The Experience of COVID-19 in a Sample of Gynecological Cancer Patients Undergoing Chemotherapy: A Focus on the Psychological Implications

Cancer patients are at an increased risk of developing severe consequences due to the COVID-19 infection. However, psychological outcomes in this population have been overlooked in the literature. The present study aims to identify significant psychological differences between gynecological cancer patients undergoing chemotherapy before and during the pandemic. Additionally, we explore the correlations between COVID-19-related concerns and anxiety, depression, distress, and quality of life levels. Forty-two patients completed the STAI-Y, the EORTC QLQ-C30, the BDI II, the DT, and an ad-hoc questionnaire that investigated COVID-19-related concerns. The analyses did not show significant differences in the psychometric scales between the two groups, highlighting a considerable resilience against mental health and quality of life deterioration during the COVID-19 pandemic in gynecologic cancer patients. However, COVID-19-related concerns were positively associated with anxiety and inversely related to emotional functioning levels. These results emphasize the importance of a comprehensive patient care and the need to implement a multidisciplinary approach that includes psychological support in the treatment plan. Moreover, it is essential to encourage clear communication to convey comprehensive information about the impact of the pandemic on physical and psychological levels, as well as to offer psychoeducational tools to face the pandemic.

The Experience of COVID-19 in a Sample of Gynecological Cancer Patients Undergoing Chemotherapy: A Focus on the Psychological Implications.

Cancer patients are at an increased risk of developing severe consequences due to the COVID-19 infection. However, psychological outcomes in this population have been overlooked in the literature. The present study aims to identify significant psychological differences between gynecological cancer patients undergoing chemotherapy before and during the pandemic. Additionally, we explore the correlations between COVID-19-related concerns and anxiety, depression, distress, and quality of life levels. Forty-two patients completed the STAI-Y, the EORTC QLQ-C30, the BDI II, the DT, and an ad-hoc questionnaire that investigated COVID-19-related concerns. The analyses did not show significant differences in the psychometric scales between the two groups, highlighting a considerable resilience against mental health and quality of life deterioration during the COVID-19 pandemic in gynecologic cancer patients. However, COVID-19-related concerns were positively associated with anxiety and inversely related to emotional functioning levels. These results emphasize the importance of a comprehensive patient care and the need to implement a multidisciplinary approach that includes psychological support in the treatment plan. Moreover, it is essential to encourage clear communication to convey comprehensive information about the impact of the pandemic on physical and psychological levels, as well as to offer psychoeducational tools to face the pandemic.

Modifiable risk factors of COVID-19 in patients with multiple sclerosis: a single-centre case-control study.

BACKGROUND: Disease and treatment-associated immune system abnormalities may confer higher risk of Coronavirus disease 2019 (COVID-19) to people with multiple sclerosis (PwMS). We assessed modifiable risk factors associated with COVID-19 in PwMS. METHODS: Among patients referring to our MS Center, we retrospectively collected epidemiological, clinical and laboratory data of PwMS with confirmed COVID-19 between March 2020 and March 2021 (MS-COVID, n = 149). We pursued a 1:2 matching of a control group by collecting data of PwMS without history of previous COVID-19 (MS-NCOVID, n = 292). MS-COVID and MS-NCOVID were matched for age, expanded disability status scale (EDSS) and line of treatment. We compared neurological examination, premorbid vitamin D levels, anthropometric variables, life-style habits, working activity, and living environment between the two groups. Logistic regression and Bayesian network analyses were used to evaluate the association with COVID-19. RESULTS: MS-COVID and MS-NCOVID were similar in terms of age, sex, disease duration, EDSS, clinical phenotype and treatment. At multiple logistic regression, higher levels of vitamin D (OR 0.93, p < 0.0001) and active smoking status (OR 0.27, p < 0.0001) emerged as protective factors against COVID-19. In contrast, higher number of cohabitants (OR 1.26, p = 0.02) and works requiring direct external contact (OR 2.61, p = 0.0002) or in the healthcare sector (OR 3.73, p = 0.0019) resulted risk factors for COVID-19. Bayesian network analysis showed that patients working in the healthcare sector, and therefore exposed to increased risk of COVID-19, were usually non-smokers, possibly explaining the protective association between active smoking and COVID-19. CONCLUSIONS: Higher Vitamin D levels and teleworking may prevent unnecessary risk of infection in PwMS.

CXCL10 levels at hospital admission predict COVID-19 outcome: hierarchical assessment of 53 putative inflammatory biomarkers in an observational study.

