Relevance of comorbidities for main outcomes during different periods of the COVID-19 pandemic

Background

Throughout the evolution of the COVID-19 pandemic, the severity of the disease has varied. The aim of this study was to determine how patients' comorbidities affected and were related to, different outcomes during this time.

Methods

Retrospective cohort study of all patients testing positive for SARS-CoV-2 infection between March 1, 2020, and January 9, 2022. We extracted sociodemographic, basal comorbidities, prescribed treatments, COVID-19 vaccination data, and outcomes such as death and admission to hospital and intensive care unit (ICU) during the different periods of the pandemic. We used logistic regression to quantify the effect of each covariate in each outcome variable and a random forest algorithm to select the most relevant comorbidities.

Results

Predictors of death included having dementia, heart failure, kidney disease, or cancer, while arterial hypertension, diabetes, ischemic heart, cerebrovascular, peripheral vascular diseases, and leukemia were also relevant. Heart failure, dementia, kidney disease, diabetes, and cancer were predictors of adverse evolution (death or ICU admission) with arterial hypertension, ischemic heart, cerebrovascular, peripheral vascular diseases, and leukemia also relevant. Arterial hypertension, heart failure, diabetes, kidney, ischemic heart diseases, and cancer were predictors of hospitalization, while dyslipidemia and respiratory, cerebrovascular, and peripheral vascular diseases were also relevant.

Conclusions

Preexisting comorbidities such as dementia, cardiovascular and renal diseases, and cancers were those most related to adverse outcomes. Of particular note were the discrepancies between predictors of adverse outcomes and predictors of hospitalization and the fact that patients with dementia had a lower probability of being admitted in the first wave.

Reference values of EORTC QLQ-C30, EORTC QLQ-BR23, and EQ-5D-5L for women with non-metastatic breast cancer at diagnosis and 2 years after

PURPOSE

To obtain reference norms of EORTC QLQ-C30, EORTC QLQ-BR23, and EQ-5D-5L, based on a population of Spanish non-metastatic breast cancer patients at diagnosis and 2 years after, according to relevant demographic and clinical characteristics.

METHODS

Multicentric prospective cohort study including consecutive women aged ≥ 18 years with a diagnosis of incident non-metastatic breast cancer from April 2013 to May 2015. Health-related quality of life (HRQoL) questionnaires were administered between diagnosis and beginning the therapy, and 2 years after. HRQoL differences according to age, comorbidity and stage were tested with ANOVA or Chi Square test and multivariate linear regression models.

RESULTS

1276 patients were included, with a mean age of 58 years. Multivariate models of EORTC QLQ-C30 summary score and EQ-5D-5L index at diagnosis and at 2-year follow-up show the independent association of comorbidity and tumor stage with HRQoL. The standardized multivariate regression coefficient of EORTC QLQ-C30 summary score was lower (poorer HRQoL) for women with stage II and III than for those with stage 0 at diagnosis (- 0.11 and - 0.07, p < 0.05) and follow-up (- 0.15 and - 0.10, p < 0.01). The EQ-5D-5L index indicated poorer HRQoL for women with Charlson comorbidity index ≥ 2 than comorbidity 0 both at diagnosis (- 0.13, p < 0.001) and follow-up (- 0.18, p < 0.001). Therefore, we provided the reference norms at diagnosis and at the 2-year follow-up, stratified by age, comorbidity index, and tumor stage.

CONCLUSION

These HRQoL reference norms can be useful to interpret the scores of women with non-metastatic breast cancer, comparing them with country-specific reference values for this population.

[Risk factors for clinical deterioration in patients admitted for COVID-19: A case-control study]

INTRODUCTION

There is controversy regarding the best predictors of clinical deterioration in COVID-19.

OBJECTIVE

This work aims to identify predictors of risk factors for deterioration in patients hospitalized due to COVID-19.

METHODS DESIGN

Nested case-control study within a cohort. Setting: 13 acute care centers of the Osakidetza-Basque Health Service. Participants: Patients hospitalized for COVID-19 with clinical deterioration-defined as onset of severe ARDS, ICU admission, or death-were considered cases. Two controls were matched to each case based on age. Sociodemographic data; comorbidities; baseline treatment; symptoms; date of onset; previous consultations; and clinical, analytical, and radiological variables were collected. An explanatory model of clinical deterioration was created by means of conditional logistic regression.

RESULTS

A total of 99 cases and 198 controls were included. According to the logistic regression analysis, the independent variables associated with clinical deterioration were: emergency department O2 saturation ≤90% (OR 16.6; 95%CI 4-68), pathological chest X-ray (OR 5.6; 95%CI 1.7-18.4), CRP >100 mg/dL (OR 3.62; 95%CI 1.62-8), thrombocytopenia with < 150,000 platelets (OR 4; 95%CI 1.84-8.6); and a medical history of acute myocardial infarction (OR 15.7; 95%CI, 3.29-75.09), COPD (OR 3.05; 95%CI 1.43-6.5), or HT (OR 2.21; 95%CI 1.11-4.4). The model's AUC was 0.86. On the univariate analysis, female sex and presence of dry cough and sore throat were associated with better clinical progress, but were not found to be significant on the multivariate analysis.

