The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis

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Looking at the prevalence data in the world and in Indonesia, the highest mortality rate due to COVID-19 involves age, gender and comorbidities such as diabetes mellitus. Severity of the condition also refers to coagulation abnormalities, such as abnormal prothrombin time values. Methods This systematic review study and meta-analysis used online literature sourced from PubMed, Science Direct, EBSCO, Cochrane and Google Scholar. This study aimed to evaluate the association between age, sex, and prothrombin time and the likelihood of hospitalization among COVID-19 patients with diabetes. The literature used here is literature that has data on age, sex and prothrombin time of COVID-19 patients with diabetes mellitus whose quality is assessed by the NOS (Newcastle-Ottawa Scale) criteria and processing data using Review Manager 5.4. Results Out of 8711 literatures that were traced from various search sources, there were 45 literatures that were included in this study. The results of the analysis on age showed the Standardized Mean Difference (SMD) value of 0.45 and P <0.0001 (95% CI: 0.23–0.68), the gender analysis showed an Odds Ratio (OR) value of 3.28 and P = 0.01 (95% CI: 1.26–8.52) and the prothrombin time analysis showed SMD values of 0.41 and P = 0.07 (95%CI = -0.03–0.85). Conclusion Patients with COVID-19 who have DM have a higher risk of hospitalization compared to those without DM. Among COVID-19 patients with DM admitted to hospitals, they were older compared to those without DM and prothrombin time values similar but slightly higher in COVID-19 patients with DM. 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F1000Research 2025, 11 :729 ( https://doi.org/10.12688/f1000research.107398.7 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Systematic Review Revised The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] Previously titled: The relationship of age, sex and prothrombin time related to the severity and mortality of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis Audrey Fabianisa Mirza https://orcid.org/0000-0003-2222-8607 1 , Ceria Halim https://orcid.org/0000-0002-1361-8147 1 , Mutiara Indah Sari https://orcid.org/0000-0001-6510-2196 2 Audrey Fabianisa Mirza https://orcid.org/0000-0003-2222-8607 1 , Ceria Halim https://orcid.org/0000-0002-1361-8147 1 , Mutiara Indah Sari https://orcid.org/0000-0001-6510-2196 2 PUBLISHED 14 Oct 2025 Author details Author details 1 Faculty of Medicine, Universitas Sumatera Utara, Medan, Sumatera Utara, 20155, Indonesia 2 Department of Biochemistry, Universitas Sumatera Utara, Medan, Sumatera Utara, 20155, Indonesia Audrey Fabianisa Mirza Roles: Conceptualization, Formal Analysis, Investigation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Ceria Halim Roles: Formal Analysis, Writing – Original Draft Preparation, Writing – Review & Editing Mutiara Indah Sari Roles: Conceptualization, Formal Analysis, Funding Acquisition, Methodology, Project Administration, Supervision OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Emerging Diseases and Outbreaks gateway. This article is included in the Coronavirus (COVID-19) collection. Abstract Background SARS-CoV-2 first appeared in Wuhan, China, in December 2019. Looking at the prevalence data in the world and in Indonesia, the highest mortality rate due to COVID-19 involves age, gender and comorbidities such as diabetes mellitus. Severity of the condition also refers to coagulation abnormalities, such as abnormal prothrombin time values. Methods This systematic review study and meta-analysis used online literature sourced from PubMed, Science Direct, EBSCO, Cochrane and Google Scholar. This study aimed to evaluate the association between age, sex, and prothrombin time and the likelihood of hospitalization among COVID-19 patients with diabetes. The literature used here is literature that has data on age, sex and prothrombin time of COVID-19 patients with diabetes mellitus whose quality is assessed by the NOS (Newcastle-Ottawa Scale) criteria and processing data using Review Manager 5.4. Results Out of 8711 literatures that were traced from various search sources, there were 45 literatures that were included in this study. The results of the analysis on age showed the Standardized Mean Difference (SMD) value of 0.45 and P <0.0001 (95% CI: 0.23–0.68), the gender analysis showed an Odds Ratio (OR) value of 3.28 and P = 0.01 (95% CI: 1.26–8.52) and the prothrombin time analysis showed SMD values of 0.41 and P = 0.07 (95%CI = -0.03–0.85). Conclusion Patients with COVID-19 who have DM have a higher risk of hospitalization compared to those without DM. Among COVID-19 patients with DM admitted to hospitals, they were older compared to those without DM and prothrombin time values similar but slightly higher in COVID-19 patients with DM. READ ALL READ LESS Keywords age, sex, prothrombine time, COVID-19, diabetes mellitus Corresponding Author(s) Mutiara Indah Sari ( [email protected] ) Close Corresponding author: Mutiara Indah Sari Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2025 Mirza AF et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Mirza AF, Halim C and Sari MI. The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.12688/f1000research.107398.7 ) First published: 01 Jul 2022, 11 :729 ( https://doi.org/10.12688/f1000research.107398.1 ) Latest published: 14 Oct 2025, 11 :729 ( https://doi.org/10.12688/f1000research.107398.7 ) Revised Amendments from Version 6 In this version, several substantive and editorial revisions have been made to improve the clarity, accuracy, and consistency of the manuscript. First, the aim of the study has been more explicitly stated in the Abstract and Introduction to emphasize that the analysis focuses on hospitalized COVID-19 patients rather than disease severity in general. The Abstract’s conclusion was also revised to clarify the specific type of risk (i.e., hospitalization) among patients with diabetes mellitus. Second, several terminology adjustments were made throughout the manuscript. The term “incidence” was replaced with “prevalence” in multiple sections to more accurately reflect the study design and data interpretation. In addition, the use of “and” in the inclusion criteria was revised to “or” to correctly represent the variables available in the included studies. The time frame of the literature search has been specified in greater detail by indicating the exact months. Third, results and discussion sections were refined to align with statistical findings. The statement regarding gender differences was revised to clearly indicate that male patients with diabetes have a higher risk of hospitalization compared to female patients. The interpretation of prothrombin time results was clarified to reflect that no statistically significant difference was found, although a trend toward higher values was observed in diabetic patients. Finally, additional clarifications were added to the discussion to ensure that all findings are appropriately contextualized within the population of hospitalized patients. These revisions address reviewer feedback and enhance the overall precision and readability of the manuscript. In this version, several substantive and editorial revisions have been made to improve the clarity, accuracy, and consistency of the manuscript. First, the aim of the study has been more explicitly stated in the Abstract and Introduction to emphasize that the analysis focuses on hospitalized COVID-19 patients rather than disease severity in general. The Abstract’s conclusion was also revised to clarify the specific type of risk (i.e., hospitalization) among patients with diabetes mellitus. Second, several terminology adjustments were made throughout the manuscript. The term “incidence” was replaced with “prevalence” in multiple sections to more accurately reflect the study design and data interpretation. In addition, the use of “and” in the inclusion criteria was revised to “or” to correctly represent the variables available in the included studies. The time frame of the literature search has been specified in greater detail by indicating the exact months. Third, results and discussion sections were refined to align with statistical findings. The statement regarding gender differences was revised to clearly indicate that male patients with diabetes have a higher risk of hospitalization compared to female patients. The interpretation of prothrombin time results was clarified to reflect that no statistically significant difference was found, although a trend toward higher values was observed in diabetic patients. Finally, additional clarifications were added to the discussion to ensure that all findings are appropriately contextualized within the population of hospitalized patients. These revisions address reviewer feedback and enhance the overall precision and readability of the manuscript. See the authors' detailed response to the review by Fajri Marindra Siregar See the authors' detailed response to the review by Ipsa Arora READ REVIEWER RESPONSES Introduction SARS-CoV-2 first appeared in Wuhan, China, on December 31, 2019 and quickly spread throughout the world. As of April 13, 2021, a total of 136,291,755 confirmed cases of COVID-19 infection with 2,941,128 confirmed cases of death have been reported in 223 countries and territories worldwide. 1 In Indonesia, according to the National Development Planning Agency/Bappenas, the first confirmed case of COVID-19 was on March 2, 2020. On April 14, 2021, there were 1,577,526 positive confirmed cases and 42,782 for the number of deaths (2.7% of the national confirmed number). 2 Diabetes mellitus (DM) is an independent prognostic factor for COVID-19 patients. The survival rate of diabetic patients is lower, and the time from the on-set of the infection to death is shorter than that of non-diabetic patients. 3 The mechanism of expression of angiotensin-converting enzyme 2 (ACE2) is increased in lung and other tissues of DM patients. This upregulation is associated with chronic inflammation, activation of endothelial cells and insulin resistance which exacerbates the inflammatory response, in short, the clinical course and prognosis of COVID-19 in DM patients is significantly worse. 4 There is an increase in the number of cases and a greater risk of severe disease with age. 5 The increase in male mortality is related to the regulation of ACE2 and the body's immune system. 6 DM patients are in a prothrombotic state due to hyperglycemia and chronic hyperinsulinism. 7 Studies on COVID-19 associated with diabetes comorbid conditions have been studied by several researchers. However, the results obtained regarding age, gender and prothrombin time showed a lot of variability, so further exploration is needed to determine their association with diabetes on COVID-19. This systematic review and meta-analysis aims to examine the relationship between age, gender and prothrombin time on the hospitalization status of COVID-19 patients with DM as a comorbidity. Methods Data sources and search strategy This research was conducted after obtaining approval from the Health Ethics Commission of Universitas Sumatera Utara (EC No.789/KEP/USU/2021). This study used online literature from PubMed, Science Direct, EBSCO, Cochrane and Google Scholar. The journals used were those which captured the data on COVID-19 patients having comorbid DM, accompanied by data on age, sex and prothrombin time values. The literature search was carried out according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta Analysis). The Checklist used in this meta-analysis was the PRISMA 2009 checklist. This research was conducted in Medan, North Sumatra and was conducted between July–October 2021. Literature search was performed on the databases with the keywords “Age” AND (“Sex” OR “Gender”) AND (“Prothrombine Time” OR “PT”) AND (“COVID -19” OR “SARS CoV-2”) AND (“Diabetes Mellitus” OR “DM”) for articles published from 2019 to 2021. Filters on each database were utilized to aid the literature search: text availability (free full text), article attribute (associated data), article type (clinical trial and randomized control trial), and publication date (five years) for PubMed; years (2019, 2020, 2021), article type (research article, case reports, and data articles), publication title (International Journal of Infectious Diseases, the Lancet Infectious Diseases, the Brazilian Journal of Infectious Diseases), subject areas (medicine and dentistry, immunology and microbiology, nursing and health professions), language (English), and access type (open access and open archive) for Science Direct; date (custom range 2019-2021), topic (infectious diseases, endocrine & metabolic), Cochrane protocols, and Cochrane trials for Cochrane; custom range (January 2019 – December 2021), sort by relevance, and any type for Google Scholar; and full text availability for Ebsco. Inclusion criteria All retrospective studies (cross-sectional, cohort and case-control) that had data on patients’ age, sex or prothrombin time values who had been hospitalized either on the ward or in the ICU were considered eligible for this study. Eligible studies compared data on age in DM and non-DM patients, gender in DM patients and prothrombin time values in DM and non-DM patients. Exclusion criteria All duplications were removed at the initial screening, followed by a second screening in which articles that did not meet the inclusion criteria were removed, such as review articles, systematic reviews, meta-analytical studies, comments, letters, animal studies and studies that were not in Indonesian or English. Journal quality review The quality of the literature used in this study was determined based on criteria of NOS (The Newcastle Ottawa Scale) and for the selection a score of 7–9 (high quality study) was used. Method of collecting data All relevant data was collected using data collection standards that had been set by two reviewers (AFM and MIS). The data taken for the age variable was the Mean and Standard Deviation (SD) of COVID-19 patients with DM and non-DM, the gender variable noted the Odds Ratio (OR) and Standard Error (SE) data from COVID-19 patients with DM, the variables taken for prothrombin time were the median and Interquartile range (IQR) which are converted into the Mean and SD of COVID-19 patients with DM and non-DM. Data was obtained from patients who had COVID-19 confirmed through reverse-transcriptase polymerase chain reaction (RT-PCR). These patients were interviewed regarding congenital diseases and blood tests was used to determine whether they had DM before being admitted to the hospital. Data analysis This study used Review Manager 5.4 software (The Cochrane Collaboration, Oxford, UK) (RevMan, RRID:SCR_003581). 55 Standardized Mean Difference (SMD) and OR were used to analyze the variables in this study. The Confidence Interval (CI) was set at 95%. P value less than 0.05 indicated statistically significant data. Chi Square test was used to assess the heterogeneity of statistical data with the symbol I 2 . If the I 2 test was worth more than 50%, it indicated that there was heterogeneity between studies and the study was conducted using a random effects model. If the I 2 test was less than 50%, it indicated that there was homogeneity between studies, the research was carried out using a fixed effects model. To reduce heterogeneity, studies which method may lead to clinical diversity that conflict with the rest of the studies are excluded. Data input was rechecked by all reviewers to ensure that they are correct. Results Study characteristics In the initial search, we found 8711 articles which can be seen in Figure 1 . The final results after selection got a total of 45 articles that were included in this meta-analysis study. Within these, 31 articles are used for age, 5 articles are used for gender, and 15 articles are used for prothrombin time. The number of studies included in each analysis is listed in Figure 2 . Figure 1. Literature Search. Figure 2. A Venn diagram of the included studies. This meta-analysis study included literature examining two groups, namely COVID-19 patients (controls) and COVID-19 patients with DM. Data from both groups were taken from medical records of patients who were treated either in the ward or in the Intensive Care Unit (ICU). Characteristics of patients based on the study literature are seen in Table 1 . Table 1. Study characteristics. Research by Year Location Number of patients Acharya et al. 16 2020 Korea 324 Alkundi et al. 19 2020 England 232 Ortega et al. 39 2021 Spain 2,069 Alshukry et al. 20 2021 Kuwait 417 Chen (a) et al. 7 2020 Wuhan, China 1,105 Chung et al. 24 2020 South Korea 117 Dennis et al. 25 2021 England 19,256 Pazoki et al. 40 2021 Iran 574 Elemam et al. 8 2021 United Arab Emirates 350 Jing Liang et al. 28 2020 Wuhan, China 211 Kim et al. 29 2020 South Korea 1,082 Koh et al. 30 2021 Singapore 1,042 Chen (c) et al. 23 2020 Wuhan, China 904 Wang et al. 46 2020 Wuhan, China 663 Liu (c) et al. 34 2020 Wuhan, China 192 Chen (b) et al. 22 2020 Hubei, China 208 Shang et al. 44 2021 Wuhan, China 584 Zhang (a) et al. 51 2020 Wuhan, China 258 Zhang et al. 50 2021 Wuhan, China 131 Leon-Abarca et al. 31 2021 Mexico 1,280,806 Dozio et al. 26 2020 Italy 33 Liu (a) et al. 32 2020 Chengdu, China 95 Liu (b) et al. 33 2020 Wuhan, China 268 Liu (d) et al. 35 2020 Wuhan, China 934 Makker et al. 36 2021 France 843 Mansour et al. 37 2020 Iran 353 Orioli et al. 38 2021 Belgium 192 Ozder et al. 13 2020 Turkey 640 Raghavan et al. 41 2021 India 845 Ricchio et al. 42 2021 Italy 61 Seiglie et al. 43 2020 America 450 Soliman et al. 11 2020 Qatar 299 Sticchi et al. 14 2021 Italy 1,656 Wu (a) et al. 47 2020 Wuxi, China 63 Wu (b) et al. 48 2020 Jiangsu, China 2,455 Xu et al. 49 2020 Wuhan, China 61 Zhang (b) et al. 52 2020 Wuhan, China 166 Zheng et al. 53 2021 Wuhan, China 71 Akbariqomi et al. 17 2020 Iran 595 Bhandari et al. 21 2021 Iran 53 Dyusupova et al. 27 2021 Kazakhstan 1,961 Huang et al. 10 2020 Wuhan, China 1,443 Li et al. 12 2020 Wuhan, China 199 Shi et al. 45 2020 Wuhan, China 306 Yan et al. 18 2020 Wuhan, China 193 Based on the entire literature that was included as many as 45 researched in 2020–2021, the most research was carried out in 2021 in as many as 28 studies. The country that researched the most literature in this meta-analysis was China, which was the initial location for the spread of COVID-19 as per as many as 21 literatures. Some studies have a small sample size, but the samples studied are COVID-19 patients who have been hospitalized and have moderate-severe symptoms so that they represent a patient population with a high risk of severity. The relationship between age and diabetes mellitus in COVID-19 patients The literature that was included in the age distribution associated with the prevalence of COVID-19 in DM and non-DM was 31 literatures. Among them were 3 literature cross-sectional research designs, 9 literature cohorts and 19 case-control literatures. Characteristics of age in patients based on the study literature can be seen in Table 2 . Table 2. Age studies in diabetes mellitus (DM) patients with COVID-19 and non-diabetic patients with COVID-19. Journal Research design NOS Score Age in DM (Mean ± SD) Age in non-DM (Mean ± SD) Acharya et al . 