Acute Kidney Injury and Associated Factors in Intensive Care Units at a Tertiary Hospital in Northern Tanzania
Notice bibliographique
Résumé
BACKGROUND: Acute kidney injury (AKI) is a recognized complication in critically ill patients. The epidemiology of AKI varies worldwide, depending on the diagnostic criteria used and the setting. The International Society of Nephrology has called for a reduction in preventable deaths from AKI to zero by the year 2025. It is suspected that the majority of AKI cases are in limited-resource countries, but the true burden of AKI in these settings remains unknown. OBJECTIVE: We aimed to determine, using standardized KDIGO (Kidney Disease Improving Global Outcomes) criteria, the prevalence of AKI, associated factors, and clinical characteristics of adult (≥18 years) patients admitted to intensive care units (ICUs) at a tertiary hospital in Tanzania. DESIGN: Prospective observational study from November 2017 to May 2018. METHODS: In all, 320 patients admitted to medical and surgical ICUs were consecutively enrolled. Baseline, clinical, and laboratory data were collected on admission and during their ICU stay. Serum creatinine and urine output were measured, and KDIGO criteria were used to determine AKI status. RESULTS: More than half (55.3%) of ICU patients were diagnosed with AKI. Of these, 80% were diagnosed within 24 hours of admission. Acute kidney injury stage 3 accounted for 35% of patients with AKI. Patients with AKI were older, more likely to have cardiovascular comorbidities, and with higher baseline serum levels of creatinine, potassium, universal vital assessment admission scores, and total white cell count ≥12. Sepsis (odds ratio [OR] = 3.81; confidence interval [CI] = 1.21-11.99), diabetes (OR = 2.54; CI = 1.24-5.17), and use of vasopressors (OR = 3.78; CI = 1.36-10.54) were independently associated with AKI in multivariable logistic regression. Less than one-third of those who needed dialysis received it. There was 100% mortality in those who needed dialysis but did not receive (n = 19). LIMITATIONS: Being based at a referral center, the findings do not represent the true burden of AKI in the community. CONCLUSION: The prevalence of AKI was very high in ICUs in Northern Tanzania. The majority of patients presented with AKI and were severely ill, suggesting late presentation, underscoring the importance of prioritizing prevention and early intervention. Further studies should explore locally suitable AKI risk scores that could be used to identify high-risk patients in the community health centers from where patients are referred.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».