Different coronavirus disease (COVID-19) testing approaches have been implemented among Italian regions, reflected in heterogeneous testing rates. We analyzed the number of COVID-19-related deaths in relation to the number of tests performed among the most affected Italian regions. We showed that regions with the highest number of tests performed (Veneto and Toscana) had the lowest 30-day crude mortality rate per 100 000 inhabitants. In addition, an inverse association between crude mortality rates and tests performed  was observed. Early identification and isolation of active cases (including asymptomatic or mildly symptomatic subjects) could have had an important effect in lowering COVID-19 mortality. The crude COVID-19 case-fatality ratio (CFR) in Italy was one of the highest in the world (~14%).4 One of the reasons might be that initial Italian testing coverage has been lower than other European countries5; a low coverage of the population at risk implies a lower chance to find positive asymptomatic individuals, thus underestimating the total number of cases, yielding an increased CFR. However, given that governance of the Italian Health System is decentralized, different COVID-19 testing approaches have been adopted by Italian regions, as reflected in the extremely variable testing rates.6The first locally transmitted case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Italy was detected on February 21, 2020. The increasing number of cases forced the Italian Government to introduce specific measures to restrict social contact at the beginning of March.7Testing subjects with diagnostic tests could facilitate early identification of active cases (including asymptomatic or mildly symptomatic subjects) and could have an effect in lowering COVID-19 mortality by isolating cases that would otherwise continue to spread the virus in the susceptible and vulnerable population. Heterogeneity in testing approaches within the same country offers the opportunity to study whether different testing strategies had an effect in lowering the COVID-19 mortality, since heterogeneity in other potential confounders  is limited within the same country.Day 1) up to 30 days (considered as Day 30). We then computed crude mortality rates (CMRs) at Day 30 with a corresponding 95% confidence interval (exact Poisson method). Finally, we fitted a multilevel Poisson regression to the cumulative number of COVID-19-related deaths that occurred in the 30 days, using the population as offset and introducing a region-specific random effect. The model was applied to study the mortality rates in relation to the cumulative number of tests performed in each region over the 30-day observation period. Tests performed were expressed as both the number of tests per identified case and the number of tests per 1000 inhabitants. Regression analysis was adjusted for the proportion of inhabitants over 65 years of age. All data were obtained from the Italian Civil Protection website,6 and an analysis was performed with the R Foundation .Since the number of confirmed cases is affected by testing coverage, we focused on the number of COVID-19-related deaths, which are less likely to be affected by testing approaches, in the 7 most affected Italian regions as of May 6, 2020. First, the cumulative mortality rate curve per 100 000 inhabitants was plotted for each region, starting from the day with at least 5 cumulative COVID-19 deaths  or the COVID-19-related deaths reported. COVID-19 mortality rates, instead, were associated with different testing approaches adopted by the investigated Italian regions. In particular, our results suggest that higher testing rates were associated with lower CMRs. Early identification of active cases (including asymptomatic or mildly symptomatic subjects) might have had an effect in lowering COVID-19 mortality, by isolating cases that would otherwise continue to spread the virus in the susceptible population and possibly preventing overwhelming of local health care systems. Increasing testing coverage and active tracing of contacts may play a relevant role in limiting the public health impact of the COVID-19 outbreak, by significantly reducing deaths in the population.The present results must be interpreted with caution, given that the study is based on aggregated regional data. As most of ecological studies, systematic differences between regions in exposure (tests performed) and outcome (COVID-19-related deaths) measurements are possible. However, since this study was performed within the same country, strong heterogeneity in these measurements is unlikely. In addition, comparing data between regions from the same country should have limited the heterogeneity in other potential confounders .The present analysis on aggregate regional Italian data suggests that higher COVID-19 testing rates were associated with lower mortality during the first month of the outbreak. These results prompt urgent studies investigating the impact that preventive strategies, including the extent of testing coverage, may exert in terms of reducing COVID-19 mortality, both in high- and low-transmission settings.


The output of the nanowire laser is channelled into an on-chip SiN waveguide with high efficiency (up to 58%) by evanescent coupling, and the directional coupling ratio between the two output ports can be varied from 90 to 10% by predesigning the coupling length of the SiN waveguide. Our results open new opportunities for both nanowire photonic devices and on-chip light sources and may pave the way towards a new category of hybrid nanolasers for chip-integrated applications.By integrating a free-standing cadmium sulfide (CdS) nanowire onto a silicon nitride (SiN) photonic chip, we demonstrate a highly compact on-chip single-mode CdS nanowire laser. The mode selection is realized using a Mach-Zehnder interferometer (MZI) structure. When the pumping intensity exceeds the lasing threshold of 4.9 kW/cm While a number of on-chip nanophotonic devices and circuits have been successfully fabricated using a complementary metal-oxide semiconductor (CMOS)-compatible technique8, on-chip light sources remain challenging10. On the other hand, bottom-up grown semiconductor nanowires have long been used for nanoscale waveguide lasers11. Benefitting from their diverse material availability and large tolerance to lattice mismatch for bandgap engineering15, nanowire lasers can now cover a broad spectral range from the ultraviolet to near-infra-red ranges17, with a number of additional advantages including compact footprints, waveguide mode quality, and excellent stability20.In the past decade, owing to its great potential ranging from optical communications25. However, due to the large discrepancy in fabrication techniques, refractive index and geometric compatibility between a freestanding nanowire and an on-chip planar waveguide, a variety of issues, including a relatively low coupling efficiency, ineffective mode selection and low reproductivity, have yet to be addressed.In recent years, increasing attention has been paid to the integration of active nanowires with on-chip planar waveguides for on-chip light sources26, we demonstrate an on-chip cadmium sulfide (CdS) nanowire laser with high coupling efficiency and stability. Moreover, by forming a hybrid Mach-Zehnder interferometer (MZI) for mode selection, we operate the laser in the single-mode regime with a side-mode suppression ratio of up to a factor of 20 (13 dB). Different directional output ratios have also been achieved by predesigning the coupling length of the waveguide bends.Relying on a highly efficient and repeatable near-field coupling approach for on-chip integration of single nanowires26. The overall size of the hybrid MZI structure is kept below 100 μm. The free spectral range (FSR) of the MZI is designed to be ~1.5 nm to ensure single-mode operation. Fibre-to-chip grating couplers are designed at both ends of the SiN waveguide, which couple the laser signal from the on-chip SiN waveguide into standard optical fibres for optical characterization.The structural design of the on-chip nanowire laser is schematically illustrated in Fig. A micromanipulation process under an optical microscope  above the laser threshold and measure the lasing output from one end of the nanowire. Before coupling the nanowire to the SiN waveguide, the lasing oscillation in the nanowire relies solely on the F-P cavity formed by the reflection from both ends of the nanowire Fig. , resulti2. The dependence of the lasing output on the pumping intensity  is slightly higher than that of the nanowire before coupling (∼4.7 kW/cm2), which is due to the insertion loss of the MZI for mode selection. Meanwhile, by comparing the lasing output intensities from the nanowire end and the grating area (Supplementary Fig. 25 and can be further improved by optimizing the coupling efficiency between the nanowire and the SiN waveguide.To characterize the on-chip nanowire laser, we measure the lasing output from the SiN waveguide via fibre-to-chip grating couplers. As shown in Fig. ity Fig.  shows thBy changing the coupling efficiency between the nanowire and the SiN waveguide and forming an asymmetric MZI lasing structure, it is also possible to adjust the ratio of the laser powers between the two directions along the SiN waveguide. To show this adjustment, we fabricate an asymmetric MZI structure with different coupling lengths for the two SiN waveguide bends that determine the coupling efficiency. Figure 17 and high flexibility for bandgap engineering15, the on-chip integration scheme demonstrated here can be readily extended to realize on-chip nanolasers from the ultraviolet to near-infra-red ranges, which may offer new opportunities for both semiconductor nanowires and on-chip photonic devices. For example, recently, free-standing single CdS nanowires have been used for refractive index28 and intracellular optical sensing29, and the on-chip single-mode nanowire laser may thus offer an opportunity to develop on-chip physical and biochemical optical sensors with higher stability and compactness.In conclusion, based on a hybrid MZI structure integrating a CdS nanowire and a SiN waveguide, we have demonstrated a new approach for on-chip lasers. Compared with previously reported chip-integrated nanowire lasers, the laser demonstrated here achieves much higher efficiency and can be operated in the single-mode regime with a small footprint and high flexibility. Benefitting from the great diversity of the available nanowire materials30, which have excellent uniformities with available diameters ranging from 100 to 500 nm (Supplementary Fig. Experimentally, on-chip SiN waveguides are fabricated on a SiN wafer using electron beam lithography and subsequent dry etching. The as-fabricated SiN waveguides are typically 300 nm in width and 250 nm in height, with a measured waveguiding loss of less than 1 dB/cm. The CdS nanowires are synthesized using a chemical vapour deposition methodSupplementary Information for On-Chip Single-Mode CdS Nanowire Laser


To review the literature on neo-vallecula diagnosis and management and to report our findings regarding 3 patients who developed neo-vallecula in the context of free-flap pharyngeal reconstruction following total laryngectomy. 2 laser endoscopic procedure.  This case series reports three patients who developed a neo-vallecula following a laryngectomy and free-flap pharyngeal reconstruction. All three patients were treated with a CO2 laser to divide the neo-vallecula, and all our patients reported improvement in their dysphagia.  Neo-vallecula formation is thought to be related to tension on the neopharyngeal closure or closure technique following total laryngectomy. Diagnosis may be obtained with swallow studies, videofluoroscopy, or endoscopy. Treatment has included external excision and endoscopic procedures such as stapling, harmonic scalpel excision, and laser removal. We utilized an endoscopic approach entailing the use of a CO2 laser is an effective way to treat dysphagia in patients following total laryngectomy with free-flap pharyngeal reconstruction. Treatment of an anterior neo-vallecula endoscopically using a CO While s2 laser diverticulectomy of his neo-vallecula. The diverticulectomy was conservative due to concern for pharyngocutaneous fistula formation. During initial follow-up, the patient noted some clinical improvements and was able to swallow liquids but remained unable to pass a pill through his neopharyngeal inlet. A second CO2 laser diverticulectomy was performed to remove the residual obstructing tissue, resulting in significant improvement, and the patient was able to tolerate a soft diet consistently thereafter. The intraoperative technique is shown in A 63-year-old man presented to our clinic for evaluation of a large, obstructing supraglottic mass. Due to the risk of airway compromise, the patient underwent an awake tracheostomy and biopsy, which confirmed the diagnosis of locally advanced squamous cell carcinoma of the larynx. The patient then underwent a total laryngectomy and partial base of tongue resection, and reconstruction with an anterolateral thigh free flap to reconstruct the pharynx and anterior neck above the stoma. The patient completed chemoradiation about 5 months postoperatively, and during routine follow-up, was noted to have significant dysphagia clinically and on swallow study evaluation. The patient lected to undergo pharyngoscopy and CO2 laser diverticulectomy of the neo-vallecula. After surgery, a swallow study demonstrated absence of the shelf-like tissue protrusion seen on the preoperative study (A 54-year-old woman presented to our clinic for evaluation of a supraglottic mass consistent with squamous cell carcinoma of the larynx. After treatment failure with chemotherapy and radiation, the patient underwent a salvage total laryngectomy and tongue base resection with a left forearm free-flap pharyngeal reconstruction. Following surgery, the patient was noted to have a pharyngocutaneous fistula, which ultimately required a pectoralis major flap. The fistula resolved, but during follow-up, the patient had persistent oropharyngeal dysphagia. Nasopharyngoscopy revealed that a neo-vallecula had developed within the patient's prior free-flap site, obstructing the pharyngeal lumen. The patient elected to undergo pharyngoscopy and COve study . Clinica2 laser