Clinical data of COVID-19 infected patients
Data files
May 15, 2024 version files 122.84 KB
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Clinical_Data_of_COVID-19_Infected_Patients.xlsx
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README.md
Abstract
Objectives
This study aimed to evaluate the clinical efficacy of Paxlovid in patients hospitalized with severe/critical COVID-19.
Methods
Data were acquired from patients with severe/critical COVID-19 diagnosed between December 2022 and January 2023 at a medical center in China. Patients were divided into the Paxlovid treatment group and the conventional treatment group. The association between Paxlovid and all-cause mortality of patients during hospitalization was evaluated using the COX regression model and inverse probability weighting method, respectively. The secondary endpoint was the improvement in patients’ lung imaging findings 1 week later. The odds ratio (OR) was estimated using logistic regression.
Results
A total of 158 eligible patients were enrolled, including 50 in-hospital deaths (50/98) in the Paxlovid group and 28 (28/60) in the conventional treatment group. The corrected hazard ratio for death was 0.51 (95% CI: 0.28–0.94, p = 0.031) and the inverse probability-weighted hazard ratio was 0.42 (95% CI: 0.24–0.75). The secondary endpoint analysis revealed that Paxlovid was associated with improved lung imaging findings 1 week later (adjusted OR: 0.35, 95% CI: 0.16–0.77).
Conclusion
Treatment with Paxlovid is associated with a significantly reduced risk of death and improved lung imaging findings in patients with severe/critical COVID-19.
README: Clinical Data of COVID-19 Infected Patients
https://doi.org/10.5061/dryad.m63xsj49r
the data were mainly acquired from a large medical center in China, where the diagnosis and treatment of critical illness is one of its strengths. Clinical data was obtained by searching in the electronic medical record system. Departments included in the search were where COVID-19 cases were centralized for treatment in our center, such as the respiratory department, the isolation wards for COVID-19 cases, and the intensive care unit (ICU). Clinical data from patients diagnosed with severe or critical COVID-19 infection were continuously collected and included in this study, with a time frame ranging from December 1, 2022, to January 15, 2023, during which the Omicron infection had peaked in mainland China.
Description of the data and file structure
The electronic medical records of patients eligible for inclusion in this hospital were analyzed, with the following data acquired: Demographic characteristics, comorbidities, age-adjusted Charlson Index, initial symptoms and timing, admission and lung CT scan or chest X-ray findings within one week of admission, diagnosis, severity (severe, critical), laboratory tests (including COVID-19 nucleic acid test CT values), prescription and medication records (including antiviral drug Paxlovid, steroids, anticoagulants, immunotherapy (Baricitinib or Tocilizumab)), and ICU hospitalization information are all documented.
Demographic characteristics mainly include age range, and we have hidden other information that may expose patient privacy.
Basic diseases: Each number represents a specific underlying disease or comorbidity condition (as indicated in the column headings), and rare potential impactful diseases have been separately annotated.
Initial symptoms: This represents the systems affected by the initial symptoms in COVID-19 patients, as indicated in the column headings.
Temperature: The body temperature on the first day of confirmed COVID-19 infection, measured in degrees Celsius.
Fever days: The number of days with body temperature above the normal range from the first day to the seventh day of onset.
Severity(D3): The severity level of the disease on the third day of onset. WHO defines severe and critical cases as follows: Severe cases are defined as having any of the following criteria: ① oxygen saturation <90% on room air, ② signs of pneumonia, ③ severe respiratory distress. Critical cases are defined as having any of the following criteria: ① requirement of life support treatment, ② acute respiratory distress syndrome, ③ sepsis, ④ septic shock.
Pulmonary CT condition: 'CT1-D1' represents the time difference in days between the first chest CT scan and the day of confirmed diagnosis, and 'CT2-D1' can be extrapolated in a similar manner. The lung CT was assessed using CT severity score (CTSS), and the severity of the disease was divided into 5 groups (1: <5%, 2: 5%–25%, 3: 26%–50%, 4: 51%–75%, and 5: > 75%, range: 1–5) based on the extent of lobar involvement. The global score was calculated by adding up the scores for 5 lobes.
Virus nucleic acid test: The CT value obtained from the nucleic acid test for the novel coronavirus can reflect the quantity of viral copies. The N gene and ORF gene are currently the target genes for nucleic acid testing of the novel coronavirus, and they are specific segments of the novel coronavirus nucleic acid. 'time1-D1' refers to the number of days between the nucleic acid test and the first day of confirmed diagnosis. Extrapolating from this. 'Negative conversion' describes the situation where a patient's novel coronavirus test result turns negative.
Antiviral drugs: The types of medications, the duration of medication (represented in days since the initial diagnosis), and the number of days of medication are recorded, as well as the details of steroid and anticoagulant usage. Additionally, we meticulously document the daily dosage of anticoagulants.
Additional Note: [null] indicates missing data, as the patients may have been transferred out or deceased, resulting in the unavailability of corresponding clinical data.