ArticleBMC infectious diseases2020
A nomogramic model based on clinical and laboratory parameters at admission for predicting the survival of COVID-19 patients.
Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Serum hydroxybutyrate dehydrogenase and COVID-19 severity and mortality: a systematic review and meta-analysis with meta-regression.Clinical and experimental medicine · 2022Pooled it
- Hematological and biochemical markers and cytokine levels in hospitalized psychiatric patients with COVID-19.Frontiers in immunology · 2025Article
- Regression without regrets -initial data analysis is a prerequisite for multivariable regression.BMC medical research methodology · 2024Article
- Associated Biochemical and Hematological Markers in COVID-19 Severity Prediction.Advances in medicine · 2023Article
- Article
- Predicting In-Hospital Mortality in Severe COVID-19: A Systematic Review and External Validation of Clinical Prediction Rules.Biomedicines · 2022Article
- Lung ultrasound predicts clinical course but not outcome in COVID-19 ICU patients: a retrospective single-center analysis.BMC anesthesiology · 2021Article
- CT-based radiomics combined with signs: a valuable tool to help radiologist discriminate COVID-19 and influenza pneumonia.BMC medical imaging · 2021Article
- Epidemiologic Characteristics of and Prognostic Factors for COVID-19 Among Hospitalized Patients: Updated Implications From Hubei Province, China.Frontiers in public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
backgroundCOVID-19 has become a major global threat. The present study aimed to develop a nomogram model to predict the survival of COVID-19 patients based on their clinical and laboratory data at admission.
methodsCOVID-19 patients who were admitted at Hankou Hospital and Huoshenshan Hospital in Wuhan, China from January 12, 2020 to March 20, 2020, whose outcome during the hospitalization was known, were retrospectively reviewed. The categorical variables were compared using Pearson's χ
resultsA total of 262 patients (134 surviving and 128 non-surviving patients) were included in the analysis. Seven variables, which included age (relative risk [RR]: 0.905, 95% confidence interval [CI]: 0.868-0.944; P < 0.001), chronic heart disease (CHD, RR: 0.045, 95% CI: 0.0097-0.205; P < 0.001, the percentage of lymphocytes (Lym%, RR: 1.125, 95% CI: 1.041-1.216; P = 0.0029), platelets (RR: 1.008, 95% CI: 1.003-1.012; P = 0.001), C-reaction protein (RR: 0.982, 95% CI: 0.973-0.991; P < 0.001), lactate dehydrogenase (LDH, RR: 0.993, 95% CI: 0.990-0.997; P < 0.001) and D-dimer (RR: 0.734, 95% CI: 0.617-0.879; P < 0.001), were identified as the independent risk factors. The nomogram model based on these factors exhibited a good discrimination, with an AUC of 0.948 (95% CI: 0.923-0.973).
conclusionsA nomogram based on age, CHD, Lym%, platelets, C-reaction protein, LDH and D-dimer was established to accurately predict the prognosis of COVID-19 patients. This can be used as an alerting tool for clinicians to take early intervention measures, when necessary.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.