to the primary analysis (regardless of any prior history). Five additional disorders were significantly associated with higher mortality risks, including hypertension with complications/secondary hypertension, CKD, cancers of the stomach, skin and bladder. View this table: View inline View popup Table 5. Significant Associations Between Cause-Specific Mortality Risks in Single CCSR Disorders With/Without Prior History and Overall/Hospitalized/Non-hospitalized COVID-19 Using Cox Regression Model (results with FDR-adjusted p<0.05 are shown). For death without a prior history, the proportion of significant associations with elevated risks decreased to 18.2% (6 out of 33; Fig. 3 , Table_5 and full results in Table_S2). The following outcomes remained significantly associated with increased mortality: peripheral/visceral vascular disease (3.51, 1.71-7.21), biliary tract disease (4.38, 1.57-12.16), other specified/unspecified gastrointestinal disorders (3.79, 1.59-9.03), unspecified malignant neoplasm (1.91, 1.20-3.04), and neurocognitive disorders (3.31, 2.00-5.46). Additionally, other specified/unspecified nutritional and metabolic disorders also exhibited a significant association (13.40, 2.53-71.07). Mortality risks of single outcomes in the hospitalized COVID-19 cohort Compared to the reference cohort, hospitalized COVID-19 infection significantly elevated mortality risk for 85.7% (36 out of 42) of CCSR outcomes examined ( Table_4b ). These outcomes encompassed multiple organ systems, including circulatory, digestive, endocrine, genitourinary, nervous and respiratory disorders, as well as external cause injuries, infectious diseases, and neoplasms. Stratifying deaths within the hospitalized COVID-19 cohort by prior history of the outcome revealed consistent patterns. A high proportion of CCSR disorders were significantly associated with greater mortality risks, with 87.1% (27 out of 31; Table_5 and Table_S2) for deaths with a pre-existing diagnosis. For deaths without a prior history ( Table_5 and Table_S2), while it seemed unlikely that COVID-19 directly induced several significant conditions such as cancers and neurocognitive disorders within the study’s timeframe, hospitalized COVID-19 infection was associated with increased mortality across a range of conditions (19 out of 21, 90.5%) without pre-existing diagnoses. This may reflect undiagnosed conditions leading to mortality. Mortality risks of single outcomes in the non-hospitalized COVID-19 cohort Table_4c indicates that a small proportion of CCSR disorders (3 out of 30, 10%) were significantly associated with increased mortality in individuals with non-hospitalized COVID-19 infection (HR > 1). These included accidental/unintentional intent of injury (HR: 3.49, 95% CI: 1.63-7.44), subsequent encounter of external cause codes (2.98, 1.42-6.26), and neurocognitive disorders (2.07, 1.56-2.73). Analysis of deaths with a prior history ( Table_5 and Table_S2) exhibited a similar pattern of significant CCSR disorders (4 out of 15, 26.7%), with only one additional outcome identified: hypertension with complications/secondary hypertension (7.60, 2.22-26.01). However, among deaths without pre-existing diagnoses ( Table_5 and Table_S2), beyond the previously identified neurocognitive disorders (3.04, 1.63 -5.68), significantly increased mortality risks were observed for peripheral/visceral vascular diseases (3.29, 1.36-7.95), biliary tract disease (4.44, 1.31-15.06), and other specified/unspecified gastrointestinal disorders (3.92, 1.46-10.51). Subgroup analysis With the detailed results for each characteristic listed in Table_S3-S14, mortality risks showing significant differences between risk factor present and absent subgroups (FDR-adjusted p 1) in both individuals with and without advanced age (> 65 years), CKD or HTN history, the magnitude of this risk was significantly greater (HR