16 Cross-sectional 9 69.8 ± 13.5 51.9 ± 21.4 Alkundi et al . 19 Cross-sectional 8 71.4 ± 13.1 69.9 ± 17.1 Ortega et al . 39 Cross-sectional 8 71.7 ± 11.9 66.6 ± 16.3 Alshukry et al. 20 Cohort 9 56.4 ± 11.64 39.5 ± 16.59 Chen (a) et al . 7 Cohort 9 63.4 ± 12.8 55.3 ± 14.5 Chung et al . 24 Cohort 8 66.3 ± 8.9 53.5 ± 17.9 Dennis et al . 25 Cohort 9 67.0 ± 14.1 66.0 ± 17.4 Pazoki et al . 40 Cohort 9 65.0 ± 12.1 53.2 ± 16.7 Elemam et al . 8 Cohort 9 53.73 ± 12.79 44.64 ± 14.38 Jing Liang et al . 28 Cohort 7 62.4 ± 7.7 63.3 ± 8.3 Kim et al . 29 Cohort 9 68.3 ± 11.9 56.5 ± 18.0 Koh et al . 30 Cohort 9 48.0 ± 13.0 36.0 ± 10.0 Leon-Abarca et al . 31 Case-control 7 57.4 ± 13.4 41.8 ± 14.7 Dozio et al . 26 Case-control 8 72.6 ± 15.8 55.6 ± 22.5 Liu (a) et al . 32 Case-control 8 59.36 ± 12.31 58.0 ± 19.24 Liu (b) et al . 33 Case-control 8 65.54 ± 11.28 64.82 ± 10.98 Liu (d) et al . 35 Case-control 8 64.5 ± 10.0 61.6 ± 14.5 Makker et al . 36 Case-control 8 65.36 ± 13.96 58.6 ± 17.53 Mansour et al . 37 Case-control 8 63.66 ± 13.32 60.76 ± 17.56 Orioli et al . 38 Case-control 8 67.0 ± 14.0 67.0 ± 14.0 Ozder et al . 13 Case-control 7 57.0 ± 11.03 58.02 ± 12.16 Raghavan et al . 41 Case-control 8 60.0 ± 13.0 51.0 ± 17.0 Ricchio et al . 42 Case-control 8 81.0 ± 16.0 75.0 ± 15.0 Seiglie et al . 43 Case-control 8 66.7 ± 14.2 61.1 ± 18.8 Soliman et al . 11 Case-control 8 52.1 ± 12.67 36.22 ± 11.43 Sticchi et al . 14 Case-control 8 70.9 ± 11.0 66.3 ± 14.0 Wu (a) et al . 47 Case-control 7 47.98 ± 15.11 51.0 ± 12.6 Wu (b) et al . 48 Case-control 8 52.55 ± 13.7 47.98 ± 15.11 Xu et al . 49 Case-control 8 65.6 ± 11.11 62.96 ± 10.71 Zhang (b) et al . 52 Case-control 7 65.6 ± 11.4 59.4 ± 16.0 Zheng et al . 53 Case-control 8 63.0 ± 10.03 54.31 ± 14.35 Based on Table 2 , the age distribution of the prevalence of COVID-19 with DM compared to non-DM, almost all studies have data on patients with DM having an older age. Forest plot analysis of the relationship between age and the prevalence of COVID with DM and non-DM can be seen in Figure 3 . Figure 3. Forest plot of the relationship of age in diabetes mellitus to COVID-19 and non-diabetes mellitus to COVID-19. The results of the literature analysis in the sub-group of cross-sectional study designs to see the comparison of age in COVID-19 patients with DM and non-DM resulted in I 2 = 87% indicating heterogeneity between studies. Subtotal SMD was 0.42 (95%CI = 0.07–0.78; P = 0.02) which indicates that the result was significant because P < 0.05 and the diamond did not touch the vertical line. The results of the analysis in the cohort study design sub-group to see the comparison of age in COVID-19 patients with DM and non-DM resulted in I 2 = 98% which indicates heterogeneity between studies. Subtotal SMD was 0.63 (95%CI = 0.29–0.98; P = 0.0003) which is that the result was significant, because P < 0.05 and the diamond did not touch the vertical line. The results of the analysis in the case-control study design sub-group to see the comparison of age in COVID-19 patients with DM and non-DM resulted in I 2 = 98% which indicates heterogeneity between studies. Subtotal SMD was 0.37 (95%CI = 0.11–0.63; P = 0.006) which indicates that the result was significant because P < 0.05 and the diamond did not touch the vertical line. The results of the literature analysis to see the comparison of age in COVID-19 patients with DM and non-DM as a whole resulted in a value of I 2 = 99% which indicated heterogeneity between studies, so the random effects model was used. Total SMD 0.45 (95%CI = 0.23–0.68; P < 0.0001) with a population confidence interval of 0.23 to 0.68 (P < 0.0001) indicating there is a significant result because P 0, indicated a difference between the two groups, where individuals in the diabetic group were slightly older than those in the non-diabetic group that might increased the risk more severe illness. The relationship between sex and diabetes mellitus in COVID-19 patients The literature that was included in the sex distribution was associated with the prevalence of COVID-19 in DM as many as 5 literatures. Among them were 2 literature cross-sectional research designs and 3 literature cohorts. Gender characteristics of patients based on the study literature can be seen in Table 3 below. Table 3. Study of gender in diabetes mellitus patients with COVID-19. Journal Research design NOS Score Male vs. Female (OR, 95%CI) Acharya et al . 16 Cross-sectional 9 0.948 (0.13–6.92) Ortega et al . 39 Cross-sectional 8 2.14 (1.014–4.5) Chen (c) et al . 23 Cohort 9 0.36 (0.17– 0.77) Pazoki et al . 40 Cohort 9 1.49 (0.77–2.87) Wang et al. 46 Cohort 9 2.81 (0.90– 9.21) Based on Table 3 , the sex distribution of the prevalence of COVID-19 with DM, overall data on the OR value shows that male patients with diabetes had a higher risk of hospitalization compared to female patients with diabetes. The forest plot analysis of the sex relationship with the prevalence of COVID with DM can be seen in Figure 4 . Figure 4. Forest plot of sex relationship in diabetes mellitus patients with COVID-19. Based on the results of the picture of the size of the square on the forest plot, the research by Ortega et al. (2021) has the largest square proportional to the greater weight value because it has a larger sample than other studies and has more influence on the results of this forest plot. The results of the analysis on the sub-group cross-sectional study design to see the sex comparison in COVID-19 patients with DM resulted in I 2 = 0% which indicated the absence of heterogeneity between studies. Subtotal OR 1.44 (95%CI = 1.07–1.94; P = 0.02) which stated that the results were significant because P < 0.05 and the diamond did not touch the vertical line. The results of the analysis on the cohort study design sub-group to see the sex comparison in COVID-19 patients with DM resulted in I 2 = 0% which indicated no heterogeneity between studies. Subtotal OR 5.71 (95%CI = 2.44–13.36; P < 0.0001) which indicates that the results were significant because P < 0.05 and the diamond did not touch the vertical line. The results of the literature analysis to see the sex comparison between men and women in COVID-19 patients with DM overall yielded a value of I 2 = 59% which indicated heterogeneity between studies, so the random effects model was used. Total OR 3.28 (95% CI = 1.26–8.52; P = 0.01) with a confidence interval for the population between 1.26 to 8.52 (P = 0.01) indicated that the results were significant because P < 0.05 and the diamond did not touch the vertical line. The meta-analysis showed that the chance of developing a more severe illness is three times higher for male than female in diabetic group patients. The Relationship between Prothrombin Time and Diabetes Mellitus in COVID-19 Patients Fifteen literature included the distribution of prothrombin time values associated with the incidence of COVID-19 in DM and non-DM. Among them were 7 literature cohort research designs and 8 case-control literatures. Characteristics of prothrombin time in patients based on the study literature can be seen in Table 4 below. Table 4. Study of prothrombin time (PT) values in diabetes mellitus (DM) patients with COVID-19 and non-diabetic patients with COVID-19 in Mean and Standard Deviation (SD). Journal Research design NOS Score PT value on DM (Mean ± SD) PT value on non-DM (Mean ± SD) Liu (c) et al. 34 Cohort 9 13.675 ± 0.325 13.55 ± 0.2 Elemam et al. 8 Cohort 9 12.45 ± 1.629 12.76 ± 6.622 Chen (a) et al. 7 Cohort 9 11.7 ± 0.333 11.3 ± 0.267 Chen (b) et al. 22 Cohort 9 11.525 ± 0.226 12.25 ± 0.3 Shang et al. 44 Cohort 9 12.73 ± 0.336 12.325 ± 0.283 Zhang (b) et al. 51 Cohort 9 12.73 ± 0.3 13.075 ± 0.25 Zhang et al. 50 Cohort 9 14.81 ± 0.707 13.686 ± 0.377 Akbariqomi et al. 17 Case-control 8 12.57 ± 0.183 12.475 ± 0.183 Bhandari et al. 21 Case-control 7 12.97 ± 0.662 12.63 ± 0.375 Dyusupova et al. 27 Case-control 8 13.71 ± 1.575 12.375 ± 0.416 Huang et al. 10 Case-control 8 11.65 ± 0.233 11.5 ± 1.667 Li et al. 12 Case-control 8 12.425 ± 0.283 12.225 ± 0.283 Liu (d) et al. 35 Case-control 8 11.425 ± 0.183 11.425 ± 0.15 Shi et al. 45 Case-control 8 12.15 ± 0.266 12.025 ± 0.216 Yan et al. 18 Case-control 8 14.86 ± 0.85 14.325 ± 0.383 Based on Table 4 , the distribution of prothrombin time values in the incidence of COVID-19 with DM is compared with non-DM in the form of Median and IQR converted into the Mean and SD which has been converted in Table 4 . Overall, it shows that the prothrombin time value in patients with DM has a slightly higher value compared to non-DM and as many as 3 studies have the opposite data. Forest plot analysis of the relationship between prothrombin time and the incidence of COVID with DM and non-DM can be seen in Figure 5 . Figure 5. Forest plot of the relationship between prothrombin time values in diabetes mellitus patients with COVID-19 and non-diabetes mellitus with COVID-19. The results of the literature analysis in the cohort study design subgroup to compare the prothrombin time values in COVID-19 patients with DM and non-DM resulted in I 2 = 99% which indicated heterogeneity between studies. Subtotal Standardized Mean Difference (SMD) 0.15 (95%CI = -0.88–1.18; P = 0.78) which means no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes. Results of literature analysis in the case-control study design sub-group to compare the prothrombin time values in COVID-19 patients with DM and non-DM produced I 2 = 92% which indicated heterogeneity between studies. Subtotal Standardized Mean Difference (SMD) 0.61 (95%CI = 0.31–0.91; P < 0.0001) which means that the result is significant because P < 0.05 and the diamond did not touch the vertical line. The results of the literature analysis to see the comparison of the prothrombin time value in COVID-19 patients with DM and COVID-19 patients without a history of DM overall yielded a value of I 2 = 98% which indicated heterogeneity between studies, so the random effects model was used. Total Standardized Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05 and the diamond touched the vertical line. The SMD > 0, indicated the difference in prothrombin time was not statistically significant, diabetic patients tended to have higher values than non-diabetic patients. Discussion This systematic review and meta-analysis included 45 articles with a total number of 1,325,334 patients who were positive for COVID-19 and divided into diabetic and non-diabetic groups which were analyzed for age, sex and prothrombin time values. Diabetes is reported to be one of the comorbidities that increases the progression and mortality of COVID-19. Diabetes can be a risk factor because of the increase in serum ACE2 in diabetic patients. In addition, patients taking inhibitors of angiotensin-converting enzyme (ACEIs) and angiotensin II receptor blockers (ARBs) showed overexpression of ACE2, the COVID-19 entry receptor. 8 The results of a systematic study and meta-analysis on the age variable, showed that patients with COVID-19 with DM were significantly older than non-diabetic patients. There is a correlation between age and the innate immune system as has been reviewed elsewhere and concluded that the elderly are particularly susceptible to developing more infections because the innate immune system declines gradually with older age. These findings apply only to hospitalized COVID-19 patients. 9 The relationship between age and the prevalence of COVID-19 in the DM group compared to non-DM is in line with several research results which state that patients infected with COVID-19 with comorbid diabetes are older than non-diabetics. In both patients with or without diabetes the severity of the disease increases with age. 10 Another study also found that diabetic patients were significantly older and had more severe symptoms than non-diabetic patients, 11 the COVID-19 patients with diabetes had a higher age than non-diabetics, 12 COVID-19 patients with pre-existing diabetes were older than those without. 7 Another study stated that diabetic and non-diabetic population significantly different in age but a slightly older non-diabetic population. 13 The results of the study among hospitalized patients on the gender variable, showed that men were more at risk of exposure to the disease and had more severe symptoms than women. Gender differences affect clinical outcome and prognosis, with males at higher risk than females. Male patients may express higher ACE2 which is regulated by male sex hormones. 9 The relationship between sex and the prevalence of COVID-19 in the DM group is in line with several research results, such as having a much larger male population than female, 14 twice as many male patient subjects as confirmed positive for COVID-19, the presentation of diabetic men at high risk of mortality and the number of hospitalizations is higher in diabetic men than women and in other comorbid diseases. 15 In contrast to a study, in the data there were more female patients than men, although there were more men in the diabetes group than non-diabetics but in both groups had more female patients. 16 The prothrombin time variable showed the same prothrombin time value in both diabetic and non-diabetic patients. Theoretically, COVID-19 patients with DM have a prolonged prothrombin time value, as well as the results in the case-control study design sub-group as seen in Figure 3 which shows a difference, namely a prolonged prothrombin time value in the DM group. Diabetic patients in a prothrombotic state due to hyperglycemia and chronic hyperinsulinism make all phases of coagulation abnormal. 7 Non-survivors have a prolonged prothrombin time compared to survivors. The timing of increases in D-dimer, prothrombin time, and activated partial thromboplastin time, with decreased fibrinogen and platelet counts, also coincided with the duration of hospitalization, ranging from 7 to 10 days after admission. Patients who are still hospitalized or have good prognostic factors are likely to have non-prolonging prothrombin time. 54 The relationship between prothrombin time and the incidence of COVID-19 in the DM and non-DM groups is in line with several studies. 17 The prothrombin time values in both groups were relatively the same and did not prolong. 12 The prothrombin time values were almost the same in both groups and within the normal range. 10 In contrast to a study that showed a slight difference in the prothrombin time value in the diabetic group, which was prolonged compared to the non-diabetic group, which was still within normal limits. 18 This study has research limitations, there are only a few studies on COVID-19 with DM as the outbreak only occurred at the end of 2019. Research on COVID-19 with DM is relatively new, and it needs to be studied further. This meta-analysis also does not study the relationship between the onset and severity of COVID-19 with diabetes. Conclusion The results of our study indicate that patients with COVID-19 who have DM have a higher risk compared to those without DM. Among COVID-19 patients with DM admitted to hospitals, they were older compared to those without DM and prothrombin time values similar but slightly higher in COVID-19 patients with DM. Within COVID-19 patients with DM, there were more male patients compared to females. Suggestion Researchers are expected to conduct further studies on the relationship between age and gender in COVID-19 patients with DM, so that the data obtained from the results of this meta-analysis are more relevant when applied in Indonesia. Clinicians are expected to provide health care, especially for patients with DM who are old and male in the era of the COVID-19 pandemic to reduce the risk factors for severity of diabetic patients being infected with COVID-19. Researchers are expected to conduct further studies on prothrombin time in COVID-19 patients with DM for a more detailed understanding. Data availability Underlying data All data underlying the results are available as part of the article and no additional source data are required. Reporting guidelines Figshare: PRISMA checklist for ‘The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis’. https://doi.org/10.6084/m9.figshare.18865103 . 