ABSTRACT
Background: Bacterial and viral airway infections are adverse factors for prognosis in people with cystic fibrosis (CF). The role of viral infections is unclear. Proper microbiological follow-up is essential, and the correlation between upper (UAW) and lower airway (LAW) microbiology may be important for lung disease management. We aim to evaluate airway microbiology in patients in stable clinical condition. Method(s): Between September 2021 and March 2022 in the Florence CF center, 144 nasal lavage-throat swab paired samples were collected from 72 clinically stable people with CF not chronically colonized by Pseudomonas aeruginosa. The study enrolled 59 children (median age 9, range 2-16) and 13 adults (median age 28, range 18-59). LAW specimens (72)were sampled as throat swab and UAWspecimens (72)were randomly collected by nasal lavage with two methods-Mainz (44) or Ryno-set (28). We performed conventional microbiological analyses on all samples. To screen for respiratory viruses, multiplex polymerase chain reaction (BioFire FilmArray RP 2.1 Plus) was performed. Respiratory symptoms and forced expiratory volume in 1 second (FEV1) valueswere evaluated for all patients. Result(s): Twenty-one (29%) patients tested positive for at least one virus in UAW and LAW specimens. The most frequently identified viruses were human rhinovirus or enterovirus (22%) and respiratory syncytial virus (6%). Two (3%) patients tested positive for SARS-CoV-2. Concordance between sampling methods for viral detection in UAW and LAW specimens was observed in 59 paired samples (82%), including 40 patients with no viral infections and 19 virus positive for both samples. Discordance was described in 13 subjects;10 of 13 did not show viral infection in nasal lavage. Twenty-one percent of positive nasal lavage was performed using Ryno-set and 36% using the Mainz approach. The prevalent bacteriumwas Staphylococcu aureus in UAW (53%) and LAW (69%) cultures, followed by Enterobacteriaceae (UAW 8%, LAW 6%), methicillin-resistant S. aureus (UAW 7%, LAW 6%), P. aeruginosa (UAW 4%, LAW 6%), and other clinically relevant gram-negative bacteria such as Achromobacter xylosoxidans, Stenotrophomonas maltophilia, and Ochrobactrum anthropi (UAW 7%, LAW 13%). Nasal lavage performed with Ryno-set tested positive in 72% of patients, and 64% of Mainz lavage were positive. Mainz nasal lavage showed different S. aureus and P. aeruginosa isolations (48% and 5%, respectively) than the samples collected with Ryno-set technique (61% and 4%, respectively). Concordance between sampling methods for bacterial detection in UAW and LAW was the same with the two methods (53%). Bacterial and viral infections were found in UAWand LAWof stable people with CF, but no clinical correlation was observed. Conclusion(s): The two methods of UAW lavage had slight differences in performance. Virus infection appeared to be less prevalent than bacterial infection in UAWand LAW.We did not find correlations between presence of viruses and respiratory symptoms, but further investigation is needed for a better understanding of the clinical role of viral infection in people with CF.Copyright © 2022, European Cystic Fibrosis Society. All rights reserved
ABSTRACT
Introduction: Breast cancer is the most common cancer in women and the leading cause of cancerrelated death in women worldwide. The high prevalence of physical and psychosocial suffering among breast cancer patients and their families justifies the need for an early interdisciplinary approach by a palliative care team. The effectiveness of early palliative care for patients with advanced cancer has been demonstrated in many studies. Early referral to outpatient palliative care services improves symptom control, reduces suffering and improves quality of end-of-life care. Aim(s): Evaluation of referral patterns of metastatic breast cancer patients to the outpatient embedded palliative care team. Method(s): We retrospectively retrieved data from electronic medical records of patients who were treated at a private community oncology practice in Brazil who died from metastatic breast cancer during the years of 2018 until 2021.We evaluated the patient's follow-up time by the palliative care team (follow-up > 12 weeks or not) and