diverticulectomy of his neo-vallecula. Clinically, the patient's swallowing significantly improved, and he was able to tolerate a regular diet.A 47-year-old man presented for evaluation of a soft tissue lesion involving the left aryepiglottic fold, false and true vocal cords, with extension to the left pyriform sinus. The patient underwent laryngoscopy and biopsy confirming invasive moderately differentiated squamous cell carcinoma. Due to mass effect leading to obstruction of part of the airway, a laser was used to debulk some of the tumor, and then chemotherapy and radiation were initiated for definitive management. One year following treatment, direct laryngoscopy showed evidence of recurrence, and the patient underwent a total laryngectomy with primary closure and a right serratus overlay. Postoperatively, the patient had progressive dysphagia to solids. Laryngoscopy demonstrated a pharyngeal diverticulum at the tongue base, and the cervical esophagus was mildly stenotic. The patient underwent esophageal dilation using Maloney dilators and CODysphagia is a relatively common complication following total laryngectomy and chemoradiation, with causes including neo-vallecula, pharyngocutaneous fistula, stricture, and reflux . FollowiA neopharyngeal pseudodiverticulum or neo-vallecula is a common cause of dysphagia following total laryngectomy and free-flap reconstruction. Neo-valleculas are pouches located at the tongue base with a posterior band of tissue resembling a pseudoepiglottis, which obstructs the neopharyngeal lumen causing dysphagia . KirchneClinically, patients with a neo-vallecula often present with regurgitation while swallowing and while there is food or mucus accumulation in the throat, sensation of a foreign body in the throat, and dysphagia. Kirchner hypothesized that breakdown of the pharyngeal closure due to tension on wound edges during swallowing, combined with contraction of tongue musculature, can lead to neo-vallecula development . In thisOther studies have supported the claim that closure technique can impact neo-vallecula incidence. One group at VU University Medical Center of Amsterdam reported that in a retrospective cohort study of 117 laryngectomy patients, 84.6% of patients with a vertical closure developed a neo-vallecula versus 18.5% of patients with a T-shaped closure  Table 1Table 1. In addition to hypothesizing causes of neo-vallecula formation, studies have investigated methods to diagnose this clinical pathology. Neo-valleculas are challenging to detect clinically, and use of barium swallow and endoscopic evaluation have helped facilitate diagnosis . TransnaVarious options have historically been pursued to manage neo-vallecula, including external and internal surgical interventions. External approaches, by design, require a neck incision to directly expose and eliminate the pouch . Gacek dIn contrast, internal approaches are less invasive and offer multiple options to address the neo-vallecula. One endoscopic option carried out by Deschler et al. entailed transoral use of monopolar cautery to perform a central wedge resection of tissue causing the neo-vallecula . This meAnother endoscopic option is endoscopic stapling . D'Souza2 laser has been used as an internal approach to divide the excess tissue of a neo-vallecula [2 laser for dysphagia; of these patients, 11 had dysphagia from a neo-vallecula [2 laser, 8 of 11 patients reported “entirely comfortable” swallowing without any remaining dysphagia symptoms, but 2 of these 8 required another operation within 9 months of the first due to dysphagia reoccurrence [2 laser division of their neo-vallecula, reporting 8 of the 9 had “obvious improvement” in swallowing, with 7 patients additionally noting less food regurgitation and 5 noting less food accumulation [2 laser in 4 patients, all with clinical resolution of symptoms and 2 with preoperative and postoperative swallow studies objectively demonstrating improvement [2 laser include low bleeding and tissue trauma, low postoperative pain, and short hospitalization with quick recovery [In addition to the above, the COallecula . Lippertallecula . After trovement  (Table 12 laser in the management of neo-vallecula. The strength of this paper lies in consistent operative technique (2 laser division.Our paper adds to the literature on the use of COechnique  and our A limitation of this paper lies in the limited number of patients studied. However, the unique aspect of our cohort is that all patients had free-flap reconstruction following total laryngectomy, while much of the literature includes patients who underwent primary closure. Our patient selection process dictated that we limit the number of patients studied. Another limitation of this paper is that not all patients were able to obtain preoperative and postoperative swallow studies. However, we would argue that the clinical improvement in our patients' swallowing provides a more valuable marker of their improvement than swallow studies.2 laser division, with notable clinical improvement in their swallowing. CO2 laser division of neo-vallecula is a minimally invasive, relatively safe, and adequate method to improve dysphagia caused by neo-vallecula formation following total laryngectomy and free-flap reconstruction.We report a case series of three patients who presented with dysphagia secondary to a neo-vallecula that developed following total laryngectomy and free-flap reconstruction. These patients were successfully treated with CO


Studies have shown that immune checkpoint inhibitors (ICIs) have limited efficacy and can even increase tumour burden in short time periods. This is usually called hyperprogressive disease (HPD). To date, there are few reports regarding HPD; fewer have analysed the relationship between HPD and radiotherapy combined with ICIs, and their conclusions are controversial.A 42-year-old woman was diagnosed with stage IV renal clear cell carcinoma. The patient had previously received sorafenib and pazopanib as first- and second-line therapies, respectively. She received radiotherapy combined with nivolumab. Eighteen days after administration of the third dose of nivolumab, the patient’s general condition deteriorated; this was associated with immune-related adverse events. Computed tomography showed that the diameter of left lung metastases had sharply increased. A biopsy of the lung metastasis showed no infiltration of lymphocytes. The patient’s general condition worsened and she died of the disease on the 70th day after administration of the third dose of nivolumab.This report describes the development of HPD following the administration of radiotherapy combined with ICIs in a case of advanced renal cell carcinoma. The case indicates that radiotherapy may show bidirectional regulation effects on anti-tumour immune response. If the immunosuppressive function of radiotherapy is dominant, combined with ICIs, it could result in HPD.The online version contains supplementary material available at 10.1186/s12894-021-00813-8. Immune checkpoint inhibitors (ICIs), especially antibodies against programmed death 1/programmed death-ligand 1 (PD-1/PD-L1) and cytotoxic T lymphocyte antigen-4 (CTLA-4), represent one of