diff > 1) in the risk factor present groups with these conditions. Older adults (> 65 years) demonstrated a significantly higher risk of post-COVID-19 mortality from circulatory diseases compared to their middle-aged counterparts (50 – 65 years). Patients with AF history experienced a higher mortality risk from nervous system diseases following COVID-19 compared to those without AF. AF comorbidity also significantly increased the risk of death due to respiratory diseases in the context of COVID-19. View this table: View inline View popup Download powerpoint Table 6. Significant Differences in Associations between Mortality Risks in Organ Systems and Overall COVID-19 Across Different Comparisons of Subgroups. Download figure Open in new tab Fig. 4. Significant Differences in Associations between Mortality Risks in Organ Systems and Overall COVID-19 Across Different Comparisons of Subgroups. Comparisons showing significant differences (pval.adj diff < 0.05) in Hazard ratios (HR) for mortality with (risk factor present) and without (risk factor absent) specific characteristics are presented. The red dashed line represents the line of no effect (hazard ratio (HR) = 1). X-axis indicates the HR of mortality post COVID-19. Y-axis indicates each CCSR disease category. Red and blue color respectively represent association results in the risk factor present and absent subgroups. Solid bars indicate significance, and transparent bars indicate non-significant associations for each subgroup. We only present the results if the number of events ≥ 5 for COVID-19 and uninfected individuals in both subgroups. Advanced age represents > 65 years old, and Middle age refers to 50 - 65 years old. While subgroup analysis for individual CCSR disease categories revealed no statistically significant results after FDR correction, trends suggested a stronger association between COVID-19 infection and heart failure in subjects with AF (Table_S3), and hypertension in subjects with CKD (Table_S5), compared to their respective risk factor absent subgroups. However, these differences were marginally significant (FDR-adjusted p < 0.10). Discussion This prospective cohort study of UKBB examined the risks of all-cause and cause-specific mortality across 12 organ systems and 47 individual CCSR-defined disease categories for up to 35 months following COVID-19. SARS-CoV-2 infection was associated with increased mortality due to circulatory, digestive, genitourinary, neurological and respiratory disorders, as well as external causes and neoplasms. Hospitalized COVID-19 cases exhibited a greater proportion of post-infection outcomes with significantly elevated mortality risks than non-hospitalized individuals. Stratified analyses revealed that prior history and demographic or comorbidity factors further modulated the mortality risks of specific COVID-19 sequelae. Previous studies[ 15 – 20 ] have reported excess mortality after the emergence of SARS-CoV-2 coronavirus. Although there was region-specific variability among different countries, the most prevalent causes of excess deaths involved respiratory, cardiovascular, neurological disorders and cancers. However, since these estimates were based on population-level aggregates without adjustment for individual confounders, they can be sensitive to the choice of pre-pandemic reference period and may reflect healthcare system overloads or socioeconomic disruptions rather than the unique effects of COVID-19[ 29 ]. While in this study, we directly assessed the relatively long-term impact of SARS-CoV-2 infection on all-cause and cause-specific mortality using individual-level data with Cox regression. Increased mortality risks were identified not only for the previously reported conditions, but also for digestive, genitourinary diseases and external injuries. Consistent with existing literature[ 11 , 12 ], we observed significantly