scholarly journals Remdesivir treatment in hospitalized patients with COVID-19: a comparative analysis of in-hospital all-cause mortality in a large multi-center observational cohort

2021 ◽  
Author(s):  
Essy Mozaffari ◽  
Aastha Chandak ◽  
Zhiji Zhang ◽  
Shuting Liang ◽  
Mark Thrun ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Statistical Significance ◽  
Invasive Mechanical Ventilation ◽  
Supplemental Oxygen ◽  
Cox Proportional Hazards ◽  
Low Flow ◽  
Healthcare Database ◽  
Cox Proportional Hazards Models ◽  
High Flow Oxygen ◽  
Oxygenation Level

Abstract Background Remdesivir (RDV) improved clinical outcomes among hospitalized COVID-19 patients in randomized trials, but data from clinical practice are limited. Methods We examined survival outcomes for US patients hospitalized with COVID-19 between Aug-Nov 2020 and treated with RDV within two-days of hospitalization vs. those not receiving RDV during their hospitalization using the Premier Healthcare Database. Preferential within-hospital propensity score matching with replacement was used. Additionally, patients were also matched on baseline oxygenation level (no supplemental oxygen charges (NSO), low-flow oxygen (LFO), high-flow oxygen/non-invasive ventilation (HFO/NIV) and invasive mechanical ventilation/ECMO (IMV/ECMO) and two-month admission window and excluded if discharged within 3-days of admission (to exclude anticipated discharges/transfers within 72-hrs consistent with ACTT-1 study). Cox Proportional Hazards models were used to assess time to 14-/28-day mortality overall and for patients on NSO, LFO, HFO/NIV and IMV/ECMO. Results 28,855 RDV patients were matched to 16,687 unique non-RDV patients. Overall, 10.6% and 15.4% RDV patients died within 14- and 28-days, respectively compared with 15.4% and 19.1% non-RDV patients. Overall, RDV was associated with a reduction in mortality at 14-days (HR[95% CI]: 0.76[0.70−0.83]) and 28-days (0.89[0.82−0.96]). This mortality benefit was also seen for NSO, LFO and IMV/ECMO at 14-days (NSO:0.69[0.57−0.83], LFO:0.68[0.80−0.77], IMV/ECMO:0.70[0.58−0.84]) and 28-days (NSO:0.80[0.68−0.94], LFO:0.77[0.68−0.86], IMV/ECMO:0.81[0.69−0.94]). Additionally, HFO/NIV RDV group had a lower risk of mortality at 14-days (0.81[0.70−0.93]) but no statistical significance at 28-days. Conclusions RDV initiated upon hospital admission was associated with improved survival among COVID-19 patients. Our findings complement ACTT-1 and support RDV as a foundational treatment for hospitalized COVID-19 patients.

scholarly journals Clinical management of hospitalized COVID-19 patients in the United States

2021 ◽  
Author(s):  
Essy Mozaffari ◽  
Aastha Chandak ◽  
Zhiji Zhang ◽  
Shuting Liang ◽  
Julie Gayle ◽  
...  
Keyword(s):  
Clinical Management ◽  
Invasive Mechanical Ventilation ◽  
Corticosteroid Treatment ◽  
The United States ◽  
Supplemental Oxygen ◽  
Low Flow ◽  
Healthcare Database ◽  
High Flow Oxygen ◽  
Evidence Based Treatments ◽  
Over Time

Abstract Objective The objective of this study was to characterize hospitalized COVID-19 patients and describe their real-world treatment patterns and outcomes over time. Methods Adult patients hospitalized 5/1/2020–12/31/2020 with a discharge diagnosis of COVID-19 were identified from the Premier Healthcare Database. Patient and hospital characteristics, treatments, baseline severity based on oxygen support, length of stay (LOS), ICU utilization and mortality were examined. Results The study included 295 657 patients (847 hospitals), with median age(IQR) of 66(54-77) years. Majority were male, white, and over 65. Approximately 85% had no supplemental oxygen charges (NSOc) or low-flow oxygen (LFO) at baseline, while 75% received no more than NSOc or LFO as maximal oxygen support at any time during hospitalization. Remdesivir (RDV) and corticosteroid treatment utilization increased over time. By December, 50% were receiving RDV and 80% were receiving corticosteroids. A higher proportion initiated COVID-19 treatments within two days of hospitalization in December vs May (RDV: 87% vs 40%; corticosteroids: 93% vs 62%; convalescent plasma: 68% vs 26%). There was a shift toward initiating RDV in patients on NSOc or LFO (68.0% (May) vs. 83.1% (December)). Median LOS decreased over time. Overall mortality was 13.5% and it was highest for severe patients (invasive mechanical ventilation/ECMO (IMV/ECMO):53.7%, high-flow oxygen/non-invasive ventilation (HFO/NIV):32.2%, LFO:11.7%, NSOc:7.3%). ICU use decreased, while mortality decreased for NSOc and LFO. Conclusions Clinical management of COVID-19 is rapidly evolving. This large observational study found that use of evidence-based treatments increased from May to December 2020, while improvement in outcomes occurred over this time-period.

