Correlation of COVID-19 Mortality with Clinical Parameters in an Urban and Suburban Nursing Home Population

This article has been Reviewed by the following groups

Read the full article

Abstract

Importance and Objective

COVID-19 has a high mortality rate amongst nursing home populations (26.4% nationally and 28.3% in New Jersey). Identification of factors influencing mortality in COVID-19 positive nursing home populations may help direct physicians towards appropriate glycemic, blood pressure, weight, kidney function, lipid, thyroid, and hematologic management to reduce COVID-19 mortality.

Design, Setting, and Participants

Retrospective cross-sectional study of patients in two nursing home facilities (one urban, one suburban) from 3/16/2020 to 7/13/2020 with positive COVID-19 PCR assays. Age, race, sex, lipids, hematologic parameters, body mass index, blood pressure, thyroid function, albumin, blood urea nitrogen, creatinine, and hemoglobin A1c were correlated with COVID-19 mortality by chi-squared analysis.

Main Outcome and Results

56 patients met the inclusion criteria for the study. Mortality was 14.3% while the New Jersey nursing home average mortality rate was 28.3% as of August 2020. Our patient cohort had a 49.5% reduction in mortality compared to the state average.

In our overall cohort, none of the clinical parameters correlated with COVID-19 mortality using chi-squared analysis. In the 56 patient cohort, average clinical and laboratory findings were 74.0 years, 62.5% female, 28.5% uncontrolled hypertension, BMI 25.6, hemoglobin A1c 6.4, TSH 2.4, vitamin B12 568.3, folate 12.4, iron 47.8, total iron binding capacity 271.8, hemoglobin 11.6, albumin 3.5, triglycerides 100.3, total cholesterol 133.5, HDL 40.9, and BUN to Creatinine ratio 22.2:1. Logistic multivariate regression analyses failed to demonstrate clinically significant correlation with COVID-19 mortality.

In the urban nursing home, BUN to creatinine ratio exceeding 20:1 was the only factor that showed statistical significance to COVID-19 mortality (p = 0.03). In the suburban nursing home, age over 80 was the only clinical factor demonstrating statistical significance to COVID-19 mortality (p = 0.003).

Conclusions and Relevance

In our COVID-19 positive nursing home patients, no one parameter was clinically significant in the overall 56-patient cohort; however, mortality in our population was 14.3% compared to New Jersey’s 28.3%, a 49.5% reduction in mortality. Rigorous control of the aforementioned clinical parameters may have contributed to this reduction in mortality. Further research requires analysis of more nursing home patients to determine whether rigorous control of clinical parameters decreases mortality from COVID-19.

Key Points

Question

What clinical parameters lead to a lower mortality rate in nursing home patients with COVID-19?

Findings

In this cross-sectional analysis of 56 SARS-CoV-2 positive New Jersey nursing home residents from March to July 2020, controlling hemoglobin A1c, blood pressure, hematologic and lipid panels to recommended levels yielded a mortality rate of 14.3%, a 49.5% reduction from the 28.3% mortality rate of COVID-19 in New Jersey nursing homes.

Meaning

Maintaining rigorous control of clinical parameters in nursing home populations may account for a decreased mortality rate of COVID-19.

Article activity feed

  1. SciScore for 10.1101/2020.10.15.20213629: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Our study was approved by the Cooper University Hospital institutional review
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableThe patient cohort was 62.5% female, the median body mass index (BMI) was 25.6 with an IQR of 23.4 to 33.0, 61% of patients had diabetes, and 91% with hypertension defined as greater than 120/80 mm Hg.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Study strengths and limitations: All patients in the cohort were treated under the auspices of a single physician, who provided uniform care to all COVID-19 positive patients. Data was collected from two nursing home facilities. A large-scale review of nursing home charts from multiple physicians in multiple nursing homes across New Jersey (and perhaps nationwide) is needed for comparison between our cohort’s clinical parameters and those of other physicians in other nursing homes in New Jersey and nationally. However, despite this limited data set, we feel that the finding of decreased mortality in our cohort compared to New Jersey’s COVID-19 positive nursing home population is supported by the rigorous clinical parameter control detailed in Table 1.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.