scholarly journals Excess Mortality Attributable to COVID-19 Among Assisted Living Residents

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 58-58
Author(s):  
Kali Thomas ◽  
Wenhan Zhang ◽  
David Dosa ◽  
Paula Carder ◽  
Philip Sloane ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Confidence Intervals ◽  
Assisted Living ◽  
Excess Mortality ◽  
Mortality Rates ◽  
All Cause Mortality ◽  
National Cohort ◽  
Adjusted Incidence Rate ◽  
Rate Ratios ◽  
Adjusted Incidence

Abstract This study examines the excess mortality attributable to COVID-19 among a national cohort of assisted living (AL) residents. To do this, we compare the weekly rate of all-cause mortality during 1/1/20-8/11/20 with the same weeks in 2019 and calculated adjusted incidence rate ratios (IRRs) and 95% confidence intervals (CIs). All-cause mortality rates, nationally, were 14% higher in 2020 compared with 2019 (mean, 2.309 vs. 2.020, respectively, per 1000 residents per week; adjusted IRR, 1.169; 95% CI 1.165-1.173). Among the 10 states with the highest community spread, the excess mortality attributable to COVID-19 was 24% higher, with 2.388 deaths per 1000 residents per week in 2020 during January-August vs 1.928 in 2019 (adjusted IRR, 1.241; 95% CI 1.233-1.250). These results suggest that AL residents suffered excess mortality due to COVID-19.

scholarly journals A Statistical Test for the Equality of Differently Adjusted Incidence Rate Ratios

2007 ◽  
Vol 167 (5) ◽  
pp. 517-522 ◽  
Author(s):  
K. Hoffmann ◽  
T. Pischon ◽  
M. Schulz ◽  
M. B. Schulze ◽  
J. Ray ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Statistical Test ◽  
Adjusted Incidence Rate ◽  
Rate Ratios ◽  
Adjusted Incidence

Prevalence and 5-year trend of incidence for medical illnesses after the diagnosis of bipolar disorder: A nationwide cohort study

2021 ◽  
pp. 000486742110468
Author(s):  
Pao-Huan Chen ◽  
Shang-Ying Tsai ◽  
Chun-Hung Pan ◽  
Yi-Lung Chen ◽  
Sheng-Siang Su ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Human Immunodeficiency Virus ◽  
Heart Disease ◽  
Incidence Rate ◽  
Cerebrovascular Diseases ◽  
First Year ◽  
Immunodeficiency Virus ◽  
Adjusted Incidence Rate ◽  
Rate Ratios ◽  
Adjusted Incidence

Objective: Medical comorbidities are prevalent in patients with bipolar disorder. Evaluating longitudinal trends of the incidence of medical illnesses enables implementation of early prevention strategies to reduce the high mortality rate in this at-risk population. However, the incidence risks of medical illnesses in the early stages of bipolar disorder remain unclear. This study investigated the incidence and 5-year trend of medical illnesses following bipolar disorder diagnosis. Methods: We identified 11,884 patients aged 13–40 years who were newly diagnosed as having bipolar disorder during 1996–2012 and 47,536 age- and sex-matched controls (1:4 ratio) who represented the general population from Taiwan’s National Health Insurance Research Database. We estimated the prevalence and incidence of individual medical illnesses yearly across the first 5 years after the index date. The adjusted incidence rate ratio was calculated to compare the occurrence of specific medical illnesses each year between the bipolar disorder group and control group using the Poisson regression model. Results: Apart from the prevalence, the adjusted incidence rate ratios of most medical illnesses were >1.00 across the first 5-year period after bipolar disorder diagnosis. Cerebrovascular diseases, ischaemic heart disease, congestive heart failure, other forms of heart disease, renal disease and human immunodeficiency virus infection exhibited the highest adjusted incidence rate ratios during the first year. Except for that of renal disease, the 5-year trends of the adjusted incidence rate ratios decreased for cerebrovascular diseases, cardiovascular diseases (e.g. ischaemic heart disease, other forms of heart disease, and vein and lymphatic disease), gastrointestinal diseases (e.g. chronic hepatic disease and ulcer disease) and communicable diseases (e.g. human immunodeficiency virus infection, upper respiratory tract infection and pneumonia). Conclusion: Incidence risks of medical illnesses are increased in the first year after bipolar disorder diagnosis. Clinicians must carefully evaluate medical illnesses during this period because the mortality rates from medical illnesses are particularly high in people with bipolar disorder.