the most significant breakthroughs in the treatment of advanced malignancies; they have been approved to treat several solid tumours. However, despite the usefulness of these drugs, a significant number of patients do not respond to them. Therefore, improving the effectiveness of immunotherapy is a major goal of clinical research. Researchers have found that radiotherapy can promote the presentation of tumour antigens and induce immune-mediated anti-tumour responses, indicating that the combination of radiotherapy and ICIs may enhance the anti-tumour immune response . A seconRecently, the number of active clinical trials testing ICIs combined with radiotherapy has seen a dramatic increase , and somUntil now, very few studies have analysed the relationship between HPD and radiotherapy combined with ICIs. Here, we present the case of a patient with advanced renal cell carcinoma who developed HPD following the administration of radiotherapy combined with nivolumab, and we review the literature on HPD associated with this treatment modality. This article hopes to provide new perspectives for researchers to explore the mechanisms underlying HPD.A 42-year-old woman was admitted to our hospital in March 2019 with a diagnosis of stage IV renal clear cell carcinoma (with multiple lung metastases). Her Eastern Cooperative Oncology Group (ECOG) and Royal Marsden Hospital (RMH) prognostic scores were 2 and 1 , respectively. The patient had previously received sorafenib and pazopanib as first- and second-line therapies, respectively, but these could not stop the progress of the disease. She had no history of autoimmune diseases, and her whole exome sequencing showed that the tumour mutation burden (TMB) was 127 mu/mb and no MDM2/4 amplification. The patient then received radiotherapy combined with nivolumab . The first dose of nivolumab was administered on 27 March 2019. After six days, she underwent radiotherapy. To induce systemic immune response and improve local tumour control, a suitable radiotherapy strategy was designed, including stereotactic body radiation therapy (SBRT) (24 Gy in 3 fractions) followed by the conventional 59.5 Gy in 17 fractions to the right kidney lesion , which function to suppress tumour-specific immunity, have been confirmed as radioresistant lymphocyte subpopulations in many studies –26. KamaThe choice of radiotherapy dose is the other key aspect of the combination therapy, and SBRT may be the best option . CompareWhile two cases are not enough to conclude that SBRT was associated with HPD, studies have also suggested that SBRT can suppress the immune system. For example, research has found that SBRT can increase the relative number of Tregs . HoweverThe patient had received sorafenib and pazopanib as first- and second-line treatments, respectively. However, Zhao et al. found that sorafenib may cause the loss of T-cell immune response by inducing apoptosis and targeting LCK . SunitinThe TMB of our patient was very high. Although the prognostic role of TMB in cancer patients receiving ICIs is controversial, some studies have found that high TMB predicts better efficacy of ICIs , 41. HowIn conclusion, this report describes the development of HPD in a case of advanced renal cell cancer following the administration of radiotherapy combined with an ICI. We argue that radiotherapy may show bidirectional regulation effects on anti-tumour immune response, and if the immunosuppressive function of these treatments is dominant, combination with ICIs could result in treatment failure or even HPD. In contrast, the positive correlative factors of the effect of ICI, including TMB and PD-L1 expression and immune-related adverse events, may be irrelevant to HPD. Further research is needed to elucidate the mechanisms of these associations.Additional file 1: Fig. S1. Haematoxylin and eosin staining of the lung metastasis biopsy sample showed no infiltration of lymphocytes.


Phase synchronization measures are widely used for investigating inter-regional functional connectivity (FC) of brain oscillations, but which phase synchronization measure should be chosen for a given experiment remains unclear. Using neuromagnetic brain signals recorded from healthy participants during somatosensory stimuli, we compared the performance of four phase synchronization measures, imaginary part of phase-locking value, imaginary part of coherency (ImCoh), phase lag index and weighted phase lag index (wPLI), for detecting stimulus-induced FCs between the contralateral primary and ipsilateral secondary somatosensory cortices. The analyses revealed that ImCoh exhibited the best performance for detecting stimulus-induced FCs, followed by the wPLI. We found that amplitude weighting, which is related to computing both ImCoh and wPLI, effectively attenuated the influence of noise contamination. A simulation study modeling noise-contaminated periodograms replicated these findings. The present results suggest that the amplitude-dependent measures, ImCoh followed by wPLI, may have the advantage in detecting stimulus-induced FCs. Functional integration of multiple regions in the central nervous system is an important concept for understanding normal brain function  and the a priori assumption about the network model. In contrast, FC is simply defined as the statistical dependence of neural signals across spatially remote brain regions , effective connectivity, or both . For com regions , which c regions , FC analFunctional connectivity has been measured using several approaches, including phase synchronization measures , amplituSeveral phase synchronization measures are less susceptible to common source effects . The common source effect is an inevitable and serious problem in electrophysiological studies , and canThe phase synchronization measures that are robust to the common source effects include imaginary part of phase-locking value (ImPLV) , imaginaIn the present study, we aimed to compare the four phase synchronization measures, which are less sensitive to near zero-lag interactions (thereby making the four FC measures robust against the common source effects), for identifying functional connectivity in real event-related MEG data. We used neuromagnetic brain signals recorded during exposure to somatosensory stimuli because somatosensory-induced FCs between the primary and secondary somatosensory areas  have been well documented , 2014. WThirty-five right-handed healthy volunteers  with a mean age of 23.8 years (from 19 to 30 years) were recruited. All participants were native Japanese speakers and had no history of neuropsychiatric disorders or head trauma. Written informed consent was obtained from all participants. The protocol was approved by the committee of medical ethics at Kyoto University.In the MEG experiment, 0.1-ms electrical pulses were delivered to the digital nerve on each side via ring electrodes. The intensity was adjusted individually so that it was twice the sensory threshold. The inter-stimulus interval varied randomly between 1500 ms and 3500 ms to attenuate the effects of stimulus anticipation of the participants. Three hundred pulses were delivered on each stimulated side. As a result, there were 300 trials on each side of stimulation (hereinafter referred to as the dataset) for each participant. Participants were seated and relaxed with their eyes open during MEG recording. They were asked not to pay attention to the stimuli.We recorded continuous signals using a whole-head 306 channel MEG system  comprised of 102 magnetometers and 204 planar gradiometers. The data were recorded at a sampling rate of 600 Hz with a 0.1 to 200 Hz bandpass filter for removing direct current drifts and signal aliasing. Participants’ head positions relative to the MEG sensor array were measured using four head-position-indicator coils immediately before data recording in each session.