elevated all-cause mortality in COVID-19 survivors, with the highest HR identified among those who required hospitalization. Our analysis of cause-specific mortality further indicated that the hospitalized COVID-19 individuals experienced increased risks of death across a broader spectrum of organ systems and CCSR disorders compared to the non-hospitalized group, thereby demonstrating a clear linkage between initial COVID-19 severity and mortality from post-infection outcomes. This addresses a critical gap in prior research, which has primarily investigated symptoms and hospitalizations as COVID-19 sequelae[ 11 – 14 ]. While some Mendelian randomization studies also support a causal association between genetic susceptibility to hospitalized (severe) COVID-19 and post-COVID-19 syndromes across cardiovascular, pulmonary, nervous and genitourinary systems [ 30 – 33 ], this method is less suited to examine COVID-19’s association with mortality risk due to methodological constraints. These are also limited by their focus on single organ systems or only a restricted number of pre-specified conditions. In contrast, our study provides a longer-term, systematic, and comprehensive assessment of post-infection mortality. By utilizing the CCSR classification, we avoided arbitrary exclusions or preferential selection of specific disease categories, enabling the identification of a wider array of high-risk outcomes. Additionally, multiple subgroup analyses were conducted to further explore differences in overall effects among various subpopulations. The observed increase in respiratory-related mortality aligns with previous studies suggesting non-COVID pneumonia and bronchiectasis as common pulmonary sequelae following COVID-19[ 2 , 34 ]. Besides, the elevated mortality risks of post-COVID cardiovascular events, such as heart failure, endocarditis and coronary atherosclerosis, may be attributable to various factors including direct viral infiltration of SARS-CoV-2, autoimmune dysregulation and the resulting inflammatory response within cardiac tissues[ 3 , 35 – 37 ]. Mainous et al.[ 22 ] also revealed an increased 12-month risk of all-cause, respiratory, and cardiovascular mortality in patients with hospitalized COVID-19. However, respiratory and cardiovascular conditions accounted for only 20.5% of the deaths in their study. This corroborates our observation that the impact of SARS-CoV-2 extends beyond these two systems. For instance, we found increased mortality for neurological disorders, as supported by Taquet et al.[ 21 ], who demonstrated that the risks of neurocognitive deficits could persist for up to 2 years after infection. Although less frequently reported in prior investigations, we observed association between COVID-19 and elevated genitourinary system mortality. This could be mediated through coronavirus’s binding to ACE2 receptors in the urinary tract, which may induce cellular damage and increase susceptibility to infections[ 38 ]. In addition, renal complications have been reported among COVID-19 survivors[ 5 ], which may be due to direct viral invasion of kidney cells, persistent tubular and microvascular injury from systemic inflammation and coagulopathy, and podocyte damage leading to conditions such as collapsing glomerulopathy. Our finding of elevated digestive system mortality also aligns with emerging evidence of viral RNA persistence in gut tissues and sustained systemic inflammation, contributing to gastrointestinal and hepatobiliary manifestations of long COVID[ 6 ]. Furthermore, the increased mortality risks from external causes, primarily accidental injuries, highlight significant secondary consequences of COVID-19. Post-infection outcomes including musculoskeletal pain, muscle weakness, fatigue, and cognitive dysfunction may collectively impair physical coordination and risk perception[ 34 , 39 ]. COVID-19 or its