56 Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Author contributions Audrey Fabianisa Mirza: Conceptualization, formal analysis, methodology, investigation, visualization, writing – original draft preparation, writing – review & editing. Ceria Halim: Formal analysis, writing – original draft preparation, writing – review & editing. Mutiara Indah Sari: Conceptualization, formal analysis, methodology, project administration, supervision, funding acquisition. Acknowledgements I would like to thank and appreciate the researchers whose research contributed greatly to this meta-analysis. References 1. World Health Organization: WHO Coronavirus (COVID-19) Dashboard.2021. accessed April 14 th 2021 . Reference Source 2. Satuan Tugas Penanganan COVID-19: Peta Sebaran COVID-19.2021. accessed April 14 th 2021. Reference Source 3. Hui Y, Li Y, Tong X, et al. : The risk factors for mortality of diabetic patients with severe COVID-19: A retrospective study of 167 severe COVID-19 cases in Wuhan. PLoS One. 2020; 15 (12): e0243602. PubMed Abstract | Publisher Full Text 4. Gao YD, Ding M, Dong X, et al. : Risk factors for severe and critically ill COVID-19 patients: A review. Allergy. 2021; 76 (2): 428–455. Publisher Full Text 5. Davies NG, Klepac P, Liu Y, et al. : Age-dependent effects in the transmission and control of COVID-19 epidemics. Nat. Med. 2020; 26 (8): 1205–1211. PubMed Abstract | Publisher Full Text 6. Gebhard C, Regitz-Zagrosek V, Neuhauser HK, et al. : Impact of sex and gender on COVID-19 outcomes in Europe. Biol. Sex Differ. 2020; 11 : 1–13. Publisher Full Text 7. Chen X, Chen Y, Wu C, et al. : Coagulopathy is a major extrapulmonary risk factor for mortality in hospitalized patients with COVID-19 with type 2 diabetes. BMJ Open Diabetes Res. Care. 8 (2): e001851. PubMed Abstract | Publisher Full Text Elemam NM, Hannawi H, Salmi IA, et al. : 2021, ‘Diabetes mellitus as a comorbidity in COVID-19 infection in the United Arab Emirates.’, Saudi Med. J. 2020; 42 (2): 170–180. PubMed Abstract | Publisher Full Text 8. Elemam NM, Hannawi H, Salmi IA, et al. : Diabetes mellitus as a comorbidity in COVID-19 infection in the United Arab Emirates. Saudi Med. J. 2021; 42 (2): 170–180. PubMed Abstract | Publisher Full Text 9. Biswas M, Rahaman S, Biswas TK, et al. : Association of sex, age, and comorbidities with mortality in COVID-19 patients: a systematic review and meta-analysis. Intervirology. 2021; 64 (1): 36–47. PubMed Abstract | Publisher Full Text 10. Huang J, Zhu L, Bai X, et al. : Multidimensional Analysis of Risk Factors for the Severity and Mortality of Patients with COVID-19 and Diabetes. Infect. Dis. Ther. 2020; 9 (4): 981–1002. PubMed Abstract | Publisher Full Text 11. Soliman AT, Prabhakaran Nair A, Al Masalamani MS, et al. : Prevalence, clinical manifestations, and biochemical data of type 2 diabetes mellitus versus nondiabetic symptomatic patients with COVID-19: A comparative study. Acta Bio-medica: Atenei Parmensis. 2020; 91 (3): e2020010. PubMed Abstract | Publisher Full Text 12. Li G, Deng Q, Feng J, et al. : Clinical Characteristics of Diabetic Patients with COVID-19’. J. Diabetes Res. 2020; 2020 : 1–1652403, 5. Publisher Full Text 13. Ozder A: A novel indicator predicts 2019 novel coronavirus infection in subjects with diabetes. Diabetes Res. Clin. Pract. 2020; 166 : 108294. PubMed Abstract | Publisher Full Text 14. Sticchi A, Cereda A, Toselli M, et al. : Diabetes and mortality in patients with COVID-19: Are we missing the link?. Anatol. J. Cardiol. 2021; 25 (6): 376–379. PubMed Abstract | Publisher Full Text 15. Belice T, Demir I: The gender differences as a risk factor in diabetic patients with COVID-19. Iranian journal of microbiology. 2020; 12 (6): 625–628. PubMed Abstract | Publisher Full Text 16. Acharya D, Lee K, Lee DS, et al. : Mortality Rate and Predictors of Mortality in Hospitalized COVID-19 Patients with Diabetes. Healthcare (Basel, Switzerland). 2020; 8 (3): 338. Publisher Full Text 17. Akbariqomi M, Hosseini MS, Rashidiani J, et al. : Clinical characteristics and outcome of hospitalized COVID-19 patients with diabetes: A single-center, retrospective study in Iran. Diabetes Res. Clin. Pract. 2020; 169 : 108467. PubMed Abstract | Publisher Full Text 18. Yan Y, Yang Y, Wang F, et al. : Clinical characteristics and outcomes of patients with severe covid-19 with diabetes. BMJ Open Diabetes Res. Care. 2020; 8 (1): e001343. PubMed Abstract | Publisher Full Text 19. Alkundi A, Mahmoud I, Musa A, et al. : Clinical characteristics and outcomes of COVID-19 hospitalized patients with diabetes in the United Kingdom: A retrospective single centre study. Diabetes Res. Clin. Pract. 2020; 165 : 108263. PubMed Abstract | Publisher Full Text 20. Alshukry A, Bu Abbas M, Ali Y, et al. : Clinical characteristics and outcomes of COVID-19 patients with diabetes mellitus in Kuwait. Heliyon. 2021; 7 (4): e06706. PubMed Abstract | Publisher Full Text 21. Bhandari S, Shaktawat AS, Tak A, et al. : Evaluating interactions between hyperglycemia and clotting factors in patients suffering with SARS-CoV-2 infection. Clinical Diabetology. 2021; 10 (1): 114–122. Publisher Full Text 22. Chen Y, Chen J, Gong X, et al. : Clinical Characteristics and Outcomes of Type 2 Diabetes Patients Infected with COVID-19: A Retrospective Study. Engineering (Beijing, China). 2020; 6 (10): 1170–1177. Publisher Full Text 23. Chen Y, Yang D, Cheng B, et al. : Clinical Characteristics and Outcomes of Patients With Diabetes and COVID-19 in Association With Glucose-Lowering Medication. Diabetes Care. 2020; 43 (7): 1399–1407. PubMed Abstract | Publisher Full Text 24. Chung SM, Lee YY, Ha E, et al. : The Risk of Diabetes on Clinical Outcomes in Patients with Coronavirus Disease 2019: A Retrospective Cohort Study. Diabetes Metab. J. 2020; 44 (3): 405–413. PubMed Abstract | Publisher Full Text 25. Dennis JM, Mateen BA, Sonabend R, et al. : Type 2 Diabetes and COVID-19-Related Mortality in the Critical Care Setting: A National Cohort Study in England, March-July 2020. Diabetes Care. 2021; 44 (1): 50–57. PubMed Abstract | Publisher Full Text 26. Dozio E, Sitzia C, Pistelli L, et al. : Soluble Receptor for Advanced Glycation End Products and Its Forms in COVID-19 Patients with and without Diabetes Mellitus: A Pilot Study on Their Role as Disease Biomarkers. J. Clin. Med. 2020; 9 (11): 3785. PubMed Abstract | Publisher Full Text 27. Dyusupova A, Faizova R, Yurkovskaya O, et al. : Clinical characteristics and risk factors for disease severity and mortality of COVID-19 patients with diabetes mellitus in Kazakhstan: A nationwide study. Heliyon. 2021; 7 (3): e06561. PubMed Abstract | Publisher Full Text 28. Jing Liang J, Liu J, Chen Y, et al. : Characteristics of laboratory findings of COVID-19 patients with comorbid diabetes mellitus. Diabetes Res. Clin. Pract. 2020; 167 : 108351. PubMed Abstract | Publisher Full Text 29. Kim MK, Jeon JH, Kim SW, et al. : The Clinical Characteristics and Outcomes of Patients with Moderate-to-Severe Coronavirus Disease 2019 Infection and Diabetes in Daegu, South Korea. Diabetes Metab. J. 2020; 44 (4): 602–613. PubMed Abstract | Publisher Full Text 30. Koh H, Moh A, Yeoh E, et al. : Diabetes predicts severity of COVID-19 infection in a retrospective cohort: A mediatory role of the inflammatory biomarker C-reactive protein. J. Med. Virol. 2021; 93 (5): 3023–3032. PubMed Abstract | Publisher Full Text 31. Leon-Abarca JA, Portmann-Baracco A, Bryce-Alberti M, et al. : Diabetes increases the risk of COVID-19 in an altitude dependent manner: An analysis of 1,280,806 Mexican patients. PLoS One. 2021; 16 (8): e0255144. PubMed Abstract | Publisher Full Text 32. Liu D, Lan L, Luo D, et al. : Lymphocyte subsets with the lowest decline at baseline and the slow lowest rise during recovery in COVID-19 critical illness patients with diabetes mellitus. Diabetes Res. Clin. Pract. 2020; 167 : 108341. PubMed Abstract | Publisher Full Text 33. Liu G, Zhang S, Hu H, et al. : The role of neutrophil-lymphocyte ratio and lymphocyte-monocyte ratio in the prognosis of type 2 diabetics with COVID-19. Scott. Med. J. 2020; 65 (4): 154–160. PubMed Abstract | Publisher Full Text 34. Liu Z, Bai X, Han X, et al. : The association of diabetes and the prognosis of COVID-19 patients: A retrospective study. Diabetes Res. Clin. Pract. 2020; 169 : 108386. PubMed Abstract | Publisher Full Text 35. Liu Z, Li J, Huang J, et al. : Association Between Diabetes and COVID-19: A Retrospective Observational Study With a Large Sample of 1,880 Cases in Leishenshan Hospital, Wuhan. Front. Endocrinol. 2020; 11 : 478. PubMed Abstract | Publisher Full Text 36. Makker J, Sun H, Patel H, et al. : Impact of Prediabetes and Type-2 Diabetes on Outcomes in Patients with COVID-19. Int. J. Endocrinol. 2021; 2021 : 1–9. Publisher Full Text 37. Mansour A, Sajjadi-Jazi SM, Kasaeian A, et al. : Clinical characteristics and outcomes of diabetics hospitalized for COVID-19 infection: a single-centered, retrospective, observational study. EXCLI J. 2020; 19 : 1533–1543. 38. Orioli L, Servais T, Belkhir L, et al. : Clinical characteristics and short-term prognosis of in-patients with diabetes and COVID-19: A retrospective study from an academic center in Belgium. Diabetes Metab. Syndr. 2021; 15 (1): 149–157. PubMed Abstract | Publisher Full Text 39. Ortega E, Corcoy R, Gratacòs M, et al. : Risk factors for severe outcomes in people with diabetes hospitalised for COVID-19: a cross-sectional database study. BMJ Open. 2021; 11 (7): e051237. PubMed Abstract | Publisher Full Text 40. Pazoki M, Keykhaei M, Kafan S, et al. : Risk indicators associated with in-hospital mortality and severity in patients with diabetes mellitus and confirmed or clinically suspected COVID-19. J. Diabetes Metab. Disord. 2021; 20 (1): 59–69. Publisher Full Text 41. Raghavan A, Nanditha A, Satheesh K, et al. : Profile and prognosis of patients hospitalized for COVID-19 virus infection with and without diabetes - An observational study from South India. Diabetes Metab. Syndr. 2021; 15 (4): 102143. Publisher Full Text 42. Ricchio M, Tassone B, Pelle MC, et al. : Characteristics, Management, and Outcomes of Elderly Patients with Diabetes in a Covid-19 Unit: Lessons Learned from a Pilot Study. Medicina (Kaunas). 2021; 57 (4): 341. PubMed Abstract | Publisher Full Text 43. Seiglie J, Platt J, Cromer SJ, et al. : Diabetes as a Risk Factor for Poor Early Outcomes in Patients Hospitalized With COVID-19. Diabetes Care. 2020; 43 (12): 2938–2944. PubMed Abstract | Publisher Full Text 44. Shang J, Wang Q, Zhang H, et al. : The Relationship Between Diabetes Mellitus and COVID-19 Prognosis: A Retrospective Cohort Study in Wuhan, China. Am. J. Med. 2021; 134 (1): e6–e14. PubMed Abstract | Publisher Full Text 45. Shi Q, Zhang X, Jiang F, et al. : Clinical Characteristics and Risk Factors for Mortality of COVID-19 Patients With Diabetes in Wuhan, China: A Two-Center, Retrospective Study. Diabetes Care. 2020; 43 (7): 1382–1391. PubMed Abstract | Publisher Full Text 46. Wang X, Liu Z, Li J, et al. : Impacts of Type 2 Diabetes on Disease Severity, Therapeutic Effect, and Mortality of Patients With COVID-19. J. Clin. Endocrinol. Metab. 2020; 105 (12): dgaa535. PubMed Abstract | Publisher Full Text 47. Wu D, Gao S: Analysis of the lymphocyte count in type 2 diabetic patients with coronavirus disease (COVID-19): A retrospective study in a centralized treatment center. Diabetes Res. Clin. Pract. 2020; 166 : 108340. PubMed Abstract | Publisher Full Text 48. Wu J, Zhang J, Sun X, et al. : Influence of diabetes mellitus on the severity and fatality of SARS-CoV-2 (COVID-19) infection. Diabetes Obes. Metab. 2020; 22 (10): 1907–1914. PubMed Abstract | Publisher Full Text 49. Xu M, Yang W, Huang T, et al. : Diabetic patients with COVID-19 need more attention and better glycemic control. World J. Diabetes. 2020; 11 (12): 644–653. PubMed Abstract | Publisher Full Text 50. Zhang P, Wang M, Wang Y, et al. : Risk factors associated with the progression of COVID-19 in elderly diabetes patients. Diabetes Res. Clin. Pract. 2021; 171 : 108550. PubMed Abstract | Publisher Full Text 51. Zhang Y, Cui Y, Shen M, et al. : Comorbid diabetes mellitus was associated with poorer prognosis in patients with COVID-19: a retrospective cohort study. MedRxiv 2020. 52. Zhang Y, Li H, Zhang J, et al. : The clinical characteristics and outcomes of patients with diabetes and secondary hyperglycaemia with coronavirus disease 2019: A single-centre, retrospective, observational study in Wuhan. Diabetes Obes. Metab. 2020; 22 (8): 1443–1454. PubMed Abstract | Publisher Full Text 53. Zheng M, Wang X, Guo H, et al. : The Cytokine Profiles and Immune Response Are Increased in COVID-19 Patients with Type 2 Diabetes Mellitus. J. Diabetes Res. 2021; 2021 : 1–8. Publisher Full Text 54. Connors JM, Levy JH: COVID-19 and its implications for thrombosis and anticoagulation. Blood. 2020; 135 (23): 2033–2040. PubMed Abstract | Publisher Full Text 55. Review Manager (RevMan) [Computer program]. Version 5.4. The Cochrane Collaboration. 2020. 56. Mirza AF, Halim C, Sari MI: ‘The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis’, figshare. Dataset. 2022. Publisher Full Text Comments on this article Comments (0) Version 7 VERSION 7 PUBLISHED 01 Jul 2022 ADD YOUR COMMENT Comment Author details Author details 1 Faculty of Medicine, Universitas Sumatera Utara, Medan, Sumatera Utara, 20155, Indonesia 2 Department of Biochemistry, Universitas Sumatera Utara, Medan, Sumatera Utara, 20155, Indonesia Audrey Fabianisa Mirza Roles: Conceptualization, Formal Analysis, Investigation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Ceria Halim Roles: Formal Analysis, Writing – Original Draft Preparation, Writing – Review & Editing Mutiara Indah Sari Roles: Conceptualization, Formal Analysis, Funding Acquisition, Methodology, Project Administration, Supervision Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (7) version 7 Revised Published: 14 Oct 2025, 11:729 https://doi.org/10.12688/f1000research.107398.7 version 6 Revised Published: 08 Aug 2024, 11:729 https://doi.org/10.12688/f1000research.107398.6 version 5 Revised Published: 25 Jul 2024, 11:729 https://doi.org/10.12688/f1000research.107398.5 version 4 Revised Published: 11 Jul 2024, 11:729 https://doi.org/10.12688/f1000research.107398.4 version 3 Revised Published: 21 Jun 2024, 11:729 https://doi.org/10.12688/f1000research.107398.3 version 2 Revised Published: 05 Jun 2024, 11:729 https://doi.org/10.12688/f1000research.107398.2 version 1 Published: 01 Jul 2022, 11:729 https://doi.org/10.12688/f1000research.107398.1 Copyright © 2025 Mirza AF et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Mirza AF, Halim C and Sari MI. The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.12688/f1000research.107398.7 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 6 VERSION 6 PUBLISHED 08 Aug 2024 Revised Views 0 Cite How to cite this report: Wang C. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r368187 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-368187 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 07 Mar 2025 Chenxiao Wang , Tulane University, New Orleans, USA Approved VIEWS 0 https://doi.org/10.5256/f1000research.169997.r368187 The manuscript systematically reviews and conducts a meta-analysis to investigate how age, sex, and prothrombin time (PT) values relate to COVID-19 severity among patients with diabetes mellitus (DM). The authors analyzed data from 45 studies sourced from prominent databases, applying ... Continue reading READ ALL The manuscript systematically reviews and conducts a meta-analysis to investigate how age, sex, and prothrombin time (PT) values relate to COVID-19 severity among patients with diabetes mellitus (DM). The authors analyzed data from 45 studies sourced from prominent databases, applying robust inclusion and exclusion criteria. Overall, the study concludes that older age and male gender significantly increase COVID-19 severity risk among patients with DM, whereas prothrombin time values were slightly prolonged in DM patients compared to non-DM patients, though not significantly so overall. The manuscript addresses a clinical issue, and the authors addressed all the questions reviewers raised. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Yes Are the conclusions drawn adequately supported by the results presented in the review? Yes If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests: No competing interests were disclosed. Reviewer Expertise: COVID-19 I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Wang C. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r368187 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-368187 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Arora I. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r313402 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-313402 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 27 Aug 2024 Ipsa Arora , Endocrinology, Central Maine Medical Center, Lewiston, Maine, USA Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.169997.r313402 Mirza et al. conducted a systematic review and meta-analysis to examine the relationship between age, gender, and prothrombin time in COVID-19 patients requiring hospitalization, with or without diabetes as a comorbidity. They found that hospitalized COVID-19 patients with diabetes were ... Continue reading READ ALL Mirza et al. conducted a systematic review and meta-analysis to examine the relationship between age, gender, and prothrombin time in COVID-19 patients requiring hospitalization, with or without diabetes as a comorbidity. They found that hospitalized COVID-19 patients with diabetes were generally older and predominantly male. Although a statistically significant association with prothrombin time was not identified, hospitalized patients with both COVID-19 and diabetes tended to have higher prothrombin time values. I recommend the following clarifications to enhance the clarity and usefulness of this publication for the readers of this journal. Abstract : The study's aim is not clearly articulated in the abstract. Conclusion : The statement "patients with COVID-19 who have diabetes have a higher risk as compared to those without diabetes" is vague. Please specify the higher risk of what—e.g., higher risk of hospitalization, severe outcomes, or mortality. Introduction : In the last sentence where the study's aim is mentioned, there seems to be a discrepancy. The study does not investigate the relationship between age, gender, and prothrombin time with the "severity of COVID-19." Instead, it examines these parameters in relation to COVID-19 cases requiring hospitalization. This should be clarified, especially since the limitations (under discussion) indicate that the meta-analysis does not explore the relationship with COVID-19 severity. Methods : In the literature search section (2019-2021), it is recommended to specify the exact months for each year. Inclusion Criteria : The first line states, "all retrospective studies... had data on patients' age, sex, and prothrombin time." It may be more accurate to say "age, sex, or prothrombin time," as not all 45 studies included data on all three variables. Page 7/25 : In the section discussing the relationship between age and diabetes in COVID-19 patients, "incidence" might not be the most appropriate term; "prevalence" could be more accurate. The same applies to page 9/25 regarding the relationship between sex and diabetes in COVID-19 patients. Page 10/25 : The phrase "Based on Table 3..." does not appropriately represent the study’s findings. It should be revised to indicate that "male patients with diabetes have a higher risk of hospitalization compared to female patients with diabetes." Page 10/25 : In the section discussing the relationship between prothrombin time and diabetes in COVID-19 patients, consider revising the conclusion to state that "no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes." Page 12/25 : The last line of the results section ("The SMD >0... more severe illness") is unclear and may need to be rewritten, taking into account the points raised in comment 8. Discussion, Paragraph 3 : Please specify that the results discussed are applicable only to hospitalized patients. Discussion, Paragraph 4 : The term "incidence" is used incorrectly; please refer to comment 6 for guidance. Discussion, Paragraph 5 : The first statement may be inaccurate and should be revised based on the information discussed in comment 7. Discussion, Paragraph 7 : The conclusion should specify that it pertains to patients with COVID-19 requiring hospitalization. Discussion, Paragraph 8 : The mention of "incidence" should be corrected as indicated in comment 6. Are the rationale for, and objectives of, the Systematic Review clearly stated? Partly Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests: No competing interests were disclosed. Reviewer Expertise: Endocrinology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Arora I. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r313402 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-313402 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 15 Oct 2025 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 15 Oct 2025 Author Response We would like to express our sincere gratitude to the reviewer for their constructive and insightful comments, which have significantly improved the clarity and precision of our manuscript. Below are ... Continue reading We would like to express our sincere gratitude to the reviewer for their constructive and insightful comments, which have significantly improved the clarity and precision of our manuscript. Below are our point-by-point responses and the corresponding revisions made in the manuscript (marked in the revised version). 1. Abstract – Aim not clearly articulated Comment: The study’s aim is not clearly stated in the abstract. Response: We agree. The aim has been revised to explicitly state the objective of the study. Revised text: “This study aimed to evaluate the association between age, sex, and prothrombin time and the likelihood of hospitalization among COVID-19 patients with diabetes mellitus.” 2. Abstract – Vague statement on “higher risk” Comment: Please specify the type of risk. Response: We agree. The phrase has been clarified to indicate the type of risk observed. Revised text: “…have a higher risk of hospitalization compared to those without diabetes mellitus.” 3. Introduction – Discrepancy in study aim Comment: The aim mentions “severity,” but the study focuses on hospitalized patients. Response: Thank you for pointing this out. The wording has been revised to accurately reflect the study’s scope. Revised text: “...to examine the relationship between age, sex, and prothrombin time in hospitalized COVID-19 patients with diabetes mellitus.” 4. Methods – Literature search period Comment: Please specify the exact months for the literature search period. Response: We agree. The time frame has been clarified. Revised text: “The literature search was conducted for studies published between January 2019 and December 2021.” 5. Inclusion Criteria – Use of “and” vs “or” Comment: Not all studies included all three variables. Response: Correct. The text has been revised accordingly. Revised text: “…had data on patients’ age, sex, or prothrombin time.” 6. Use of “incidence” vs “prevalence” Comment: “Incidence” is not the correct term in this context. Response: We agree and have replaced “incidence” with “prevalence” throughout the manuscript in the relevant sections (pages 7, 9, and Discussion paragraphs 4 and 8). 7. Page 10 – Misrepresentation of gender findings Comment: “Based on Table 3” does not accurately reflect the results. Response: We have revised this statement to reflect the actual finding. Revised text: “Male patients with diabetes had a higher risk of hospitalization compared to female patients with diabetes.” 8. Page 10 – Prothrombin time conclusion Comment: The conclusion should be revised to reflect non-significance. Response: We agree. The statement has been modified. Revised text: “no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes.” 9. Page 12 – “SMD > 0” unclear Comment: The statement should be clarified. Response: We have revised this to provide a clear interpretation of the result. Revised text: “….the difference in prothrombin time was not statistically significant, diabetic patients tended to have higher values than non-diabetic patients.” 10. Discussion Paragraph 3 – Context limitation Comment: The results apply only to hospitalized patients. Response: We agree. A clarifying statement has been added. Revised text: “These findings apply only to hospitalized COVID-19 patients.” 11. Discussion Paragraph 4 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: Corrected as suggested. 12. Discussion Paragraph 5 – Inaccurate statement Comment: The first statement should be aligned with the actual findings. Response: We have revised the text to reflect the higher risk of hospitalization among male patients with diabetes. 13. Discussion Paragraph 7 – Overgeneralization Comment: The conclusion should specify the study population. Response: We have added clarification indicating that the conclusions pertain to hospitalized patients. 14. Discussion Paragraph 8 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: The term has been corrected accordingly. We thank the reviewer once again for their valuable feedback. All suggested revisions have been addressed carefully, and we believe these changes have strengthened the clarity, accuracy, and overall quality of the manuscript. We would like to express our sincere gratitude to the reviewer for their constructive and insightful comments, which have significantly improved the clarity and precision of our manuscript. Below are our point-by-point responses and the corresponding revisions made in the manuscript (marked in the revised version). 1. Abstract – Aim not clearly articulated Comment: The study’s aim is not clearly stated in the abstract. Response: We agree. The aim has been revised to explicitly state the objective of the study. Revised text: “This study aimed to evaluate the association between age, sex, and prothrombin time and the likelihood of hospitalization among COVID-19 patients with diabetes mellitus.” 2. Abstract – Vague statement on “higher risk” Comment: Please specify the type of risk. Response: We agree. The phrase has been clarified to indicate the type of risk observed. Revised text: “…have a higher risk of hospitalization compared to those without diabetes mellitus.” 3. Introduction – Discrepancy in study aim Comment: The aim mentions “severity,” but the study focuses on hospitalized patients. Response: Thank you for pointing this out. The wording has been revised to accurately reflect the study’s scope. Revised text: “...to examine the relationship between age, sex, and prothrombin time in hospitalized COVID-19 patients with diabetes mellitus.” 4. Methods – Literature search period Comment: Please specify the exact months for the literature search period. Response: We agree. The time frame has been clarified. Revised text: “The literature search was conducted for studies published between January 2019 and December 2021.” 5. Inclusion Criteria – Use of “and” vs “or” Comment: Not all studies included all three variables. Response: Correct. The text has been revised accordingly. Revised text: “…had data on patients’ age, sex, or prothrombin time.” 6. Use of “incidence” vs “prevalence” Comment: “Incidence” is not the correct term in this context. Response: We agree and have replaced “incidence” with “prevalence” throughout the manuscript in the relevant sections (pages 7, 9, and Discussion paragraphs 4 and 8). 7. Page 10 – Misrepresentation of gender findings Comment: “Based on Table 3” does not accurately reflect the results. Response: We have revised this statement to reflect the actual finding. Revised text: “Male patients with diabetes had a higher risk of hospitalization compared to female patients with diabetes.” 8. Page 10 – Prothrombin time conclusion Comment: The conclusion should be revised to reflect non-significance. Response: We agree. The statement has been modified. Revised text: “no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes.” 9. Page 12 – “SMD > 0” unclear Comment: The statement should be clarified. Response: We have revised this to provide a clear interpretation of the result. Revised text: “….the difference in prothrombin time was not statistically significant, diabetic patients tended to have higher values than non-diabetic patients.” 10. Discussion Paragraph 3 – Context limitation Comment: The results apply only to hospitalized patients. Response: We agree. A clarifying statement has been added. Revised text: “These findings apply only to hospitalized COVID-19 patients.” 11. Discussion Paragraph 4 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: Corrected as suggested. 12. Discussion Paragraph 5 – Inaccurate statement Comment: The first statement should be aligned with the actual findings. Response: We have revised the text to reflect the higher risk of hospitalization among male patients with diabetes. 13. Discussion Paragraph 7 – Overgeneralization Comment: The conclusion should specify the study population. Response: We have added clarification indicating that the conclusions pertain to hospitalized patients. 14. Discussion Paragraph 8 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: The term has been corrected accordingly. We thank the reviewer once again for their valuable feedback. All suggested revisions have been addressed carefully, and we believe these changes have strengthened the clarity, accuracy, and overall quality of the manuscript. Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 15 Oct 2025 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 15 Oct 2025 Author Response We would like to express our sincere gratitude to the reviewer for their constructive and insightful comments, which have significantly improved the clarity and precision of our manuscript. Below are ... Continue reading We would like to express our sincere gratitude to the reviewer for their constructive and insightful comments, which have significantly improved the clarity and precision of our manuscript. Below are our point-by-point responses and the corresponding revisions made in the manuscript (marked in the revised version). 1. Abstract – Aim not clearly articulated Comment: The study’s aim is not clearly stated in the abstract. Response: We agree. The aim has been revised to explicitly state the objective of the study. Revised text: “This study aimed to evaluate the association between age, sex, and prothrombin time and the likelihood of hospitalization among COVID-19 patients with diabetes mellitus.” 2. Abstract – Vague statement on “higher risk” Comment: Please specify the type of risk. Response: We agree. The phrase has been clarified to indicate the type of risk observed. Revised text: “…have a higher risk of hospitalization compared to those without diabetes mellitus.” 3. Introduction – Discrepancy in study aim Comment: The aim mentions “severity,” but the study focuses on hospitalized patients. Response: Thank you for pointing this out. The wording has been revised to accurately reflect the study’s scope. Revised text: “...to examine the relationship between age, sex, and prothrombin time in hospitalized COVID-19 patients with diabetes mellitus.” 4. Methods – Literature search period Comment: Please specify the exact months for the literature search period. Response: We agree. The time frame has been clarified. Revised text: “The literature search was conducted for studies published between January 2019 and December 2021.” 5. Inclusion Criteria – Use of “and” vs “or” Comment: Not all studies included all three variables. Response: Correct. The text has been revised accordingly. Revised text: “…had data on patients’ age, sex, or prothrombin time.” 6. Use of “incidence” vs “prevalence” Comment: “Incidence” is not the correct term in this context. Response: We agree and have replaced “incidence” with “prevalence” throughout the manuscript in the relevant sections (pages 7, 9, and Discussion paragraphs 4 and 8). 7. Page 10 – Misrepresentation of gender findings Comment: “Based on Table 3” does not accurately reflect the results. Response: We have revised this statement to reflect the actual finding. Revised text: “Male patients with diabetes had a higher risk of hospitalization compared to female patients with diabetes.” 8. Page 10 – Prothrombin time conclusion Comment: The conclusion should be revised to reflect non-significance. Response: We agree. The statement has been modified. Revised text: “no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes.” 9. Page 12 – “SMD > 0” unclear Comment: The statement should be clarified. Response: We have revised this to provide a clear interpretation of the result. Revised text: “….the difference in prothrombin time was not statistically significant, diabetic patients tended to have higher values than non-diabetic patients.” 10. Discussion Paragraph 3 – Context limitation Comment: The results apply only to hospitalized patients. Response: We agree. A clarifying statement has been added. Revised text: “These findings apply only to hospitalized COVID-19 patients.” 11. Discussion Paragraph 4 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: Corrected as suggested. 12. Discussion Paragraph 5 – Inaccurate statement Comment: The first statement should be aligned with the actual findings. Response: We have revised the text to reflect the higher risk of hospitalization among male patients with diabetes. 13. Discussion Paragraph 7 – Overgeneralization Comment: The conclusion should specify the study population. Response: We have added clarification indicating that the conclusions pertain to hospitalized patients. 