®  scripts.We performed the following data analysis with custom-made MATLABThe session data were first processed using the signal-space projection method. We then checked inter-session head position movement by computing the Euclidean distance of the head positions in two sessions in each dataset for each participant. Because the inter-session head position distances were less than 7 mm (around one-fifth of the averaged distance between sensors in the MEG system) in all but four of the 63 datasets  and the mean of these distances was 3.3 mm, we did not perform head movement correction . We usedWe extracted peri-event signals (0.7 s before to 0.7 s after each stimulus onset) from each trial of these processed data. Trials containing large artifacts  were excluded from further analysis. In this procedure, both datasets of three participants and one dataset of one participant were excluded because a substantial number of trials were rejected due to artifact contamination . In the rest of the datasets (63 datasets), the percentages of rejected trials ranged from 0.0% to 14.0% with a mean of 3.1%. After the quality assurance, we concatenated the remaining trials .We identified channels over the contralateral SI to the stimulus (c-SI) using somatosensory-evoked fields (SEFs). After the application of a 1-Hz high-pass filter, we computed SEFs by averaging signals of the OTDs. The three channels that clearly showed the early SEF components  on visual inspection  were selWhen stimuli evoke stimulus-locked responses  in remote regions, these may result in “apparent” phase locking between those regions even if there is no actual interaction  between each of the c-SI channels and the other 203 channels in each dataset. We transformed the time series of each trial of the OTD into a time-frequency domain using short-time Fourier transform with 333.3 ms (200 time points) Hanning windows with 92.5% overlap. The analyzed frequency range was up to 45 Hz. The FC values were then rescaled in each of the FC measures by dividing them by the root mean squares of the FC values extracted from all the “pixels”  of all the channels. These rescaled FC values were averaged across the FC measures in each pixel and channel.Using this rescaled and averaged FC values, we selected the channel pair (one for the c-SI channels and the other for the i-SII channels) between which the greatest FC values were identified during the poststimulus period (0–0.5 s) in each dataset. In each of the datasets where somatosensory-induced FCs were poorly identified visually (19 out of 63 datasets), we selected the channel pair, which showed the largest SEFs in the c-SI and the i-SII channels.a priori knowledge about null distributions of these test statistics , we used a surrogate data method to obtain these null distributions  FCs . In addiibutions .We generated surrogate data of each dataset in the following procedure . From thFor assessing the significance of somatosensory-induced FCs, we used the following two-step thresholding method. We first conducted value-based thresholding in each pixel of the time-frequency space (pixel-based test). We then conducted cluster-size-based thresholding by grouping neighboring pixels with suprathreshold values as clusters (cluster-based test)  for solvWe obtained the thresholds for the pixel-based test in each dataset as follows ((1)N trials of data randomly sampled from the RTD  and collecting the maximum value in each frequency row 1000 times to compute null distributions of surrogate FC values in each frequency row and each of the FC measures.Computing each FC measure between the pre-selected channel pair using (2)Computing the 95th percentiles of these null distributions as threshold values of each frequency row and each of the FC measures for the pixel-based test.We obtained the thresholds for the cluster-based test in each dataset as follows ((3)N trials of data randomly sampled from the RTD  and thresholding these surrogate FC values by applying the corresponding threshold values computed in the step (2) in each frequency row and each FC measure.Computing each of the FC measures between the pre-selected channel pair using (4)Grouping 4-connected neighboring pixels (constituted with time bins and frequency bins) with suprathreshold values as clusters and collecting the maximum cluster size (number of pixels in each cluster) in each FC measure.(5)Iterating steps (3) + (4) 500 times to obtain null distributions of the maximum cluster size in each of the FC measures and computing the 95th percentiles of these null distributions as threshold cluster sizes of each FC measure for the cluster-based test.We then applied the two-step thresholding method to each OTD as follows ((6)N trials  randomly sampled from the OTD.Computing each FC measure between the pre-selected channel pair using (7)Conducting the pixel-based test to these FC values in the same way to the step (3) and grouping 4-connected neighboring pixels with suprathreshold values as clusters.(8)Leaving clusters with cluster sizes larger than the threshold cluster size as statistically significant FCs in each FC measure .(9)Iterating steps (6) + (7) + (8) 250 times.We thus obtained sets of 250 dFCs for each number of trials and each FC measure in each dataset. This procedure controlled for a family-wise error rate of each dFC at 0.05 after the multiple comparison correction in the time-frequency space.We averaged 250 dFCs to obtain the individual-level averages of dFCs in each dataset. We then computed the grand-averages of dFCs by averaging these individual-averages of dFCs across all the datasets for each number of trials and each of the FC measures.Using the RTDs as the surrogate data, by construction, we should be able to detect stimulus-induced FCs only during the poststimulus period but not during the prestimulus period (at a 0.05 family-wise error rate). Thus, to assess correct and false detection rates of these FC measures, we computed true positive rates (TPRs) and true negative rates (TNRs) using the dFCs in the following way. First, time bins in each 50-ms period immediately before and after the stimulus onset were excluded from this analysis because time windows of these bins were considerably affected by both prestimulus and poststimulus brain signals. We then computed the maximum cluster size in each of the prestimulus and poststimulus periods for each dFC (zero if no cluster survived). We computed the TPRs as proportions of dFCs in which the maximum cluster sizes in the poststimulus period were greater