Electrocoagulation

All procedures were performed with intravenous inhalation combined with anesthesia + double lumen endotracheal intubation. The operation used 3 cm small uni-portal method (Figure 1a): the patient’s lateral side of the midline of the 5th intercostal line 3 cm incision into the thoracoscope (the left side can also choose the 6th intercostal space), elbow cavity mirror suction device, electrocoagulation hook, If necessary, insert a double joint clamp to hold the lobes. At the end of the operation, two 12G microtubules were placed for chest drainage. After the end of one side of the operation, turn over the same side of the same the law. The specific surgical plan is based on the size and location of the bilateral lung GGO, the lung function reserve and the intraoperative frozen examination results. All patients underwent preoperative three-dimensional CT reconstruction and CT-guided methylene blue staining location except central lensions (Fig. 1b and Fig. 1c). In order to avoid the spread of methylene blue, we take the following methods: 1. Surgery as soon as possible after staining is complete; 2. The place marked by methylene blue is next to the lesion, and it will not affect the pathological diagnosis of the lesion. Surgical strategy: ①Pure GGO preferentially choose wedge resection or segmentectomy. ② Peripheral lesions are preferentially treated with wedge resection, and if they are central lesions, lobectomy is performed. ③The lesion is larger than 2 cm and the imaging is considered as an invasive lesion, which will be considered lobectomy. ④Rapid pathology during resection of the lesion is considered as lobectomy for invasive adenocarcinoma.⑤The priority side of the operation is based on the preoperative three-dimensional reconstruction to select the side of the lung tissue that is expected to be resected, such as the wedge resection or segmentectomy. If all are sublobar resection, the right side surgery is preferred.
Fig. 1

a The surgical incision (3 cm small uni-portal) during the operation. b Using methylene blue staining to locate the pulmonary nodules. c Three-dimensional reconstruction images of pulmonary nodules

Preprocessing was carried out with Natus NeuroWorks (Natus Medical Inc.) and in-built MATLAB code (MathWorks Inc., Natick, MA). Ear electrodes (M1 and M2) were excluded from the final analysis due to poor surface-to-skin contact for the majority of infants.
EEG signals were re-montaged to a nearest neighbor Laplacian reference using distances along the scalp surface to weight neighboring electrode contributions. We applied an anti-aliasing filter of 80 Hz and down-sampled the EEG data to 256 Hz.
EEG dynamics were analyzed at three distinct periods of (1) MOSSA, (2) awake (pre-anesthesia), and (3) emergence from general anesthesia. (1) MOSSA analysis: in the first part of this study, we were interested in characterizing EEG features during MOSSA. For each infant, a 10-min EEG segment during a period of maintenance of general anesthesia adequate for surgery and where end-tidal sevoflurane concentration was maintained at a constant concentration (+0.1%) was identified. Within this time segment, a 5-min epoch was selected from ‘artifact-free’ EEG, where motion or electrocautery artifacts were not present in the EEG. Channels with noise or artifacts were excluded from the analysis by visual inspection. EEG data analyzed during MOSSA involved epochs with median time after propofol or nitrous oxide administration of 77 min (IQR 32–93 min). (2) Awake state to MOSSA analysis: in the second part of this study, we were interested in characterizing the relationship with EEG features during the awake state, and comparing them to MOSSA. For each infant, the EEG and video recording starting before any anesthetics were administered was identified. Each video was reviewed and the sleep state of the infant identified using behavioral and vocal markers. The awake state was defined as having one of three features (1) eyes open, (2) body movement, and/or (3) crying. For each corresponding EEG segment, we extracted an 11-s ‘artifact-free’ epoch by visual inspection. If there was no ‘artifact-free’ data available then we did not include that epoch in the analysis. (3) Emergence from general anesthesia analysis: in the third part of this study, we were interested in characterizing relationship with EEG features, end-tidal sevoflurane concentration and onset of body movement. For each infant, an EEG segment starting from 10 min before sevoflurane gas was turned off, and finishing when end-tidal sevoflurane concentration was 0% was identified. For each EEG segment, we extracted a 30-s ‘artifact-free’ epoch by visual inspection at 10 end-tidal sevoflurane concentration ranges: (1) 0 to <0.3%; (2) 0.3 to <0.6%; (3) 0.6 to <0.9%; (4) 0.9 to <1.2%; (5) 1.2 to <1.5%; (6) 1.5 to <1.8%; (7) 1.8 to <2.1%; (8) 2.1 to <2.4%; (9) 2.4 to <2.7%; and (10) 2.7 to <3.0%. A 15- or 20-s epoch was used in three occasions. If there was no ‘artifact-free’ data available in a specific concentration range then we did not include that epoch in the analysis.

Hypoxemia was defined as SpO₂ less than 95% during general anesthesia regardless of the duration. The limit of 95% was selected in line with the definition of hypoxemia of perioperative respiratory adverse events [5 (link)]. All 13,130 vitalDB records were manually checked for the detection of hypoxic episodes by an anesthesiologist. The data retrieved from the VitalDB database were rechecked manually by the second anesthesiologist for quality control. The observed events were marked and annotated in all the databases. The true hypoxemia was verified by SpO₂ value, electronic medical records, vital signs, including heart rate, blood pressure, arterial blood pressure waveform, and pulse oximetry, plethysmographic waveform, and ventilator parameters, including EtCO₂ curve, PIP, and TV. Genuine hypoxemic events were discriminated using the following exclusion criteria: 1) when the measured pulse oximetry pulse rate differed by more than 20% from the electrocardiogram heart rate, the associated SpO₂, [2 (link)] 2) when anesthesiologists in charge recorded inaccurate measurement of oxygen saturation, and 3) when plethysmogram waveforms were severely distorted owing to position change or external pressure so that the signal quality reported in the monitor was severely low [2 (link)]. Artifacts that were mostly caused by motion, positioning, electrocautery, sensor dislodgement, and low peripheral perfusion were not annotated as hypoxemia and were retained in the dataset without further processing. Periods of hypoxemic episodes, divided into induction, maintenance, and emergence, were annotated in each database to determine the incidence of intraoperative hypoxemia in each period. We also investigated the total time of hypoxemia, duration from the minimum saturation to recovery until the saturation recovered to the initial value where saturation began to gradually decrease, and the cause of the hypoxemia episode suggested by the anesthesiologists based on various indicators. Patients were assigned to one of the four groups to confirm the incidence of the hypoxemic episodes stratified by age: 0–28 days (neonate), 29 days to 12 months (infant), 1–7 years, and 8–18 years [2 (link)]. Demographic data including age, sex, height, and weight were analyzed in each group.
Several parameters, such as SpO₂, EtCO2, FiO₂, TV, and PIP included in 1-minute length of segments from the determined hypoxemia episodes to the corresponding 1 minute ahead, were extracted. If a hypoxemic event defined as SpO₂ dropping below 95%, in the upcoming 1 min was observed, the target was assigned as 1; it was assigned 0 otherwise. Note that target 1 was assigned for the segment where the input SpO₂ was less than 95% while being included in the hypoxemia episode. Moreover, the patient’ demographic information (age, sex, height, and weight) was extracted corresponding to the segment and the target.