clinical treatment (e.g., glucocorticoid) may also accelerate bone loss and osteoporosis progression, further raising the likelihood of fractures and fatal injuries[ 40 ]. Post-COVID mortality from multiple neoplasms was also elevated. One possible explanation is that COVID-19 may exacerbate pre-existing malignancies by inducing immune dysregulation. The viral infection is known to trigger an excessive release of inflammatory cytokines, fostering a pro-tumorigenic environment[ 41 , 42 ]. Moreover, SARS-CoV-2 may cause a significant depletion of critical cancer-fighting immune cells, such as the CD4+ and CD8+ T cells responsible for tumor destruction[ 42 ]. This impaired immune surveillance can compromise the body’s ability to suppress malignancies, leading to accelerated disease progression and poorer prognoses in cancer patients following COVID-19 infection[ 43 ]. Interestingly, increased neoplasm mortality was also observed in COVID-19 patients without a prior cancer diagnosis, particularly among those requiring hospitalization. Given the study timeframe, it seems unlikely that COVID-19 directly induced the formation of new cancers. A more plausible explanation is that the significant physiological stress and systemic inflammation from severe infection may have promoted the growth of pre-existing but undiagnosed tumors, precipitating their clinical presentations[ 44 ]. While mortality risks appeared less pronounced in individuals without a prior history of the examined CCSR outcomes, we identified several lethal complications possibly developed after COVID-19 infection. Peripheral and visceral vascular disease may arise from SARS-CoV-2 invasion of vascular epithelial cells via ACE2 receptors, leading to severe intravascular thrombotic events and endothelial dysfunction[ 45 , 46 ]; In addition, biliary tract disease may result from SAR-CoV-2 viral toxicity to cholangiocytes, mediating biliary epithelium damage or inflammatory responses, and subsequently triggering cholecystitis or cholangitis in COVID-19 survivors[ 6 , 47 ]. Our subgroup analysis indicated that older adults with a history of chronic conditions (CKD and HTN) were more vulnerable to deleterious consequences of SARS-CoV-2 infection with elevated all-cause and cardiovascular mortality. Moreover, patients with AF demonstrated increased mortality risks for both neurological and respiratory diseases, which potentially suggests a synergistic prothrombotic effect between AF and COVID-19. This aligns with existing evidence that both AF and COVID-19 may induce thromboembolic complications such as ischemic stroke and pulmonary embolism, contributing to the corresponding organ dysfunction and observed mortality patterns[ 48 , 49 ]. Importantly, although at a lower magnitude than in their corresponding risk factor present counterparts, significantly elevated all-cause mortality was also observed in risk factor absent groups (e.g., middle-aged individuals, or without CKD/HTN history). This highlights that post-COVID-19 mortality risks are multifactorial and cautions should be taken once infected. Strengths and limitations The present study possesses unique strengths. It leveraged the breadth and depth of the electronic health record system within the UKBB to establish a large cohort with a sufficient sample size and follow-up period. Instead of focusing on symptoms or hospitalizations, we analyzed the long-term impact of COVID-19 by examining mortality, the most severe consequence of post-infection disorders. The contribution of SARS-CoV-2 infection to deaths was assessed via Cox statistical model rather than estimating excess mortality. Besides, we systemically categorized the causes of post-COVID mortality into 12 organ systems and 47 single disorders using the CCSR classification system. Moreover, we performed additional analyses stratified by COVID-19 disease severity, prior