INTRODUCTIONAnti-thyroid antibodies are associated with extra-thyroid diseases such as Graves' ophthalmopathy and Hashimoto's encephalopathy. Some evidence suggests that anti-thyroid antibodies are also associated with depression. Interleukin (IL)-17 appears to play an important role in autoimmune thyroid disease. This study investigated whether specific thyroid autoantibodies and IL-17 distinguished persons with depression from non-depressed controls.

MATERIALS AND METHODSForty-seven adult females with non-psychotic, current major depressive disorder and 80 healthy female controls participated in this study. Thyroid peroxidase antibodies, thyroglobulin antibodies, thyroid-stimulating hormone (TSH) receptor antibodies, free T3 and T4, TSH and IL-17 were measured from the serum. Measurements were repeated to assess test-retest reliability. Receiver operating characteristic (ROC) curves were used to estimate discriminatory values of the measurements. Differences between groups and associations between the clinical and biochemical assessments were analysed.

RESULTSMedian TSH receptor antibody concentration was significantly higher in the depressed than control group (P <0.001). Area under the ROC curve was 0.80 (95% CI, 0.73 to 0.88). Higher TSH receptor antibody titres were associated with greater depression severity scores (r = 0.33, P <0.05). IL-17 levels were not associated with TSH receptor antibody levels or depression severity scores. Thyroid function and other thyroid autoantibodies were not associated with depression severity.

CONCLUSIONTSH receptor antibodies might be a biomarker of immune dysfunction in depression.

Adult ; Autoantibodies ; blood ; Biomarkers ; blood ; Depressive Disorder, Major ; diagnosis ; immunology ; Female ; Humans ; Immunoglobulins, Thyroid-Stimulating ; blood ; Interleukin-17 ; blood ; Middle Aged ; Psychiatric Status Rating Scales ; ROC Curve ; Statistics as Topic ; Thyroid Gland ; immunology

INTRODUCTIONMedication discrepancies and poor documentation of medication changes (e.g. lack of justification for medication change) in physician discharge summaries can lead to preventable medication errors and adverse outcomes. This study aimed to identify and characterise discrepancies between preadmission and discharge medication lists, to identify associated risk factors, and in cases of intentional medication discrepancies, to determine the adequacy of the physician discharge summaries in documenting reasons for the changes.

METHODSA retrospective clinical record review of 150 consecutive elderly patients was done to estimate the number of medication discrepancies between preadmission and discharge medication lists. The two lists were compared for discrepancies (addition, omission or duplication of medications, and/or a change in dosage, frequency or formulation of medication). The patients' clinical records and physician discharge summaries were reviewed to determine whether the discrepancies found were intentional or unintentional. Physician discharge summaries were reviewed to determine if the physicians endorsed and documented reasons for all intentional medication changes.

RESULTSA total of 279 medication discrepancies were identified, of which 42 were unintentional medication discrepancies (35 were related to omission/addition of a medication and seven were related to a change in medication dosage/frequency) and 237 were documented intentional discrepancies. Omission of the baseline medication was the most common unintentional discrepancy. No reasons were provided in the physician discharge summaries for 54 (22.8%) of the intentional discrepancies.

CONCLUSIONUnintentional medication discrepancies are a common occurrence at hospital discharge. Physician discharge summaries often do not have adequate information on the reasons for medication changes.

Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Medical Records ; Medication Errors ; prevention & control ; statistics & numerical data ; Medication Reconciliation ; statistics & numerical data ; Patient Admission ; Patient Discharge ; Retrospective Studies ; Risk Factors ; Singapore ; Tertiary Care Centers ; Treatment Outcome