the year of referral to the service (pre-2020 vs 2020 and later) associated to the service referral type: Late referral (more than 8 weeks of metastatic diagnosis) or early referral. Each group was followed-up by cancer physicians and after referral was also followed-up by a palliative care multidisciplinary team who regularly evaluated cancer patients during their treatments at outpatient setting. During COVID-19 pandemic, some patients were evaluated by telemedicine appointments. We performed univariate comparisons analysis by Fisher's Exact Test. p < 0.1 was deemed as statistically significant. Result(s): Of the 211 patients whose data were assessed, 99 patients were referred to Palliative Care team before 2020 and 112 patients after 2020. 13.1% of patients pre-2020 received early palliative care versus 33.9% of patients in the post-2020 referral group, resulting in a 3.37-fold odds of an early palliative care integration after 2020 (OR 3.37, CI95: 1.61 - 7.45;p< 0.001). Overall, 30.4% of longer follow-up patients were an early referral versus 19.3% of the shorter follow-up, resulting in an 82% greater chance (OR 1.82, CI: 0.92-3.63;p< 0.1) of prolonged assistance with early referral. Conclusion(s): In this analysis, early palliative care integration for patients with metastatic breast cancer has increased after 2019 despite the COVID-19 pandemic, leading to prolonged time of accompaniment by the multidisciplinary palliative care team. This suggests that even in the face of this challenging moment, a mature and consolidated service is offered by the palliative care team. Also, according to previous data in literature, prematurely integration show signs of correlation with better quality of life and death, supporting early palliative care for this group of patients. However, further work is needed to examine the effect of this care model in our cohort.
ABSTRACT
Purpose: The SARS-CoV-2 pandemic was declared a global public health emergency. Determinants of mortality in the general population are now clear, but specific data on patients with breast cancer (BC) remain limited, particularly in developing nations. Material(s) and Method(s): We conducted a longitudinal, multicenter cohort study in patients with BC and confirmed SARS-CoV-2 infection. The primary end point was the proportion of patients on treatment for severe SARS-CoV-2 infection (defined as need for hospitalization) or early death (within 30 days of diagnosis). Data were evaluated sequentially in the following way: i) univariate Fisher's exact test;ii) multivariable logistic regression analysis;and iii) multivariable logistic regression. In items i and ii only those with P< 0.1 are considered significant and in stage iii only those with p< 0.05 were the final significant variables. We divided patients' data into three major variable domains: a) signs and symptoms;b) comorbidities;and c) tumor and treatment characteristics;in item ii each variable domain was tested separately, finally, in item iii the significant variables of all domains were tested together and we called it the integrative step. Result(s): From April 2020 to June 2021, 413 patients with BC and COVID-19 were retrospectively registered, of which 288 (70%) had an identified molecular subtype and 273 (66%) had stage information. Most patients were on active systemic therapy or radiotherapy (73.2%), most of them in the curative setting (69.5%). The overall rate of severe SARS-CoV-2 was 19.7% (95% CI, 15.3-25.1). In the integrative multivariate analysis, factors associated with severe infection were metastatic setting, chronic pain, acute dyspnea, and cardiovascular comorbidities. Recursive partitioning modeling used acute dyspnea, metastatic setting, and cardiovascular comorbidities to predict nonprogression to severe infection, yielding a negative predictive value of 84.9% (95% CI, 78.9%-88.3%). Conclusion(s): The rate of severe COVID-19 in patients with BC is influenced by prognostic factors that partially overlap with those reported in the general population. High-risk patients should be considered candidates to active preventive measures to reduce the risk of infection, close monitoring in the case of exposure or SARS-CoV-2 -related symptoms and prophylactic treatment once infected.
