Few interventions are known to reduce the incidence of respiratory failure that occurs following elective surgery (postoperative respiratory failure; PRF). We previously reported risk factors ...associated with PRF that occurs within the first 5 days after elective surgery (early PRF; E-PRF); however, PRF that occurs six or more days after elective surgery (late PRF; L-PRF) likely represents a different entity. We hypothesized that L-PRF would be associated with worse outcomes and different risk factors than E-PRF.
This was a retrospective matched case-control study of 59,073 consecutive adult patients admitted for elective non-cardiac and non-pulmonary surgical procedures at one of five University of California academic medical centers between October 2012 and September 2015. We identified patients with L-PRF, confirmed by surgeon and intensivist subject matter expert review, and matched them 1:1 to patients who did not develop PRF (No-PRF) based on hospital, age, and surgical procedure. We then analyzed risk factors and outcomes associated with L-PRF compared to E-PRF and No-PRF.
Among 95 patients with L-PRF, 50.5% were female, 71.6% white, 27.4% Hispanic, and 53.7% Medicare recipients; the median age was 63 years (IQR 56, 70). Compared to 95 matched patients with No-PRF and 319 patients who developed E-PRF, L-PRF was associated with higher morbidity and mortality, longer hospital and intensive care unit length of stay, and increased costs. Compared to No-PRF, factors associated with L-PRF included: preexisiting neurologic disease (OR 4.36, 95% CI 1.81-10.46), anesthesia duration per hour (OR 1.22, 95% CI 1.04-1.44), and maximum intraoperative peak inspiratory pressure per cm H
0 (OR 1.14, 95% CI 1.06-1.22).
We identified that pre-existing neurologic disease, longer duration of anesthesia, and greater maximum intraoperative peak inspiratory pressures were associated with respiratory failure that developed six or more days after elective surgery in adult patients (L-PRF). Interventions targeting these factors may be worthy of future evaluation.
Postoperative respiratory failure is the most common serious postoperative pulmonary complication, yet little is known about factors that can reduce its incidence. We sought to elucidate modifiable ...factors associated with respiratory failure that developed within the first 5 d after an elective operation.
Matched case-control study of adults who had an operation at five academic medical centers between October 1, 2012 and September 30, 2015. Cases were identified using administrative data and confirmed via chart review by critical care clinicians. Controls were matched 1:1 to cases based on hospital, age, and surgical procedure.
Our total sample (n = 638) was 56.4% female, 71.3% white, and had a median age of 62 y (interquartile range 51, 70). Factors associated with early postoperative respiratory failure included male gender (odds ratio OR 1.72, 95% confidence interval CI 1.12-2.63), American Society of Anesthesiologists class III or greater (OR 2.85, 95% CI 1.74-4.66), greater number of preexisting comorbidities (OR 1.14, 95% CI 1.004-1.30), increased operative duration (OR 1.14, 95% CI 1.06-1.22), increased intraoperative positive end-expiratory pressure (OR 1.23, 95% CI 1.13-1.35) and tidal volume (OR 1.13, 95% CI 1.004-1.27), and greater net fluid balance at 24 h (OR 1.17, 95% CI 1.07-1.28).
We found greater intraoperative ventilator volume and pressure and 24-h fluid balance to be potentially modifiable factors associated with developing early postoperative respiratory failure. Further studies are warranted to independently verify these risk factors, explore their role in development of early postoperative respiratory failure, and potentially evaluate targeted interventions.
•Postoperative respiratory failure is a common and serious complication.•This multisite, matched case-control study (n = 638) explored risk factors.•Patient risk factors included male gender and number of comorbidities.•Intraoperative risk factors include increased ventilator volume and pressure.•Perioperative risk factors included positive 24-hour fluid balance.
Accurately measuring the risk of pressure injury remains the most important step for effective prevention and intervention. Time-dependent risk factors for pressure injury development in the adult ...intensive care unit setting are not well understood.
To develop and validate a dynamic risk prediction model to estimate the risk of developing a hospital-acquired pressure injury among adult ICU patients.
ICU admission data were split into training and validation sets. With death as a competing event, both static and dynamic Fine-Gray models were developed to predict hospital-acquired pressure injury development less than 24, 72, and 168 hours postadmission. Model performance was evaluated using Wolbers' concordance index, Brier score, net reclassification improvement, and integrated discrimination improvement.
We performed a retrospective cohort study of ICU patients in a tertiary care hospital located in San Francisco, CA, from November 2013 to August 2017.
Data were extracted from electronic medical records of 18,019 ICU patients (age ≥ 18 yr; 21,220 encounters). Record of hospital-acquired pressure injury data was captured in our institution's incident reporting system. The information is periodically reviewed by our wound care team. Presence of hospital-acquired pressure injury during an encounter and hospital-acquired pressure injury diagnosis date were provided.
The dynamic model predicting hospital-acquired pressure injury more than 24 hours postadmission, including predictors age, body mass index, lactate serum, Braden scale score, and use of vasopressor and antifungal medications, had adequate discrimination ability within 6 days from time of prediction (
= 0.73). All dynamic models produced more accurate risk estimates than static models within 26 days postadmission. There were no significant differences in Brier scores between dynamic and static models.
A dynamic risk prediction model predicting hospital-acquired pressure injury development less than 24 hours postadmission in ICU patients for up to 7 days postadmission was developed and validated using a large dataset of clinical variables readily available in the electronic medical record.
Postoperative respiratory failure (PRF) is associated with increased hospital charges and worse patient outcomes. Reliable prediction models can help to guide postoperative planning to optimize care, ...to guide resource allocation, and to foster shared decision-making with patients.
Can a predictive model be developed to accurately identify patients at high risk of PRF?
