Evidence map›Paper›PMID 42016286›Full record

ArticleHealth science reports2026

Profiling Disease Patterns Using ICD-11 at a University Hospital in Ghana: A Retrospective Analysis of Cross-Sectional Data From 2018 to 2021.

Brenda Abena Ampah, Douglas Aninng Opoku, Eugene Sackeya, Nana Kwame Ayisi-Boateng, Emmanuel Konadu, Mercy Addae, Phyllis Tawiah, Kofi Akohene Mensah

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Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Brenda Abena AmpahUniversity Hospital Kwame Nkrumah University of Science and Technology Kumasi Ghana.
Douglas Aninng OpokuUniversity Hospital Kwame Nkrumah University of Science and Technology Kumasi Ghana.ORCID https://orcid.org/0000-0003-2321-387X
Eugene SackeyaRegional Health Directorate Tamale Northern Region Ghana.
Nana Kwame Ayisi-BoatengUniversity Hospital Kwame Nkrumah University of Science and Technology Kumasi Ghana.ORCID https://orcid.org/0000-0002-0961-4434
Emmanuel KonaduUniversity Hospital Kwame Nkrumah University of Science and Technology Kumasi Ghana.
Mercy AddaeSchool of Public Health Kwame Nkrumah University of Science and Technology Kumasi Ghana.
Phyllis TawiahUniversity Hospital Kwame Nkrumah University of Science and Technology Kumasi Ghana.
Kofi Akohene MensahSchool of Public Health Kwame Nkrumah University of Science and Technology Kumasi Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: Over the years, disease classification has evolved from 10 classes to 2400 distinct diseases. The International List of Causes of Death became the name of the first standardized categorization of diseases. It was later extended to include coding for causes of morbidity and called the International Classification of Diseases (ICD). In sub-Saharan Africa, and in Ghana in particular, disease classification using ICD-11 has been limited. This study, therefore, aimed at profiling disease patterns in a student clinic at a Ghanaian university and to formally assess trends in disease incidence over time using count-based regression models. Methods: A retrospective review of clinical data was employed at the Students' Clinic of the Kwame Nkrumah University of Science and Technology in Kumasi, Ghana. The data were described using frequencies, percentages, mean, and standard deviation, where necessary. The trend analysis covered 2018-2021, and disease categories were ranked in descending order. Negative binomial regression with an offset term (log of total annual clinic attendances) was used to assess temporal trends in disease burden. Results: A total of 107,393 patient records were analyzed with a mean age of 22.01 ( ± 4.03) years and a female preponderance. Certain infections or parasitic diseases (30.96% in 2018, 27.39% in 2019, 22.40% in 2020 and 26.14% in 2021), respiratory conditions (20.07% in 2018, 18.2% in 2019, 14.49% in 2020 and 14.31% in 2021), and symptoms, signs or clinical findings not elsewhere classified (10.49% in 2018, 11.85% in 2019, 13.98% in 2020 and 12.58% in 2021) were the top three most common causes of morbidity at the clinic. Significant increases were observed for mental, behavioral or neurodevelopmental disorder (IRR = 1.50, 95% CI: 1.27-2.01), neoplasms (IRR = 1.22, 95% CI: 1.03-1.46), and endocrine, nutritional or metabolic diseases (IRR = 1.22, 95% CI: 1.08-1.39). Conclusion: Certain infections or parasitic diseases, respiratory conditions, and symptoms, signs, or clinical findings not elsewhere classified were common among students at the public university in Kumasi, Ghana. This provides essential data for public health and policy interventions.

Indexed as

disease patterndisease trendICD‐11students

Identifiers

PMID42016286
PMCPMC13092488

What Socratic holds

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.