Delayed Diagnosis of Charcot Foot: A Systematic Review

This study aims to examine the duration and rate of delayed diagnosis in Charcot foot. We systematically reviewed articles published in Medline, SCOPUS, and Cumulative Index of Nursing and Allied Health Literature to identify articles discussing delayed or misdiagnosis of Charcot foot. Random-effects models were generated to determine the average time from symptom onset to correct diagnosis (diagnostic delay duration) and proportion of patients misdiagnosed prior to being correctly diagnosed (delayed diagnosis rate). Our search identified 142 articles, 7 of which are included in this review. The review found that 53.2% of cases of Charcot osteoarthropathy experienced a delay in diagnosis (95% CI: 28.9%-77.4%). Overall, the duration of diagnostic delay was determined to be 86.9 days (95% CI: 10.5-162.1). We found that patients with Charcot foot experienced prolonged delays from symptom onset to correct diagnosis, and a majority of patients are misdiagnosed. These delays in diagnosis contribute to worse patient outcomes.

Predicting in-hospital mortality after traumatic brain injury: External validation of CRASH-basic and IMPACT-core in the national trauma data bank

BACKGROUND

Traumatic brain injury (TBI) prognostic prediction models offer value to individualized treatment planning, systematic outcome assessments and clinical research design but require continuous external validation to ensure generalizability to different settings. The Corticosteroid Randomization After Significant Head Injury (CRASH) and International Mission on Prognosis and Analysis on Clinical Trials in TBI (IMPACT) models are widely available but lack robust assessments of performance in a current national sample of patients. The purpose of this study is to assess the performance of the CRASH-Basic and IMPACT-Core models in predicting in-hospital mortality using a nationwide retrospective cohort from the National Trauma Data Bank (NTDB).

METHODS

The 2016 NTDB was used to analyze an adult cohort with moderate-severe TBI (Glasgow Coma Scale [GCS] ≤ 12, head Abbreviated Injury Scale of 2-6). Observed in-hospital mortality or discharge to hospice was compared to the CRASH-Basic and IMPACT-Core models' predicted probability of 14-day or 6-month mortality, respectively. Performance measures included discrimination (area under the receiver operating characteristic curve [AUC]) and calibration (calibration plots and Brier scores). Further sensitivity analysis included patients with GCS ≤ 14 and considered patients discharged to hospice to be alive at 14-days.

RESULTS

A total of 26,228 patients were included in this study. Both models demonstrated good ability in differentiating between patients who died and those who survived, with IMPACT demonstrating a marginally greater AUC (0.863; 95% CI: 0.858 - 0.867) than CRASH (0.858; 0.854 - 0.863); p < 0.001. On calibration, IMPACT overpredicted at lower scores and underpredicted at higher scores but had good calibration-in-the-large (indicating no systemic over/underprediction), while CRASH consistently underpredicted mortality. Brier scores were similar (0.152 for IMPACT, 0.162 for CRASH; p < 0.001). Both models showed slight improvement in performance when including patients with GCS ≤ 14.

CONCLUSION

Both CRASH-Basic and IMPACT-Core accurately predict in-hospital mortality following moderate-severe TBI, and IMPACT-Core performs well beyond its original GCS cut-off of 12, indicating potential utility for mild TBI (GCS 13-15). By demonstrating validity in the NTDB, these models appear generalizable to new data and offer value to current practice in diverse settings as well as to large-scale research design.