14. Discussion Paragraph 8 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: The term has been corrected accordingly. We thank the reviewer once again for their valuable feedback. All suggested revisions have been addressed carefully, and we believe these changes have strengthened the clarity, accuracy, and overall quality of the manuscript. We would like to express our sincere gratitude to the reviewer for their constructive and insightful comments, which have significantly improved the clarity and precision of our manuscript. Below are our point-by-point responses and the corresponding revisions made in the manuscript (marked in the revised version). 1. Abstract – Aim not clearly articulated Comment: The study’s aim is not clearly stated in the abstract. Response: We agree. The aim has been revised to explicitly state the objective of the study. Revised text: “This study aimed to evaluate the association between age, sex, and prothrombin time and the likelihood of hospitalization among COVID-19 patients with diabetes mellitus.” 2. Abstract – Vague statement on “higher risk” Comment: Please specify the type of risk. Response: We agree. The phrase has been clarified to indicate the type of risk observed. Revised text: “…have a higher risk of hospitalization compared to those without diabetes mellitus.” 3. Introduction – Discrepancy in study aim Comment: The aim mentions “severity,” but the study focuses on hospitalized patients. Response: Thank you for pointing this out. The wording has been revised to accurately reflect the study’s scope. Revised text: “...to examine the relationship between age, sex, and prothrombin time in hospitalized COVID-19 patients with diabetes mellitus.” 4. Methods – Literature search period Comment: Please specify the exact months for the literature search period. Response: We agree. The time frame has been clarified. Revised text: “The literature search was conducted for studies published between January 2019 and December 2021.” 5. Inclusion Criteria – Use of “and” vs “or” Comment: Not all studies included all three variables. Response: Correct. The text has been revised accordingly. Revised text: “…had data on patients’ age, sex, or prothrombin time.” 6. Use of “incidence” vs “prevalence” Comment: “Incidence” is not the correct term in this context. Response: We agree and have replaced “incidence” with “prevalence” throughout the manuscript in the relevant sections (pages 7, 9, and Discussion paragraphs 4 and 8). 7. Page 10 – Misrepresentation of gender findings Comment: “Based on Table 3” does not accurately reflect the results. Response: We have revised this statement to reflect the actual finding. Revised text: “Male patients with diabetes had a higher risk of hospitalization compared to female patients with diabetes.” 8. Page 10 – Prothrombin time conclusion Comment: The conclusion should be revised to reflect non-significance. Response: We agree. The statement has been modified. Revised text: “no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes.” 9. Page 12 – “SMD > 0” unclear Comment: The statement should be clarified. Response: We have revised this to provide a clear interpretation of the result. Revised text: “….the difference in prothrombin time was not statistically significant, diabetic patients tended to have higher values than non-diabetic patients.” 10. Discussion Paragraph 3 – Context limitation Comment: The results apply only to hospitalized patients. Response: We agree. A clarifying statement has been added. Revised text: “These findings apply only to hospitalized COVID-19 patients.” 11. Discussion Paragraph 4 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: Corrected as suggested. 12. Discussion Paragraph 5 – Inaccurate statement Comment: The first statement should be aligned with the actual findings. Response: We have revised the text to reflect the higher risk of hospitalization among male patients with diabetes. 13. Discussion Paragraph 7 – Overgeneralization Comment: The conclusion should specify the study population. Response: We have added clarification indicating that the conclusions pertain to hospitalized patients. 14. Discussion Paragraph 8 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: The term has been corrected accordingly. We thank the reviewer once again for their valuable feedback. All suggested revisions have been addressed carefully, and we believe these changes have strengthened the clarity, accuracy, and overall quality of the manuscript. Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r312342 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-312342 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 Aug 2024 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia Approved VIEWS 0 https://doi.org/10.5256/f1000research.169997.r312342 The author has revised the ... Continue reading READ ALL The author has revised the manuscript according to the reviewer's input. Competing Interests: No competing interests were disclosed. Reviewer Expertise: biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r312342 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-312342 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 5 VERSION 5 PUBLISHED 25 Jul 2024 Revised Views 0 Cite How to cite this report: Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169449.r306939 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v5#referee-response-306939 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 01 Aug 2024 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.169449.r306939 1) There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2) The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can ... Continue reading READ ALL 1) There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2) The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can be concluded that old age and male sex are associated with a more severe disease." this cannot be answered based on the results of the study presented. Authors are advised to recheck the manuscript before submitting a revision, and ensure that what is written in the abstract is in line with the data presented in the contents of the manuscript. Competing Interests: No competing interests were disclosed. Reviewer Expertise: biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169449.r306939 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v5#referee-response-306939 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 08 Aug 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 08 Aug 2024 Author Response Thank you for the review 1: There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2: The conclusion in ... Continue reading Thank you for the review 1: There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2: The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can be concluded that old age and male sex are associated with a more severe disease." this cannot be answered based on the results of the study presented. Response: I apologize for any inconsistencies. I have reviewed the manuscript and ensured that it is revised before, I revised it again to match the abstract with the data content. Sincerely, Mutiara Indah Sari Thank you for the review 1: There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2: The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can be concluded that old age and male sex are associated with a more severe disease." this cannot be answered based on the results of the study presented. Response: I apologize for any inconsistencies. I have reviewed the manuscript and ensured that it is revised before, I revised it again to match the abstract with the data content. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 08 Aug 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 08 Aug 2024 Author Response Thank you for the review 1: There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2: The conclusion in ... Continue reading Thank you for the review 1: There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2: The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can be concluded that old age and male sex are associated with a more severe disease." this cannot be answered based on the results of the study presented. Response: I apologize for any inconsistencies. I have reviewed the manuscript and ensured that it is revised before, I revised it again to match the abstract with the data content. Sincerely, Mutiara Indah Sari Thank you for the review 1: There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2: The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can be concluded that old age and male sex are associated with a more severe disease." this cannot be answered based on the results of the study presented. Response: I apologize for any inconsistencies. I have reviewed the manuscript and ensured that it is revised before, I revised it again to match the abstract with the data content. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Version 4 VERSION 4 PUBLISHED 11 Jul 2024 Revised Views 0 Cite How to cite this report: Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.168875.r301754 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v4#referee-response-301754 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 19 Jul 2024 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.168875.r301754 The revision submitted by the author has not addressed the reviewer's questions. 1) The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure ... Continue reading READ ALL The revision submitted by the author has not addressed the reviewer's questions. 1) The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. For every variable, why not use all of the articles in the final stage? Further clarification is required. Apart from that, clarification is needed due to the inconsistency in the number of articles at the final stage, whether 46 or 45 because there is a difference between the abstract and the results section. 2) In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. It is advisable to omit that particular sentence from the conclusion. Competing Interests: No competing interests were disclosed. Reviewer Expertise: biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.168875.r301754 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v4#referee-response-301754 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 25 Jul 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 25 Jul 2024 Author Response Thank you for the review. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure ... Continue reading Thank you for the review. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. For every variable, why not use all of the articles in the final stage? Further clarification is required. Apart from that, clarification is needed due to the inconsistency in the number of articles at the final stage, whether 46 or 45 because there is a difference between the abstract and the results section. Response: The literature used is 45. We apologize for the discrepancy. We have thoroughly reviewed the literature used to process 45 data. There were duplicated references in Table 1 earlier, however, this does not affect the results of the forest plot data processing, only the numerical counts in the characteristics. We cannot use all literature for each variable because not all data for each variable is available in every literature we used. Therefore, in total for the three variables, we used 45 literature sources, with 31 articles used for age, 5 articles for gender, and 15 articles for prothrombin time. Among these, there are overlapping articles that contain data for two variables.​​​​​​​ 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. It is advisable to omit that particular sentence from the conclusion. Response: We have omit that particular sentence from the conclusion. Sincerely, Mutiara Indah Sari Thank you for the review. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. For every variable, why not use all of the articles in the final stage? Further clarification is required. Apart from that, clarification is needed due to the inconsistency in the number of articles at the final stage, whether 46 or 45 because there is a difference between the abstract and the results section. Response: The literature used is 45. We apologize for the discrepancy. We have thoroughly reviewed the literature used to process 45 data. There were duplicated references in Table 1 earlier, however, this does not affect the results of the forest plot data processing, only the numerical counts in the characteristics. We cannot use all literature for each variable because not all data for each variable is available in every literature we used. Therefore, in total for the three variables, we used 45 literature sources, with 31 articles used for age, 5 articles for gender, and 15 articles for prothrombin time. Among these, there are overlapping articles that contain data for two variables.​​​​​​​ 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. It is advisable to omit that particular sentence from the conclusion. Response: We have omit that particular sentence from the conclusion. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 25 Jul 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 25 Jul 2024 Author Response Thank you for the review. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure ... Continue reading Thank you for the review. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. For every variable, why not use all of the articles in the final stage? Further clarification is required. Apart from that, clarification is needed due to the inconsistency in the number of articles at the final stage, whether 46 or 45 because there is a difference between the abstract and the results section. Response: The literature used is 45. We apologize for the discrepancy. We have thoroughly reviewed the literature used to process 45 data. There were duplicated references in Table 1 earlier, however, this does not affect the results of the forest plot data processing, only the numerical counts in the characteristics. We cannot use all literature for each variable because not all data for each variable is available in every literature we used. Therefore, in total for the three variables, we used 45 literature sources, with 31 articles used for age, 5 articles for gender, and 15 articles for prothrombin time. Among these, there are overlapping articles that contain data for two variables.​​​​​​​ 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. It is advisable to omit that particular sentence from the conclusion. Response: We have omit that particular sentence from the conclusion. Sincerely, Mutiara Indah Sari Thank you for the review. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. For every variable, why not use all of the articles in the final stage? Further clarification is required. Apart from that, clarification is needed due to the inconsistency in the number of articles at the final stage, whether 46 or 45 because there is a difference between the abstract and the results section. Response: The literature used is 45. We apologize for the discrepancy. We have thoroughly reviewed the literature used to process 45 data. There were duplicated references in Table 1 earlier, however, this does not affect the results of the forest plot data processing, only the numerical counts in the characteristics. We cannot use all literature for each variable because not all data for each variable is available in every literature we used. Therefore, in total for the three variables, we used 45 literature sources, with 31 articles used for age, 5 articles for gender, and 15 articles for prothrombin time. Among these, there are overlapping articles that contain data for two variables.​​​​​​​ 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. It is advisable to omit that particular sentence from the conclusion. Response: We have omit that particular sentence from the conclusion. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Version 3 VERSION 3 PUBLISHED 21 Jun 2024 Revised Views 0 Cite How to cite this report: Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.168129.r294009 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v3#referee-response-294009 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 05 Jul 2024 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.168129.r294009 The author has made several improvements, but the following 2 things still concern reviewers: 1) The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure ... Continue reading READ ALL The author has made several improvements, but the following 2 things still concern reviewers: 1) The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. In the latest revision the author only mentions "The final results after selection got a total of 46 articles that were included in this meta-analysis study. Within these, 31 articles are utilized for age, 5 articles are utilized for gender, and 15 articles are utilized for prothrombin time." without any further explanation. 2) In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. Competing Interests: No competing interests were disclosed. Reviewer Expertise: biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.168129.r294009 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v3#referee-response-294009 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 11 Jul 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 11 Jul 2024 Author Response Thank you for the review. We will revise the manuscript based on your suggestions. 1: In the latest revision the author only mentions "The final results after selection got a ... Continue reading Thank you for the review. We will revise the manuscript based on your suggestions. 