Assessment of quality of life in IPF Patients: a multicenter observational study.

AIM: This study aimed to examine how dyspnea, cough, sleep disruption, anxiety, depression, and physiological factors affect the quality of life in newly diagnosed, untreated IPF patients. METHODS: This study is a multicenter observational study. Patients not receiving antifibrotic treatment were included. To assess patients' quality of life, Leicester Cough Questionnaire (LCQ), St. George's Respiratory Questionnaire (SGRQ), Short Form-36 (SF-36), Hospital Anxiety and Depression Scale (HADS), Borg Dyspnea Index (BDI), Modified Medical Research Council Dyspnea Scale (MMRC) score, Composite Physiological Index (CPI), Gender Age and physiology (GAP) score, and Pittsburgh Sleep Quality Index (PSQI) were administered. RESULTS: Among 88 patients (mean age: 67.6±8.5 years), 81.9% were diagnosed with IPF through HRCT, 14.8% through surgery, and 3.4% via cryobiopsy. The average disease duration was 2.2±2.9 years. Over 50% experienced moderate to severe depression, and 40% had moderate to severe anxiety. In the IPF group, 13.6% had possible usual interstitial pneumonia (UIP), and 81.8% had definite UIP pattern. No significant differences were found between UIP groups in various scores. Anxiety and depression correlated negatively with respiratory function and positively with MMRC score and BDI. Sleep quality scores had similar correlations. Patients with good sleep quality had better respiratory parameters (p=0.013), lower MMRC (p=0.004), BDI (p=0.026), and CPI (p=0.047). -Conclusion: A notable number of IPF patients in follow-up show symptoms of anxiety and depression. Moreover, declining respiratory function not only diminishes sleep quality but also elevates dyspnea scores.

Comparison of Pulse Rate Variability and Heart Rate Variability for Hypoglycemia Syndrome.

BACKGROUND: Heart rate variability (HRV) is a signal obtained from RR intervals of electrocardiography (ECG) signals to evaluate the balance between the sympathetic nervous system and the parasympathetic nervous system; not only HRV but also pulse rate variability (PRV) extracted from finger pulse plethysmography (PPG) can reflect irregularities that may occur in heart rate and control procedures. OBJECTIVES: The purpose of this study is to compare the HRV and PRV during hypoglycemia in order to evaluate the features that computed from PRV that can be used in detection of hypoglycemia. METHODS: To this end, PRV and HRV of 10 patients who required testing with insulin-induced hypoglycemia (IIHT) in Clinics of Endocrinology and Metabolism Diseases of Bezm-i Alem University (Istanbul, Turkey), were obtained. The recordings were done at three stages: prior to IIHT, during the IIHT, and after the IIHT. We used Bland-Altman analysis for comparing the parameters and to evaluate the correlation between HRV and PRV if exists. RESULTS: Significant correlation (r > 0.90, p < 0.05) and close agreement were found between HRV and PRV for mean intervals, the root-mean square of the difference of successive intervals, standard deviation of successive intervals and the ratio of the low-to-high frequency power. CONCLUSIONS: In conclusion, all the features computed from PRV and HRV have close agreement and correlation according to Bland-Altman analyses' results and features computed from PRV can be used in detection of hypoglycemia.