ABSTRACT
Background: Thrombotic thrombocytopenic purpura (TTP) has occasionally been described after vaccination. Since the availability of anti-SARS- CoV- 2 vaccines, 12 cases have been described on a possible association with TTP onset. Aim(s): This study aims to evaluate the relapse rates in patients affected by TTP undergoing anti-SARS- CoV- 2 vaccination. Method(s): All consecutive TTP patients undergoing anti-SARS- CoV- 2 vaccination from March to May 2021 were enrolled. Blood samples were collected before vaccination (T0), 2 weeks after the first (T1) and the second dose (T2) to evaluate ADAMTS13 activity and anti-ADAMTS13 antibody titer. Result(s): A total of 49 TTP patients were enrolled (48 acquired and 1 congenital), all vaccinated with an mRNA vaccine. No patients had a clinical TTP relapse, with an ADAMTS13 relapse rate of 1.36% per month. Mean levels of ADAMTS13 activity were stable among the three timepoints (Figure). In only two patients a significant drop in ADAMTS13 levels occurred after the first dose (from 28% to <3% and from 101% to 82%), and both remained stable after the second dose, with negative anti-ADAMTS13 antibodies. Due to a stable undetectable ADAMTS13, the first patient was treated with 4 doses of weekly 375 mg/m2 rituximab with a rapid ADAMTS13 response. One patient had positive basal anti-ADAMTS13 antibodies with a titer remaining stable after the two vaccine doses, while in another patient anti-ADAMTS13 antibodies became detectable after the first dose, with no corresponding drop in ADAMTS13 levels and a stable titer after the second dose. Conclusion(s): The result of our study prospectively evaluating the effect of anti-SARS- CoV- 2 vaccination on the risk of relapse in a large cohort of patients with TTP in Milan showed a lower than reported relapse rate (1.36% vs 2.6%) with an observed to expected incidence rate ratio of 0.52, confirming the safety of mRNA-based anti-SARS- CoV- 2 vaccination in TTP patients.
ABSTRACT
Background: As a reaction to the COVID-19 pandemic, a nation-wide lockdown was enforced in Brazil in March 2020, cancer care was impacted, and cancer screening reduced. Therefore, an increase in cancer diagnoses at more advanced stages was expected. In this study, we extracted data from our nationwide real-world database to evaluate the impact of the COVID-19 pandemic on the stage at diagnosis of breast cancer (BC) cases. Methods: We explored curated electronic medical record data of female patients, over 18 years of age, diagnosed with BC and with established disease stage based on the AJCC 8th edition, who started treatment or follow-up in the Oncoclínicas (OC) between Jan 1, 2018, and Dec 31, 2021. The primary objective was to compare stage distribution at first visit during COVID- 19 pandemic (2020-2021) with a historical control cohort from a period prior to the pandemic (2018- 2019). We investigated stage distribution according to age at diagnosis and tumor ER/HER2 subtype in univariate models. Associations were considered significant if they had a minimum significance (P < 0.1 in Chi-square test). The historical numbers of patients with BC at OC make it possible to identify differences in the prevalence of stages in the order of 5% comparing pre and post pandemic periods with a statistical power greater than 80%. Results: We collected data for 11,752 patients with initial diagnosis of BC, with 6,492 patients belonging to the pandemic (2020-2021) and 5,260 patients to the pre-pandemic period (2018-2019). For both ER+/ HER2- and HER2+ tumors, there was a lower percentage of patients with early-stage (defined as stage I-II) in the years 2020-2021 vs 2018-2019 and a considerable increase in advanced-stage disease (defined as stage IV). For triple negative BC (TNBC), there was a significant higher percentage of patients with advanced-stage disease in the pandemic vs pre-pandemic period (table 1). Age over 50 years was associated with a greater risk of advanced stage at diagnosis after the onset of the pandemic, with an absolute increase of 7% (P twosided <0.01). Conclusions: We observed a substantial increase in cases of advanced-stage BC in OC institutions as a result of delays in BC diagnoses due to the COVID-19 pandemic. The impact appeared greater in older adults, potentially because of stricter confinement in this group.