Significance of tertiary pattern 5 in patients with gleason score 7 after radical prostatectomy.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 117-117
Author(s):  
Jiakun Li ◽  
Yaochuan Guo ◽  
Shi Qiu ◽  
Mingjing He ◽  
Kun Jin ◽  
...  
Keyword(s):  
Radical Prostatectomy ◽  
Gleason Score ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Statistical Significance ◽  
Strong Association ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Gleason Pattern ◽  
Cox Proportional Hazards Models

117 Background: To evaluate the association between tertiary Gleason pattern (TGP) 5 and the biochemical recurrence (BCR) in patients with prostate cancer (PCa) of Gleason score (GS) 7 after radical prostatectomy(RP). Methods: This retrospective study collected 387 patients received RP and diagnosed GS 7 (3+4 or 4+3) in the West China Hospital from January 2009 to December 2017.Regardlessly the first Gleason pattern, patients were divide into 2 groups: TGP5 absence and TGP5 presence. Furthermore, we added the primary Gleason pattern to divided patients into 4 groups: GS 3+4, GS 3+4/TGP 5, Gleason 4+3, Gleason 4+3/TGP 5. Cox proportional-hazards models was used to evaluate the association between the status of TGP5 and BCR after adjusting the confounding factors with follow-up time as the underlying time scale. All the analyses were conducted with the use of statistical software packages Rnand EmpowerStats and conducted as two sides and P values less than 0.05 were considered statistical significance. Results: In the results by using Cox proportional-hazards model, regardless the primary Gleason pattern, comparing TGP5 absence (89.7%) and presence (10.3%), the risk of BCR for patients with tertiary Gleason pattern 5 presence was statistically significantly higher than absence (P = 0.02, HR = 2.24, 95%Cl: 1.12-4.49). In terms of the patients with primary Gleason pattern 4, the risk of BCR for patients with Gleason 4+3/TGP5 was statistically significantly higher than Gleason 4+3.(P = 0.02, HR = 2.56, 95%Cl: 1.16-5.67). There was a marked trend that patients with Gleason 3+4/TGP 5 has a higher risk of BCR compared with patients with Gleason 3+4, although there was no statistical difference (P = 0.58, HR = 1.82, 95%Cl: 0.22-14.96). Conclusions: The TGP5 in patients with GS 7 had strong association with the risk of BCR and it was an independent predictor for BCR. This result was more obvious in patients with GS 7 (4+3) in our study. Further researches with larger data size were needed to confirm these funding.

scholarly journals Characteristics and outcomes of an international cohort of 400,000 hospitalised patients with Covid-19

2021 ◽  
Author(s):  
◽  
Christiana Kartsonaki
Keyword(s):  
Clinical Outcomes ◽  
Proportional Hazards ◽  
Invasive Mechanical Ventilation ◽  
Case Fatality ◽  
Cox Proportional Hazards ◽  
Risk Of Death ◽  
Cox Proportional Hazards Models ◽  
Hospitalised Patients ◽  
Male Sex ◽  
Viable Model

Background: Policymakers need robust data to respond to the COVID-19 pandemic. We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, the world's largest international, standardised cohort of hospitalised patients. Methods: The dataset analysed includes COVID-19 patients hospitalised between January 2020 and May 2021. We investigated how symptoms on admission, comorbidities, risk factors, and treatments varied by age, sex, and other characteristics. We used Cox proportional hazards models to investigate associations between demographics, symptoms, comorbidities, and other factors with risk of death, admission to intensive care unit (ICU), and invasive mechanical ventilation (IMV). Findings: 439,922 patients with laboratory-confirmed (91.7%) or clinically-diagnosed (8.3%) SARS-CoV-2 infection from 49 countries were enrolled. Age (adjusted hazard ratio [HR] per 10 years 1.49 [95% CI 1.49-1.50]) and male sex (1.26 [1.24-1.28]) were associated with a higher risk of death. Rates of admission to ICU and use of IMV increased with age up to age 60, then dropped. Symptoms, comorbidities, and treatments varied by age and had varied associations with clinical outcomes. Tuberculosis was associated with an 86% higher risk of death, and HIV with an 87% higher risk of death. Case fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients. Interpretation: The size of our international database and the standardized data collection method makes this study a reliable and comprehensive international description of COVID-19 clinical features. This is a viable model to be applied to future epidemics.

