scholarly journals Metformin-associated lactic acidosis exacerbated by acute kidney injury in an overseas traveler

2021 ◽  
Author(s):  
Ayano Hayashi ◽  
Takuya Ishimura ◽  
Hisashi Sugimoto ◽  
Hiroyuki Suzuki ◽  
Akihiro Hamasaki ◽  
...  

AbstractWe report the case of metformin-associated lactic acidosis (MALA) exacerbated by acute kidney injury (AKI) in a 65-year-old Asian American woman who was an overseas traveler. She had vomiting and diarrhea before arriving in Osaka, Japan, from the Philippines. She suffered from worsening respiratory distress, consciousness loss and anuria the day after coming to Japan. When she arrived at our emergency room via ambulance, she appeared to be in a state shock. Arterial blood gas analysis revealed severe lactic acidosis (pH 6.681, PO2 302 Torr under O2 supplementation, PCO2 15 Torr, HCO3−1.7 mmol/L, and lactate 17.00 mmol/L). She also had renal failure (BUN 108 mg/dL and serum creatinine 8.68 mg/dL) with hyperkalemia (6.1 mEq/L). We collected medical information from family members, and found her prescription medicines including metformin, diuretics and angiotensin-converting enzyme inhibitor (ACEI). We diagnosed her with MALA due to an unintended overdose of metformin resulting from acute kidney injury that can be induced by ACEI and diuretics in the volume-depleted condition. We immediately started hemodialysis therapy. Although she had a temporary cardiopulmonary arrest at the beginning of the treatment, her physical status was gradually improved and the severe acidemia resolved. On hospital day 4, she had urine and no longer needed hemodialysis therapy. On day 14, she was discharged and returned to the United States without noticeable sequelae. This is a case report of an overseas traveler who was successfully rescued through the collection of accurate medical information and understanding of the pathological condition.

2021 ◽  
Author(s):  
Steven L. Flamm ◽  
Kimberly Brown ◽  
Hani M. Wadei ◽  
Robert S. Brown ◽  
Marcelo Kugelmas ◽  
...  

2021 ◽  
Vol 10 (2) ◽  
pp. 168
Author(s):  
Anne-Lise Rolland ◽  
Anne-Sophie Garnier ◽  
Katy Meunier ◽  
Guillaume Drablier ◽  
Marie Briet

Background: Acute kidney injury (AKI) is a public health concern. Among the pathological situations leading to AKI, drugs are preventable factors but are still under-notified. We aimed to provide an overview of drug-induced AKI (DIAKI) using pharmacovigilance and medical administrative databases Methods: A query of the PMSI database (French Medical Information System Program) of adult inpatient hospital stays between 1 January 2017 and 31 December 2018 was performed using ICD-10 (International Classification of Diseases 10th revision) codes to identify AKI cases which were reviewed by a nephrologist and a pharmacovigilance expert to identify DIAKI cases. In parallel, DIAKIs notified in the French Pharmacovigilance Database (FPVDB) were collected. A capture-recapture method was performed to estimate the total number of DIAKIs. Results: The estimated total number of DIAKIs was 521 (95%CI 480; 563), representing 20.0% of all AKIs. The notification was at a rate of 12.9% (95%CI 10.0; 15.8). According to the KDIGO classification, 50.2% of the DIAKI cases were stage 1 and 49.8% stage 2 and 3. The mortality rate was 11.1% and 9.6% required hemodialysis. Conclusion: This study showed that drugs are involved in a significant proportion of patients developing AKI during a hospital stay and emphasizes the severity of DIAKI cases.


2018 ◽  
Vol 32 (2) ◽  
pp. 297-306 ◽  
Author(s):  
Paolo Greco ◽  
Giuseppe Regolisti ◽  
Umberto Maggiore ◽  
Elena Ferioli ◽  
Filippo Fani ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-2 ◽  
Author(s):  
Rishika Singh ◽  
Dilip R. Patel ◽  
Sherry Pejka

Rhabdomyolysis can occur because of multiple causes and account for 7% of all cases of acute kidney injury annually in the United States. Identification of specific cause can be difficult in many cases where multiple factors could potentially cause rhabdomyolysis. We present a case of 16-year-old male who had seizures and was given levetiracetam that resulted in rhabdomyolysis. This side effect has been rarely reported previously and like in our case diagnosis may be delayed.