ABSTRACT
Background: SARS-CoV-2 infection can compromise respiratory function and cause thrombotic events. SARS-CoV-2 binds to and mediates downregulation of angiotensin converting enzyme 2 (ACE2) on infected cells. Diminished enzymatic activity of ACE2 could result in increased concentrations of the pro-inflammatory molecules angiotensin II and bradykinin, contributing to SARS-CoV-2 pathology. Methods: Immunofluorescence microscopy and digital image data quantification, Computer assisted molecular docking analyses, Western blot. Results: Using immunofluorescence microscopy of lung tissues from uninfected and SARS-CoV-2 infected individuals, we find evidence that ACE2 is highly expressed in the pulmonary alveolar epithelium and is significantly reduced along the alveolar lining of SARS-CoV-2 infected lungs. Ex vivo analyses indicate that ACE2 is readily detected on primary human pulmonary alveolar epithelial and primary human aortic endothelial cells (HAoECs). Exposure of these cells to recombinant SARS-CoV-2 spike protein was sufficient to reduce surface ACE2 expression. Moreover, exposure of HAoECs to spike protein induced endothelial dysfunction (increased expression of von Willebrand Factor and decreased expression of Krüppel-like Factor 2), caspase activation, and apoptosis. Exposure of HAoECs to bradykinin (BK, 10μ M) induced calcium signaling and endothelial dysfunction but did not adversely affect viability. Computer assisted analyses of molecules with potential to bind bradykinin receptor B2 (BKRB2) suggested a potential role for aspirin as a bradykinin antagonist. When tested in our in vitro model, we found that aspirin (1μM) could significantly blunt cell signaling, and endothelial dysfunction caused by bradykinin in these cells. Conclusion: SARS-CoV-2 causes complex effects on microvascular homeostasis that potentially contribute to organ dysfunction and coagulopathies. Reduced ACE2 enzymatic activity could contribute to inflammation and pathology in the lung. Our studies add to this understanding by providing evidence that spike protein alone can mediate adverse effects on vascular cells. Understanding these mechanisms of pathogenesis may provide rationale for interventions, such as interference with the interactions of spike protein or bradykinin with endothelial cells, that could limit microvascular events associated with SARS-CoV-2 infection and stabilize microvascular homeostasis in COVID-19 disease.
ABSTRACT
Background : Several thrombotic manifestations have been reported with SARS-Cov-2 infection including liver vascular involvement. Aims : We present a dramatic case of acute liver necrosis in a 36-year-old SARS-Cov-2 positive Italian woman with no respiratory symptoms and triple positive antiphospholipid syndrome (APS). Methods : The patient was referred to our University Hospital for acute hypertransaminasemia and liver failure (Figure). She had systemic lupus erythematosus (positivity for: ANA, anti-dsDNA, complement activation, Coombs;thrombocytopenia, previous arthritis). Anti-phopspholipid antibodies (aPL) were detected for the first time in 2015 during routine pregnancy screening and chronically treated with aspirin. Apparently, no venous/arterial nor obstetric events were recorded up to the recent hospitalization. FIGURE 1 Results : At arrival, US-Doppler and CT-scan were consistent with signs of chronic liver disease and occlusion of the three hepatic veins defining a Budd-Chiari syndrome. We opted for a stepwise approach considering anticoagulation (clexane 100 UI/Kg b.i.d) the first line of therapy before any invasive intervention. Dexamethasone 6 mg/ day b.i.d., 6 sessions of plasma-exchange, i.v.-immunoglobulin were sequentially planned to revert the liver damage sustained by aPL. After 5-days, two hepatic-veins resulted recanalized in association with amelioration of liver-enzyme/function and aPL quantification. Then we performed hepatic vein catheterization and transjugular liver biopsy. The histology showed multiple areas of necrosis associated with liver cirrhosis. Unexpectedly, no signs of acute Budd-Chiari were observed (e.g. intraparenchymal hemorrhages, centrilobular congestion, sinusoidal dilation). Other etiologies were also excluded and we hypothesized the involvement of small arteries of the liver in a triple positive APS in a patients with SLE. We finally addressed the patient to a liver transplant program and a tight multispecialistic follow-up. Conclusions : Thrombosis of arterial/venous vessels or microcirculation causes liver damage in some patients with aPL. Our report suggests that SARS-Cov-2 can exacerbate this prothrombotic condition determining a life-threatening complication such as acute liver failure.