history, demographic factors, and comorbidities to evaluate their associations with specific mortality risks following COVID-19. Our work also has several limitations. Firstly, the UKBB cohort comprises primarily older, white individuals with better health and higher levels of education[ 50 ], which may limit the generalizability of the observed mortality rates to other populations. However, the underlying pathophysiological mechanisms by which COVID-19 triggers post-infection outcomes and elevates mortality risks are likely to be broadly applicable across diverse populations. Therefore, the fundamental insights derived from our findings remain highly relevant beyond the study cohort. Secondly, due to the observational nature of this study, we cannot establish causality between COVID-19 and the mortality risks of post-infection disorders. While we adjusted for a comprehensive set of covariates, unmeasured confounding cannot be completely ruled out. Thirdly, our results represent average mortality risks observed during the study period (January 2020 to December 2022). Further investigation is warranted to evaluate the longer-term impact of COVID-19 beyond this timeframe. In addition, as we relied on ICD-10 codes to identify causes of death, our study could be subject to misclassification bias. Inadequate statistical power related to rare events may also constrain our ability to detect significant associations or conduct meaningful analyses. Furthermore, we cannot exclude the possibility that mild or asymptomatic COVID-19 infections were misclassified into the reference cohort, leading to an underestimated mortality burden. Lastly, due to limitation of data access during analysis, vaccination records such as booster dose for UKBB participants is incomplete. Hence, we only treated vaccination status as a binary covariate (receiving any doses vs. none) and did not examine its potential impact on post-COVID mortality. Clinical implications This study demonstrates that COVID-19 is associated with elevated all-cause and cause-specific mortality across multiple organ systems, with hospitalized SARS-CoV-2 infections showing significantly increased risks across a broader spectrum of post-infection outcomes. This underscores the critical need of preventive strategies to mitigate COVID-19 severity through vaccination and early treatment. Furthermore, even non-hospitalized COVID-19 infection is linked to modestly increased all-cause mortality and deaths from neurological disorders or external cause injuries. Given the huge number of infections worldwide, the absolute mortality burden imposed by COVID-19 sequelae could be substantial. Since the post-pandemic era has come, public health policies should prioritize the management of post-COVID-19 complications by allocating healthcare resources for long-term follow-up and risk assessment of COVID-19 survivors, especially older adults and those with pre-existing high-risk comorbidities. Future research is crucial to investigate the underlying mechanisms, identify effective interventions to ameliorate the mortality burden, and examine the long-term trajectory of mortality risks tied to these post-COVID-19 health outcomes. Data Availability The UK Biobank data is available to all registered researchers upon application. All other data produced in the present work are contained in the manuscript. Author Contributions Ruoyu Zhang: Writing – review & editing, Writing – original draft, Validation, Software, Resources, Methodology, Formal analysis. Yong Xiang: Writing – review & editing, Visualization, Validation, Software, Formal analysis. Jinghong Qiu: Writing – review & editing, Visualization, Validation, Formal analysis. Hon-Cheong So: Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Funding acquisition, Data curation, Conceptualization. Acknowledgements We gratefully acknowledge support from the National Natural Science Foundation of China (Grant-81971706), the Lo-Kwee-Seong Biomedical Research Fund, and the Joint Laboratory of Bioresources and Molecular Research of Common Diseases of the Kunming Institute of Zoology and The Chinese University of Hong Kong, China. Special thanks to Prof. Pak Sham for data access. References 1. ↵ WHO , COVID-19 epidemiological update – 13 February 2025, in Emergency Situational Updates . 