scholarly journals Mortality in Norway and Sweden before and after the Covid-19 outbreak: a cohort study

2020 ◽  
Author(s):  
Frederik E Juul ◽  
Henriette C Jodal ◽  
Ishita Barua ◽  
Erle Refsum ◽  
Ørjan Olsvik ◽  
...  
Keyword(s):  
Excess Mortality ◽  
Mortality Rates ◽  
List Type ◽  
School Closures ◽  
Epidemic Period ◽  
All Cause Mortality ◽  
Specific Mortality ◽  
Before And After ◽  
Rate Ratios ◽  
Expected Mortality

AbstractObjectivesNorway and Sweden are similar countries regarding ethnicity, socioeconomics and health care. To combat Covid-19, Norway implemented extensive measures such as school closures and lock-downs, while Sweden has been criticised for relaxed measures against Covid-19. We compared the effect of the different national strategies on all-cause and Covid-19 associated mortality.DesignRetrospective cohort.SettingThe countries Norway and Sweden.ParticipantsAll inhabitants.Main outcome measuresWe calculated weekly mortality rates (MR) with 95% confidence intervals (CI) per 100,000 individuals as well as mortality rate ratios (MRR) comparing the epidemic year (29th July, 2019 to 26th July, 2020) to the four preceding years (July 2015 to July 2019). We also compared Covid-19 associated deaths and mortality rates for the weeks of the epidemic in Norway and Sweden (16th March to 26th July, 2020).ResultsIn Norway, mortality rates were stable during the first three 12-month periods of 2015/16; 2016/17 and 2017/18 (MR 14.8 to 15.1 per 100,000), and slightly lower in the two most recent periods including during epidemic period (2018/19 and 2019/20; 14.5 per 100,000). In Sweden, all-cause mortality was stable during the first three 12-month periods of 2015/16; 2016/17 and 2017/18 (MR 17.2 to 17.5 per 100,000), but lower in the year 2018/19 immediately preceding the epidemic (16.2 per 100,000). Covid-19 associated mortality rates were 0.2 per 100,000 (95%CI 0.1 to 0.4) in Norway and 2.9 (95%CI 1.9 to 3.9) in Sweden. The increase in mortality was confined to individuals in 70 years or older.ConclusionsAll-cause mortality remained unaltered in Norway. In Sweden, the observed increase in all-cause mortality during Covid-19 was partly due to a lower than expected mortality preceding the epidemic and the observed excess mortality, was followed by a lower than expected mortality after the first Covid-19 wave. This may suggest mortality displacement.Strengths and limitations of this studyCompares two similar contries in all aspects but the handling of the Covid-19 epidemicEvaluates the mortality for several years before and during the epidemicProvides a possible explanation of the observed mortality changesDiscusses the socioeconomic effects of the different strategies in the two countriesDoes not evaluate cause-specific mortality

scholarly journals Association of Health Insurance Payer Type and Outcomes After Durable Left Ventricular Assist Device Implantation: An Analysis of the STS-INTERMACS Registry

2021 ◽  
Author(s):  
Sameed Ahmed M. Khatana ◽  
Thomas C. Hanff ◽  
Ashwin S. Nathan ◽  
Elias J. Dayoub ◽  
E. Wilson Grandin ◽  
...  
Keyword(s):  
Adverse Event ◽  
Incidence Rate ◽  
Left Ventricular ◽  
Subdistribution Hazard ◽  
Ventricular Assist ◽  
Left Ventricular Assist ◽  
All Cause Mortality ◽  
Adjusted Incidence Rate ◽  
Insured Patients ◽  
Adjusted Incidence

Background: Due to the high cost of left ventricular assist device (LVAD) therapy, payer type may be an important factor in determining eligibility. How payer type influences outcomes after LVAD implantation is unclear. We, therefore, aimed to study the association of health insurance payer type with outcomes after durable LVAD implantation. Methods: Using STS-INTERMACS (Society of Thoracic Surgeons-Interagency Registry for Mechanically Assisted Circulatory Support), we studied nonelderly adults receiving a durable LVAD from 2016 to 2018 and compared all-cause mortality and postindex hospitalization adverse event episode rate by payer type. Multivariable Fine-Gray and generalized linear models were used to compare the outcomes. Results: Of the 3251 patients included, 26.0% had Medicaid, 24.9% had Medicare alone, and 49.1% had commercial insurance. Compared with commercially insured patients, mortality did not differ for patients with Medicaid (subdistribution hazard ratio, 1.00 [95% CI, 0.75–1.34], P =0.99) or Medicare (subdistribution hazard ratio, 1.09 [95% CI, 0.84–1.41], P =0.52). Medicaid was associated with a significantly lower adjusted incidence rate (incidence rate ratio, 0.88 [95% CI, 0.78–0.99], P =0.041), and Medicare was associated with a significantly higher adjusted incidence rate (incidence rate ratio, 1.16 [95% CI, 1.03–1.30], P =0.011) of adverse event episodes compared with commercially insured patients. Conclusions: All-cause mortality after durable LVAD implantation did not differ significantly by payer type. Payer type was associated with the rate of adverse events, with Medicaid associated with a significantly lower rate, and Medicare with a significantly higher rate of adverse event episodes compared with commercially insured patients.