ABSTRACT
Background : The novel coronavirus disease 2019 (COVID-19) presents an important and urgent threat to global health. Identifying strong predictors of mortality could assist medical staff in treating patients and allocating limited healthcare resources. Aims : The primary aim of this paper was to study the effect of ddimer levels at admission as a predictive marker for in-hospital mortality. Methods : This was a retrospective cohort study evaluating hospitalized patients (age > 18 years), who were positive for COVID-19 based on real-time PCR at one of nine COVID-19 units during the period of the first COVID-19 wave in Lombardy, Italy. The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Predictive power was assessed using Harrell's C-index. Results : Out of 1049 patients that were admitted to the emergency department and subsequently hospitalized, 501 patients had evaluable data for d-dimer. Of these 501 patients, 96 did not survive. Cumulative incidence of in-hospital mortality within 30 days was 20%, and the majority of deaths occurred within the first 10 days. (Figure 1) When compared to patients in the lowest quartile of d-dimer blood concentration, the hazard ratio of in-hospital mortality for patients in the 2 nd , 3 rd and 4 th quartile was 3.9 (95CI: 1.5-10.0), 5.8 (95CI: 2.3-14.7), and 4.6 (95CI: 1.8-11.5) respectively, after multivariable adjustment for age, sex and number of comorbidities. The C-statistic of d-dimer for in-hospital mortality was 0.67 (95CI: 0.62-0.71). (Table 2) Conclusions : Higher d-dimer levels were strongly associated with inhospital mortality. However, the predictive power of d-dimer alone was not high enough to be useful as a risk prediction score. Future research should focus on the added value of d-dimer as part of a larger risk prediction score.
ABSTRACT
Background: The COVID-19 pandemic remains a public health emergency of global concern, with higher mortality rates in cancer patients as compared to the general population. However, early mortality of COVID19 in cancer patients has not been compared to historical real-world data from oncology population in pre-pandemic times. Methods: Longitudinal multicenter cohort study of patients with cancer and confirmed COVID-19 from Oncoclínicas Group in Brazil from March to December 2020. The primary endpoint was 30-day mortality after isolation of the SARS-CoV-2 by RT-PCR. As historical control, we selected patients from Oncoclínicas Data Lake treated before December 2019 and propensity score-matched to COVID-19 cases (3:1) based on the following clinical characteristics: age, gender, tumor type, disease setting (curative or palliative), time from diagnosis of cancer (or metastatic disease) to COVID-19 infection. Results: In total, 533 cancer patients with COVID-19 were prospectively registered in the database, with median age 60 years, 67% females, most frequent tumor types breast (34%), hematological (16%), gastrointestinal (15%), genitourinary (12%) and respiratory tract malignancies (10%). Most patients were on active systemic therapy or radiotherapy (84%), largely for advanced or metastatic disease (55%). In the overall population, early death rate was 15%, which was numerically higher than the Brazilian general population with COVID-19 diagnosis in 2020 (2.5%). We were able to match 442 cancer patients with COVID-19 to 1,187 controls with cancer from pre-pandemic times. The 30-day mortality rate was 12.4% in COVID-19 cases as compared to 5.4% in pre-pandemic controls with cancer (Odds Ratio 2.49, 95%CI 1.67 - 3.70;P value < 0.01, Power 97.5%). COVID-19 cancer patients had significantly higher death events than historical controls (Hazard Ratio 2.18, 95%CI 1.52 - 3.12;P value < 0.01, Power 99.7%), particularly from 20 to 30 days after diagnosis of the infection. Conclusions: Cancer patients with COVID-19 have an excess mortality 30 days after the infection when compared to matched cancer population from pre-pandemic times and the general population with COVID-19, reinforcing the need for priority vaccination in public health strategies. Legal entity responsible for the study: Oncoclínicas Group. Funding: Amgen. Disclosure: All authors have declared no conflicts of interest.