2025 : Geneva, Switzerland . 2. ↵ Al-Jahdhami , I. , A. Al-Mawali , and S.M. Bennji , Respiratory Complications after COVID-19 . Oman Med J , 2022 . 37 ( 1 ): p. e343 . OpenUrl PubMed 3. ↵ Mohammad , K.O. , A. Lin , and J.B.C. Rodriguez , Cardiac Manifestations of Post-Acute COVID-19 Infection . Curr Cardiol Rep , 2022 . 24 ( 12 ): p. 1775 – 1783 . OpenUrl PubMed 4. ↵ Ahmad , S.J. , et al. , Neurological Sequelae of COVID-19 . JIN , 2022 . 21 ( 3 ). 5. ↵ Copur , S. , et al. , Post-acute COVID-19 syndrome and kidney diseases: what do we know? J Nephrol , 2022 . 35 ( 3 ): p. 795 – 805 . OpenUrl PubMed 6. ↵ Rizvi , A. , et al. , Gastrointestinal and Hepatobiliary Symptoms and Disorders with Long (Chronic) COVID Infection . Gastroenterology Clinics , 2023 . 52 ( 1 ): p. 139 – 156 . OpenUrl PubMed 7. ↵ Parotto , M. , et al. , Post-acute sequelae of COVID-19: understanding and addressing the burden of multisystem manifestations . The Lancet Respiratory Medicine , 2023 . 11 ( 8 ): p. 739 – 754 . OpenUrl PubMed 8. ↵ Al-Aly , Z. , Y. Xie , and B. Bowe , High-dimensional characterization of post-acute sequelae of COVID-19 . Nature , 2021 . 594 ( 7862 ): p. 259 – 264 . OpenUrl CrossRef PubMed 9. ↵ Nyberg , T. , et al. , Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study . Lancet , 2022 . 399 ( 10332 ): p. 1303 – 1312 . OpenUrl PubMed 10. ↵ Xie , Y. , et al. , Cases, Hospitalization, and Mortality in COVID-19 and Influenza Among Veterans in 2022-2025 Influenza Seasons . JAMA Network Open , 2025 . 8 ( 7 ): p. e2520673 – e2520673 . OpenUrl 11. ↵ Cai , M. , et al. , Three-year outcomes of post-acute sequelae of COVID-19 . Nat Med , 2024 . 30 ( 6 ): p. 1564 – 1573 . OpenUrl CrossRef PubMed 12. ↵ Bowe , B. , Y. Xie , and Z. Al-Aly , Postacute sequelae of COVID-19 at 2 years . Nat Med , 2023 . 29 ( 9 ): p. 2347 – 2357 . OpenUrl CrossRef PubMed 13. ↵ Xiang , Y. , et al. , Increased risk of hospitalization for various disorders after COVID-19 infection: A Cohort study of the UK biobank spanning over a hundred disease categories. Journal of Microbiology , Immunology and Infection , 2025 . 14. ↵ Mainous , A.G. , 3rd . , B.J. Rooks , and F.A. Orlando , Risk of New Hospitalization Post-COVID-19 Infection for Non-COVID-19 Conditions . J Am Board Fam Med , 2021 . 34 ( 5 ): p. 907 – 913 . OpenUrl Abstract / FREE Full Text 15. ↵ Çelik , C. , U. Ata , and N.E. Saka , Evaluation of Mortality Statistics in Turkey from 2017 to 2022: An Analysis of the Impact of COVID-19 . Iran J Public Health , 2024 . 53 ( 10 ): p. 2318 – 2327 . OpenUrl PubMed 16. Auger , N. , et al. , Hospitalization and hospital mortality rates during the first and second waves of the COVID-19 pandemic in Quebec: interrupted time series and decomposition analysis . Public Health , 2023 . 225 : p. 28 – 34 . OpenUrl PubMed 17. Luck , A.N. , et al. , Associations between mortality from COVID-19 and other causes: A state-level analysis . PLoS One , 2023 . 18 ( 3 ): p. e0281683 . OpenUrl PubMed 18. Asta , F. , et al. , [Impact of the COVID-19 epidemic on total and cause-specific mortality in Rome (Italy) in 2020] . Epidemiol Prev , 2022 . 46 ( 1-2 ): p. 59 – 67 . OpenUrl 19. Glei , D.A ., The US Midlife Mortality Crisis Continues: Excess Cause-Specific Mortality During 2020 . Am J Epidemiol , 2022 . 191 ( 10 ): p. 1677 – 1686 . OpenUrl CrossRef PubMed 20. ↵ Grande , E. , et al. , Variation in Cause-Specific Mortality Rates in Italy during the First Wave of the COVID-19 Pandemic: A Study Based on Nationwide Data . Int J Environ Res Public Health , 2022 . 