Desk-rejection of manuscripts: A necessary step for quality and
efficiency
Authors
- M Mostafa ZamanDepartment of Public Health and Informatics, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh https://orcid.org/0000-0002-1736-1342
DOI:
https://doi.org/10.3329/bsmmuj.v18i1.80740Keywords
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Published by Bangabandhu Sheikh
Mujib Medical University
We have examined the causes of desk rejections in the Bangabandhu Sheikh Mujib Medical University Journal. In 2024, we received 223 submissions; of which 85 (38%) were desk-rejected before reaching the peer review process. This rate is not unexpected, as high-standing journals, such as the New England Journal of Medicine and the British Medical Journal, experience desk rejections of 80%–90% [4]. Conducting an audit of the triage process is essential to inform potential authors and prevent unnecessary time and effort from being wasted on both sides.
The major reasons for desk rejections are shown in Figure 1. The rejections were largely due to formatting and preparation issues, such as non-compliance with the IMRD (Introduction, Methods, Results, and Discussion), as well as the failure to submit the necessary documents, including the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) checklists [5]. It appears that a substantial proportion of the authors do not carefully review the submission guidelines [6]. Additionally, some submissions lacked institutional ethical approval. In a few cases, the scientific writing quality was exceptionally poor. Many manuscripts did not meet the fundamental criteria, including word count, the number of data visuals, and the ORCID of the corresponding authors. Although our threshold for initiating peer review was a text similarity index of 15%, we allowed authors with a higher similarity index to revise their manuscripts to an acceptable level before making a final decision. However, submissions having more than 30% similarity index were rejected.







Categories | Number (%) |
Sex |
|
Male | 36 (60.0) |
Female | 24 (40.0) |
Age in yearsa | 8.8 (4.2) |
Education |
|
Pre-school | 20 (33.3) |
Elementary school | 24 (40.0) |
Junior high school | 16 (26.7) |
Cancer diagnoses |
|
Acute lymphoblastic leukemia | 33 (55) |
Retinoblastoma | 5 (8.3) |
Acute myeloid leukemia | 4 (6.7) |
Non-Hodgkins lymphoma | 4 (6.7) |
Osteosarcoma | 3 (5) |
Hepatoblastoma | 2 (3.3) |
Lymphoma | 2 (3.3) |
Neuroblastoma | 2 (3.3) |
Medulloblastoma | 1 (1.7) |
Neurofibroma | 1 (1.7) |
Ovarian tumour | 1 (1.7) |
Pancreatic cancer | 1 (1.7) |
Rhabdomyosarcoma | 1 (1.7) |
aMean (standard deviation) |
Categories | Number (%) |
Sex |
|
Male | 36 (60.0) |
Female | 24 (40.0) |
Age in yearsa | 8.8 (4.2) |
Education |
|
Pre-school | 20 (33.3) |
Elementary school | 24 (40.0) |
Junior high school | 16 (26.7) |
Cancer diagnoses |
|
Acute lymphoblastic leukemia | 33 (55) |
Retinoblastoma | 5 (8.3) |
Acute myeloid leukemia | 4 (6.7) |
Non-Hodgkins lymphoma | 4 (6.7) |
Osteosarcoma | 3 (5) |
Hepatoblastoma | 2 (3.3) |
Lymphoma | 2 (3.3) |
Neuroblastoma | 2 (3.3) |
Medulloblastoma | 1 (1.7) |
Neurofibroma | 1 (1.7) |
Ovarian tumour | 1 (1.7) |
Pancreatic cancer | 1 (1.7) |
Rhabdomyosarcoma | 1 (1.7) |
aMean (standard deviation) |
Characteristic | Mild (n=187) | Moderate (n=358) | Severe (n=113) |
Age | |||
20s | 65 (34.8) | 105 (29.3) | 44 (38.9) |
30s | 122 (65.2) | 53 (70.7) | 269 (61.1) |
Sex | |||
Men | 85 (45.5) | 199 (55.6) | 63 (55.8) |
Women | 102 (54.5) | 159 (44.4) | 50 (44.2) |
Smoking | |||
No | 139 (74.3) | 282 (78.8) | 94 (83.2) |
Yes | 48 (25.7) | 76 (21.2) | 19 (16.8) |
Frequency of smoking | |||
Daily | 40 (21.4) | 56 (15.6) | 12 (10.6) |
Non-daily | 8 (4.3) | 20 (5.6) | 7 (6.2) |
Method of smoking | |||
Cigarette | 18 (9.6) | 35 (9.8) | 10 (8.8) |
Hookah | 20 (10.7) | 23 (6.4) | 3 (2.7) |
Both | 10 (5.3) | 18 (5.0) | 6 (5.3) |
aNone of these variables were significantly different between pain categories |