BACKGROUND: Host inflammation contributes to determine whether SARS-CoV-2 infection causes mild or life-threatening disease. Tools are needed for early risk assessment. METHODS: We studied in 111 COVID-19 patients prospectively followed at a single reference Hospital fifty-three potential biomarkers including alarmins, cytokines, adipocytokines and growth factors, humoral innate immune and neuroendocrine molecules and regulators of iron metabolism. Biomarkers at hospital admission together with age, degree of hypoxia, neutrophil to lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP) and creatinine were analysed within a data-driven approach to classify patients with respect to survival and ICU outcomes. Classification and regression tree (CART) models were used to identify prognostic biomarkers. RESULTS: Among the fifty-three potential biomarkers, the classification tree analysis selected CXCL10 at hospital admission, in combination with NLR and time from onset, as the best predictor of ICU transfer (AUC [95% CI] = 0.8374 [0.6233-0.8435]), while it was selected alone to predict death (AUC [95% CI] = 0.7334 [0.7547-0.9201]). CXCL10 concentration abated in COVID-19 survivors after healing and discharge from the hospital. CONCLUSIONS: CXCL10 results from a data-driven analysis, that accounts for presence of confounding factors, as the most robust predictive biomarker of patient outcome in COVID-19.

Quantitative assessment of lung involvement on chest CT at admission: Impact on hypoxia and outcome in COVID-19 patients.

BACKGROUND: The aim of this study was to quantify COVID-19 pneumonia features using CT performed at time of admission to emergency department in order to predict patients' hypoxia during the hospitalization and outcome. METHODS: Consecutive chest CT performed in the emergency department between March 1st and April 7th 2020 for COVID-19 pneumonia were analyzed. The three features of pneumonia (GGO, semi-consolidation and consolidation) and the percentage of well-aerated lung were quantified using a HU threshold based software. ROC curves identified the optimal cut-off values of CT parameters to predict hypoxia worsening and hospital discharge. Multiple Cox proportional hazards regression was used to analyze the capability of CT quantitative features, demographic and clinical variables to predict the time to hospital discharge. RESULTS: Seventy-seven patients (median age 56-years-old, 51 men) with COVID-19 pneumonia at CT were enrolled. The quantitative features of COVID-19 pneumonia were not associated to age, sex and time-from-symptoms onset, whereas higher number of comorbidities was correlated to lower well-aerated parenchyma ratio (rho = -0.234, p = 0.04) and increased semi-consolidation ratio (rho = -0.303, p = 0.008). Well-aerated lung (≤57%), semi-consolidation (≥17%) and consolidation (≥9%) predicted worst hypoxemia during hospitalization, with moderate areas under curves (AUC 0.76, 0.75, 0.77, respectively). Multiple Cox regression identified younger age (p < 0.01), female sex (p < 0.001), longer time-from-symptoms onset (p = 0.049), semi-consolidation ≤17% (p < 0.01) and consolidation ≤13% (p = 0.03) as independent predictors of shorter time to hospital discharge. CONCLUSION: Quantification of pneumonia features on admitting chest CT predicted hypoxia worsening during hospitalization and time to hospital discharge in COVID-19 patients.

Chest CT-derived pulmonary artery enlargement at the admission predicts overall survival in COVID-19 patients: insight from 1461 consecutive patients in Italy.

OBJECTIVES: Enlarged main pulmonary artery diameter (MPAD) resulted to be associated with pulmonary hypertension and mortality in a non-COVID-19 setting. The aim was to investigate and validate the association between MPAD enlargement and overall survival in COVID-19 patients. METHODS: This is a cohort study on 1469 consecutive COVID-19 patients submitted to chest CT within 72 h from admission in seven tertiary level hospitals in Northern Italy, between March 1 and April 20, 2020. Derivation cohort (n = 761) included patients from the first three participating hospitals; validation cohort (n = 633) included patients from the remaining hospitals. CT images were centrally analyzed in a core-lab blinded to clinical data. The prognostic value of MPAD on overall survival was evaluated at adjusted and multivariable Cox's regression analysis on the derivation cohort. The final multivariable model was tested on the validation cohort. RESULTS: In the derivation cohort, the median age was 69 (IQR, 58-77) years and 537 (70.6%) were males. In the validation cohort, the median age was 69 (IQR, 59-77) years with 421 (66.5%) males. Enlarged MPAD (≥ 31 mm) was a predictor of mortality at adjusted (hazard ratio, HR [95%CI]: 1.741 [1.253-2.418], p < 0.001) and multivariable regression analysis (HR [95%CI]: 1.592 [1.154-2.196], p = 0.005), together with male gender, old age, high creatinine, low well-aerated lung volume, and high pneumonia extension (c-index [95%CI] = 0.826 [0.796-0.851]). Model discrimination was confirmed on the validation cohort (c-index [95%CI] = 0.789 [0.758-0.823]), also using CT measurements from a second reader (c-index [95%CI] = 0.790 [0.753;0.825]). CONCLUSION: Enlarged MPAD (≥ 31 mm) at admitting chest CT is an independent predictor of mortality in COVID-19. KEY POINTS: • Enlargement of main pulmonary artery diameter at chest CT performed within 72 h from the admission was associated with a higher rate of in-hospital mortality in COVID-19 patients. • Enlargement of main pulmonary artery diameter (≥ 31 mm) was an independent predictor of death in COVID-19 patients at adjusted and multivariable regression analysis. • The combined evaluation of clinical findings, lung CT features, and main pulmonary artery diameter may be useful for risk stratification in COVID-19 patients.