19 ( 2 ). 21. ↵ Taquet , M. , et al. , Neurological and psychiatric risk trajectories after SARS-CoV-2 infection: an analysis of 2-year retrospective cohort studies including 1 284 437 patients . The Lancet Psychiatry , 2022 . 9 ( 10 ): p. 815 – 827 . OpenUrl PubMed 22. ↵ Mainous , A.G. , 3rd . , et al. , COVID-19 Post-acute Sequelae Among Adults: 12 Month Mortality Risk . Front Med (Lausanne) , 2021 . 8 : p. 778434 . OpenUrl PubMed 23. ↵ Sudlow , C. , et al. , UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age . PLoS Med , 2015 . 12 ( 3 ): p. e1001779 . OpenUrl CrossRef PubMed 24. ↵ Zhou , Z. , et al. , Survival Bias Associated with Time-to-Treatment Initiation in Drug Effectiveness Evaluation: A Comparison of Methods . American Journal of Epidemiology , 2005 . 162 ( 10 ): p. 1016 – 1023 . OpenUrl CrossRef PubMed Web of Science 25. ↵ Clinical Classifications Software Refined (CCSR) for ICD-10-CM Diagnoses, v2022.1 . [cited 2022 April 2]; Available from: www.hcup-us.ahrq.gov/toolssoftware/ccsr/dxccsr.jsp . 26. ↵ Mayer , M. , missRanger: Fast Imputation of Missing Values . 2024 . 27. ↵ Zhao , S.D. and Y. Li , Principled sure independence screening for Cox models with ultra-high-dimensional covariates . Journal of Multivariate Analysis , 2012 . 105 ( 1 ): p. 397 – 411 . OpenUrl PubMed 28. ↵ Benjamini , Y. and Y. Hochberg , Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing . Journal of the Royal Statistical Society. Series B (Methodological) , 1995 . 57 ( 1 ): p. 289 – 300 . OpenUrl CrossRef PubMed Web of Science 29. ↵ Barbiellini Amidei , C. , et al. , Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared . Int J Environ Res Public Health , 2023 . 20 ( 11 ). 30. ↵ Zheng , M ., COVID-19 Predisposition Inherently Increases Cardiovascular Risk Before SARS-CoV-2 Infection . Cardiovasc Toxicol , 2025 . 25 ( 6 ): p. 821 – 829 . OpenUrl PubMed 31. Tao , Y. , et al. , Assessing the causal relationship between COVID-19 and post-COVID-19 syndrome: A Mendelian randomisation study . J Glob Health , 2023 . 13 : p. 06054 . OpenUrl PubMed 32. Baranova , A. , H. Cao , and F. Zhang , Severe COVID-19 increases the risk of schizophrenia . Psychiatry Res , 2022 . 317 : p. 114809 . OpenUrl CrossRef PubMed 33. ↵ Chang , Z. , et al. , The genetic associations of COVID-19 on genitourinary symptoms . Front Immunol , 2023 . 14 : p. 1216211 . OpenUrl PubMed 34. ↵ Graham , E.L. , et al. , Musculoskeletal, Pulmonary, and Cardiovascular COVID-19 Sequelae in the Context of Firefighter Occupational Health: A Narrative Review . Int J Environ Res Public Health , 2024 . 21 ( 10 ). 35. ↵ Tian , S. , et al. , Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsies . Modern Pathology , 2020 . 33 ( 6 ): p. 1007 – 1014 . OpenUrl PubMed 36. Kole , C. , et al. , Acute and Post-Acute COVID-19 Cardiovascular Complications: A Comprehensive Review . Cardiovasc Drugs Ther , 2024 . 38 ( 5 ): p. 1017 – 1032 . OpenUrl PubMed 37. ↵ Eberhardt , N. , et al. , SARS-CoV-2 infection triggers pro-atherogenic inflammatory responses in human coronary vessels . Nat Cardiovasc Res , 2023 . 2 ( 10 ): p. 899 – 916 . OpenUrl CrossRef PubMed 38. ↵ Chichirelo-Konstantynovych , K. and T. Konstantynovych , P16 COVID-19 and urinary tract infection: the main manifestations and their management . JAC-Antimicrobial Resistance , 2023 . 5 ( Supplement_3 ). 39. ↵ Appelman , B. , et al. , Muscle abnormalities worsen after post-exertional malaise in long COVID . Nat Commun , 2024 . 15 ( 1 ): p. 17 . OpenUrl CrossRef PubMed 40. ↵ Tang , J ., COVID-19 Pandemic and Osteoporosis in Elderly Patients . Aging Dis , 2022 . 13 ( 4 ): p. 960 – 969 . OpenUrl PubMed 41. ↵ Rahimmanesh , I. , et al. , Cancer Occurrence as the Upcoming Complications of COVID-19 . Front Mol Biosci , 2021 . 