ABSTRACT
Background: Early palliative care has shown an improvement in the quality of life of cancer patients by reducing overtreatment at the end of life and improving symptomatic control. Little is known about the quality of death in developing countries. End-of-life cancer care varies widely, and very few centers evaluate it systematically. The aim of the present study is to analyze the impact of follow-up of cancer patients by an outpatient palliative care team (OPCT) on the end-of-life outcomes at a Cancer Center in Brazil. Methods: We retrospectively retrieved data from electronic medical records of cancer patients who were treated at a Cancer Center in Brazil and who died from cancer or associated complications during the year of 2020. They were divided into two groups: OPCT and No-OPCT. OPCT group was followedup by a multidisciplinary team composed of physician, nurse, physiotherapist, psychologist, nutritionist, social worker, speech-language therapist, and pharmacist, who regularly evaluated cancer patients during their treatments at outpatient setting. During COVID-19 pandemic, some patients were evaluated by telemedicine appointments. No-OPCT group was followed-up by cancer physicians exclusively. We performed univariate comparisons and multivariate analysis by Cox proportional hazards model. p < 0.05 was deemed as statistically significant. Results: A total of 315 patients were included in the study: OPCT (N=122) and No-OPCT (N=193). The groups were well balanced in relation to median age (61yo vs 63yo), gender (women: 51% vs 54%), and TNM stage (stage IV: 69% vs 65%). Gastrointestinal and breast cancers were the most prevalent. The rate of home death was 44% in the OPCT group, compared to 16% in the No-OPCT group (p<0.001). The rate of admission in intensive care unit in the last 30 days of life (ICU30) was 13% vs 10%, respectively (p=0.413). Likewise, the rate of patients treated with chemotherapy in the last 30 days of life (CT30) was 42% vs 51% (p=0.146). In multivariate analysis, follow-up by the OPCT was the strongest independent predictor of home death (Table). In contrast, ICU30 and CT30 were inversely correlated with this outcome. Age, gender, and TNM stage did not have influence on the place of death. Conclusions: Follow-up by an OPCT had a strong positive impact on end-of-life care of cancer patients in a country which does not have Hospice culture. The OPCT was able to offer home death to a greater number of patients, with proximity to caregivers, and respect to their beliefs and values. Our data highlight the importance of early conversations about goals of care, prognostic awareness, and end-of-life preferences, while also reinforcing the need of early referral to a palliative care team. (Table Presented).
ABSTRACT
Background: COVID-19 is a challenge for clinical decision-making in cancer patients and the allocation of healthcare resources. An accurate prognosis prediction to effectively triage patients is needed, especially in the community oncology practice. Methods:Nationwide cohort from Oncoclínicas Brazil was used to validate previously developed multivariable logistic regression (mLR) model (Ferrari et al, JCO GO 2021) and to construct a machine learning Random Forest (RF) algorithm as predictor of 30-day mortality after SARS-CoV-2 detection by RT-PCR in cancer patients diagnosed in an outpatient setting. To find the most important baseline clinical determinants of early COVID19-related death via Gini index, a RF with 100,000 trees was trained in 75% of the dataset, and the performance was assessed in the remaining 25%. We then compared the accuracy of different models in terms of sensitivity, specificity and area under the receiver operating characteristics curves (AUC). Results:From March to December 2020, 533 patients with COVID-19 were prospectively registered in the database. Median age was 60 years (19-93) and 67% were female. Most frequent cancers were breast in 34%, hematological in 16%, and gastrointestinal in 15%. Comorbidities were common (52%), as was current/former smoking history (17%). Most patients were on active systemic therapy or radiotherapy (84%) in the advanced or metastatic disease setting (55%). The overall mortality rate was 15% (CI95% 12%-18%). We validated the original mLR model trained in the first 198 patients: management in a noncurative setting (odds ratio [OR] 3.7), age ≥ 60 years (OR 2.3), and current/former smoking (OR 1.9) were significant predictors of death in the expanded cohort. Presence of comorbidities (OR 1.9) also defined poor outcome in the updated mLR model, which yielded low sensitivity (74%), specificity (68%) and AUC (0.78). With RF modeling, the most significant predictors of 30-day death after COVID-19 (in decreasing order) were older age, treatment of advanced or metastatic disease, tumor type (respiratory tract, brain and unknown primary cancers had higher mortality), COVID-related symptom burden at baseline evaluation and treatment regimen (immunotherapy combinations had higher mortality). The RF model demonstrated high sensitivity (89%), specificity (88%) and AUC (0.96). Conclusions:The results highlight the possibility that machine learning algorithms are able to predict early mortality after COVID-19 in cancer patients with high accuracy. The proposed prediction model may be helpful in the prompt identification of high-risk patients based on clinical features alone, without having to wait for the results of additional tests such as laboratory or radiologic studies. It can also help prioritize medical resources and redefine vaccination strategies. A web-based mortality risk calculator will be created for clinical decision support.