1: In the latest revision the author only mentions "The final results after selection got a total of 46 articles that were included in this meta-analysis study. Within these, 31 articles are utilized for age, 5 articles are utilized for gender, and 15 articles are utilized for prothrombin time." without any further explanation. Response: For further explanation, we have added a venn diagram included studies for each variables. 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. Response: We have added some explanation related to our study in the results section. All samples in the articles we reviewed were hospitalized patients, where the severity was more severe than those who were only isolated at home. Among patients with severe disease, we compared diabetic and non-diabetic group. Sincerely, Mutiara Indah Sari Thank you for the review. We will revise the manuscript based on your suggestions. 1: In the latest revision the author only mentions "The final results after selection got a total of 46 articles that were included in this meta-analysis study. Within these, 31 articles are utilized for age, 5 articles are utilized for gender, and 15 articles are utilized for prothrombin time." without any further explanation. Response: For further explanation, we have added a venn diagram included studies for each variables. 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. Response: We have added some explanation related to our study in the results section. All samples in the articles we reviewed were hospitalized patients, where the severity was more severe than those who were only isolated at home. Among patients with severe disease, we compared diabetic and non-diabetic group. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 11 Jul 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 11 Jul 2024 Author Response Thank you for the review. We will revise the manuscript based on your suggestions. 1: In the latest revision the author only mentions "The final results after selection got a ... Continue reading Thank you for the review. We will revise the manuscript based on your suggestions. 1: In the latest revision the author only mentions "The final results after selection got a total of 46 articles that were included in this meta-analysis study. Within these, 31 articles are utilized for age, 5 articles are utilized for gender, and 15 articles are utilized for prothrombin time." without any further explanation. Response: For further explanation, we have added a venn diagram included studies for each variables. 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. Response: We have added some explanation related to our study in the results section. All samples in the articles we reviewed were hospitalized patients, where the severity was more severe than those who were only isolated at home. Among patients with severe disease, we compared diabetic and non-diabetic group. Sincerely, Mutiara Indah Sari Thank you for the review. We will revise the manuscript based on your suggestions. 1: In the latest revision the author only mentions "The final results after selection got a total of 46 articles that were included in this meta-analysis study. Within these, 31 articles are utilized for age, 5 articles are utilized for gender, and 15 articles are utilized for prothrombin time." without any further explanation. Response: For further explanation, we have added a venn diagram included studies for each variables. 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. Response: We have added some explanation related to our study in the results section. All samples in the articles we reviewed were hospitalized patients, where the severity was more severe than those who were only isolated at home. Among patients with severe disease, we compared diabetic and non-diabetic group. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Version 2 VERSION 2 PUBLISHED 05 Jun 2024 Revised Views 0 Cite How to cite this report: Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.167093.r286853 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v2#referee-response-286853 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 18 Jun 2024 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.167093.r286853 The author has made several improvements to complete the information, especially in the methods section, but several things still need to be clarified. The author should clarify the criteria used to evaluate each variable in the ... Continue reading READ ALL The author has made several improvements to complete the information, especially in the methods section, but several things still need to be clarified. The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are utilized for the age variable, 5 articles are utilized for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. In the results section, the author compares the average age and prothrombin time between COVID-19 patients with and without DM. However, regarding the gender variable, the author only examines the comparison of male and female genders in COVID-19 patients with DM. To ensure consistency with the age and PT variables, it would be appropriate to analyze the sex ratio in COVID-19 patients with and without DM for the gender variable. In the results section, the sentence "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P < 0.05." should be corrected to "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05. " The conclusion section has not adequately addressed the concerns raised by the previous reviewer. I suggest revising the conclusion to align it with the results section. Specifically, the revised conclusion should state that the findings of this meta-analysis indicate that COVID-19 patients with comorbid DM tend to be older and male compared to COVID-19 patients without DM. However, there was no significant difference in the results of prothrombin time. Competing Interests: No competing interests were disclosed. Reviewer Expertise: biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.167093.r286853 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v2#referee-response-286853 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 21 Jun 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 21 Jun 2024 Author Response Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should clarify the criteria used to evaluate each variable in ... Continue reading Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are utilized for the age variable, 5 articles are utilized for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. Response: Further clarification is added as suggested. 2: In the results section, the author compares the average age and prothrombin time between COVID-19 patients with and without DM. However, regarding the gender variable, the author only examines the comparison of male and female genders in COVID-19 patients with DM. To ensure consistency with the age and PT variables, it would be appropriate to analyze the sex ratio in COVID-19 patients with and without DM for the gender variable.​​​​​​​ Response: We analyzed gender differences between male and female to assess gender as a risk factor, particularly among COVID-19 patients with comorbid diabetes, to determine whether more male or female were hospitalized. We processed gender data using odds ratios, unlike age and prothrombin time variables, which utilized mean and standard deviation. Additionally, there was a lack of odds ratio data for non-diabetic patients in the literature we reviewed. ​​​​​​​ 3: In the results section, the sentence "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P < 0.05." should be corrected to "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05. "​​​​​​​ Response: We will rectify the typographical error. 4: The conclusion section has not adequately addressed the concerns raised by the previous reviewer. I suggest revising the conclusion to align it with the results section. Specifically, the revised conclusion should state that the findings of this meta-analysis indicate that COVID-19 patients with comorbid DM tend to be older and male compared to COVID-19 patients without DM. However, there was no significant difference in the results of prothrombin time. Response: We will revise the conclusion to align it with the results. Sincerely, Mutiara Indah Sari Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are utilized for the age variable, 5 articles are utilized for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. Response: Further clarification is added as suggested. 2: In the results section, the author compares the average age and prothrombin time between COVID-19 patients with and without DM. However, regarding the gender variable, the author only examines the comparison of male and female genders in COVID-19 patients with DM. To ensure consistency with the age and PT variables, it would be appropriate to analyze the sex ratio in COVID-19 patients with and without DM for the gender variable.​​​​​​​ Response: We analyzed gender differences between male and female to assess gender as a risk factor, particularly among COVID-19 patients with comorbid diabetes, to determine whether more male or female were hospitalized. We processed gender data using odds ratios, unlike age and prothrombin time variables, which utilized mean and standard deviation. Additionally, there was a lack of odds ratio data for non-diabetic patients in the literature we reviewed. ​​​​​​​ 3: In the results section, the sentence "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P < 0.05." should be corrected to "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05. "​​​​​​​ Response: We will rectify the typographical error. 4: The conclusion section has not adequately addressed the concerns raised by the previous reviewer. I suggest revising the conclusion to align it with the results section. Specifically, the revised conclusion should state that the findings of this meta-analysis indicate that COVID-19 patients with comorbid DM tend to be older and male compared to COVID-19 patients without DM. However, there was no significant difference in the results of prothrombin time. Response: We will revise the conclusion to align it with the results. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 21 Jun 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 21 Jun 2024 Author Response Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should clarify the criteria used to evaluate each variable in ... Continue reading Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are utilized for the age variable, 5 articles are utilized for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. Response: Further clarification is added as suggested. 2: In the results section, the author compares the average age and prothrombin time between COVID-19 patients with and without DM. However, regarding the gender variable, the author only examines the comparison of male and female genders in COVID-19 patients with DM. To ensure consistency with the age and PT variables, it would be appropriate to analyze the sex ratio in COVID-19 patients with and without DM for the gender variable.​​​​​​​ Response: We analyzed gender differences between male and female to assess gender as a risk factor, particularly among COVID-19 patients with comorbid diabetes, to determine whether more male or female were hospitalized. We processed gender data using odds ratios, unlike age and prothrombin time variables, which utilized mean and standard deviation. Additionally, there was a lack of odds ratio data for non-diabetic patients in the literature we reviewed. ​​​​​​​ 3: In the results section, the sentence "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P < 0.05." should be corrected to "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05. "​​​​​​​ Response: We will rectify the typographical error. 4: The conclusion section has not adequately addressed the concerns raised by the previous reviewer. I suggest revising the conclusion to align it with the results section. Specifically, the revised conclusion should state that the findings of this meta-analysis indicate that COVID-19 patients with comorbid DM tend to be older and male compared to COVID-19 patients without DM. However, there was no significant difference in the results of prothrombin time. Response: We will revise the conclusion to align it with the results. Sincerely, Mutiara Indah Sari Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are utilized for the age variable, 5 articles are utilized for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. Response: Further clarification is added as suggested. 2: In the results section, the author compares the average age and prothrombin time between COVID-19 patients with and without DM. However, regarding the gender variable, the author only examines the comparison of male and female genders in COVID-19 patients with DM. To ensure consistency with the age and PT variables, it would be appropriate to analyze the sex ratio in COVID-19 patients with and without DM for the gender variable.​​​​​​​ Response: We analyzed gender differences between male and female to assess gender as a risk factor, particularly among COVID-19 patients with comorbid diabetes, to determine whether more male or female were hospitalized. We processed gender data using odds ratios, unlike age and prothrombin time variables, which utilized mean and standard deviation. Additionally, there was a lack of odds ratio data for non-diabetic patients in the literature we reviewed. ​​​​​​​ 3: In the results section, the sentence "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P < 0.05." should be corrected to "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05. "​​​​​​​ Response: We will rectify the typographical error. 4: The conclusion section has not adequately addressed the concerns raised by the previous reviewer. I suggest revising the conclusion to align it with the results section. Specifically, the revised conclusion should state that the findings of this meta-analysis indicate that COVID-19 patients with comorbid DM tend to be older and male compared to COVID-19 patients without DM. However, there was no significant difference in the results of prothrombin time. Response: We will revise the conclusion to align it with the results. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 01 Jul 2022 Views 0 Cite How to cite this report: Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.118616.r269067 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v1#referee-response-269067 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 May 2024 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.118616.r269067 The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Next, the author must certify that the results of ... Continue reading READ ALL The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Next, the author must certify that the results of the literature search are articles published until when? The analysis of statistical results states that there is very high (significant) variability in each variable; has the author made any efforts to lessen this heterogeneity? (Please refer to https://handbook-5-1.cochrane.org/chapter_9/9_5_3_strategies_for_addressing_heterogeneity.htm ) Furthermore, the conclusions presented are not in accordance with the results obtained by the author. In the conclusion the author stated "Patients with older age with diabetes tend to have more severe disease than non-diabetics" even though the meta-analysis carried out only compared age between the Covid group with DM vs without DM, there was no study of morbidity variables. Likewise, the statement "Patients with diabetes who are hospitalized are more likely to be male, indicating that males are more susceptible to severe disease" in our opinion is not appropriate considering that there are no variables for hospitalization status or degree of disease that were studied by the author in the meta-analysis section. Furthermore, considering that there are still several limitations that may not be avoidable, these need to be explored further by the author in the discussion section, such as the influence of disease onset and disease degree. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are the conclusions drawn adequately supported by the results presented in the review? No If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) No Competing Interests: No competing interests were disclosed. Reviewer Expertise: biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Marindra Siregar F. Reviewer Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.118616.r269067 ) The direct URL for this report is: https://f1000research.com/articles/11-729/v1#referee-response-269067 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 21 Jun 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 21 Jun 2024 Author Response Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should properly clarify the search method utilised in each ... Continue reading Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Response: We will add more details on the search strategy such as the filters for each database in the text. 2: Next, the author must certify that the results of the literature search are articles published until when? Response: We will add the publication years for the included literatures in the text. 3: The analysis of statistical results states that there is very high (significant) variability in each variable; has the author made any efforts to lessen this heterogeneity? Response: Referring to the handbook, we performed point 1 (rechecking the data) and 7 (studies exclusion) to reduce heterogeneity. We will add brief information on this in the text. 4: Furthermore, the conclusions presented are not in accordance with the results obtained by the author. In the conclusion the author stated "Patients with older age with diabetes tend to have more severe disease than non-diabetics" even though the meta-analysis carried out only compared age between the Covid group with DM vs without DM, there was no study of morbidity variables. Likewise, the statement "Patients with diabetes who are hospitalized are more likely to be male, indicating that males are more susceptible to severe disease" in our opinion is not appropriate considering that there are no variables for hospitalization status or degree of disease that were studied by the author in the meta-analysis section. Response: It is true that our result is comparing COVID patients with vs without DM, so we will make changes on the conclusion and a few other parts of the text (for consistency and clarification) based on your suggestion. However, we would like to note that as DM is a comorbidity in COVID, we use it as an indicator of a more severe disease. 5: Furthermore, considering that there are still several limitations that may not be avoidable, these need to be explored further by the author in the discussion section, such as the influence of disease onset and disease degree. Response: We will add the limitations to the text as suggested. Sincerely, Mutiara Indah Sari Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Response: We will add more details on the search strategy such as the filters for each database in the text. 2: Next, the author must certify that the results of the literature search are articles published until when? Response: We will add the publication years for the included literatures in the text. 3: The analysis of statistical results states that there is very high (significant) variability in each variable; has the author made any efforts to lessen this heterogeneity? Response: Referring to the handbook, we performed point 1 (rechecking the data) and 7 (studies exclusion) to reduce heterogeneity. We will add brief information on this in the text. 4: Furthermore, the conclusions presented are not in accordance with the results obtained by the author. In the conclusion the author stated "Patients with older age with diabetes tend to have more severe disease than non-diabetics" even though the meta-analysis carried out only compared age between the Covid group with DM vs without DM, there was no study of morbidity variables. Likewise, the statement "Patients with diabetes who are hospitalized are more likely to be male, indicating that males are more susceptible to severe disease" in our opinion is not appropriate considering that there are no variables for hospitalization status or degree of disease that were studied by the author in the meta-analysis section. Response: It is true that our result is comparing COVID patients with vs without DM, so we will make changes on the conclusion and a few other parts of the text (for consistency and clarification) based on your suggestion. However, we would like to note that as DM is a comorbidity in COVID, we use it as an indicator of a more severe disease. 5: Furthermore, considering that there are still several limitations that may not be avoidable, these need to be explored further by the author in the discussion section, such as the influence of disease onset and disease degree. Response: We will add the limitations to the text as suggested. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 21 Jun 2024 Mutiara Indah Sari , Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia 21 Jun 2024 Author Response Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should properly clarify the search method utilised in each ... Continue reading Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Response: We will add more details on the search strategy such as the filters for each database in the text. 2: Next, the author must certify that the results of the literature search are articles published until when? Response: We will add the publication years for the included literatures in the text. 3: The analysis of statistical results states that there is very high (significant) variability in each variable; has the author made any efforts to lessen this heterogeneity? Response: Referring to the handbook, we performed point 1 (rechecking the data) and 7 (studies exclusion) to reduce heterogeneity. We will add brief information on this in the text. 4: Furthermore, the conclusions presented are not in accordance with the results obtained by the author. In the conclusion the author stated "Patients with older age with diabetes tend to have more severe disease than non-diabetics" even though the meta-analysis carried out only compared age between the Covid group with DM vs without DM, there was no study of morbidity variables. Likewise, the statement "Patients with diabetes who are hospitalized are more likely to be male, indicating that males are more susceptible to severe disease" in our opinion is not appropriate considering that there are no variables for hospitalization status or degree of disease that were studied by the author in the meta-analysis section. Response: It is true that our result is comparing COVID patients with vs without DM, so we will make changes on the conclusion and a few other parts of the text (for consistency and clarification) based on your suggestion. However, we would like to note that as DM is a comorbidity in COVID, we use it as an indicator of a more severe disease. 5: Furthermore, considering that there are still several limitations that may not be avoidable, these need to be explored further by the author in the discussion section, such as the influence of disease onset and disease degree. Response: We will add the limitations to the text as suggested. Sincerely, Mutiara Indah Sari Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Response: We will add more details on the search strategy such as the filters for each database in the text. 2: Next, the author must certify that the results of the literature search are articles published until when? Response: We will add the publication years for the included literatures in the text. 3: The analysis of statistical results states that there is very high (significant) variability in each variable; has the author made any efforts to lessen this heterogeneity? Response: Referring to the handbook, we performed point 1 (rechecking the data) and 7 (studies exclusion) to reduce heterogeneity. We will add brief information on this in the text. 4: Furthermore, the conclusions presented are not in accordance with the results obtained by the author. In the conclusion the author stated "Patients with older age with diabetes tend to have more severe disease than non-diabetics" even though the meta-analysis carried out only compared age between the Covid group with DM vs without DM, there was no study of morbidity variables. Likewise, the statement "Patients with diabetes who are hospitalized are more likely to be male, indicating that males are more susceptible to severe disease" in our opinion is not appropriate considering that there are no variables for hospitalization status or degree of disease that were studied by the author in the meta-analysis section. Response: It is true that our result is comparing COVID patients with vs without DM, so we will make changes on the conclusion and a few other parts of the text (for consistency and clarification) based on your suggestion. However, we would like to note that as DM is a comorbidity in COVID, we use it as an indicator of a more severe disease. 5: Furthermore, considering that there are still several limitations that may not be avoidable, these need to be explored further by the author in the discussion section, such as the influence of disease onset and disease degree. Response: We will add the limitations to the text as suggested. Sincerely, Mutiara Indah Sari Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 7 VERSION 7 PUBLISHED 01 Jul 2022 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 Version 7 (revision) 14 Oct 25 Version 6 (revision) 08 Aug 24 read read read Version 5 (revision) 25 Jul 24 read Version 4 (revision) 11 Jul 24 read Version 3 (revision) 21 Jun 24 read Version 2 (revision) 05 Jun 24 read Version 1 01 Jul 22 read Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Indonesia Ipsa Arora , Central Maine Medical Center, Lewiston, USA Chenxiao Wang , Tulane University, New Orleans, USA Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Wang C. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 07 Mar 2025 | for Version 6 Chenxiao Wang , Tulane University, New Orleans, USA 0 Views copyright © 2025 Wang C. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The manuscript systematically reviews and conducts a meta-analysis to investigate how age, sex, and prothrombin time (PT) values relate to COVID-19 severity among patients with diabetes mellitus (DM). The authors analyzed data from 45 studies sourced from prominent databases, applying robust inclusion and exclusion criteria. Overall, the study concludes that older age and male gender significantly increase COVID-19 severity risk among patients with DM, whereas prothrombin time values were slightly prolonged in DM patients compared to non-DM patients, though not significantly so overall. The manuscript addresses a clinical issue, and the authors addressed all the questions reviewers raised. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Yes Are the conclusions drawn adequately supported by the results presented in the review? Yes If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests No competing interests were disclosed. Reviewer Expertise COVID-19 I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Wang C. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r368187) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-368187 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Arora I. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 27 Aug 2024 | for Version 6 Ipsa Arora , Endocrinology, Central Maine Medical Center, Lewiston, Maine, USA 0 Views copyright © 2024 Arora I. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Mirza et al. conducted a systematic review and meta-analysis to examine the relationship between age, gender, and prothrombin time in COVID-19 patients requiring hospitalization, with or without diabetes as a comorbidity. They found that hospitalized COVID-19 patients with diabetes were generally older and predominantly male. Although a statistically significant association with prothrombin time was not identified, hospitalized patients with both COVID-19 and diabetes tended to have higher prothrombin time values. I recommend the following clarifications to enhance the clarity and usefulness of this publication for the readers of this journal. Abstract : The study's aim is not clearly articulated in the abstract. Conclusion : The statement "patients with COVID-19 who have diabetes have a higher risk as compared to those without diabetes" is vague. Please specify the higher risk of what—e.g., higher risk of hospitalization, severe outcomes, or mortality. Introduction : In the last sentence where the study's aim is mentioned, there seems to be a discrepancy. The study does not investigate the relationship between age, gender, and prothrombin time with the "severity of COVID-19." Instead, it examines these parameters in relation to COVID-19 cases requiring hospitalization. This should be clarified, especially since the limitations (under discussion) indicate that the meta-analysis does not explore the relationship with COVID-19 severity. Methods : In the literature search section (2019-2021), it is recommended to specify the exact months for each year. Inclusion Criteria : The first line states, "all retrospective studies... had data on patients' age, sex, and prothrombin time." It may be more accurate to say "age, sex, or prothrombin time," as not all 45 studies included data on all three variables. Page 7/25 : In the section discussing the relationship between age and diabetes in COVID-19 patients, "incidence" might not be the most appropriate term; "prevalence" could be more accurate. The same applies to page 9/25 regarding the relationship between sex and diabetes in COVID-19 patients. Page 10/25 : The phrase "Based on Table 3..." does not appropriately represent the study’s findings. It should be revised to indicate that "male patients with diabetes have a higher risk of hospitalization compared to female patients with diabetes." Page 10/25 : In the section discussing the relationship between prothrombin time and diabetes in COVID-19 patients, consider revising the conclusion to state that "no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes." Page 12/25 : The last line of the results section ("The SMD >0... more severe illness") is unclear and may need to be rewritten, taking into account the points raised in comment 8. Discussion, Paragraph 3 : Please specify that the results discussed are applicable only to hospitalized patients. Discussion, Paragraph 4 : The term "incidence" is used incorrectly; please refer to comment 6 for guidance. Discussion, Paragraph 5 : The first statement may be inaccurate and should be revised based on the information discussed in comment 7. Discussion, Paragraph 7 : The conclusion should specify that it pertains to patients with COVID-19 requiring hospitalization. Discussion, Paragraph 8 : The mention of "incidence" should be corrected as indicated in comment 6. Are the rationale for, and objectives of, the Systematic Review clearly stated? Partly Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests No competing interests were disclosed. Reviewer Expertise Endocrinology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 15 Oct 2025 Mutiara Indah Sari, Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia We would like to express our sincere gratitude to the reviewer for their constructive and insightful comments, which have significantly improved the clarity and precision of our manuscript. Below are our point-by-point responses and the corresponding revisions made in the manuscript (marked in the revised version). 1. Abstract – Aim not clearly articulated Comment: The study’s aim is not clearly stated in the abstract. Response: We agree. The aim has been revised to explicitly state the objective of the study. Revised text: “This study aimed to evaluate the association between age, sex, and prothrombin time and the likelihood of hospitalization among COVID-19 patients with diabetes mellitus.” 2. Abstract – Vague statement on “higher risk” Comment: Please specify the type of risk. Response: We agree. The phrase has been clarified to indicate the type of risk observed. Revised text: “…have a higher risk of hospitalization compared to those without diabetes mellitus.” 3. Introduction – Discrepancy in study aim Comment: The aim mentions “severity,” but the study focuses on hospitalized patients. Response: Thank you for pointing this out. The wording has been revised to accurately reflect the study’s scope. Revised text: “...to examine the relationship between age, sex, and prothrombin time in hospitalized COVID-19 patients with diabetes mellitus.” 4. Methods – Literature search period Comment: Please specify the exact months for the literature search period. Response: We agree. The time frame has been clarified. Revised text: “The literature search was conducted for studies published between January 2019 and December 2021.” 5. Inclusion Criteria – Use of “and” vs “or” Comment: Not all studies included all three variables. Response: Correct. The text has been revised accordingly. Revised text: “…had data on patients’ age, sex, or prothrombin time.” 6. Use of “incidence” vs “prevalence” Comment: “Incidence” is not the correct term in this context. Response: We agree and have replaced “incidence” with “prevalence” throughout the manuscript in the relevant sections (pages 7, 9, and Discussion paragraphs 4 and 8). 7. Page 10 – Misrepresentation of gender findings Comment: “Based on Table 3” does not accurately reflect the results. Response: We have revised this statement to reflect the actual finding. Revised text: “Male patients with diabetes had a higher risk of hospitalization compared to female patients with diabetes.” 8. Page 10 – Prothrombin time conclusion Comment: The conclusion should be revised to reflect non-significance. Response: We agree. The statement has been modified. Revised text: “no statistically significant difference was identified in prothrombin time between hospitalized COVID-19 patients with or without diabetes; however, values were generally higher in patients with diabetes.” 9. Page 12 – “SMD > 0” unclear Comment: The statement should be clarified. Response: We have revised this to provide a clear interpretation of the result. Revised text: “….the difference in prothrombin time was not statistically significant, diabetic patients tended to have higher values than non-diabetic patients.” 