than those in the prestimulus period in each set of 250 dFCs. We computed the TNRs as proportions of dFCs in which the maximum cluster size in the prestimulus period was greater than zero among each set of 250 dFCs. We thus obtained the TPRs and TNRs for each number of trials and each FC measure in each dataset.post hoc analysis was conducted using the one-tailed Wilcoxon signed-rank test to the directional alternative hypothesis, which states that the rates of one FC measure were greater than those of another measure . For the multiple comparison procedure, the Benjamini–Hochberg method  using the Friedman test. A g method  was usedAmplitudes of time-frequency transformed signals can affect FC values, particularly when computing coherence and related measures . As shown in Appendix, amplitudes work as a weighting factor of cross-periodograms for computing these measures . To investigate the effects of signal amplitudes on performance differences among the FC measures, we conducted the following analyses.To investigate event-related amplitude changes, we computed event-related amplitude coherence (AC) in each dataset according to the formula in Appendix . For staTo investigate the relationship of the amplitudes of signals with the synchronized phases, we analyzed cross-periodograms  from pixels of the time-frequency represented OTD. Computing the rescaled and averaged FCs as in section “MATERIALS AND METHODS Selection of Channel Pairs,” we extracted cross-periodograms from the pixel with the greatest value in each dataset, and computed the magnitudes  and angles  of these cross-periodograms.We computed phase lags (angles of phase locking) of stimulus-induced FCs in each dataset as the mean angle of angles of complex-valued phase-locking values and coherencies computed using the cross-periodograms. The phases of the cross-periodograms were converted to the angles relative to the estimated phase lag in each dataset (relative phases ranging from 0 to pi). We then summarized the relationship between the amplitudes of the cross-periodograms and the relative phases derived from all datasets by dividing the amplitudes into 9 bins from 0 to pi according to the relative phases.We also estimated signal-to-noise ratios (SNRs) of the stimulus-induced FCs using these cross-periodograms because the phase lags and SNRs were likely the major determining factors for the performance of the FC measures. The SNR was computed in each dataset as the ratio of the squared magnitude of mean of the cross-periodograms and the squared magnitudes of the residuals (after subtracting the mean from the cross-periodograms). Note that this computation was based on the assumption that phase-locked cross-periodograms were constant across trials. When phase-locked cross-periodograms were not constant , these variations were included in the residuals, which probably resulted in an underestimation of the SNRs.To investigate the underlying mechanism for the performance difference between the two amplitude-dependent measures (ImCoh and wPLI) , we computed a range of population parameters as means and coefficients of variance (CVs) of these two FC measures in each pixel in each dataset. We first defined a mask image for stimulus-induced FCs in the time-frequency space by thresholding the grand-averaged dFCs. We also defined the pixels, ranging from 20 to 40 Hz in the frequency bands and 0.5 to 0.3 s before the stimulus onset in the time bins, as a mask image for prestimulus FCs. Using a bootstrap method , we obtained sets of FC values from these two mask images in the two FC measures. To correct for the difference in scales of the FC values between the FC measures, we divided these sets of FC values by the averaged prestimulus FC value in each FC measure, producing normalized FC values. We then computed means and CVs of these sets of normalized FC values, and compared these values between the FC measures. A detail of this analysis is described in To substantiate the preceding results based on the actual MEG data from a numerical point of view, we applied the same analyses to simulated noise-contaminated periodograms. We simply generated a single pair or a set of 10 pairs (multiple pairs) of phase-locked complex numbers  and added random complex numbers (noises) to them. For this data simulation, we set three parameters: SNRs, phase lags and numbers of trials. We used a surrogate data method for statistical analysis in this data simulation. As surrogate simulation data, we generated a single pair or multiple pairs of phase-UNLOCKED complex numbers with noise. Using the thresholded results, we computed true positive rates (TPRs) as the proportions of the simulations where one or more simulated FCs survived. We then compared TPRs among the FC measures. We also conducted the descriptive statistics analysis for ImCoh and wPLI using these simulated data . Using the FC values in the single-pair simulation, we computed means and CVs of these FC values normalized by the FC values computed from the surrogate simulation data. A detail of the data simulation is described in In all 63 datasets, SEFs were visually identified in the channels over the c-SI and i-SII. After selecting a channel pair in each dataset (see section “MATERIALS AND METHODS Section Selection of Channel Pairs”), we conducted the following analyses.Conspicuous stimulus-induced FCs were found during a period of 50–250 ms after the stimulus and in the frequencies ranging from 3 Hz to 12 Hz in all FC measures . Both Imp < 0.001 for both 100 trials and 200 trials). In the post hoc analysis (p < 0.05). The TPRs of ImCoh were significantly greater than those of wPLI for 100 trials, while not for 200 trials.The TPR analysis revealed differences in the TPRs among the FC measures . A Friedanalysis , the TPRp = 0.934) or 200 (p = 0.863) trials. Thus, the post hoc analysis was not conducted for the TNRs.Contrary to the TPRs, the TNRs were around 0.975 for all the FC measures and for both the numbers of trials . The FriThe grand-average of dACs was less evident  in compap < 0.001, Kruskal–Wallis test). These findings indicate that cross-periodograms with angles close to the actual phase lag have large amplitudes and thus should be heavily weighted in the amplitude weighting for computing wPLI and ImCoh.Focusing on the amplitudes of cross-periodograms, the amplitudes became greater as these phases became closer to the estimated phase lag as exemplified in The phase lags of the stimulus-induced FCs, which were rescaled from 0 to pi/2 as the minimum angle from the horizontal in the polar coordinates, ranged from 0.300 to 0.997 times of pi/2 among all datasets (25th–75th percentiles: 0.544–0.846 times of pi/2), and were more than pi/4 in 50 out of these 63 datasets. The SNRs ranged from 0.012 to 0.207 (25th–75th percentiles: 0.026–0.069).p < 0.001, F-test). These findings indicate that ImCoh take higher mean and CVs than wPLI in pixels where the stimulus-induced FCs are stronger.The descriptive statistics analysis revealed that statistical properties  of normalized FCs were somewhat different between ImCoh and wPLI in stimulus-induced FCs, while quite similar in prestimulus FCs . It appeThe simulation study