Abstract 15633: Clinical Features and Prognosis of Acute Cardiac Injury in Hospitalized Patients With Covid-19: A Retrospective Cohort Study

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Mingxing XIE ◽  
Li Zhang ◽  
Yuji Xie ◽  
yanting zhang ◽  
Wei Sun ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Proportional Hazards ◽  
Troponin I ◽  
Clinical Laboratory ◽  
Invasive Mechanical Ventilation ◽  
Cardiac Injury ◽  
Final Analysis ◽  
Cox Proportional Hazards ◽  
Hospitalized Patients ◽  
High Flow Oxygen

Background: The number of fatalities due to coronavirus disease 2019 (COVID-19) is escalating. However, information on critical complications in hospitalized patients of COVID-19 is scant. We aimed to explore the prevalence of acute cardiac injury and its association with in-hospital mortality in COVID-19 patients. Method: This retrospective study analyzed patients confirmed with COVID-19 in Union Hospital (Wuhan, China) from Jan 24 to March 18, 2020. Clinical outcomes (discharge, or death) were monitored to April 9, 2020, the latest date of follow-up. Demographic, clinical, laboratory, echocardiographic data as well as treatment and prognosis were analyzed. Comparisons were made between patients with acute cardiac injury and those without. An association of acute cardiac injury and in-hospital mortality was identified. Results: A total of 235 COVID-19 patients were included in the final analysis. Their median age was 66 years (interquartile range 57 - 73 years), and 131 (55.7%) were men. 98 (41.7%) patients were diagnosed with acute cardiac injury, of whom 60 (61.2%) died. There were more comorbidities in those who had acute cardiac injury than those who did not have. A higher proportion of patients with acute cardiac injury received glucocorticoid therapy (68.0% vs 37.0%; P < 0.001), immunoglobulin (53.1% vs 30.1%; P < 0.001), high-flow oxygen (79.6% vs 43.1%; P < 0.001), and invasive mechanical ventilation (40.8% vs 6.6%; P < 0.001) than those without acute cardiac injury. The percentage of patients who were admitted to intensive care unit (39.8 % vs 8.0%; P < 0.001) or died during hospitalization (61.2% vs 8.0%, P < 0.001) were also higher in those with acute cardiac injury. Plasma high-sensitivity troponin I levels correlated significantly with plasma interleukin -6, procalcitonin and C-reactive protein levels in COVID-19 patients. Echocardiography showed the cardiac function was attenuated in acute cardiac injury patients. Multivariable Cox proportional hazards regression analysis showed acute cardiac injury was an independent risk factor for higher in-hospital mortality in COVID-19 patients (HR, 3.393; 95% CI, 1.647- 6.987, P <0.001).

Utilization and outcomes of early respiratory support in 6.5 million acute heart failure hospitalizations

2019 ◽  
Author(s):  
Thomas S Metkus ◽  
Robert Scott Stephens ◽  
Steven Schulman ◽  
Steven Hsu ◽  
David A Morrow ◽  
...  
Keyword(s):  
Heart Failure ◽  
High Risk ◽  
Hospital Mortality ◽  
Acute Heart Failure ◽  
Proportional Hazards ◽  
Invasive Mechanical Ventilation ◽  
Cox Proportional Hazards ◽  
Respiratory Support ◽  
High Risk Population ◽  
Cox Proportional Hazards Models

