Impact of the COVID-19 pandemic on diagnosis of respiratory diseases in the Northern Metropolitan Area in Barcelona (Spain).

Objective: The COVID-19 pandemic has had a great effect on the management of chronic diseases, by limiting the access to primary care and to diagnostic procedures, causing a decline in the incidence of most diseases. Our aim was to analyze the impact of the pandemic on primary care new diagnoses of respiratory diseases. Methods: Observational retrospective study performed to describe the effect of COVID-19 pandemic on the incidence of respiratory diseases according to primary care codification. Incidence rate ratio between pre-pandemic and pandemic period was calculated. Results: We found a decrease in the incidence of respiratory conditions (IRR 0.65) during the pandemic period. When we compared the different groups of diseases according to ICD-10, we found a significant decrease in the number of new cases during the pandemic period, except in the case of pulmonary tuberculosis, abscesses or necrosis of the lungs and other respiratory complications (J95). Instead, we found increases in flu and pneumonia (IRR 2.17) and respiratory interstitial diseases (IRR 1.41). Conclusion: There has been a decrease in new diagnosis of most respiratory diseases during the COVID-19 pandemic.

Objetivo: La pandemia de COVID-19 ha tenido efecto sobre el seguimiento de las enfermedades crónicas. Nuestro objetivo fue analizar el impacto de la pandemia por COVID-19 en los nuevos diagnósticos respiratorios en atención primaria. Metodología: Estudio observacional retrospectivo realizado para describir el impacto de la COVID-19 sobre la incidencia de diagnósticos respiratorios en atención primaria. Se ha calculado la tasa relativa de incidencia entre el periodo prepandémico y el pandémico. Resultados: Hallamos una reducción en la incidencia de patología respiratoria (IRR 0,65) durante la pandemia. Al comparar los distintos grupos de enfermedades (CIE-10), encontramos una reducción significativa en el número de nuevos casos durante la pandemia, excepto en el caso de tuberculosis pulmonar, abscesos o necrosis pulmonar y otras complicaciones respiratorias. Por otro lado, se detectaron incrementos en nuevos diagnósticos de gripe y neumonía (IRR 2,17) y enfermedades respiratorias intersticiales (IRR 1,41). Conclusión: Se ha producido un descenso en el número de nuevos diagnósticos de la mayoría de las enfermedades respiratorias durante la pandemia por COVID-19.

Impact of the COVID-19 pandemic on diagnosis of respiratory diseases in the Northern Metropolitan Area in Barcelona (Spain).

OBJECTIVE: The COVID-19 pandemic has had a great effect on the management of chronic diseases, by limiting the access to primary care and to diagnostic procedures, causing a decline in the incidence of most diseases. Our aim was to analyze the impact of the pandemic on primary care new diagnoses of respiratory diseases. METHODS: Observational retrospective study performed to describe the effect of COVID-19 pandemic on the incidence of respiratory diseases according to primary care codification. Incidence rate ratio between pre-pandemic and pandemic period was calculated. RESULTS: We found a decrease in the incidence of respiratory conditions (IRR 0.65) during the pandemic period. When we compared the different groups of diseases according to ICD-10, we found a significant decrease in the number of new cases during the pandemic period, except in the case of pulmonary tuberculosis, abscesses or necrosis of the lungs and other respiratory complications (J95). Instead, we found increases in flu and pneumonia (IRR 2.17) and respiratory interstitial diseases (IRR 1.41). CONCLUSION: There has been a decrease in new diagnosis of most respiratory diseases during the COVID-19 pandemic.

