Risk of mortality in COVID-19 patients: a meta- and network analysis
Abstract Introduction: Understanding the most relevant hematological/biochemical characteristics, pre-existing health conditions and complications in survivors and non-survivor will aid in predicting COVID-19 patient mortality. Materials and Methods: A literature review was conducted for COVID-19 mortality in PubMed, Scopus, and various preprint servers (bioRxiv, medRxiv and SSRN), with 97 observational studies and preprints, consisting of survivor and non-survivor sub-populations. This meta/network analysis comprised 19014 COVID-19 patients, consisting of 14359 survivors and 4655 non-survivors. Meta and network analyses were performed using META-MAR V2.7.0 and PAST software. Results: The study revealed that non-survivors of COVID-19 had elevated levels of gamma-glutamyl transferase and creatinine, as well as a higher number of neutrophils. Non-survivors had fewer lymphocytes and platelets, as well as lower hemoglobin and albumin concentrations. Age, hypertension, and cerebrovascular disease were shown to be the most influential risk factors among non-survivors. The most common complication among non-survivors was heart failure, followed by septic shock and respiratory failure.Conclusion: This meta-analysis showed that inexpensive and fast biochemical and hematological tests, as well as pre-existing conditions and complications, can be used to estimate the risk of mortality in COVID-19 patients..
| Medienart: |
|
|---|
Preprint| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
ResearchSquare.com - (2023) vom: 16. Okt. Zur Gesamtaufnahme - year:2023 |
|---|
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Kowsar, Rasoul [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| doi: |
10.21203/rs.3.rs-1510431/v1 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
XRA035764201 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | XRA035764201 | ||
| 003 | DE-627 | ||
| 005 | 20231017132746.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 220415s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.21203/rs.3.rs-1510431/v1 |2 doi | |
| 035 | |a (DE-627)XRA035764201 | ||
| 035 | |a (ResearchSquare)10.21203/rs.3.rs-1510431/v1 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Kowsar, Rasoul |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Risk of mortality in COVID-19 patients: a meta- and network analysis |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Abstract Introduction: Understanding the most relevant hematological/biochemical characteristics, pre-existing health conditions and complications in survivors and non-survivor will aid in predicting COVID-19 patient mortality. Materials and Methods: A literature review was conducted for COVID-19 mortality in PubMed, Scopus, and various preprint servers (bioRxiv, medRxiv and SSRN), with 97 observational studies and preprints, consisting of survivor and non-survivor sub-populations. This meta/network analysis comprised 19014 COVID-19 patients, consisting of 14359 survivors and 4655 non-survivors. Meta and network analyses were performed using META-MAR V2.7.0 and PAST software. Results: The study revealed that non-survivors of COVID-19 had elevated levels of gamma-glutamyl transferase and creatinine, as well as a higher number of neutrophils. Non-survivors had fewer lymphocytes and platelets, as well as lower hemoglobin and albumin concentrations. Age, hypertension, and cerebrovascular disease were shown to be the most influential risk factors among non-survivors. The most common complication among non-survivors was heart failure, followed by septic shock and respiratory failure.Conclusion: This meta-analysis showed that inexpensive and fast biochemical and hematological tests, as well as pre-existing conditions and complications, can be used to estimate the risk of mortality in COVID-19 patients. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Rahimi, Amir Mohammad |4 aut | |
| 700 | 1 | |a Sr, Magdalena |4 aut | |
| 700 | 1 | |a Mansouri, Alireza |4 aut | |
| 700 | 1 | |a Sadeghi, Khaled |4 aut | |
| 700 | 1 | |a Bonakdar, Elham |4 aut | |
| 700 | 1 | |a Kateb, Sayed Farshad |4 aut | |
| 700 | 1 | |a Mahdavi, Amir Hossein |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t ResearchSquare.com |g (2023) vom: 16. Okt. |
| 773 | 1 | 8 | |g year:2023 |g day:16 |g month:10 |
| 856 | 4 | 0 | |u https://doi.org/10.1038/s41598-023-29364-8 |z lizenzpflichtig |3 Volltext |
| 856 | 4 | 0 | |u http://dx.doi.org/10.21203/rs.3.rs-1510431/v1 |z kostenfrei |3 Volltext |
| 912 | |a GBV_XRA | ||
| 951 | |a AR | ||
| 952 | |j 2023 |b 16 |c 10 | ||