CONCLUSION

The variables identified could be useful in clinical practice for the detection of patients at high risk of poor outcomes.

Risk factors for clinical deterioration in patients admitted for COVID-19: A case-control study

INTRODUCTION

There is controversy regarding the best predictors of clinical deterioration in COVID-19.

OBJECTIVE

This work aims to identify predictors of risk factors for deterioration in patients hospitalized due to COVID-19.

METHODS DESIGN

Nested case-control study within a cohort.

SETTING

13 acute care centers of the Osakidetza-Basque Health Service.

PARTICIPANTS

patients hospitalized for COVID-19 with clinical deterioration-defined as onset of severe ARDS, ICU admission, or death-were considered cases. Two controls were matched to each case based on age. Sociodemographic data; comorbidities; baseline treatment; symptoms; date of onset; previous consultations; and clinical, analytical, and radiological variables were collected. An explanatory model of clinical deterioration was created by means of conditional logistic regression.

RESULTS

A total of 99 cases and 198 controls were included. According to the logistic regression analysis, the independent variables associated with clinical deterioration were: emergency department O2 saturation ≤90% (OR 16.6; 95%CI 4-68), pathological chest X-ray (OR 5.6; 95%CI 1.7-18.4), CRP > 100 mg/dL (OR 3.62; 95%CI 1.62-8), thrombocytopenia with <150,000 platelets (OR 4; 95%CI 1.84-8.6); and a medical history of acute myocardial infarction (OR 15.7; 95%CI, 3.29-75.09), COPD (OR 3.05; 95%CI 1.43-6.5), or HT (OR 2.21; 95%CI 1.11-4.4). The model's AUC was 0.86. On the univariate analysis, female sex and presence of dry cough and sore throat were associated with better clinical progress, but were not found to be significant on the multivariate analysis.

CONCLUSION

The variables identified could be useful in clinical practice for the detection of patients at high risk of poor outcomes.

Predictors of mortality of COVID-19 in the general population and nursing homes

The factors that predispose an individual to a higher risk of death from COVID-19 are poorly understood. The goal of the study was to identify factors associated with risk of death among patients with COVID-19. This is a retrospective cohort study of people with laboratory-confirmed SARS-CoV-2 infection from February to May 22, 2020. Data retrieved for this study included patient sociodemographic data, baseline comorbidities, baseline treatments, other background data on care provided in hospital or primary care settings, and vital status. Main outcome was deaths until June 29, 2020. In the multivariable model based on nursing home residents, predictors of mortality were being male, older than 80 years, admitted to a hospital for COVID-19, and having cardiovascular disease, kidney disease or dementia while taking anticoagulants or lipid-lowering drugs at baseline was protective. The AUC was 0.754 for the risk score based on this model and 0.717 in the validation subsample. Predictors of death among people from the general population were being male and/or older than 60 years, having been hospitalized in the month before admission for COVID-19, being admitted to a hospital for COVID-19, having cardiovascular disease, dementia, respiratory disease, liver disease, diabetes with organ damage, or cancer while being on anticoagulants was protective. The AUC was 0.941 for this model's risk score and 0.938 in the validation subsample. Our risk scores could help physicians identify high-risk groups and establish preventive measures and better follow-up for patients at high risk of dying.ClinicalTrials.gov Identifier: NCT04463706.

Health services research in patients with breast cancer (CAMISS-prospective): study protocol for an observational prospective study

Background

Though breast cancer remains a major health problem, there is a lack of information on health care provided to patients with this disease and associated costs. In addition, there is a need to update and validate risk stratification tools in Spain. Our purpose is to evaluate the health services provided for breast cancer in Spain, from screening and diagnosis to treatment and prognosis.

Methods

Prospective cohort study involving 13 hospitals in Spain with a follow-up period of up to 5 years after diagnostic biopsy. Eligibility criteria: Patients diagnosed with breast cancer between April 2013 and May 2015 that have consented to participate in the study. Data collection: Data will be collected on the following: pre-intervention medical history, biological, clinical, and sociodemographic characteristics, mode of cancer detection, hospital admission, treatment, and outcomes up to 5 years after initial treatment. Questionnaires about quality of life (EuroQoL EQ-5D-5 L, the European Organization For Research And Treatment Of Cancer Core Quality Of Life Questionnaire EORTC QLQ-C30 join to the specific breast cancer module (QLQ-BR23), as well as Hospital Anxiety and Depression Scale were completed by the patients before the beginning of the initial treatment and at the end of follow-up period, 2 years later. The end-points of the study were changes in health-related quality of life, recurrence, complications and readmissions at 2 and 5 years after initial treatment. Statistical analysis: Descriptive statistics will be calculated and multivariate models will be used where appropriate to adjust for potential confounders. In order to create and validate a prediction model, split validation and bootstrapping will be performed. Cost analysis will be carried out from the perspective of a national health system.

Discussion

The results of this coordinated project are expected to generate scientifically valid and clinically and socially important information to inform the decision-making of managers and the authorities responsible for ensuring equality in care processes as well in health outcomes. For clinicians, clinical prediction rules will be developed which are expected to serve as the basis for the development of software applications.

Trial registration

NCT02439554. Date of registration: May 8, 2015 (retrospectively registered) .