In this single-site proof-of-concept study, we used structured query language to extract, transform, and load electronic health record data from 23,999 consecutive adult patients admitted for elective surgery (2014-2021). Our primary outcome was PRF, defined as mechanical ventilation after surgery of > 48 h. Predictors of interest included demographics, comorbidities, and intraoperative factors. We used logistic regression to build a predictive model and the least absolute shrinkage and selection operator procedure to select variables and to estimate model coefficients. We evaluated model performance using optimism-corrected area under the receiver operating curve and area under the precision-recall curve and calculated sensitivity, specificity, positive and negative predictive values, and Brier scores.
Two hundred twenty-five patients (0.94%) demonstrated PRF. The 18-variable predictive model included: operations on the cardiovascular, nervous, digestive, urinary, or musculoskeletal system; surgical specialty orthopedic (nonspine); Medicare or Medicaid (as the primary payer); race unknown; American Society of Anesthesiologists class ≥ III; BMI of 30 to 34.9 kg/m
; anesthesia duration (per hour); net fluid at end of the operation (per liter); median intraoperative FIO
, end title CO
, heart rate, and tidal volume; and intraoperative vasopressor medications. The optimism-corrected area under the receiver operating curve was 0.835 (95% CI,0.808-0.862) and the area under the precision-recall curve was 0.156 (95% CI, 0.105-0.203).
This single-center proof-of-concept study demonstrated that a structured query language extract, transform, and load process, based on readily available patient and intraoperative variables, can be used to develop a prediction model for PRF. This PRF prediction model is scalable for multicenter research. Clinical applications include decision support to guide postoperative level of care admission and treatment decisions.
To compare Descemet membrane endothelial keratoplasty (DMEK) outcomes using nondiabetic grafts in diabetic and nondiabetic recipients.
All eyes that underwent DMEK between February 2013 and October ...2016 (follow-up ≥3 months, without prior keratoplasty) were included. Recipients were divided into diabetic (insulin dependent IDDM or noninsulin dependent NIDDM) and nondiabetic groups. Main outcome measures included postoperative visual acuity, rebubble procedure rates, and graft failure rates.
Of 334 eyes (243 subjects) included for analysis, 63 eyes (18.8%) were from diabetic recipients. At each timepoint, best-corrected visual acuity trended lower for IDDM recipients compared to NIDDM and nondiabetic recipients. There were no statistically significant differences in rebubble rates of diabetic compared to nondiabetic recipients (20.6% vs. 12.9%, p = 0.17), or IDDM compared to nondiabetic recipients (27.3% vs. 12.9%, p = 0.08; hazard ratio 2.26). Overall, 13 grafts (3.9%) failed (mean follow-up, 565 days; range, 90-1293 days). Graft failures did not differ between diabetic and nondiabetic recipients (4.0% vs. 4.9%, p = 0.15) regardless of subgroup (p = 0.36).
DMEK provides excellent outcomes for patients with and without diabetes. DMEK outcomes were excellent with improvements in visual acuity and low rates of graft failure. Our findings were unable to determine differences between rebubble procedure rates but do emphasize the need for further research using stratified groups based on diabetes severity.
Using small-molecule donor (SMD) semiconductors in organic photovoltaics (OPVs) has historically afforded lower power conversion efficiencies (PCEs) than their polymeric counterparts. The PCE ...difference is attributed to shorter conjugated backbones, resulting in reduced intermolecular interactions. Here, a new pair of SMDs is synthesized based on the diketopyrrolopyrrole–benzodithiophene–diketopyrrolopyrrole (BDT-DPP2) skeleton but having fluorinated and fluorine-free aromatic side-chain substituents. Ternary OPVs having varied ratios of the two SMDs with PC61BM as the acceptor exhibit tunable open-circuit voltages (V ocs) between 0.833 and 0.944 V due to a fluorination-induced shift in energy levels and the electronic “alloy” formed from the miscibility of the two SMDs. A 15% increase in PCE is observed at the optimal ternary SMD ratio, with the short-circuit current density (J sc) significantly increased to 9.18 mA/cm2. The origin of J sc enhancement is analyzed via charge generation, transport, and diffuse reflectance measurements, and is attributed to increased optical absorption arising from a maximum in film crystallinity at this SMD ratio, observed by grazing incidence wide-angle X-ray scattering.
We assess the importance and robustness of cluster analysis and latent class analysis as methods to account for unobserved heterogeneity. We provide a critique and comparison of both methods in the ...context of measuring environmental attitudes and a contingent valuation study involving endangered species. We find strong evidence of robustness for these methods: group characterization and assignment of individuals to groups are similar between methods, and willingness-to-pay estimates are consistent. In addition, there are significant differences in willingness-to-pay across environmental attitudinal groups, and we find that accounting for unobservable heterogeneity provides a significantly better fitting model.
The fill factor (FF) of organic photovoltaic (OPV) devices has proven difficult to optimize by synthetic modification of the active layer materials. In this contribution, a series of small-molecule ...donors (SMDs) incorporating chalcogen atoms of increasing atomic number (Z), namely oxygen, sulfur, and selenium, into the side chains are synthesized and the relationship between the chalcogen Z and the FF of OPV devices is characterized. Larger Z chalcogen atoms are found to consistently enhance FF in bulk-heterojunction OPVs containing PC61BM as the acceptor material. A significant ∼8% FF increase is obtained on moving from O to S to Se across three series of SMDs. The FF enhancement is found to result from the combination of more ordered morphology and decreased charge recombination in blend films for the high-Z-chalcogen SMDs. Because this FF enhancement is found within three series of SMDs, the overall strategy is promising for new SMD materials design.
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