BASELINE METABOLIC PROFILING AND RISK OF DEATH FROM COVID-19

ObjectiveTo derive a predicted probability of death (PDeathLabs) based upon complete value sets for 11 clinical measurements (CM) obtained on patients prior to their diagnosis of coronavirus disease (COVID-19). PDeathLabs is intended for use as a summary metric for baseline metabolic status in multivariate models for COVID-19 death. MethodsCases were identified through the COVID-19 Shared Data Resource (CSDR) of the Department of Veterans Affairs. The diagnosis required at least one positive nucleic acid amplification test (NAAT). The primary outcome was death within 60 days of the first positive test. We retrieved all values for systolic blood pressure (SBP), diastolic blood pressure (DBP), oxygen saturation (O2SAT), body mass index (BMI), estimated glomerular filtration rate (EGFR), alanine aminotransferase (ALT), serum albumin (ALB), hematocrit (HCT), LDL cholesterol (LDL) hemoglobin A1c (A1C), and HDL cholesterol (HDL) if they were done at least 14 days prior to the NAAT. Clinicians evaluate several attributes of CM that are of critical importance: metabolic control, disease burden, chronicity, refractoriness, tendency to relapse, temporal trends, and lability. We derived 1-3 parameters for each of these attributes: the most recent value (metabolic control); time-weighted average and abnormal area under a severity versus time curve (disease burden); time and number of readings above or below goal (chronicity); longest abnormal cluster and time/number of consecutive readings above goal if the last value was abnormal (refractoriness); number of abnormal clusters (tendency to relapse); long- and short-term changes (temporal trends); and coefficient of variation and mean deviation between consecutive readings (lability). We created computer programs to derive cumulative values for these 13 parameters for all 11 CM as each new value is added. A fitted logistic model was developed for each CM to determine which of the 13 parameters contributed to the risk of death. A main logistic model was developed to determine which of the 13 x 11 = 143 metabolic parameters were independently predictive of death. The resulting model was used to derive PDeathLabs for each patient and the area under its receiver operating characteristic (ROC) curve calculated. Single variable logistic models were also derived for age at diagnosis, the Charlson 2-year (Charl2Yr) and lifetime (CharlEver) scores, and the Elixhauser 2-year (Elix2Yrs) and lifetime (ElixEver) scores. Stata was used to compare the ROCs for PDeathDx and each of the other metrics. ResultsOn September 30, 2021, there were 347,220 COVID-19 patients in the CSDR. 329,491 (94.9%) patients had CM performed at least 14 days prior to the COVID-19 diagnosis and form the basis for this report. 17,934 (5.44%) died within 60 days of the diagnosis. On the subset regressions, the number of significant parameters ranged from all 13 for SBP to 7 for HDL. 239,393 patients had complete sets of data for developing the main model. Of 143 candidate predictors, 49 parameters were identified as statistically significant, independent predictors of death. The most influential domains were the most recent value, disease burden, temporal trends, and tendency to relapse. The ROC area for PDeathLabs was 0.785 +/- 0.002. No difference was found in the ROC areas of PDeathLabs and age at diagnosis (0.783 +/- 0.002; P = NS). However, the ROC area for PDeathLabs was significantly greater than that of Charl2Yrs (0.704 +/- 0.002; P < 0.001), CharlEver (0.729 +/- 0.002; P < 0.001), Elix2Yrs (0.675 {+/-} 0.002; P < 0.001), and ElixEver (0.707 +/- 0.002; P < 0.001). A poor prognosis was found for chronic systolic hypertension. On the other hand, a higher BMI was protective once SBP, DBP, HDL, LDL and A1C were considered. ConclusionsOur study confirms that parameters derived for 11 CM are significant determinants of COVID-19 death. The most recent value should not be selected over other parameters for multivariate modeling unless there is a physiologic basis for doing so. PDeathLabs has the same discriminating power as age at diagnosis and outperforms comorbidity indices as a summary metric for pre-existing conditions. If validated by others, this approach provides a robust approach to handling CM in multivariate models.

ESTIMATING THE EFFECT OF VACCINATION ON THE CASE-FATALITY RATE FOR COVID-19

ObjectiveTo evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections. DesignMultivariate modeling of data from electronic medical records Setting130 medical centers of the United States Department of Veterans Affairs Participants339,772 patients with COVID-19 confirmed by nucleic acid amplification testing as of September 30, 2021 MethodsThe primary outcome was death within 60 days of the diagnosis. Patients were considered vaccinated if they had completed a full series >= 14 days prior to diagnosis. Cases presenting in July - September of 2021 were considered to have the delta variant. Logistic regression was used to derive adjusted odds ratios (OR) for vaccination and infection with delta versus earlier variants. Models were adjusted for demographic traits, standard comorbidity indices, selected clinical terms, and 3 novel parameters representing all prior diagnoses, all prior vital signs/ baseline laboratory tests, and current outpatient treatment. Patients with a delta infection were divided into 8 cohorts based upon the time from vaccination to diagnosis (in 4-week blocks). A common model was used to estimate the odds of death associated with vaccination for each cohort relative that of all unvaccinated patients. Results9.1% of subjects had been fully vaccinated, and 21.5% were presumed to have the delta variant. 18,120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for delta infection was 1.87 +/- 0.05 which corresponds to a relative risk of 1.78. The overall adjusted OR for prior vaccination was 0.280 +/- 0.011 corresponding to a relative risk of 0.291. The study of vaccine cohorts with a delta infection showed that the raw CFR rose steadily after 10-14 weeks. However, the OR for vaccination remained stable for 10-34 weeks. ConclusionsOur study confirms that delta is substantially more lethal than earlier variants and that vaccination is an effective means of preventing COVID death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks.