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Evaluation of invasive ventilation rate and comorbidities, clinical signs and lab findings among COVID-19 patients.

ABSTRACT: The severity of COVID-19 has been to be associated with comorbidities. It is defined as the presentation of severe respiratory dysfunction or failure, leading to the need for ventilation and mortality. The aim of this study is the evaluate the factors predicting the rate of invasive ventilation among these patients. This retrospective study involved 317 COVID-19 patients referred to (XXX) Hospital in Qom, Iran. The following data were obtained for all the patients: demographic parameters, comorbidities, need for mechanical ventilation, signs and symptoms and lab findings. The results from the demographic data of the study indicated that the need for mechanical ventilation is significantly associated with advanced age, p = 0.001. Additionally, hypertension, leukopenia and blood urea nitrogen to creatinine ratio p = 0.008. p = 0.042 and p < 0.001, respectively, are significantly associated with an increased need for mechanical ventilation. Malignancy, diabetes, asthma, chronic obstructive pulmonary disease, headache, fever, platelet count, prothrombin time, c-reactive protein, erythrocyte sedimentation rate and creatinine phosphatase were not significantly different in the two groups, p > 0.05. Prediction of the extent of severity among COVID-19 patients using clinical parameters and comorbidities prepare medical practitioners and health care centres to take immediate measurements and reduce the burden of the scarcity of health supplies and care.

SUBMITTER: Farzan N

PROVIDER: S-EPMC8302482 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Coronavirus disease-2019, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was a disaster in 2020. Accurate and early diagnosis of coronavirus disease-2019 (COVID-19) is still essential for health policymaking. Reverse transcriptase-polymerase chain reaction (RT-PCR) has been performed as the operational gold standard for COVID-19 diagnosis. We aimed to design and implement a reliable COVID-19 diagnosis method to provide the risk of infection using demographics, symptoms and signs, blood markers, and family history of diseases to have excellent agreement with the results obtained by the RT-PCR and CT-scan. Our study primarily used sample data from a 1-year hospital-based prospective COVID-19 open-cohort, the Khorshid COVID Cohort (KCC) study. A sample of 634 patients with COVID-19 and 118 patients with pneumonia with similar characteristics whose RT-PCR and chest CT scan were negative (as the control group) (dataset 1) was used to design the system and for internal validation. Two other online datasets, namely, some symptoms (dataset 2) and blood tests (dataset 3), were also analyzed. A combination of one-hot encoding, stability feature selection, over-sampling, and an ensemble classifier was used. Ten-fold stratified cross-validation was performed. In addition to gender and symptom duration, signs and symptoms, blood biomarkers, and comorbidities were selected. Performance indices of the cross-validated confusion matrix for dataset 1 were as follows: sensitivity of 96% [confidence interval, CI, 95%: 94-98], specificity of 95% [90-99], positive predictive value (PPV) of 99% [98-100], negative predictive value (NPV) of 82% [76-89], diagnostic odds ratio (DOR) of 496 [198-1,245], area under the ROC (AUC) of 0.96 [0.94-0.97], Matthews Correlation Coefficient (MCC) of 0.87 [0.85-0.88], accuracy of 96% [94-98], and Cohen's Kappa of 0.86 [0.81-0.91]. The proposed algorithm showed excellent diagnosis accuracy and class-labeling agreement, and fair discriminant power. The AUC on the datasets 2 and 3 was 0.97 [0.96-0.98] and 0.92 [0.91-0.94], respectively. The most important feature was white blood cell count, shortness of breath, and C-reactive protein for datasets 1, 2, and 3, respectively. The proposed algorithm is, thus, a promising COVID-19 diagnosis method, which could be an amendment to simple blood tests and screening of symptoms. However, the RT-PCR and chest CT-scan, performed as the gold standard, are not 100% accurate.

Project description:ObjectivesPatients with COVID-19 frequently develop acute respiratory distress syndrome (ARDS) requiring intensive care unit (ICU) admission. Data on long-term survival of these patients are lacking. The authors investigated 1-year survival, quality of life, and functional recovery of patients with COVID-19 ARDS requiring invasive mechanical ventilation.DesignProspective observational study.SettingTertiary-care university hospital.ParticipantsAll patients with COVID-19 ARDS receiving invasive mechanical ventilation and discharged alive from hospital.InterventionsPatients were contacted by phone after 1 year. Functional, cognitive, and psychological outcomes were explored through a questionnaire and assessed using validated scales. Patients were offered the possibility to undergo a follow-up chest computed tomography (CT) scan.Measurements and main resultsThe study included all adult (age ≥18 years) patients with COVID-19-related ARDS admitted to an ICU of the authors' institution between February 25, 2020, and April 27, 2020, who received at least 1 day of invasive mechanical ventilation (IMV). Of 116 patients who received IMV, 61 (52.6%) survived to hospital discharge. These survivors were assessed 1 year after discharge and 56 completed a battery of tests of cognition, activities of daily living, and interaction with family members. They had overall good functional recovery, with >80% reporting good recovery and no difficulties in usual activities. A total of 52 (93%) of patients had no dyspnea at rest. Severe anxiety/depression was reported by 5 (8.9%) patients. Comparing 2-month and 1-year data, the authors observed the most significant improvements in the areas of working status and exertional dyspnea. One-year chest CT scans were available for 36 patients; fibrotic-like changes were present in 4 patients.ConclusionsAll patients who survived the acute phase of COVID-19 and were discharged from the hospital were alive at the 1-year follow up, and the vast majority of them had good overall recovery and quality of life.

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Evaluation of invasive ventilation rate and comorbidities, clinical signs and lab findings among COVID-19 patients.

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