MO514CARDIORENAL OUTCOMES AND MORTALITY IN PATIENTS WITH TYPE 2 DIABETES MELLITUS: A MULTINATIONAL PROSPECTIVE COHORT STUDY (PROVALID)

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Stefanie Thöni ◽  
Felix Keller ◽  
Sara Denicolo ◽  
Susanne Eder ◽  
Laszlo Rosivall ◽  
...  
Keyword(s):  
Risk Factors ◽  
The Netherlands ◽  
Incidence Rate ◽  
Composite Endpoint ◽  
Incidence Rates ◽  
European Countries ◽  
All Cause Mortality ◽  
Adjusted Incidence Rate ◽  
Adjusted Incidence

Abstract Background and Aims PROVALID is a prospective, observational, multinational cohort study in 4000 patients with type 2 diabetes mellitus. Our aim was to determine the incidence rate of renal and cardiovascular endpoints, as well as all-cause-mortality in different European countries and to identify risk factors associated with the investigated outcomes. Method Potential risk factors associated with the investigated outcomes were identified by calculation of the incidence rate ratio. Crude and adjusted incidence rates for every country were estimated using generalized linear (poisson) regression models and corresponding 95 % confidence intervals were computed. Incidence rates were adjusted for different risk factors including age, sex, estimated GFR, albuminuria, HbA1c, LDL, HDL, total cholesterol, systolic blood pressure, BMI and cardiovascular and renal comorbidities; among these several show significant impact on outcomes. The renal outcome was a composite of a sustained decline in the estimated GFR of at least 40%, a sustained increase in albuminuria of at least 30 % including the progression from normo- to micro- or macroalbuminuria, end-stage kidney disease, or death from renal causes. The cardiovascular composite endpoint was death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke. Results 3461 participants of four European countries (Austria 18 %, Hungary 41 %, Netherlands 26 % and Scotland 15 %) with a mean follow up time of 3.9 years were included into this study. Participants from Poland were excluded due to missing follow-up data. In total, 9.2 % and 6.4 % participants reached the renal and cardiovascular composite endpoint, respectively. 7.0 % of the participants died within this timeframe. The adjusted incidence rate for the renal endpoint ranged from 14.5 to 25.3 (per 1000 patient-years) with no significant differences between countries. On average, the incidence rate was lower in Scotland (IR, 14.5; 95 % CI, 8.7 to 22.5) and in the Netherlands (IR, 15.7; 95 % CI, 10.9 to 21.8) compared to Hungary (IR, 25.3; 95 % CI, 20.7 to 30.6) and Austria (IR 21.3; 95 % CI, 16.2 to 27.5). The adjusted incidence rate for the cardiovascular endpoint ranged from 7.0 to 20.3 and was significantly lower in Hungary (IR, 7.0; 95 % CI, 5.1 to 9.3) and the Netherlands (IR, 7.6; 95 % CI, 4.4 to 12.2) compared to Austria (IR, 16.7; 95 % CI, 12.4 to 22.1) and Scotland (IR, 20.3; 95 % CI, 13.8 to 28.9). The adjusted incidence rate for all-cause-mortality ranged from 4.2 to 15.9 and was significantly lower in the Netherlands (IR, 4.2; 95 % CI, 2.2 to 7.6) compared to Scotland (IR, 15.9; 95 % CI, 10.9 to 22.6). No significant difference in the incidence rates between Austria (IR, 9.8; 95 % CI, 7.0 to 13.4) and Hungary (IR, 9.3; 95 % CI, 6.8 to 12.4) was found. Conclusion After adjustment for known risk factors, incidence rates of cardiovascular endpoints, as well as all-cause-mortality still vary significantly between four European countries. This may be due to manifold reasons. Further analysis of the national therapeutic practice pattern within the PROVALID cohort may provide additional information.