ABSTRACT
Background: The province of Cremona had one of the highest incidence of COVID-19 (COV-19) infection in Italy. The pandemic determined a significant shrinkage of our healthcare resources with difficulty for many patients (pts) to be assisted in the hospital, especially for the risk of being infected. Therefore, we created a homecare project for cancer pts with the aim of reducing hospitalizations, accesses to the oncology ward and emergency room. Methods: The team was composed by oncologists and nurses from the Oncology Unit of Cremona Community Hospital, supported by a secretary with a dedicated telephone number. The assistance was provided from Monday to Saturday, 9 AM-5 PM. Cancer pts were eligible if presenting confirmed diagnosis or suggestive symptoms for COV-19. A telephonic triage was performed. Cancer pts and their cohabitants were tested with at least 2 nasopharyngeal swabs (NPS). Blood test, medical examinations and vital parameters were performed. We advised screened individuals to follow the quarantine procedures, providing them with an information leaflet. We administered oral/infusional treatments, including antiviral drugs. Results: From March 23rd to April 30th 2020, 71 cancer pts were assisted at home, with a total of 191 visits. Of the 71 pts tested with NPS, 26 resulted COV-19 positive (COV-19+). 19 of COV-19+ pts had mild symptoms;7 pts with stable vital parameters and initial pneumonia were successfully treated at home with hydroxychloroquine, antivirals and NSAIDs. 7 pts with severe symptoms were promptly hospitalized. 4 of them died, 2 due to the infection, 2 to progression disease. 52 cohabitants were screened with NPS, 28 lived with a COV-19+ cancer patient;in this subgroup, 16 resulted COV-19+. 15 of them were completely asymptomatic. Conclusions: This project demonstrated the feasibility of an innovative model based on homecare assistance for COV-19+ cancer pts with mild symptoms. This strategy, limiting the number of hospital accesses for COV-19+ pts, might be useful to contain the spread of the infection. Further studies are needed to test this strategy in COV-19 negative cancer pts. Moreover, our experience indicates a high probability of identifying asymptomatic positive individuals cohabiting with COVID+ pts. NPS screening for asymptomatic subjects is not routinely performed in Italy. There is a urgent need to extend the screening to this population.
ABSTRACT
Human-Data Interaction (HDI) is a growing field concerned by placing humans at the center of data flows and providing mechanisms for people to interact explicitly with systems and data. Understanding HDI from a sociotechnical perspective, we argue that technical and human issues must be approached in an interconnected way throughout a data lifecycle. In this paper, grounding our discussions in a conceptual artifact named Extended Semiotic Framework, we discuss how different interested parties, different levels of signs, and different stages in data lifecycle can affect HDI. We apply this artifact into a local COVID-19 information website and use its results to inform the website redesign. Our discussion and results show the Extended Semiotic Framework as capable to promote a systemic view considering both human and technical issues, as well as to identify problems and challenges at different data stages. © 2020 ACM.