8 : p. 813175 . OpenUrl PubMed 42. ↵ Ogarek , N. , et al. , SARS-CoV-2 infection as a potential risk factor for the development of cancer . Front Mol Biosci , 2023 . 10 : p. 1260776 . OpenUrl PubMed 43. ↵ Cai , G. , et al. , Immunological alternation in COVID-19 patients with cancer and its implications on mortality . Oncoimmunology , 2021 . 10 ( 1 ): p. 1854424 . OpenUrl PubMed 44. ↵ Gregory , T.A. , et al. , Accelerated tumor progression after COVID-19 infection in patients with glioblastoma: A retrospective case-control study . Neurooncol Pract , 2024 . 11 ( 4 ): p. 475 – 483 . OpenUrl PubMed 45. ↵ Tanzadehpanah , H. , et al. , Role of SARS-COV-2 and ACE2 in the pathophysiology of peripheral vascular diseases . Biomedicine & Pharmacotherapy , 2023 . 166 : p. 115321 . OpenUrl PubMed 46. ↵ Rastogi , A. , H. Dogra , and E.B. Jude , COVID-19 and peripheral arterial complications in people with diabetes and hypertension: A systematic review . Diabetes Metab Syndr , 2021 . 15 ( 5 ): p. 102204 . OpenUrl PubMed 47. ↵ Faruqui , S. , K. Shanbhogue , and I.M. Jacobson , Biliary Tract Injury in Patients With COVID-19: A Review of the Current Literature . Gastroenterol Hepatol (N Y ), 2022 . 18 ( 7 ): p. 380 – 387 . OpenUrl PubMed 48. ↵ Karadavut , S. , M. Cetin , and O. Sahin , The effect of COVID-19 on the thromboembolic outcomes in atrial fibrillation patients in the long run . Acta Cardiol , 2024 . 79 ( 3 ): p. 344 – 350 . OpenUrl PubMed 49. ↵ Raatikainen , P. and R. Lassila , COVID-19: another reason for anticoagulation in patients with atrial fibrillation . Heart , 2022 . 108 ( 12 ): p. 902 . OpenUrl FREE Full Text 50. ↵ Schoeler , T. , et al. , Participation bias in the UK Biobank distorts genetic associations and downstream analyses . Nature Human Behaviour , 2023 . 7 ( 7 ): p. 1216 – 1227 . OpenUrl PubMed View the discussion thread. Back to top Previous Next Posted August 02, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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Share Association of COVID-19 with risks of all-cause and cause-specific mortality post-infection: A UK Biobank cohort study Ruoyu Zhang , Yong Xiang , Jinghong Qiu , Hon-Cheong So medRxiv 2025.08.01.25332496; doi: https://doi.org/10.1101/2025.08.01.25332496 Share This Article: Copy Citation Tools Association of COVID-19 with risks of all-cause and cause-specific mortality post-infection: A UK Biobank cohort study Ruoyu Zhang , Yong Xiang , Jinghong Qiu , Hon-Cheong So medRxiv 2025.08.01.25332496; doi: https://doi.org/10.1101/2025.08.01.25332496 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Infectious Diseases (except HIV/AIDS) Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (299) Cardiovascular Medicine (4426) Dentistry and Oral Medicine (443) Dermatology (382) Emergency Medicine (607) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1507) Epidemiology (15222) Forensic Medicine (30) Gastroenterology (1123) Genetic and Genomic Medicine (6589) Geriatric Medicine (667) Health Economics (997) Health Informatics (4525) Health Policy (1368) Health Systems and Quality Improvement (1612) Hematology (540) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15910) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (145) Nephrology (667) Neurology (6588) Nursing (346) Nutrition (998) Obstetrics and Gynecology (1143) Occupational and Environmental Health (956) Oncology (3331) Ophthalmology (971) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (663) Pediatrics (1690) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5440) Public and Global Health (9221) Radiology and Imaging (2195) Rehabilitation Medicine and Physical Therapy (1369) Respiratory Medicine (1196) Rheumatology (593) Sexual and Reproductive Health (710) Sports Medicine (529) Surgery (711) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9ffea3a24c8458f4',t:'MTc3OTQ4MjQ2MA=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();