scholarly journals Causes of Death in People With Cardiovascular Disease: A UK Biobank Cohort Study

2021 ◽  
Author(s):  
Michael Drozd ◽  
Mar Pujades‐Rodriguez ◽  
Fei Sun ◽  
Kevin N. Franks ◽  
Patrick J. Lillie ◽  
...  
Keyword(s):  
Cohort Study ◽  
Incidence Rate ◽  
Causes Of Death ◽  
Sociodemographic Factors ◽  
Cardiovascular Death ◽  
Uk Biobank ◽  
Personalized Care ◽  
Adjusted Incidence Rate ◽  
Rate Ratios ◽  
Adjusted Incidence

Background Therapeutic advances have reduced cardiovascular death rates in people with cardiovascular diseases (CVD). We aimed to define the rates of cardiovascular and noncardiovascular death in people with specified CVDs or accruing cardiovascular multimorbidity. Methods and Results We studied 493 280 UK residents enrolled in the UK Biobank cohort study. The proportion of deaths attributed to cardiovascular, cancer, infection, or other causes were calculated in groups defined by 9 distinct self‐reported CVDs at baseline, or by the number of these CVDs at baseline. Poisson regression analyses were then used to define adjusted incidence rate ratios for these causes of death, accounting for sociodemographic factors and comorbidity. Of 27 729 deaths, 20.4% were primarily attributed to CVD, 53.6% to cancer, 5.0% to infection, and 21.0% to other causes. As cardiovascular multimorbidity increased, the proportion of cardiovascular and infection‐related deaths was greater, contrasting with cancer and other deaths. Compared with people without CVD, those with 3 or more CVDs experienced adjusted incidence rate ratios of 7.0 (6.2–7.8) for cardiovascular death, 4.4 (3.4–5.6) for infection death, 1.5 (1.4–1.7) for cancer death, and 2.0 (1.7–2.4) for other causes of death. There was substantial heterogeneity in causes of death, both in terms of crude proportions and adjusted incidence rate ratios, among the 9 studied baseline CVDs. Conclusions Noncardiovascular death is common in people with CVD, although its contribution varies widely between people with different CVDs. Holistic and personalized care are likely to be important tools for continuing to improve outcomes in people with CVD.

scholarly journals Mortality in Norway and Sweden during the COVID-19 pandemic

2021 ◽  
pp. 140349482110471
Author(s):  
Frederik E. Juul ◽  
Henriette C. Jodal ◽  
Ishita Barua ◽  
Erle Refsum ◽  
Ørjan Olsvik ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Excess Mortality ◽  
Mortality Rates ◽  
Mitigation Measures ◽  
Real World Data ◽  
School Closures ◽  
All Cause Mortality ◽  
Rate Ratios ◽  
Excess Deaths ◽  
Related Mortality

Background: Norway and Sweden are similar countries in terms of socioeconomics and health care. Norway implemented extensive COVID-19 measures, such as school closures and lockdowns, whereas Sweden did not. Aims: To compare mortality in Norway and Sweden, two similar countries with very different mitigation measures against COVID-19. Methods: Using real-world data from national registries, we compared all-cause and COVID-19-related mortality rates with 95% confidence intervals (CI) per 100,000 person-weeks and mortality rate ratios (MRR) comparing the five preceding years (2015–2019) with the pandemic year (2020) in Norway and Sweden. Results: In Norway, all-cause mortality was stable from 2015 to 2019 (mortality rate 14.6–15.1 per 100,000 person-weeks; mean mortality rate 14.9) and was lower in 2020 than from 2015 to 2019 (mortality rate 14.4; MRR 0.97; 95% CI 0.96–0.98). In Sweden, all-cause mortality was stable from 2015 to 2018 (mortality rate 17.0–17.8; mean mortality rate 17.1) and similar to that in 2020 (mortality rate 17.6), but lower in 2019 (mortality rate 16.2). Compared with the years 2015–2019, all-cause mortality in the pandemic year was 3% higher due to the lower rate in 2019 (MRR 1.03; 95% CI 1.02–1.04). Excess mortality was confined to people aged ⩾70 years in Sweden compared with previous years. The COVID-19-associated mortality rates per 100,000 person-weeks during the first wave of the pandemic were 0.3 in Norway and 2.9 in Sweden. Conclusions: All-cause mortality in 2020 decreased in Norway and increased in Sweden compared with previous years. The observed excess deaths in Sweden during the pandemic may, in part, be explained by mortality displacement due to the low all-cause mortality in the previous year.