Abstract Aims  The incidence and outcomes of a requirement for non-invasive ventilation (NIV) or invasive mechanical ventilation (IMV) in acute heart failure (AHF) hospitalization are not clearly established. Thus, we aimed to characterize the incidence and trends in use of IMV and NIV in AHF and to estimate the magnitude of hazard for mortality associated with requiring IMV and NIV in AHF. Methods and results  We used the National Inpatient Sample (NIS) to identify AHF hospitalizations between 2008 and 2014. The exposure variable of interest was IMV or NIV use within 24 h of hospital admission compared to no respiratory support. We analysed the association between ventilation strategies and in-hospital mortality using Cox proportional hazards models adjusting for demographics and comorbidities. We included 6 534 675 hospitalizations for AHF. Of these, 271 589 (4.16%) included NIV and 51 459 (0.79%) included IMV within the first 24 h of hospitalization and rates of NIV and IMV use increased over time. In-hospital mortality for AHF hospitalizations including NIV was 5.0% and 27% for IMV compared with 2.1% for neither (P < 0.001 for both). In an adjusted model, requirement for NIV was associated with over two-fold higher risk for in-hospital mortality [hazard ratio (HR) 2.10, 95% confidence interval (CI) 2.01–2.19; P < 0.001] and requirement for IMV was associated with over three-fold higher risk for in-hospital mortality (HR 3.39, 95% CI 3.14–3.66; P < 0.001). Conclusion  Respiratory support is used in many AHF hospitalizations, and AHF patients who require respiratory support are at high risk for in-hospital mortality. Our work should inform prospective intervention trials and quality improvement ventures in this high-risk population.

Incidence and survival of patients with T0N1 breast cancers.

2014 ◽  
Vol 32 (26_suppl) ◽  
pp. 56-56
Author(s):  
Shoko Emily Abe ◽  
Kendall W. Carpenter ◽  
Yimei Han ◽  
Teresa Flippo ◽  
Terry Sarantou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Proportional Hazards ◽  
Statistical Significance ◽  
Breast Cancer Incidence ◽  
Cox Proportional Hazards ◽  
Breast Cancers ◽  
Chi Square ◽  
Cox Proportional Hazards Models ◽  
Seer Data ◽  
Chi Square Test

56 Background: As imaging modalities have improved, breast cancers are increasingly detected at earlier stages. Patients rarely present with axillary disease but no mammographically evident breast tumor. Based on analysis of Surveillance, Epidemiology and End Results (SEER) data, we determined that there has been an increase in incidence of T1aN1 breast cancers. In response, we hypothesize that T0N1 breast cancer incidence has decreased with increased MRI use. Moreover, SEER analysis showed that T1aN1 patients have worse survival than T1bN1 patients. We thus hypothesize that T0N1 patients have worse survival than T1N1 patients. Methods: We identified 36,093 female patients diagnosed with T0-1 N1 invasive breast cancer from the SEER database. We compared patient and tumor characteristics: age, race, histology, hormone receptor status, and diagnosis year group (1990-1994, 1995-1999, 2000-2005, 2006-2010) – by TN category (T0N1/T1aN1/T1bN1/T1cN1) using chi-square test and ANOVA. Kaplan-Meier method was used to estimate disease specific survival (DSS) for each TN category and diagnosis year group separately. Adjusted hazard ratios were estimated using Cox proportional hazards models. Results: Stage distribution was: T0N1=129, T1aN1=1294, T1bN1=6731, and T1cN1=27942 patients. Median ages were 59.6, 56.3, 59.1, and 58.1, respectively. Time trend analysis of T0N1 cancers showed an increase in incidence from 1990 to 1999 and stability after 2000. Five-year DSS was significantly worse for patients with T0N1 tumors than T1aN1 tumors (84.5% versus 94.1%, HR 0.513, p < 0.0001). T0N1 tumors were more likely to be ER negative than T1b-cN1 tumors (23% versus 16%, p < 0.0001). T0N1 tumors were also more likely to be ER negative than T1aN1 tumors, but did not reach statistical significance (23% vs. 20%, p = 0.09). The proportion of lobular cancers was significantly higher in T0N1 than T1aN1 or T1b-cN1 patients (18% versus 8%, p < 0.0001). Conclusions: Our analysis suggests that T0N1 tumors may differ biologically from T1N1 tumors. Although the incidence of T0N1 tumors did not decrease, it remained stable after 2000 when the use of MRI for occult breast cancers became widely accepted. Our second hypothesis that survival is worse in patients with T0N1 tumors was confirmed by our analysis.

scholarly journals Dexamethasone in hospitalised coronavirus-19 patients not on intensive respiratory support