Impacto de la pandemia por Covid-19 en los diagnósticos respiratorios en el Área Metropolitana Norte de Barcelona (España) Impact of the COVID-19 pandemic on diagnosis of respiratory diseases in the Northern Metropolitan Area in Barcelona (Spain)

Objetivo: La pandemia de COVID-19 ha tenido efecto sobre el seguimiento de las enfermedades crónicas. Nuestro objetivo fue analizar el impacto de la pandemia por COVID-19 en los nuevos diagnósticos respiratorios en atención primaria. Metodología: Estudio observacional retrospectivo realizado para describir el impacto de la COVID-19 sobre la incidencia de diagnósticos respiratoris en atención primaria. Se ha calculado la tasa relativa de incidencia entre el periodo prepandémico y el pandémico. Resultados: Hallamos una reducción en la incidencia de patología respiratoria (IRR 0.65) durante la pandemia. Al comparar los distintos grupos de enfermedades (CIE-10), encontramos una reducción significativa en el número de nuevos casos durante la pandemia, excepto en el caso de tuberculosis pulmonar, abscesos o necrosis pulmonar y otras complicaciones respiratorias. Por otro lado, se detectaron incrementos en nuevos diagnósticos de gripe y neumonía (IRR 2.17) y enfermedades respiratorias intersticiales (IRR 1.41). Conclusión: Se ha producido un descenso en el número de nuevos diagnósticos de la mayoría de enfermedades respiratorias durante la pandemia por COVID-19.

A novel intelligent radiomic analysis of perfusion SPECT/CT images to optimize pulmonary embolism diagnosis in COVID-19 patients.

BACKGROUND: COVID-19 infection, especially in cases with pneumonia, is associated with a high rate of pulmonary embolism (PE). In patients with contraindications for CT pulmonary angiography (CTPA) or non-diagnostic CTPA, perfusion single-photon emission computed tomography/computed tomography (Q-SPECT/CT) is a diagnostic alternative. The goal of this study is to develop a radiomic diagnostic system to detect PE based only on the analysis of Q-SPECT/CT scans. METHODS: This radiomic diagnostic system is based on a local analysis of Q-SPECT/CT volumes that includes both CT and Q-SPECT values for each volume point. We present a combined approach that uses radiomic features extracted from each scan as input into a fully connected classification neural network that optimizes a weighted cross-entropy loss trained to discriminate between three different types of image patterns (pixel sample level): healthy lungs (control group), PE and pneumonia. Four types of models using different configuration of parameters were tested. RESULTS: The proposed radiomic diagnostic system was trained on 20 patients (4,927 sets of samples of three types of image patterns) and validated in a group of 39 patients (4,410 sets of samples of three types of image patterns). In the training group, COVID-19 infection corresponded to 45% of the cases and 51.28% in the test group. In the test group, the best model for determining different types of image patterns with PE presented a sensitivity, specificity, positive predictive value and negative predictive value of 75.1%, 98.2%, 88.9% and 95.4%, respectively. The best model for detecting pneumonia presented a sensitivity, specificity, positive predictive value and negative predictive value of 94.1%, 93.6%, 85.2% and 97.6%, respectively. The area under the curve (AUC) was 0.92 for PE and 0.91 for pneumonia. When the results obtained at the pixel sample level are aggregated into regions of interest, the sensitivity of the PE increases to 85%, and all metrics improve for pneumonia. CONCLUSION: This radiomic diagnostic system was able to identify the different lung imaging patterns and is a first step toward a comprehensive intelligent radiomic system to optimize the diagnosis of PE by Q-SPECT/CT. HIGHLIGHTS: Artificial intelligence applied to Q-SPECT/CT is a diagnostic option in patients with contraindications to CTPA or a non-diagnostic test in times of COVID-19.

Bronchoscopy in Critically Ill COVID-19 Patients: Findings, Microbiological Profile, and Coinfection.

BACKGROUND: Bronchoscopy is a widely use technique in critically ill patients. Nosocomial coinfections are a cause of morbidity and mortality in intensive care units. OBJECTIVES: Our aim was to describe bronchoscopy findings and analyze microbiological profile and probably coinfection through bronchial aspirate (BA) samples in patients with coronavirus disease 2019 pneumonia requiring intensive care unit admission. METHODS: Retrospective observational study analyzing the BA samples collected from intubated patients with coronavirus disease 2019 in a referral Hospital (Spain). RESULTS: One hundred fifty-five consecutive BA samples were collected from 75 patients. Ninety (58%) were positive cultures for different microorganisms, 11 (7.1%) were polymicrobial, and 37 (23.7%) contained resistant microorganisms. There was a statistically significant association between increased days of orotracheal intubation and positive BA (18.9 vs. 10.9 d, P<0.01), polymicrobial infection (22.11 vs. 13.54, P<0.01) and isolation of resistant microorganisms (18.88 vs. 10.94, P<0.01). In 88% of the cases a new antibiotic or change in antibiotic treatment was made. CONCLUSION: Bronchoscopy in critically ill patient was safe and could be useful to manage these patients and conduct the microbiological study, that seems to be higher and different than in nonepidemic periods. The longer the intubation period, the greater the probability of coinfection, isolation of resistant microorganisms and polymicrobial infection.

