Nocturnal Oxygen Desaturation Index Correlates with Respiratory Depression in Post-Surgical Patients Receiving Opioids - A Post-Hoc Analysis from the Prediction of Opioid-Induced Respiratory Depression in Patients Monitored by Capnography (PRODIGY) Study.

Purpose: Postoperative monitoring of respiratory status on general care wards typically consists of intermittent checks of oxyhemoglobin saturation and respiratory rate, allowing substantial unmonitored time for severe opioid induced respiratory depression (RD) to develop unnoticed. Oxygen desaturation index (ODI) can be computed solely by continuous pulse oximetry monitoring. In this post-hoc analysis, we evaluate whether nocturnal ODI correlates with RD. Patients and Methods: The PRODIGY trial (NCT02811302) was a multinational study conducted where adult patients receiving parenteral opioids on the general care floor were continuously monitored by blinded pulse oximetry and capnography monitoring to detect episodes of RD. An RD episode was defined as: respiratory rate ≤5 breaths/min (bpm) for ≥3 minutes, oxygen saturation (SpO2) ≤85% for ≥3 minutes, end-tidal carbon dioxide (EtCO2) ≤15 or ≥60 mm Hg for ≥3 minutes, apnea episode lasting >30 seconds, or any respiratory opioid-related adverse event. Data were used to calculate nocturnal (00:00 ─ 06:00) ODI4% based on desaturation episodes (4% decrease from mean oxyhemoglobin saturation in the past 120 seconds, lasting ≥10 seconds). Continuous monitoring began after a patient received parenteral opioids, allowing identification of potential RD and ODI4% episodes during opioid therapy. The average number of ODI4% episodes (≥1, ≥5, ≥10, ≥15 episodes/hour) were analyzed. Logistic regression and area under the receiver operating characteristic curve (AUC) were computed. Results: A final cohort of 1072 (out of 1335) patients had sufficient data, with 76% (N=817/1072) having ≥1 episode of ODI4%. Multivariable logistic regression showed that ODI4% was strongly associated with RD, with greater risk for higher ODI4% scores: ≥5 episodes/hour odds ratio 2.59 (95% CI 1.72-3.89, p<0.0001); ≥10 episodes/hour 3.39 (95% CI 1.80-6.39, p=0.0002); ≥15 episodes/hour 4.71 (95% CI 1.93-11.47, p=0.0006).There was no significant association between ODI4% and respiratory adverse events. Conclusion: Nocturnal ODI4% was highly correlated with RD among hospitalized patients receiving parenteral opioids. Patients with a high ODI4%, especially with ≥15 episodes/hour, are more likely to experience RD and should be evaluated for the need of closer monitoring after opioid administration.

The neglected perioperative population of undiagnosed diabetics - a retrospective cohort study.

BACKGROUND: Diabetes is known to increase morbidity and 30-day mortality in adults undergoing non-cardiac surgery, but longer term outcomes are less studied. This study was done to explore how undiagnosed and known diabetes affect 30-day and one-year morbidity and mortality outcomes. The secondary aim was to study the prevalence of undiagnosed diabetics in our perioperative Asian surgical population. METHODS: A retrospective cohort study of 2106 patients aged > 45 years undergoing non-cardiac surgery in a single tertiary hospital was performed. Undiagnosed diabetics were identified (HbA1c ≥6.5% or fasting blood glucose ≥126 mg/dL) and relevant demographic, clinical and surgical data were analyzed to elicit the relationship to adverse outcomes. Univariate analysis was first performed to identify significant variables with p-values ≤0.1, which were then analyzed using multiple logistic regression to calculate the adjusted odds ratio. RESULTS: The prevalence of undiagnosed diabetes was 7.4%. The mean and median HbA1c of known diabetics were 7.9 and 7.5%, while the mean and median HbA1c for undiagnosed diabetics were 7.2 and 6.8% respectively. 36.4% of known diabetics and 20.5% of undiagnosed diabetics respectively had a random blood glucose > 200 mg/dL. Undiagnosed diabetics had a three-fold increase in 1-year mortality compared to non-diabetics (adjusted OR 3.46(1.80-6.49) p < 0.001) but this relationship was not significant between known and non-diabetics. Compared to non-diabetics, known diabetics were at increased risks of new-onset atrial fibrillation (aOR 2.48(1.01-6.25) p = 0.047), infection (aOR 1.49(1.07-2.07) p = 0.017), 30-day readmission (aOR 1.62(1.17-2.25) p = 0.004) and 30-day mortality (aOR 3.11(1.16-8.56) p = 0.025). CONCLUSIONS: Although undiagnosed diabetics have biochemically less severe disease compared to known diabetics at the point of testing, they are at a one-year mortality disadvantage which is not seen among known diabetics. This worrying trend highlights the importance of identifying and treating diabetes. Congruent to previous studies, known diabetics have higher morbidity and 30-day mortality compared to non-diabetics.

Factors predicting one-year post-surgical mortality amongst older Asian patients undergoing moderate to major non-cardiac surgery - a retrospective cohort study.

BACKGROUND: While short-term perioperative outcomes have been well studied in Western surgical populations, the aim of this study is to look at the one-year perioperative mortality and its associated factors in an Asian surgical population after non-cardiac surgery. METHODS: A retrospective cohort study of 2163 patients aged above 45 undergoing non-cardiac surgery in a university-affiliated tertiary hospital from January to July 2015 was performed. Relevant demographic, clinical and surgical data were analysed to elicit their relationship to mortality at one year after surgery. A univariate analysis was first performed to identify significant variables with p-values ≤ 0.2, which were then analysed using Firth multiple logistic regression to calculate the adjusted odds ratio. RESULTS: The one-year mortality in our surgical population was 5.9%. The significant factors that increased one-year mortality include smoking (adjusted OR 2.17 (1.02-4.45), p = 0.044), anaemia (adjusted OR 1.32 (1.16-1.47), p < 0.001, for every 1 g/dL drop in haemoglobin level), lower BMI (adjusted OR 0.93 (0.87-0.98), p = 0.005, for every 1 point increase in BMI), Malay and Indian ethnicity (adjusted OR 2.68 (1.53-4.65), p = 0.001), peripheral vascular disease (adjusted OR 4.21 (1.62-10.38), p = 0.004), advanced age (adjusted OR 1.04 (1.01-1.06), p = 0.004, for every one year increase in age), emergency surgery (adjusted OR 2.26 (1.29-3.15), p = 0.005) and malignancy (adjusted OR 3.20 (1.85-5.52), p < 0.001). CONCLUSIONS: Our study shows that modifiable risk factors such as malnutrition, anaemia and smoking which affect short term mortality extend beyond the immediate perioperative period into longer term outcomes. Identification and optimization of this subset of patients are therefore vital. Further similar large studies should be done to develop a risk scoring system for post-operative long-term outcomes. This would aid clinicians in risk stratification, counselling and surgical planning, which will help in patients' decision making and care planning.