10. Discussion Paragraph 3 – Context limitation Comment: The results apply only to hospitalized patients. Response: We agree. A clarifying statement has been added. Revised text: “These findings apply only to hospitalized COVID-19 patients.” 11. Discussion Paragraph 4 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: Corrected as suggested. 12. Discussion Paragraph 5 – Inaccurate statement Comment: The first statement should be aligned with the actual findings. Response: We have revised the text to reflect the higher risk of hospitalization among male patients with diabetes. 13. Discussion Paragraph 7 – Overgeneralization Comment: The conclusion should specify the study population. Response: We have added clarification indicating that the conclusions pertain to hospitalized patients. 14. Discussion Paragraph 8 – Incorrect use of “incidence” Comment: Should use “prevalence.” Response: The term has been corrected accordingly. We thank the reviewer once again for their valuable feedback. All suggested revisions have been addressed carefully, and we believe these changes have strengthened the clarity, accuracy, and overall quality of the manuscript. View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Arora I. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r313402) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-313402 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 Aug 2024 | for Version 6 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The author has revised the manuscript according to the reviewer's input. Competing Interests No competing interests were disclosed. Reviewer Expertise biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Marindra Siregar F. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169997.r312342) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v6#referee-response-312342 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 01 Aug 2024 | for Version 5 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions 1) There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2) The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can be concluded that old age and male sex are associated with a more severe disease." this cannot be answered based on the results of the study presented. Authors are advised to recheck the manuscript before submitting a revision, and ensure that what is written in the abstract is in line with the data presented in the contents of the manuscript. Competing Interests No competing interests were disclosed. Reviewer Expertise biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 08 Aug 2024 Mutiara Indah Sari, Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia Thank you for the review 1: There is still a difference between the number of articles that entered the final stage in the abstract and results sections 2: The conclusion in the abstract still states "As diabetes is a comorbidity in COVID-19, it can be concluded that old age and male sex are associated with a more severe disease." this cannot be answered based on the results of the study presented. Response: I apologize for any inconsistencies. I have reviewed the manuscript and ensured that it is revised before, I revised it again to match the abstract with the data content. Sincerely, Mutiara Indah Sari View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Marindra Siregar F. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.169449.r306939) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v5#referee-response-306939 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 19 Jul 2024 | for Version 4 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The revision submitted by the author has not addressed the reviewer's questions. 1) The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. For every variable, why not use all of the articles in the final stage? Further clarification is required. Apart from that, clarification is needed due to the inconsistency in the number of articles at the final stage, whether 46 or 45 because there is a difference between the abstract and the results section. 2) In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. It is advisable to omit that particular sentence from the conclusion. Competing Interests No competing interests were disclosed. Reviewer Expertise biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 25 Jul 2024 Mutiara Indah Sari, Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia Thank you for the review. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. For every variable, why not use all of the articles in the final stage? Further clarification is required. Apart from that, clarification is needed due to the inconsistency in the number of articles at the final stage, whether 46 or 45 because there is a difference between the abstract and the results section. Response: The literature used is 45. We apologize for the discrepancy. We have thoroughly reviewed the literature used to process 45 data. There were duplicated references in Table 1 earlier, however, this does not affect the results of the forest plot data processing, only the numerical counts in the characteristics. We cannot use all literature for each variable because not all data for each variable is available in every literature we used. Therefore, in total for the three variables, we used 45 literature sources, with 31 articles used for age, 5 articles for gender, and 15 articles for prothrombin time. Among these, there are overlapping articles that contain data for two variables.​​​​​​​ 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. It is advisable to omit that particular sentence from the conclusion. Response: We have omit that particular sentence from the conclusion. Sincerely, Mutiara Indah Sari View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Marindra Siregar F. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.168875.r301754) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v4#referee-response-301754 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 05 Jul 2024 | for Version 3 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The author has made several improvements, but the following 2 things still concern reviewers: 1) The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are used for the age variable, 5 articles are used for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. In the latest revision the author only mentions "The final results after selection got a total of 46 articles that were included in this meta-analysis study. Within these, 31 articles are utilized for age, 5 articles are utilized for gender, and 15 articles are utilized for prothrombin time." without any further explanation. 2) In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. Competing Interests No competing interests were disclosed. Reviewer Expertise biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 11 Jul 2024 Mutiara Indah Sari, Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia Thank you for the review. We will revise the manuscript based on your suggestions. 1: In the latest revision the author only mentions "The final results after selection got a total of 46 articles that were included in this meta-analysis study. Within these, 31 articles are utilized for age, 5 articles are utilized for gender, and 15 articles are utilized for prothrombin time." without any further explanation. Response: For further explanation, we have added a venn diagram included studies for each variables. 2: In the conclusion the author states "Since DM is a comorbidity in COVID-19, it can be concluded that older age and male sex are associated with more severe disease". While this proposition may be true in theory, the findings of this study do not address this particular aspect. Response: We have added some explanation related to our study in the results section. All samples in the articles we reviewed were hospitalized patients, where the severity was more severe than those who were only isolated at home. Among patients with severe disease, we compared diabetic and non-diabetic group. Sincerely, Mutiara Indah Sari View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Marindra Siregar F. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.168129.r294009) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v3#referee-response-294009 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 18 Jun 2024 | for Version 2 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The author has made several improvements to complete the information, especially in the methods section, but several things still need to be clarified. The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are utilized for the age variable, 5 articles are utilized for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. In the results section, the author compares the average age and prothrombin time between COVID-19 patients with and without DM. However, regarding the gender variable, the author only examines the comparison of male and female genders in COVID-19 patients with DM. To ensure consistency with the age and PT variables, it would be appropriate to analyze the sex ratio in COVID-19 patients with and without DM for the gender variable. In the results section, the sentence "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P < 0.05." should be corrected to "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05. " The conclusion section has not adequately addressed the concerns raised by the previous reviewer. I suggest revising the conclusion to align it with the results section. Specifically, the revised conclusion should state that the findings of this meta-analysis indicate that COVID-19 patients with comorbid DM tend to be older and male compared to COVID-19 patients without DM. However, there was no significant difference in the results of prothrombin time. Competing Interests No competing interests were disclosed. Reviewer Expertise biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 21 Jun 2024 Mutiara Indah Sari, Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should clarify the criteria used to evaluate each variable in the article, considering the varying number of assessed articles. According to Figure 1, there are a total of 46 articles. However, out of these, only 31 articles are utilized for the age variable, 5 articles are utilized for gender, and 15 articles are used for Prothrombin Time. Further clarification is required. Response: Further clarification is added as suggested. 2: In the results section, the author compares the average age and prothrombin time between COVID-19 patients with and without DM. However, regarding the gender variable, the author only examines the comparison of male and female genders in COVID-19 patients with DM. To ensure consistency with the age and PT variables, it would be appropriate to analyze the sex ratio in COVID-19 patients with and without DM for the gender variable.​​​​​​​ Response: We analyzed gender differences between male and female to assess gender as a risk factor, particularly among COVID-19 patients with comorbid diabetes, to determine whether more male or female were hospitalized. We processed gender data using odds ratios, unlike age and prothrombin time variables, which utilized mean and standard deviation. Additionally, there was a lack of odds ratio data for non-diabetic patients in the literature we reviewed. ​​​​​​​ 3: In the results section, the sentence "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P < 0.05." should be corrected to "Total Standardised Mean Difference (SMD) 0.41 (95%CI = -0.03–0.85; P = 0.07) with a confidence interval for the population between -0.03 to 0.85 (P = 0.07) showed that there were insignificant results because P > 0.05. "​​​​​​​ Response: We will rectify the typographical error. 4: The conclusion section has not adequately addressed the concerns raised by the previous reviewer. I suggest revising the conclusion to align it with the results section. Specifically, the revised conclusion should state that the findings of this meta-analysis indicate that COVID-19 patients with comorbid DM tend to be older and male compared to COVID-19 patients without DM. However, there was no significant difference in the results of prothrombin time. Response: We will revise the conclusion to align it with the results. Sincerely, Mutiara Indah Sari View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Marindra Siregar F. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.167093.r286853) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v2#referee-response-286853 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 May 2024 | for Version 1 Fajri Marindra Siregar , Universitas Riau, Pekanbaru, Riau, Indonesia 0 Views copyright © 2024 Marindra Siregar F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Next, the author must certify that the results of the literature search are articles published until when? The analysis of statistical results states that there is very high (significant) variability in each variable; has the author made any efforts to lessen this heterogeneity? (Please refer to https://handbook-5-1.cochrane.org/chapter_9/9_5_3_strategies_for_addressing_heterogeneity.htm ) Furthermore, the conclusions presented are not in accordance with the results obtained by the author. In the conclusion the author stated "Patients with older age with diabetes tend to have more severe disease than non-diabetics" even though the meta-analysis carried out only compared age between the Covid group with DM vs without DM, there was no study of morbidity variables. Likewise, the statement "Patients with diabetes who are hospitalized are more likely to be male, indicating that males are more susceptible to severe disease" in our opinion is not appropriate considering that there are no variables for hospitalization status or degree of disease that were studied by the author in the meta-analysis section. Furthermore, considering that there are still several limitations that may not be avoidable, these need to be explored further by the author in the discussion section, such as the influence of disease onset and disease degree. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are the conclusions drawn adequately supported by the results presented in the review? No If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) No Competing Interests No competing interests were disclosed. Reviewer Expertise biochemistry, health and medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 21 Jun 2024 Mutiara Indah Sari, Department of Biochemistry, Universitas Sumatera Utara, Medan, 20155, Indonesia Dear Reviewer, Thank you for the review. We will revise the manuscript based on your suggestions. 1: The author should properly clarify the search method utilised in each database, as each database has a unique search algorithm, so that other scholars can easily adapt it. Response: We will add more details on the search strategy such as the filters for each database in the text. 2: Next, the author must certify that the results of the literature search are articles published until when? Response: We will add the publication years for the included literatures in the text. 3: The analysis of statistical results states that there is very high (significant) variability in each variable; has the author made any efforts to lessen this heterogeneity? Response: Referring to the handbook, we performed point 1 (rechecking the data) and 7 (studies exclusion) to reduce heterogeneity. We will add brief information on this in the text. 4: Furthermore, the conclusions presented are not in accordance with the results obtained by the author. In the conclusion the author stated "Patients with older age with diabetes tend to have more severe disease than non-diabetics" even though the meta-analysis carried out only compared age between the Covid group with DM vs without DM, there was no study of morbidity variables. Likewise, the statement "Patients with diabetes who are hospitalized are more likely to be male, indicating that males are more susceptible to severe disease" in our opinion is not appropriate considering that there are no variables for hospitalization status or degree of disease that were studied by the author in the meta-analysis section. Response: It is true that our result is comparing COVID patients with vs without DM, so we will make changes on the conclusion and a few other parts of the text (for consistency and clarification) based on your suggestion. However, we would like to note that as DM is a comorbidity in COVID, we use it as an indicator of a more severe disease. 5: Furthermore, considering that there are still several limitations that may not be avoidable, these need to be explored further by the author in the discussion section, such as the influence of disease onset and disease degree. Response: We will add the limitations to the text as suggested. Sincerely, Mutiara Indah Sari View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Marindra Siregar F. Peer Review Report For: The relationship of age, sex and prothrombin time related to the severity of COVID-19 patients with diabetes mellitus: a systematic review and meta analysis [version 7; peer review: 2 approved, 1 approved with reservations] . F1000Research 2025, 11 :729 ( https://doi.org/10.5256/f1000research.118616.r269067) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/11-729/v1#referee-response-269067 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. 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