2021 ◽  
pp. 2102532
Author(s):  
Kristina Crothers ◽  
Rian DeFaccio ◽  
Janet Tate ◽  
Patrick R. Alba ◽  
Matthew Bidwell Goetz ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Respiratory Support ◽  
Low Flow ◽  
Potential Harm ◽  
Cox Proportional Hazards Models ◽  
Veterans Affairs Hospitals ◽  
Increased Risk ◽  
All Cause Mortality ◽  
Mortality Hazard Ratio

IntroductionDexamethasone decreases mortality in coronavirus disease 2019 (COVID-19) patients on intensive respiratory support (IRS) but is of uncertain benefit if less severely ill. We determined whether early (within 48 h) dexamethasone was associated with mortality in patients hospitalised with COVID-19 not on IRS.MethodsWe included patients admitted to Veterans Affairs hospitals between June 7, 2020-May 31, 2021 within 14-days after SARS-CoV-2 positive test. Exclusions included recent prior corticosteroids and IRS within 48 h. We used inverse probability of treatment weights (IPTW) to balance exposed and unexposed groups, and Cox proportional hazards models to determine 90-day all-cause mortality.ResultsOf 19 973 total patients (95% men, median age 71, 27% black), 15 404 (77%) were without IRS within 48 h. Of these, 3514/9450 (34%) patients on no oxygen received dexamethasone and 1042 (11%) died; 4472/5954 (75%) patients on low-flow nasal cannula (NC) received dexamethasone and 857 (14%) died. In IPTW stratified models, patients on no oxygen who received dexamethasone experienced 76% increased risk for 90-day mortality (hazard ratio [HR] 1.76, 95% confidence interval [CI] 1.47 to 2.12); there was no association with mortality among patients on NC (HR 1.08, 95% CI 0.86 to 1.36).ConclusionIn patients hospitalised with COVID-19, early initiation of dexamethasone was common and was associated with no mortality benefit among those on no oxygen or NC in the first 48 h; instead, we found evidence of potential harm. These real-world findings do not support the use of early dexamethasone in hospitalised COVID-19 patients without IRS.

scholarly journals Impact of Multiple Social Determinants of Health on Incident Stroke

Stroke ◽  
2020 ◽  
Vol 51 (8) ◽  
pp. 2445-2453 ◽  
Author(s):  
Evgeniya Reshetnyak ◽  
Mariella Ntamatungiro ◽  
Laura C. Pinheiro ◽  
Virginia J. Howard ◽  
April P. Carson ◽  
...  
Keyword(s):  
Social Determinants Of Health ◽  
Racial Differences ◽  
Social Determinants ◽  
Proportional Hazards ◽  
Statistical Significance ◽  
Cox Proportional Hazards ◽  
Hazard Ratio ◽  
Determinants Of Health ◽  
Cox Proportional Hazards Models ◽  
The Individual

Background and Purpose: Social determinants of health (SDOH) have been previously associated with incident stroke. Although SDOH often cluster within individuals, few studies have examined associations between incident stroke and multiple SDOH within the same individual. The objective was to determine the individual and cumulative effects of SDOH on incident stroke. Methods: This study included 27 813 participants from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study, a national, representative, prospective cohort of black and white adults aged ≥45 years. SDOH was the primary exposure. The main outcome was expert adjudicated incident stroke. Cox proportional hazards models examined associations between incident stroke and SDOH, individually and as a count of SDOH, adjusting for potential confounders. Results: The mean age was 64.7 years (SD 9.4) at baseline; 55.4% were women and 40.4% were blacks. Over a median follow-up of 9.5 years (IQR, 6.0–11.5), we observed 1470 incident stroke events. Of 10 candidate SDOH, 7 were associated with stroke ( P <0.10): race, education, income, zip code poverty, health insurance, social isolation, and residence in one of the 10 lowest ranked states for public health infrastructure. A significant age interaction resulted in stratification at 75 years. In fully adjusted models, among individuals <75 years, risk of stroke rose as the number of SDOH increased (hazard ratio for one SDOH, 1.26 [95% CI, 1.02–1.55]; 2 SDOH hazard ratio, 1.38 [95% CI, 1.12–1.71]; and ≥3 SDOH hazard ratio, 1.51 [95% CI, 1.21–1.89]) compared with those without any SDOH. Among those ≥75 years, none of the observed effects reached statistical significance. Conclusions: Incremental increases in the number of SDOH were independently associated with higher incident stroke risk in adults aged <75 years, with no statistically significant effects observed in individuals ≥75 years. Targeting individuals with multiple SDOH may help reduce risk of stroke among vulnerable populations.

