Evidence map›Paper›PMID 42856520›Full record

ArticleFrontiers in endocrinology2026

Catamenial diabetic ketoacidosis in a rural area of Kananga, Democratic Republic of the Congo: a case report.

John K Bukasa, Branly K Mbunga, Bedel Lukoki-Beudin, Guy Kikuni Makinga, Manasse Bukasa, Isis Kalambayi Kapinga, Claude Mbuyi, Daniel Lushimba, Eric Ditu Tshitshi, Patrick Ngoy Kalambayi and 2 more

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Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

John K BukasaDepartment of Endocrinology, University Hospital Center of Liege, University of Liege, Liege, Belgium.
Branly K MbungaDepartment of Nutrition, School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of Congo.
Bedel Lukoki-BeudinNephrology unit, Department of Internal Medicine, University Clinics of Kinshasa, Kinshasa, Democratic Republic of Congo.
Guy Kikuni MakingaCommunity Health Service, Makala General Hospital, Kinshasa, Democratic Republic of Congo.
Manasse BukasaDepartment of Endocrinology, Manasse Endocrinology Clinics, Kananga, Democratic Republic of Congo.
Isis Kalambayi KapingaDepartment of Endocrinology, Manasse Endocrinology Clinics, Kananga, Democratic Republic of Congo.
Claude MbuyiDepartment of Internal Medicine, Notre Dame University of Kasayi, Kananga, Democratic Republic of Congo.
Daniel LushimbaDepartment of Internal Medicine, Notre Dame University of Kasayi, Kananga, Democratic Republic of Congo.
Eric Ditu TshitshiMedical Imaging and Diagnosis Unit, Nuclear Medicine Section, CGEA/CREN-K, Kinshasa, Democratic Republic of Congo.
Patrick Ngoy KalambayiMedical Imaging and Diagnosis Unit, Nuclear Medicine Section, CGEA/CREN-K, Kinshasa, Democratic Republic of Congo.
Ariel MakembiUniversity Hospital Center Of Guiana/Saint-Laurent, Cayenne, France.
Ayrton BangoloDepartment of Hematology and oncology, John Theurer Cancer Center, Hackensack, NJ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic ketoacidosis (DKA) is a life-threatening acute complication of diabetes mellitus most commonly triggered by infection, metabolic stress, or inadequate insulin therapy. We report an unusual case of a young woman with type 1 diabetes who experienced recurrent episodes of ketoacidosis during the premenstrual period, suggesting a catamenial form of DKA. This case highlights the importance of considering hormonal fluctuations related to the menstrual cycle in diabetes management and in identifying factors of imbalance. The patient presented with abdominal pain, severe fatigue, and polyuria-polydipsia, with a blood glucose level of 560 mg/dL, beta-hydroxybuturate of 3.6 mmol/L, potassium of 2.4 mmol/L and pH of 7.24. Inflammatory markers were absent and no usual precipitating factors were identified. Management included intravenous insulin therapy, rehydration, potassium supplementation, and transition to basal-bolus insulin. Part of the serum was sent to France for diabetes typing, confirming type 1 diabetes and additional assays. The patient reported that these episodes occurred 3 to 4 days before menstruation. This case underscores the need to consider hormonal fluctuations related to the menstrual cycle in diabetes management, particularly in a resource-limited settings, to adjust insulin strategies and prevent serious complications.

Indexed as

Diabetes Mellitus, Type 1Diabetic KetoacidosisMenstrual CycleAdultBlood GlucoseDemocratic Republic of the CongoFemaleHumansInsulinRural PopulationBlood GlucoseInsulincatamenialDemocratic Republic of Congodiabetic ketoacidosishormonal cyclerural region

Identifiers

PMID42856520
PMCPMC13649377

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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 OpenQuestion graph.