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Record W3129889086 · doi:10.1097/md.0000000000023991

Clinical characteristics and outcomes of 48 patients hospitalized for COVID-19 infection in Wuxi

2021· article· en· W3129889086 on OpenAlexaff
Meiping Chu, Linjie Bian, Jiehui Huang, Yigang Chen, Danping Wu, Hao Wang

Bibliographic record

VenueMedicine · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)BetacoronavirusMEDLINECoronavirus InfectionsInternal medicineVirologyIntensive care medicineOutbreakInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

ABSTRACT: Since the first infected case of Coronavirus Disease 2019 (COVID-19) was reported in Wuhan, China in December 2019, the virus has spread swiftly, inflicting upon millions of people around the globe. The objective of the study is to investigate and analyze the clinical characteristics and outcomes of patients infected with COVID-19 in Wuxi, China.Cross-sectional study.The Fifth People's Hospital of Wuxi, China.A total of 48 COVID-19 patients were enrolled in the study from 23 January 2020 to 8 March 2020, and the clinical data of these subjects were collected.Epidemiological, clinical, laboratory, and radiologic characteristics, as well as treatment and outcome data, were collected and analyzed.Of these 48 patients with confirmed COVID-19, 3 were mild cases (6.3%), 44 were moderate cases (91.7%), 1 was severe case (2.1%). The median age of the subjects was 45 years (interquartile range [IQR], 24-59; range, 5-75 years). Twenty-five of the patients (52.1%) were male and 23 (47.9%) were female. Twenty-eight cases (58.3%) returned to Wuxi, Jiangsu Province. Thirty-four (70.8%) cases were infected due to clustering epidemic and 29 cases (85.3%) were attributable to family-clustering epidemic. No obvious clinical symptoms were observed in the cohort of patients, except for 3 mild cases. The most common symptoms include fever (41 [85.4%]), cough (28 [58.3%]), asthenia (13 [27.1%]), expectoration (11 [22.9%]), diarrhea (10 [20.8%]), and dyspnea (5 [10.4%]). Seventeen (35.4%) patients had lower lymphocyte values than baseline, 31 patients (64.6%) had higher d-dimers to exceed the normal range. The distribution of high-resolution computed tomography (HRCT)-positive lesions were as follows: left lung in 5 cases (10.4%), right lung in 9 cases (18.8%), and bilateral lungs in 31 cases (64.6%). In terms of density of lesions: 28 cases (58.3%) showed ground glass shadows in the lung, 7 cases (14.6%) showed solid density shadows, and 10 cases (20.8%) showed mixed density shadows. Extrapulmonary manifestations found that mediastinal lymph nodes were enlarged in 2 cases (4.2%) and that pleural effusion was present in 1 case (2.1%). All patients underwent treatment in quarantine. Forty-five (93.8%) patients received antiviral treatments, 22 (45.8%) patients received antibacterial treatments, 6 (12.5%) patients received glucocorticoid treatments, 2 (4.2%) patients received high flow oxygen inhalation treatments, and 6 (12.5%) patients received noninvasive ventilation treatments. As of 8 March 2020, all 48 patients included in this study were cured. The average time of hospitalization of the 48 patients was 18 ± 6 (mean ± SD) days, the average time of the lesion resorption was 11 ± 4 days, and the average time taken to achieve negativity in the result of nucleic acid examination was (10 ± 4) days.The epidemiological characteristics of 48 COVID-19 patients in Wuxi were mainly imported cases and clustered cases. The clinical manifestations of these patients were mainly fever and cough. Laboratory results showed that the lymphocytopenia and increased d-dimer are positively correlated with disease severity. Pulmonary imaging showed unilateral or bilateral ground glass infiltration. Most of the patients entered clinical recovery stage within 15 days after hospitalization.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.510
Teacher spread0.419 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations6
Published2021
Admission routes1
Has abstractyes

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