scholarly journals Factors Predictive of Obliteration After Arteriovenous Malformation Radiosurgery

2011 ◽  
Vol 38 (6) ◽  
pp. 845-850 ◽  
Author(s):  
C. Herbert ◽  
V. Moiseenko ◽  
M. McKenzie ◽  
G. Redekop ◽  
F. Hsu ◽  
...  
Keyword(s):  
Stereotactic Radiosurgery ◽  
Arteriovenous Malformations ◽  
Proportional Hazards ◽  
Statistical Significance ◽  
Univariate Analysis ◽  
Cox Proportional Hazards ◽  
Rank Test ◽  
Log Rank Test ◽  
Cox Proportional Hazards Models ◽  
Complete Obliteration

Objective:To investigate predictive factors of complete obliteration following treatment with linac-based stereotactic radiosurgery for intracerebral arteriovenous malformations.Methods:Archived plans for 48 patients treated at the British Columbia Cancer Agency and who underwent post-treatment digital subtraction angiography to assess obliteration were studied. Actuarial estimates of obliteration were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of incidence of obliteration. Log-rank test was used to search for parameters associated with obliteration.Results:Complete nidus obliteration was achieved in 38/48 patients (79.2%). Actuarial rate of obliteration was 75.9% at 4 years (95% confidence interval 63.1%-88.6%). On univariate analysis, prescribed dose to the margin (p=0.002) and dose to isocentre (p=0.022) showed statistical significance. No parameters were significant in a multivariate model. According to the log-rank test, prescribed dose to the margin of >20 Gy (p=0.004) and dose to the isocentre of >25 Gy (p=0.004) were associated with obliteration.Conclusion:Reported series in the literature suggest a number of different factors are predictive of complete obliteration of arteriovenous malformations following radiosurgery. However, differing definitions of volume and complete obliteration makes direct comparison between series difficult. This study demonstrates that complete obliteration of the nidus following linear accelerator-based stereotactic radiosurgery for arteriovenous malformations appears to be most closely related to the prescribed marginal dose. In particular, a marginal dose of >20Gy is strongly associated with obtaining complete obliteration of the nidus.

scholarly journals A semi-supervised approach for rapidly creating clinical biomarker phenotypes in the UK Biobank using different primary care EHR and clinical terminology systems

JAMIA Open ◽  
2020 ◽  
Author(s):  
Spiros Denaxas ◽  
Anoop D Shah ◽  
Bilal A Mateen ◽  
Valerie Kuan ◽  
Jennifer K Quint ◽  
...  
Keyword(s):  
Primary Care ◽  
Proportional Hazards ◽  
Biomarker Discovery ◽  
Data Extraction ◽  
Cox Proportional Hazards ◽  
Research Quality ◽  
Uk Biobank ◽  
Expert Review ◽  
Cox Proportional Hazards Models ◽  
The Uk

Abstract Objectives The UK Biobank (UKB) is making primary care electronic health records (EHRs) for 500 000 participants available for COVID-19-related research. Data are extracted from four sources, recorded using five clinical terminologies and stored in different schemas. The aims of our research were to: (a) develop a semi-supervised approach for bootstrapping EHR phenotyping algorithms in UKB EHR, and (b) to evaluate our approach by implementing and evaluating phenotypes for 31 common biomarkers. Materials and Methods We describe an algorithmic approach to phenotyping biomarkers in primary care EHR involving (a) bootstrapping definitions using existing phenotypes, (b) excluding generic, rare, or semantically distant terms, (c) forward-mapping terminology terms, (d) expert review, and (e) data extraction. We evaluated the phenotypes by assessing the ability to reproduce known epidemiological associations with all-cause mortality using Cox proportional hazards models. Results We created and evaluated phenotyping algorithms for 31 biomarkers many of which are directly related to COVID-19 complications, for example diabetes, cardiovascular disease, respiratory disease. Our algorithm identified 1651 Read v2 and Clinical Terms Version 3 terms and automatically excluded 1228 terms. Clinical review excluded 103 terms and included 44 terms, resulting in 364 terms for data extraction (sensitivity 0.89, specificity 0.92). We extracted 38 190 682 events and identified 220 978 participants with at least one biomarker measured. Discussion and conclusion Bootstrapping phenotyping algorithms from similar EHR can potentially address pre-existing methodological concerns that undermine the outputs of biomarker discovery pipelines and provide research-quality phenotyping algorithms.

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