2019 ◽  
Vol 9 (12) ◽  
pp. 933-941 ◽  
Author(s):  
Christina Bradshaw ◽  
Jialin Han ◽  
Glenn M. Chertow ◽  
Jin Long ◽  
Scott M. Sutherland ◽  
...  

2020 ◽  
Vol 86 (8) ◽  
pp. 950-954
Author(s):  
Andrew L. Drahos ◽  
Anthony M. Scott ◽  
Tracy J. Johns ◽  
Dennis W. Ashley

Background There is an opioid epidemic in the United States. With the increased concern of over-prescribing opioids, physicians are seeking alternative pain management strategies. The purpose of this study is to review the impact of instituting a multimodal analgesia (MMA) guideline on decreasing opioid use in trauma patients at a Level 1 trauma center. Methods In 2017, an MMA guideline was developed and included anti-inflammatories, muscle relaxants, neuropathic agents, and local analgesics in addition to opioids. Staff were educated and the guideline was implemented. A retrospective review of medications prescribed to patients admitted from 2016 through 2018 was performed. Patients admitted in 2016 served as the control group (before MMA). In 2018, all patients received multimodal pain therapy as standard practice, and served as the comparison group. Results A total of 10 340 patients were admitted to the trauma service from 2016 through 2018. There were 3013 and 3249 patients for review in 2016 and 2018, respectively. Total morphine milligram equivalents were 2 402 329 and 1 975 935 in 2016 and 2018, respectively, a 17.7% decrease ( P < .001). Concurrently, there was a statistically significant increase in the use of multimodal pain medications. A secondary endpoint was studied to evaluate for changes in acute kidney injury; there was not a statistically significant increase (0.56% versus 0.68%, P = .55). Discussion Implementation of an MMA guideline significantly reduced opioid use in trauma patients. The use of nonopioid MMA medications increased without an increased incidence of acute kidney injury.


2019 ◽  
Vol 58 (5) ◽  
pp. 375-382 ◽  
Author(s):  
Anthony Corchia ◽  
Alain Wynckel ◽  
Julien Journet ◽  
Julie Moussi Frances ◽  
Nihel Skandrani ◽  
...  

2020 ◽  
Vol 15 (11) ◽  
pp. 1557-1565 ◽  
Author(s):  
Kumardeep Chaudhary ◽  
Akhil Vaid ◽  
Áine Duffy ◽  
Ishan Paranjpe ◽  
Suraj Jaladanki ◽  
...  

Background and objectivesSepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records.Design, setting, participants, & measurementsWe used the Medical Information Mart for Intensive Care III database, which consists of electronic health record data from intensive care units in a tertiary care hospital in the United States. We included patients ≥18 years with sepsis who developed AKI within 48 hours of intensive care unit admission. We then used deep learning to utilize all available vital signs, laboratory measurements, and comorbidities to identify subphenotypes. Outcomes were mortality 28 days after AKI and dialysis requirement.ResultsWe identified 4001 patients with sepsis-associated AKI. We utilized 2546 combined features for K-means clustering, identifying three subphenotypes. Subphenotype 1 had 1443 patients, and subphenotype 2 had 1898 patients, whereas subphenotype 3 had 660 patients. Subphenotype 1 had the lowest proportion of liver disease and lowest Simplified Acute Physiology Score II scores compared with subphenotypes 2 and 3. The proportions of patients with CKD were similar between subphenotypes 1 and 3 (15%) but highest in subphenotype 2 (21%). Subphenotype 1 had lower median bilirubin levels, aspartate aminotransferase, and alanine aminotransferase compared with subphenotypes 2 and 3. Patients in subphenotype 1 also had lower median lactate, lactate dehydrogenase, and white blood cell count than patients in subphenotypes 2 and 3. Subphenotype 1 also had lower creatinine and BUN than subphenotypes 2 and 3. Dialysis requirement was lowest in subphenotype 1 (4% versus 7% [subphenotype 2] versus 26% [subphenotype 3]). The mortality 28 days after AKI was lowest in subphenotype 1 (23% versus 35% [subphenotype 2] versus 49% [subphenotype 3]). After adjustment, the adjusted odds ratio for mortality for subphenotype 3, with subphenotype 1 as a reference, was 1.9 (95% confidence interval, 1.5 to 2.4).ConclusionsUtilizing routinely collected laboratory variables, vital signs, and comorbidities, we were able to identify three distinct subphenotypes of sepsis-associated AKI with differing outcomes.


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