ABSTRACT
Background: The multisystem involvement of covid-19 lingers in post-covid phase. The significance of baseline resting pulse rate was looked for in long-covid relating to symptoms in acute phase, 2-chair test response, and echocardiography. Methods: Serial long-covid patients attending out-patient department were included. They were evaluated on demographic (age, height, weight, and BMI), characteristics, symptom score in acute phase (symptom severity in 0 to 5 scale X duration of symptoms), variables (pulse-rate and SpO2 changes) related to 2 chair test and resting Doppler echocardiography (LV ejection fraction, TSAPSE, left and right ventricular free wall GLS, and LV filling pressure. Two groups with pulse rate below or above 90/minute were compared. Results: The mean duration of acute illness for both the group is computed to be (118.44±95.95 vs. 152.77±102.25, p- value= 0.42) respectively. The baseline pulse rate were significantly different between those above (n=12) and below 90 (n=23) per minute (101±5.83 vs.72.85±8.14;p<0.0001);so is the post-exercise maximum pulse rate (p<0.004). Subjects with lower pulse rate had better height (p=0.05), weight (p=0.06), and higher anosmia (p=0.005) but lower total symptoms score (26.4±51.02 vs.29.66±66.12;p=0.008). The spirometric parameters (FVC, FEV1, FWV1/FVC) were better (although not significant) in those with lower pulse rate. The echocardiographic parameters as LVEF, TAPSE, LVFP were similar;the free wall GLS of both RV and LV were reduced in both the groups but that of RV (and LV were affected more in lower and higher pulse rate group respectively. Conclusion: Baseline pulse-rate in post covid subjects is likely related to neuro-inflammatory symptoms (anosmia) and poor LVGLS suggesting LV myocardial dysfunction.
ABSTRACT
Background: Covid-19 affected our population in multiple waves. We have looked for the differences in frequency and the weight/impact of symptoms between the first and the second waves. Method: The post-covid-19 subjects attending our out-patient department for post-covid-19 problems after the 1st and he 2nd waves were enquired retrospectively about the demography with the frequency and severity of different symptoms cough, breathlessness, throat pain, nasal discharge, fever, body-ache, weakness, diarrhoea, constipation, pedal/finger swelling, headache, expectoration. anosmia, and loss of taste) that they suffered from. The weight/impact of a symptom was derived by multiplying the duration of symptoms (in days) with the severity (in Likert scale;0 to 5;0=none and 5=maximum possible symptoms). The data was analysed statistically using unpaired 't-test' and 'chi-square test' to compare between the two covid-19 waves. Result: 185 and 222 subjects' data were included for the 1st and the 2nd waves of covid-19 respectively. The gender ratio was similar but the mean age was significantly lower in the victims of the second wave (56.17±13.64, 51.32±15.59;p=0.0017). As regards the symptom-frequency, fever (p=0.0154), constipation (p=0.0243), headache (p=0.0014), anosmia (p=<0.0001) and loss of taste (p=0.0009) were significantly worse in the 2nd wave. The symptom severity of cough (p=0.0184), throat pain (p=0.039), mild weakness (p=0.0063), anosmia (p=0.0004) and loss of taste (p=0.0026) were also higher in the 2nd wave of Covid-19. Conclusion: It appears that each wave of the pandemic was distinct as regards the symptomatology. Such peculiarity in the clinical dynamics of Covid-19 needs to be noticed and followed in future.
ABSTRACT
Background: The second wave of Covid-19 had a huge number of asymptomatic, false negative (indeterminant) and symptomatic untested cases (query Covid). Objective: The aim is to understand the dynamics among these groups to know their impact on the spread of the diseases. Methods: In a prospective online survey we collected data using snowball sampling method via social media, from in and around Kolkata with the help of Google forms. The data included Covid related symptoms, evaluation, and behavior related to treatment during first and second wave of the disease. The discrepancies and duplicities were first excluded, and 989 respondents' data were statistically analyzed using SPSSver26. Results: The percentage of RT-PCR confirmed symptomatic and asymptomatic Covid cases were 21.84% (n=216) and 2.12% (n=21) respectively. Symptomatic but unconfirmed cases (query Covid) were 17.18% (n=170) and symptomatic false-negative cases (indeterminant) were 93 (9.40%). Rest 489 (49.44%) did not have any symptoms or never tested positive. The analysis revealed the reasons for doing RT-PCR test include a) less symptoms severity (47.06%), b)considering test unnecessary (22.94%),c) home collection unavailability(14.71%) and d)longer waiting time for results(8.82%). According to regression analysis, compared to confirmed Covid symptomatic group, only 47% [OR: 0.13(0.57-0.30) p<0.0001] of query covid patients consulted doctor for test or treatment and 21% [OR:9.55 (1.97-46.16), p<0.001] of indeterminant cases took medicine based on advice of friends/ relatives. Conclusion: There is a high percentage of untested (query Covid) and probable false negative cases (indeterminant) likely going unreported. The reasons for poor testing and seeking medical attention inadequately needs to be addressed and further investigated.
ABSTRACT
Background: High morbidity and mortality has been observed with COVID-19 infection;however, there are limited data on clinical characteristics including exposures, coinfections, and antimicrobial use among cancer patients. We aimed to better characterize clinical features and outcomes in this population. Methods: We conducted a retrospective chart review of consecutive patients at the Seattle Cancer Care Alliance diagnosed with SARS-CoV-2 infection by RT-PCR between February 28, 2020 and May 3, 2020. We obtained demographic and clinical data including coinfections, antimicrobial use and outcomes at 30 days after diagnosis. Results: Of 60 patients reviewed, the median age was 62 years (range 22-98) and 43% were male. 34 (57%) patients had solid tumors and 16 (27%) hematologic malignancies. Breast (12%), colorectal (8%) and non-Hodgkin lymphoma (8%) were the most prevalent cancers. 34 (57%) had ≥ 2 comorbidities. The majority of identified exposures were from long-term care facilities (LTCF) (27%) or household contacts (25%) (Fig 1). The most common symptoms at diagnosis were cough (72%), fevers/chills (57%), shortness of breath (38%), nasal congestion/rhinorrhea (35%), and diarrhea (30%). 18 (31%) patients were prescribed at least one course of antibiotics within 30 days of diagnosis;antibiotics were prescribed to 54% of hospitalized patients (Fig 2). 6 (10%) had a documented bacterial infection;of these, 3 were respiratory coinfections. No viral or fungal copathogens were reported. 26 (43%) patients were hospitalized, 9 (15%) admitted to intensive care, and one (2%) required mechanical ventilation. 12 (20%) died within 30 days of diagnosis (Fig 3);of these, 10 (83%) had ≥ 2 comorbidities and 8 (67%) had LTCF exposure.