Non-Severe vs Severe Symptomatic COVID-19: 104 Cases from the Outbreak on the Cruise Ship 'Diamond Princess' in Japan

Tabata, Sakiko; Imai, K.; Kawano, Shuichi; Ikeda, Mayu; Kodama, Tatsuhiko; Miyoshi, Kazuyasu; Obinata, Hirofumi; Mimura, Satoshi; Kodera, Tsutomu; Kitagaki, Manabu; Sato, Michiya; Suzuki, Satoshi; Ito, Tsuyoshi; Uwabe, Yasuhide; Tamura, Kouichi

doi:10.2139/ssrn.3551331

Cited by 11 publications

(13 citation statements)

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“…1). There were a total of 3099 patients from 23 studies [5][6][7][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Baseline characteristics are presented in Table 1.…”

Section: Baseline Characteristics and Study Selectionmentioning

confidence: 99%

Lymphopenia in severe coronavirus disease-2019 (COVID-19): systematic review and meta-analysis

2020

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Objective: Clinical and laboratory biomarkers to predict the severity of coronavirus disease 2019 (COVID-19) are essential in this pandemic situation of which resource allocation must be urgently prepared especially in the context of respiratory support readiness. Lymphocyte count has been a marker of interest since the first COVID-19 publication. We conducted a systematic review and meta-analysis in order to investigate the association of lymphocyte count on admission and the severity of COVID-19. We would also like to analyze whether patient characteristics such as age and comorbidities affect the relationship between lymphocyte count and COVID-19. Methods: Comprehensive and systematic literature search was performed from PubMed, SCOPUS, EuropePMC, ProQuest, Cochrane Central Databases, and Google Scholar. Research articles in adult patients diagnosed with COVID-19 with information on lymphocyte count and several outcomes of interest, including mortality, acute respiratory distress syndrome (ARDS), intensive care unit (ICU) care, and severe COVID-19, were included in the analysis. Inverse variance method was used to obtain mean differences and its standard deviations. Maentel-Haenszel formula was used to calculate dichotomous variables to obtain odds ratios (ORs) along with its 95% confidence intervals. Random-effect models were used for meta-analysis regardless of heterogeneity. Restrictedmaximum likelihood random-effects meta-regression was performed for age, gender, cardiac comorbidity, hypertension, diabetes mellitus, COPD, and smoking. Results: There were a total of 3099 patients from 24 studies. Meta-analysis showed that patients with poor outcome have a lower lymphocyte count (mean difference − 361.06 μL [− 439.18, − 282.95], p < 0.001; I 2 84%) compared to those with good outcome. Subgroup analysis showed lower lymphocyte count in patients who died (mean difference − 395.35 μL [− 165.64, − 625.07], p < 0.001; I 2 87%), experienced ARDS (mean difference − 377.56 μL [− 271.89, − 483.22], p < 0.001; I 2 0%), received ICU care (mean difference − 376.53 μL [− 682.84, − 70.22], p = 0.02; I 2 89%), and have severe COVID-19 (mean difference − 353.34 μL [− 250.94, − 455.73], p < 0.001; I 2 85%). Lymphopenia was associated with severe COVID-19 (OR 3.70 [2.44, 5.63], p < 0.001; I 2 40%). Meta-regression showed that the association between lymphocyte count and composite poor outcome was affected by age (p = 0.034). Conclusion: This meta-analysis showed that lymphopenia on admission was associated with poor outcome in patients with COVID-19.

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Section: Baseline Characteristics and Study Selectionmentioning

confidence: 99%

Lymphopenia in severe coronavirus disease-2019 (COVID-19): systematic review and meta-analysis

2020

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“…Full text screening then resulted in 148 included articles (Fig 1). [166,167], the USA [168,169], Singapore [170,171], Italy [172,173], Australia [174], Japan [175], Korea [176] and the Netherlands [177]. The mean age of patients was 49 years (SD 11) and where sex data were available, the ratio of males:females was 1.2:1 (10,306:8593).…”

Section: Study Selectionmentioning

confidence: 99%

The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARS-CoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries

et al. 2020

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Background To limit the spread of SARS-CoV-2, an evidence-based understanding of the symptoms is critical to inform guidelines for quarantining and testing. The most common features are purported to be fever and a new persistent cough, although the global prevalence of these symptoms remains unclear. The aim of this systematic review is to determine the prevalence of symptoms associated with COVID-19 worldwide. Methods We searched PubMed, Embase, CINAHL, AMED, medRxiv and bioRxiv on 5 th April 2020 for studies of adults (>16 years) with laboratory test confirmed COVID-19. No language or publication status restrictions were applied. Data were independently extracted by two review authors into standardised forms. All datapoints were independently checked by three other review authors. A random-effects model for pooling of binomial data was applied to estimate the prevalence of symptoms, subgrouping estimates by country. I 2 was used to assess inter-study heterogeneity. Results Of 851 unique citations, 148 articles were included which comprised 24,410 adults with confirmed COVID-19 from 9 countries. The most prevalent symptoms were fever (78% [95% CI 75%-81%]; 138 studies, 21,701 patients; I 2 94%), a cough (57% [95% CI 54%-60%]; 138 studies, 21,682 patients; I 2 94%) and fatigue (31% [95% CI 27%-35%]; 78 studies, 13,385 patients; I 2 95%). Overall, 19% of hospitalised patients required non-invasive ventilation (44 studies,

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“…Older age was found to be a risk factor for ARDS and death in a single-center study of 201 patients [8]. A possible association between Chest CT findings and severe COVID-19, suggested in a study of 104 patients aboard the "Diamond Princess" cruise ship [9], is discussed below.…”

Section: Clinical Risk Factorsmentioning

confidence: 93%

“…In the setting of high clinical suspicion for COVID-19, a negative CT can be detrimental as it can lead to false reassurances. On the "Diamond Princess" cruise ship, Chest CT abnormalities were found in 56.6% (43/76) of the non-severe cases and 82.1% (23/28) of the severe cases [9]; although there is a clinically significant difference in the number of abnormal CTs, clinical decisions on likelihood of deterioration would be unreliable.…”

Section: Ct Risk Factorsmentioning

confidence: 99%

Imaging & other potential predictors of deterioration in COVID-19

Shah¹,

Kamler²,

Phan³

et al. 2020

The American Journal of Emergency Medicine

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Non-Severe vs Severe Symptomatic COVID-19: 104 Cases from the Outbreak on the Cruise Ship 'Diamond Princess' in Japan

Cited by 11 publications

References 0 publications

Lymphopenia in severe coronavirus disease-2019 (COVID-19): systematic review and meta-analysis

Lymphopenia in severe coronavirus disease-2019 (COVID-19): systematic review and meta-analysis

The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARS-CoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries

Imaging & other potential predictors of deterioration in COVID-19

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