supported the results from the actual MEG data, revealing that ImCoh and wPLI showed higher TPRs than ImPLV and PLI in almost all pairs of parameters. The results were roughly consistent across the single-pair  and the The properties of descriptive statistics (means and CVs) showed similar results to those of the actual MEG data , particuIn the present study, we compared the performance of the four FC measures  for detecting somatosensory stimulus-induced FCs. ImCoh and wPLI exhibited superior performance in detecting the stimulus-induced FCs compared with ImPLV and PLI while the four methods, similarly, rejected prestimulus FCs to be taken as stimulus-induced FCs. The comparison between ImCoh and wPLI revealed that ImCoh showed slightly superior performance in detecting the stimulus-induced FCs.In the present study, we focused on somatosensory stimulus-induced FCs between the c-SI and i-SII . PreviouThe somatosensory-induced FCs in the present study showed smaller FCs in a relatively high frequency range  in reference to previous studies , 2014. SWhen we applied the two-step statistical procedure to the “baseline” data , no cluster was expected to survive in 95% of cases if the procedure correctly controlled for a family-wise error rate of 0.05. The results of the TNR analysis revealed that TNRs were around 0.975 irrespective of the FC measures and the number of trials, yielding the family-wise error rates of the two-step procedure around 0.025. Although we controlled the family-wise error rates of false detection of any clusters only during the peristimulus periods (prestimulus and poststimulus) under 0.05, we considered clusters only during the prestimulus period for the TNR analysis, which explains why the family-wise error rates were approximately half of 0.05 in the current result. For this reason, we confirmed that our procedure is a valid method to control the family-wise error rate at 0.05 for statistical analysis of time-frequency represented data.ImCoh and wPLI showed significantly higher TPR than ImPLV and PLI, while there was no significant difference in TNRs among the four FC measures. These results suggest that ImCoh and wPLI had advantages in detecting somatosensory-induced functional connectivities over ImPLV and PLI, at least in the experimental condition employed here. Both ImCoh and wPLI are computed from coherences, while ImPLV and PLI are computed from phase information. As noted in several previous studies , coherenWe first investigated the possibility that event-related changes in amplitude of oscillations caused the difference in the performance. However, the AC analysis revealed that event-related amplitude changes were not significant and had little effect on the difference of dFCs among the four FC measures in the present data. This finding indicates that event-related amplitude changes were less likely to explain the difference between ImCoh/wPLI and ImPLV/PLI.We next examined cross-periodograms because phase synchronization is computed using this information . This crBetween the two amplitude-dependent FC measures, ImCoh exhibited slightly better performance than wPLI in the TPR analysis . This diOur data simulation also revealed that ImCoh showed better performance in considering periodograms of multiple-pair data than those of single-pair data. Because considering multiple-pair data is expected to reduce the influence of CVs in comparison with single-pair data, it can be inferred that the difference of TRPs was more related to the difference of means in our descriptive statistics analysis. Therefore, the higher contrast of means in ImCoh was likely to be more crucial for the statistical significance of stimulus-induced FCs in the time-frequency space.Only a few previous studies directly compared FC detection performance among FC measures that are not affected by the common source effects . These sSecond, PLI and wPLI are thought to be robust to noise contamination when noise is small enough not to change the signs of imaginary parts of cross-periodograms. In simulated data and human EEG data of absence seizures in a previous report , PLI andThe current results focusing on the stimulus-induced FC are not directly applicable to resting-state electrophysiological data. However, our findings suggest that the amplitude weighting, which can attenuate the effect of noise on computing FCs, may be critical for the difference of performance between the amplitude-dependent and independent measures. Because the amplitude weighting is presumed to be effective in computing resting-state FCs, our results may be applicable, to some extent, to resting-state FC analysis.An important issue of cluster-based analysis should be considered when interpreting the current results. In the cluster-based method, we considered clusters composed of time and frequency bins in the time-frequency space. However, to use the sizes of these clusters as a fair measure of extent, the assumption must be satisfied that frequency bins are equivalent to temporal bins in terms of smoothness . However, this may not be the case because, in time-frequency transform methods such as short-time Fourier transform, the smoothness of frequency bins usually differs from that of temporal bins . Using dIn the present study, focusing on the FC measures that are robust to the common source effects, we investigated the performance of these measures in detecting somatosensory-induced FCs. Overall, ImCoh was the most sensitive method for detecting stimulus-induced FCs, at least in the present experimental condition. The difference in the performance was partially explained by the notion that the amplitude weighting was effective for attenuating negative effects of noise contamination in computing FCs and by different properties of descriptive statistics among these measures. The present work offers a useful insight into functional connectivity studies with electrophysiological data.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by the committee of medical ethics at Kyoto University. The patients/participants provided their written informed consent to participate in this study.KY, MM, HF, RT, and TH did the proposal of the work and experimental design. KY acquired the data. KY and MM performed the data analysis including scripting. KY, MM, TM, TH, and AI wrote and revised the manuscript. All of the authors have read and approved the manuscript.Department of Epilepsy, Movement Disorders and Physiology (AI and MM) is the Industry-Academia Collaboration Courses, supported by Eisai Co., Ltd., Nihon Kohden Corporation, Otsuka Pharmaceuticals Co., and UCB Japan Co., Ltd.