Background. Most information on bone-joint (BJ)-tuberculosis is based on data from high-incidence areas. We conducted a nationwide register-based analysis of BJ-tuberculosis in Denmark from 1994 to 2011. Methods. We linked data from the national tuberculosis surveillance system on BJ-tuberculosis, hospital records, the Danish Hospital and Civil Registration System. Results. We identified 282 patients with BJ-tuberculosis, 3.6% of all tuberculosis cases (n = 7936). Spinal tuber- culosis was found in 153 of 282 patients (54.3%); 83.3% of all cases were immigrants. Danes were older and had higher Charlson comorbidity index scores than immigrants (P < .01). C-reactive protein and erythrocyte sedimentation rates were elevated in most cases. Median time to diagnosis after first hospital contact was 19.5 days for spinal tuberculosis and 28 days for other forms of BJ-tuberculosis (P = .01). Of patients with spinal tuberculosis, 54/133 (40.6%) had neurologic deficits at admission and 17.3% presented with cauda equina. Diagnosis was culture verified in 87%. (Resistance to any drug was found in 10.2%). Median time on antituberculous treatment for patients with spinal and other forms of BJ-tuberculosis was 9 months and 7 months, respectively (P < .01). Surgery was required in 44.4% patients with spinal tuberculosis and in 32.6% patients with other forms of BJ-tuberculosis (P = .04). Sequelae were reported in 57.5% of patients with spinal tuberculosis and 29.1% of patient with other forms of BJ-tuberculosis (P < .01). One-year mortality was 25.5% among Danes compared with 1.3% among immigrants (P < .01). Conclusions. BJ-tuberculosis was rare and seen mainly in younger immigrants in Denmark. More than half of cases were spinal tuberculosis, presenting with more severe symptoms and worse outcome, compared with other forms of BJ-tuberculosis.

Credible measures of disease incidence, trends and mortality can be obtained through surveillance using manual chart review, but this is both time-consuming and expensive. ICD-10 discharge diagnoses are used as surrogate markers of infection, but knowledge on the validity of infections in general is sparse. The aim of the study was to determine how well ICD-10 discharge diagnoses identify patients with community-acquired infections in a medical emergency department (ED), overall and related to sites of infection and patient characteristics. We manually reviewed 5977 patients admitted to a medical ED in a one-year period (September 2010-August 2011), to establish if they were hospitalised with community-acquired infection. Using the manual review as gold standard, we calculated the sensitivity, specificity, predictive values, and likelihood ratios of discharge diagnoses indicating infection. Two thousand five hundred eleven patients were identified with community-acquired infection according to chart review (42.0%, 95% confidence interval [95%CI]: 40.8–43.3%) compared to 2550 patients identified by ICD-10 diagnoses (42.8%, 95%CI: 41.6–44.1%). Sensitivity of the ICD-10 diagnoses was 79.9% (95%CI: 78.1–81.3%), specificity 83.9% (95%CI: 82.6–85.1%), positive likelihood ratio 4.95 (95%CI: 4.58–5.36) and negative likelihood ratio 0.24 (95%CI: 0.22–0.26). The two most common sites of infection, the lower respiratory tract and urinary tract, had positive likelihood ratios of 8.3 (95%CI: 7.5–9.2) and 11.3 (95%CI: 10.2–12.9) respectively. We identified significant variation in diagnostic validity related to age, comorbidity and disease severity. ICD-10 discharge diagnoses identify specific sites of infection with a high degree of validity, but only a moderate degree when identifying infections in general.

Introduction: We aimed to examine if severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) cycle quantification (C_q) value, as a surrogate for SARS-CoV-2 viral load, could predict hospitalisation and disease severity in adult patients with coronavirus disease 2019 (COVID-19). Methods: We performed a prospective cohort study of adult patients with PCR positive SARS-CoV-2 airway samples including all out-patients registered at the Department of Infectious Diseases, Odense University Hospital (OUH) March 9-March 17 2020, and all hospitalised patients at OUH March 10-April 21 2020. To identify associations between C_q-values and a) hospital admission and b) a severe outcome, logistic regression analyses were used to compute odds ratios (OR) and 95% Confidence Intervals (CI), adjusting for confounding factors (aOR). Results: We included 87 non-hospitalised and 82 hospitalised patients. The median baseline C_q-value was 25.5 (interquartile range 22.3–29.0). We found a significant association between increasing C_q-value and hospital-admission in univariate analysis (OR 1.11, 95% CI 1.04–1.19). However, this was due to an association between time from symptom onset to testing and C_q-values, and no association was found in the adjusted analysis (aOR 1.08, 95% CI 0.94–1.23). In hospitalised patients, a significant association between lower C_q-values and higher risk of severe disease was found (aOR 0.89, 95% CI 0.81–0.98), independent of timing of testing. Conclusions: SARS-CoV-2 PCR C_q-values in outpatients correlated with time after symptom onset, but was not a predictor of hospitalisation. However, in hospitalised patients lower C_q-values were associated with higher risk of severe disease.

Purpose: To examine the positive predictive value (PPV) of International Classification version 10 (ICD-10) diagnosis codes for Coronavirus disease 2019 (COVID-19). Patients and Methods: Medical record review of all patients assigned a diagnosis code of COVID-19 (DB342A or DB972A) at six Danish departments of infectious diseases from February 27 through May 4, 2020. Confirmed COVID-19 diagnosis was defined as either: 1) definite, a positive polymerase chain reaction (PCR) for severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) on a respiratory sample combined with symptoms suggestive of COVID-19: 2) probable, clinical presentation of COVID-19 without detection of SARS-CoV-2 and no alternative diagnoses considered more likely; or 3) possible, clinical presentation of COVID-19 without detection of SARS-CoV-2, and the patient was discharged or deceased before further investigations were carried out. We computed the PPV with 95% confidence intervals (CI) as the number of patients with confirmed (i.e., definite, probable, and possible) COVID-19 divided by the number of patients assigned a diagnosis code for COVID-19. Results: The study included 710 patients with a median age of 61 years (interquartile range [IQR] 47– 74) and 285/710 (40%) were female. COVID-19 was confirmed in 706/710 (99%) with 705/710 (99%) categorized as definite, 1/710 (0.1%) as probable, and 0 patients as possible COVID-19. The diagnosis was disproven in 4/710 (0.6%) patients who were hospitalized due to bacterial pneumonia (n = 2), influenza (n = 1), and urinary tract infection (n = 1). The overall PPV for COVID-19 was 99% (95% CI 99– 100) and remained consistently high among all subgroups including sex, age groups, calendar period, and stratified by diagnosis code and department of infectious diseases (range 97– 100%). Conclusion: The overall PPV of diagnosis codes for COVID-19 in Denmark was high and may be suitable for future registry-based prognosis studies of COVID-19.