No Effects of Meteorological Factors on the SARS-CoV-2 Infection Fatality Rate.

OBJECTIVE: Previous studies have shown that meteorological factors may increase COVID-19 mortality, likely due to the increased transmission of the virus. However, this could also be related to an increased infection fatality rate (IFR). We investigated the association between meteorological factors (temperature, humidity, solar irradiance, pressure, wind, precipitation, cloud coverage) and IFR across Spanish provinces ( n = 52) during the first wave of the pandemic (weeks 10-16 of 2020). METHODS: We estimated IFR as excess deaths (the gap between observed and expected deaths, considering COVID-19-unrelated deaths prevented by lockdown measures) divided by the number of infections (SARS-CoV-2 seropositive individuals plus excess deaths) and conducted Spearman correlations between meteorological factors and IFR across the provinces. RESULTS: We estimated 2,418,250 infections and 43,237 deaths. The IFR was 0.03% in < 50-year-old, 0.22% in 50-59-year-old, 0.9% in 60-69-year-old, 3.3% in 70-79-year-old, 12.6% in 80-89-year-old, and 26.5% in ≥ 90-year-old. We did not find statistically significant relationships between meteorological factors and adjusted IFR. However, we found strong relationships between low temperature and unadjusted IFR, likely due to Spain's colder provinces' aging population. CONCLUSION: The association between meteorological factors and adjusted COVID-19 IFR is unclear. Neglecting age differences or ignoring COVID-19-unrelated deaths may severely bias COVID-19 epidemiological analyses.

Predicting pulmonary embolism in patients infected with COVID-19 based on D-dimer levels and days between diagnosis of the infection and D-dimer determination.

Ruling out pulmonary embolism (PE) can be challenging in a situation of elevated D-dimer values such as in a case of COVID-19 infection. Our objective was to evaluate the difference in D-dimer values of subjects infected with COVID-19 in those with PE and those without and to analyze the predictive value of D-dimer for PE in these subjects based on the day of D-dimer determination. This was an observational, retrospective study, conducted at a tertiary hospital. All subjects with PCR-confirmed COVID-19 infection requiring hospital admission at our institution between the months of March and April 2020 were included in the study. We compared D-dimer levels in subjects who went on to develop a PE and those who did not. We then created a model to predict the subsequent development of a PE with the current D-dimer levels of the subject. D-dimer levels changed over time from COVID-19 diagnosis, but were always higher in subjects who went on to develop a PE. Regarding the predictive model created, the area under the curve of the ROC analyses of the cross-validation predictions was 0.72. The risk of pulmonary embolism for the same D-dimer levels varied depending on the number of days elapsed since COVID-19 diagnosis and D-dimer determination. To conclude, D-dimer levels were elevated in subjects with a COVID-19 infection, especially in those with PE. D-dimer levels increased during the first 10 days after the diagnosis of the infection and can be used to predict the risk of PE in COVID-19 subjects.

D-dimer in patients infected with COVID-19 and suspected pulmonary embolism.

OBJECTIVE: To analyze the risk factors for pulmonary embolism (PE) in patients infected with COVID-19. METHODS: We conducted an observational, retrospective study. Patients with severe infection with COVID-19 and suspected PE were included. RESULTS: Patients with higher levels of D-dimer and those requiring intubation were at a higher risk of developing PE. Higher D-dimer levels were associated with a greater probability of PE 3, 6, 9 and 12 days after determining D-dimer levels with an OR of 1.7, 2.0, 2.4 and 2.4, respectively. CONCLUSION: In conclusion, patients infected with COVID-19 requiring OTI with higher levels of D-dimer have an increased risk of developing PE.