Citations

Background: Thrombotic thrombocytopenic purpura (TTP) is a life-threatening hematologic emergency caused by ADAMTS13 deficiency, leading to microvascular thrombosis, haemolytic anaemia, thrombocytopenia, and end-organ damage. Neurological symptoms occur in up to 90% of cases and are frequently misdiagnosed as stroke. Prompt recognition and treatment reduce the mortality rate from over 90% to 10–20%. Case presentation: A 70-year-old woman with no significant medical history presented with acute aphasia and right-sided facial and upper extremity numbness. Five days prior, she had experienced fatigue, headache, and bruising. On admission, she had stable vitals with mild aphasia and purpuric ecchymoses noted on examination. Laboratory findings revealed haemolytic anaemia (haemoglobin 7.8 g/dl, lactate dehydrogenase 875 U/l, total bilirubin 2.4 mg/dl), thrombocytopenia (35 ×109/l), and unremarkable coagulation studies (partial thromboplastin time 30 sec, prothrombin time-international normalized ratio 1, fibrinogen 370 mg/dl, D-dimer 2.15 ng/ml). Peripheral smear showed no schistocytes but noted 2+spherocytes. Stroke was ruled out with brain magnetic resonance imaging/magnetic resonance angiography. Given the bicytopenia with possible haemolysis along with new neurological symptoms, TTP was considered in the differential diagnosis. A PLASMIC score of 5 suggested a high probability of TTP. Plasma exchange and corticosteroids were initiated within 5 hours of presentation. ADAMTS13 activity <1% confirmed the diagnosis 4 days after presentation. After five plasma exchange sessions, the patient’s platelet count normalized and neurologic deficits resolved by discharge. Conclusion: This case underscores the importance of considering TTP in stroke mimics, even in the absence of schistocytes, if clinical suspicion is high. Early recognition and initiation of treatment significantly improve patient outcomes.

Background: There is suspicion that estrogen may protect against atherosclerosis. Women who experience menarche earlier, and thus have earlier estrogen exposure, might develop atherosclerosis later. The relationship between menarche age and the onset of angina pectoris, a symptom of coronary artery disease, remains unknown. Goal: This study aims to find the correlation between menarche age and the onset age of angina pectoris, and the association between early menarche (onset of menarche ≤ 10 y/o) and early onset of angina pectoris (onset of angina pectoris ≤ 40 y/o). Methods: A cross-sectional study using a population from the 2017-2020 National Health and Nutrition Examination Survey (NHANES). The question collects self-reported data on onset of menarche and onset of angina pectoris. The relationship between menarche age and age in onset of angina pectoris was analyzed by linear and logistic regression analysis. Multivariate analysis adjusted for race, age, body mass index (BMI), smoking , diabetes mellitus (DM), hypertension, and dyslipidemia status. Results: Among 4,816 females who reported their menarche age, 88(1.8 %) have had an angina pectoris. The study involved 82 females who reported both the age of menarche and the age of onset of angina pectoris. The mean ± SD of the age at menarche and the age at onset of angina pectoris was 12.53 ± 1.79 y/o and 51.66 ± 15.16 y/o, respectively. The study found a significant association between the menarche age and the age at onset of angina pectoris. After adjusting for confounders, we found that every 1-year increase in the age of menarche will delay the onset of angina pectoris by 1.43 years, with a 95% CI of 0.01 to 2.86.(Table 1A,Graph 1A-1B) We also found that early menarche has a significantly increased risk 2.8 times (95%CI: 1.3, 6.2) of early onset of angina pectoris.After adjusting for confounders, the association became even stronger. The odds ratio (OR) increased to 3.3 (95%CI: 1.4, 8.0), indicating that women with early menarche were 3.3 times more likely to experience early angina pectoris compared to those with later menarche.(Table 2A) Conclusion: In contrast to our hypothesis, age at menarche is positively associated with onset of angina pectoris. The earlier onset of menarche is linked to the earlier onset of angina pectoris. We suspected that factors beyond estrogen levels may contribute to this unexpected finding. Additional studies are needed to examine the cause of this correlation.

An 18-year-old previously healthy Filipino male presented with abdominal pain, vomiting, dyspnoea and fever. Initial investigations revealed severe hepatosplenomegaly, pancytopaenia, elevated liver enzymes, coagulopathy and extremely high ferritin levels. Bone marrow biopsy confirmed an abnormal CD8+ T-cell population with haemophagocytosis. Extensive workup was performed, and he was ultimately diagnosed with haemophagocytic lymphohistiocytosis (HLH) secondary to Epstein-Barr virus-positive T-cell lymphoma of childhood (EBV-TCL), a rare and aggressive malignancy. Despite the initiation of modified dexamethasone, methotrexate, ifosfamide, L-asparaginase and etoposide (SMILE) chemotherapy along with high-dose glucocorticoids, the patient did not respond to the treatment and expired. This case underscores the critical importance of early recognition and prompt intervention in EBV-TCL-associated HLH which is a unique condition and a rare entity. The diagnosis of this entity can be particularly challenging, given its rapid progression and high mortality rate. Therefore, timely diagnosis and the initiation of appropriate therapy are essential for improving patient outcomes. General medicine providers play a key role in identifying warning signs to avoid delays in treatment initiation.

