Journal of investigative medicine : the official publication of the American Federation for Clinical Research
-
Early studies have reported various electrolyte abnormalities at admission in patients with severe COVID-19. 104 out of 193 patients admitted to our institution presented with hypermagnesemia at presentation. It is believed this may be important in the evaluation of severe SARS-CoV-2 infections. This study evaluated the outcomes of hypermagnesemia in patients with COVID-19. ⋯ With age-adjusted logistic regression analysis hypermagnesemia was associated with mortality (p=0.007). This study demonstrates that hypermagnesemia is a significant marker of disease severity and adverse outcome in SARS-CoV-2 infections. We recommend serum magnesium be added to the panel of tests routinely ordered in evaluation of severe SARS-CoV-2 infections.
-
AI relates broadly to the science of developing computer systems to imitate human intelligence, thus allowing for the automation of tasks that would otherwise necessitate human cognition. Such technology has increasingly demonstrated capacity to outperform humans for functions relating to image recognition. Given the current lack of cost-effective confirmatory testing, accurate diagnosis and subsequent management depend on visual detection of characteristic findings during otoscope examination. The aim of this manuscript is to perform a comprehensive literature review and evaluate the potential application of artificial intelligence for the diagnosis of ear disease from otoscopic image analysis.
-
The ISARIC4C consortium developed and internally validated the 4C Score for prediction of mortality only in hospitalized patients. We aimed to assess the validity of the 4C Score in mortality prediction of patients with COVID-19 who had been home isolated or hospitalized. This retrospective cross-sectional study was performed after the first wave of COVID-19. ⋯ Other components of the model had non-significant predictions. In conclusion, the 4C Mortality Score has good sensitivity and specificity in early risk stratification and mortality prediction of patient with COVID-19. Within the model, only hypoxia, tachypnea, high BUN, and CRP were the independent mortality predictors with the possibility of overlooking other important predictors.
-
Septic arthritis is important to consider in any patient who presents with joint pain because it is a medical emergency with an 11% fatality rate. Diagnosis and treatment may improve prognosis; however, many patients do not regain full joint function. In patients with end-stage renal disease (ESRD), immune dysfunction due to uremia and chronic vascular access leads to increased risk of infection. ⋯ Significant risk factors for septic arthritis included history of joint disease, immune compromise (diabetes, HIV, cirrhosis), bacteremia and urinary tract infection. One of the four sequelae examined (joint replacement, amputation, osteomyelitis, Clostridioides difficile infection) occurred in 25% of septic arthritis cases. The high incidence of septic arthritis and the potential for serious sequelae in patients with ESRD suggest that physicians treating individuals with ESRD and joint pain/inflammation should maintain a high clinical suspicion for septic arthritis.
-
Comparative Study
Prospective predictive performance comparison between clinical gestalt and validated COVID-19 mortality scores.
Most COVID-19 mortality scores were developed at the beginning of the pandemic and clinicians now have more experience and evidence-based interventions. Therefore, we hypothesized that the predictive performance of COVID-19 mortality scores is now lower than originally reported. We aimed to prospectively evaluate the current predictive accuracy of six COVID-19 scores and compared it with the accuracy of clinical gestalt predictions. 200 patients with COVID-19 were enrolled in a tertiary hospital in Mexico City between September and December 2020. ⋯ Adjusting scores with locally derived likelihood ratios did not improve their performance; however, some scores outperformed clinical gestalt predictions when clinicians' confidence of prediction was <80%. Despite its subjective nature, clinical gestalt has relevant advantages in predicting COVID-19 clinical outcomes. The need and performance of most COVID-19 mortality scores need to be evaluated regularly.