scholarly journals Comparison of Indexes to Measure Comorbidity Burden and Predict All-Cause Mortality in Rheumatoid Arthritis

2021 ◽  
Author(s):  
Yun Ju Huang ◽  
Jung Sheng Chen ◽  
Shue Fen Luo ◽  
Chang Fu Kuo
Keyword(s):  
Rheumatoid Arthritis ◽  
Incidence Rate ◽  
Predictive Ability ◽  
Mortality Rates ◽  
Population Based ◽  
Comorbidity Burden ◽  
All Cause Mortality ◽  
Before And After ◽  
Comorbidity Index ◽  
Rate Ratios

Objectives To examine the comorbidity burden in patients with rheumatoid arthritis (RA) patients using a nationwide population-based cohort by assessing the Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), Multimorbidity Index (MMI), and Rheumatic Disease Comorbidity Index (RDCI) scores and to investigate their predictive ability for all-cause mortality. Methods We identified 24,767 RA patients diagnosed between 1998–2008 in Taiwan and followed up until December 31, 2013. The incidence of comorbidities was estimated in three periods (before, during, and after the diagnostic period). The incidence rate ratios were calculated by comparing during vs. before and after vs. before the diagnostic period. One- and 5-year mortality rates were calculated and discriminated by low and high-score groups and modified models for each index. Results The mean score at diagnosis is 0.8 in CCI, 2.8 in ECI, 0.7 in MMI, and 1.3 in RDCI, and annual percentage changes are 11.0%, 11.3%, 9.7%, and 6.8%, respectively. The incidence of any increase in the comorbidity index is significantly higher in the periods of ‘during’ and ‘after’ the RA diagnosis (incidence rate ratios for different indexes: 1.33-2.77). The mortality rate significantly differs between the high and low-score groups measured by each index (adjusted hazard ratios: 2.5-4.3 for different indexes). CCI is slightly better in the prediction of 1- and 5-year mortality rates. Conclusion Comorbidities are common before and after RA diagnosis, and the rate of accumulation accelerates after RA diagnosis. All four comorbidity indexes are useful to measure the temporal changes and to predict mortality.

scholarly journals Comparison of Indexes to Measure Comorbidity Burden and Predict All-Cause Mortality in Rheumatoid Arthritis

2021 ◽  
Vol 10 (22) ◽  
pp. 5460
Author(s):  
Yun-Ju Huang ◽  
Jung-Sheng Chen ◽  
Shue-Fen Luo ◽  
Chang-Fu Kuo
Keyword(s):  
Rheumatoid Arthritis ◽  
Incidence Rate ◽  
Predictive Ability ◽  
Mortality Rates ◽  
Population Based ◽  
Comorbidity Burden ◽  
All Cause Mortality ◽  
Before And After ◽  
Comorbidity Index ◽  
Rate Ratios

Objectives: To examine the comorbidity burden in patients with rheumatoid arthritis (RA) patients using a nationwide population-based cohort by assessing the Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), Multimorbidity Index (MMI), and Rheumatic Disease Comorbidity Index (RDCI) scores and to investigate their predictive ability for all-cause mortality. Methods: We identified 24,767 RA patients diagnosed from 1998 to 2008 in Taiwan and followed up until 31 December 2013. The incidence of comorbidities was estimated in three periods (before, during, and after the diagnostic period). The incidence rate ratios were calculated by comparing during vs. before and after vs. before the diagnostic period. One- and 5-year mortality rates were calculated and discriminated by low and high-score groups and modified models for each index. Results: The mean score at diagnosis was 0.8 in CCI, 2.8 in ECI, 0.7 in MMI, and 1.3 in RDCI, and annual percentage changes are 11.0%, 11.3%, 9.7%, and 6.8%, respectively. The incidence of any increase in the comorbidity index was significantly higher in the periods of “during” and “after” the RA diagnosis (incidence rate ratios for different indexes: 1.33–2.77). The mortality rate significantly differed between the high and low-score groups measured by each index (adjusted hazard ratios: 2.5–4.3 for different indexes). CCI was slightly better in the prediction of 1- and 5-year mortality rates. Conclusions: Comorbidities are common before and after RA diagnosis, and the rate of accumulation accelerates after RA diagnosis. All four comorbidity indexes are useful to measure the temporal changes and to predict mortality.

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