ABSTRACT Background Cognitive impairment (CI) is a critical complication in peritoneal dialysis (PD) patients, associated with decreased quality of life and increased hospitalization. Despite its significant impact, the prevalence, risk factors, and consequences of CI in PD patients are not well understood. We aimed to determine the prevalence, risk factors, and outcomes of CI in PD patients. Methods We performed systematic reviews in OVID Medline, Embase, and Cochrane databases until February 2024 to identify cross-sectional and cohort studies on prevalence of CI (identified by cognitive assessment scales) in PD patients. The Newcastle–Ottawa Scale was used to assess risk of bias. A pooled meta-analysis of CI prevalence in PD and a subgroup analysis comparing the risk of CI between PD and non-PD settings were performed using a random-effects model. Results A total of 19 studies were identified, involving 2882 PD patients. The pooled prevalence of CI in PD patients was 47.7% (95%CI: 35.8–59.9%). CI in patients undergoing PD appears to be associated with older age, female gender, lower levels of education, and is linked to higher rates of hospitalization and peritonitis, compared to those without CI. However, it is not associated with increased mortality. Compared to hemodialysis, PD showed a trend toward a lower risk of CI (OR 0.64, 95%CI 0.39–1.03; P = .068). Conclusion CI is highly prevalent and associated with several adverse clinical outcomes in PD patients. These findings could contribute to facilitate the development of screening and early intervention strategies to reduce the burden of disease in this population.

Background: Despite the prevalence and incidence of kidney stones progressively increasing worldwide, public awareness of this condition remains unclear. Understanding trends of awareness can assist healthcare professionals and policymakers in planning and implementing targeted health interventions. This study investigated online search interest in “kidney stone” by analyzing Google Trends, focusing on stationarity of the trends and predicting future trends. Methods: We performed time series analysis on worldwide Google monthly search data from January 2004 to November 2023. The Augmented Dickey–Fuller (ADF) test was used to assess the stationarity of the data, with a p-value below 0.05 indicating stationarity. Time series forecasting was performed using the autoregressive integrated moving average to predict future trends. Results: The highest search interest for “kidney stone” (score 100) was in August 2022, while the lowest was in December 2007 (score 36). As of November 2023, search interest remained high, at 92. The ADF test was significant (p = 0.023), confirming data stationarity. The time series forecasting projected continued high public interest, likely reflecting ongoing concern and awareness. Notably, diverse regions such as Iran, the Philippines, Ecuador, the United States, and Nepal showed significant interest, suggesting widespread awareness of nephrolithiasis. Conclusion: This study highlighted that “kidney stone” is a consistently relevant health issue globally. The increase and stationarity of search trends, the forecasted sustained interest, and diverse regional interest emphasize the need for collaborative research and educational initiatives. This study’s analysis serves as a valuable tool for shaping future healthcare policies and research directions in addressing nephrolithiasis related health challenges.

Accurate information regarding oxalate levels in foods is essential for managing patients with hyperoxaluria, oxalate nephropathy, or those susceptible to calcium oxalate stones. This study aimed to assess the reliability of chatbots in categorizing foods based on their oxalate content. We assessed the accuracy of ChatGPT-3.5, ChatGPT-4, Bard AI, and Bing Chat to classify dietary oxalate content per serving into low (<5 mg), moderate (5–8 mg), and high (>8 mg) oxalate content categories. A total of 539 food items were processed through each chatbot. The accuracy was compared between chatbots and stratified by dietary oxalate content categories. Bard AI had the highest accuracy of 84%, followed by Bing (60%), GPT-4 (52%), and GPT-3.5 (49%) (p < 0.001). There was a significant pairwise difference between chatbots, except between GPT-4 and GPT-3.5 (p = 0.30). The accuracy of all the chatbots decreased with a higher degree of dietary oxalate content categories but Bard remained having the highest accuracy, regardless of dietary oxalate content categories. There was considerable variation in the accuracy of AI chatbots for classifying dietary oxalate content. Bard AI consistently showed the highest accuracy, followed by Bing Chat, GPT-4, and GPT-3.5. These results underline the potential of AI in dietary management for at-risk patient groups and the need for enhancements in chatbot algorithms for clinical accuracy.