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The effects of SARS-CoV-2 in pregnancy are not fully delineated. We will describe the incidence of COVID-19 in pregnancy at population level in Scotland, in a prospective cohort study using linked data. We will determine associations between COVID-19 and adverse pregnancy, neonatal and maternal outcomes and the proportion of confirmed cases of SARS-CoV-2 infection in neonates associated with maternal COVID-19.Prospective cohort study using national linked data sets. We will include all women in Scotland, UK, who were pregnant on or became pregnant after, 1 March 2020 (the date of the first confirmed case of SARS-CoV-2 infection in Scotland) and all births in Scotland from 1 March 2020 onwards. Individual-level data will be extracted from data sets containing details of all livebirths, stillbirth, terminations of pregnancy and miscarriages and ectopic pregnancies treated in hospital or attending general practice. Records will be linked within the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) platform, which includes primary care records, virology and serology results and details of COVID-19 Community Hubs and Assessment Centre contacts and deaths. We will perform analyses using definitions for confirmed, probable and possible COVID-19 and report serology results (where available). Outcomes will include congenital anomaly, miscarriage, stillbirth, termination of pregnancy, preterm birth, neonatal infection, severe maternal disease and maternal deaths. We will perform descriptive analyses and appropriate modelling, adjusting for demographic and pregnancy characteristics and the presence of comorbidities. The cohort will provide a platform for future studies of the effectiveness and safety of therapeutic interventions and immunisations for COVID-19 and their effects on childhood and developmental outcomes.COVID-19 in Pregnancy in Scotland is a substudy of EAVE II(, which has approval from the National Research Ethics Service Committee. Findings will be reported to Scottish Government, Public Health Scotland and published in peer-reviewed journals. We will interrogate Scottish national data at the population level to provide information on the incidence of, and outcomes following, COVID-19 outcomes in pregnant women.We are expanding an existing national pandemic reporting platform  to include assessment of all pregnancy outcomes. EAVE II uses deidentified individual patient-level data for almost the entire population of Scotland from general practices, hospitals, death registry, virology (reverse transcriptase PCR) and serology tests to investigate the epidemiology of COVID-19.This is an observational study and residual confounding is a potential concern.The effects of novel SARS-CoV-2 in pregnancy are yet to be fully delineated.2–4To inform public health policy, it is crucial to determine the effects of SARS-CoV-2 infection on maternal, pregnancy and neonatal health. SARS-CoV-2 transmission from mother to baby  appears to be possible,1Understanding the effects of COVD-19 at different stages in pregnancy and perinatally will help inform policy on shielding strategies and advice to pregnant women and those considering pregnancy. It is also essential to inform immunisation strategies when vaccines are available. For example, immunisation in early pregnancy may help protect against maternal infection during pregnancy and reduce complications; but immunisation in later pregnancy may be preferential to provide passive immunisation to babies if neonatal infection is the predominant concern.There are a number of surveillance studies gathering data on pregnant women with COVID-19 currently underway in the UK, summarised in Collectively, these surveillance studies can provide detailed characterisation of selected groups of pregnant women (and neonates) affected by COVID-19. The study outlined in this protocol will complement these existing studies by providing population-based information (for the whole of Scotland) on the risks of, and outcomes following, COVID-19 at any stage of pregnancy for women in the community and/or admitted to hospital.The primary objectives of the COVID-19 in Pregnancy in Scotland study are to:Describe the incidence of SARS-CoV-2 infection and COVID-19, in the pregnant population.Determine associations between COVID-19 and adverse maternal, pregnancy and neonatal outcomes.Determine the proportion of neonates with confirmed SARS-CoV-2 infections that are associated with COVID-19 in the baby’s motherSecondary objectives are to:Assess the proportion of COVID-19 cases in pregnant women and neonates who are included in relevant other enhanced surveillance studies , Clinical Characterisation Protocol Tier 0 study (CO-CIN))Provide a platform to assess the safety and effectiveness of any new or existing prophylactic or therapeutic interventions  in pregnant women and their babies.Enable evaluation of the longer term sequelae of maternal SARS-CoV-2 and therapeutic interventions to mitigate SARS-CoV-2 in pregnancy and in children.This COVID-19 in Pregnancy in Scotland (COPS) study is a substudy of the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II).Parents and pregnant women have not been involved in design of this protocol. However, we will work in partnership with a patient and public involvement group set up for the EAVE II study regarding interpretation of results, presentation and dissemination of findings. We also have close links with Tommy’s charity who will codevelop dissemination plans and help ensure that findings reach relevant stakeholders.This is a prospective cohort study using national maternity, community, hospital and laboratory-linked data sets, in Scotland, UK. We will include all women in Scotland who were pregnant on or became pregnant after 1 March 2020 (the date of the first confirmed case of SARS-CoV-2 infection in Scotland)Women in the cohort with the earliest dates of conception will only have been at risk of COVID-19 at the very end of their pregnancy. Women with more recent dates of conception will have been at risk for longer, up to women with date of conception from 1 March 2020 onwards, who will be at risk from conception onwards .We aim to use a dynamic cohort of the entire pregnant population; therefore, selection bias is not anticipated and the data set will be fully generalisable to Scotland .Individual-level data will be extracted from the datasets listed below. Records relating to the same individual will be linked deterministically using the Community Health Index (CHI) number.An overall scheme for the planned linkage is provided in Antenatal booking records: this is a new national data return developed as part of the response to the COVID-19 pandemic providing information on all women booking for antenatal care with NHS maternity services throughout Scotland. It will be used for identification of women with ongoing pregnancies in near real time. All other records identify end of pregnancy events, thus, there is a time-lag before records are generated. More than 99% of births in Scotland book for antenatal care with NHS maternity services.23Abortion Act Scotland (AAS) records: these are statutory notifications of termination of pregnancy and will be used to identify all terminations of pregnancy, including terminations of pregnancy indicated by congenital anomaly.24National Records of Scotland (NRS) statutory stillbirth registrations: Scottish legislation requires all stillbirths at 24 weeks gestation or more to be registered with NRS.25NRS statutory live birth registrations: Scottish legislation requires all live births at any gestation to be registered with NRS.26NHS Scottish health board live births: A new national data return developed as part of the response to the COVID-19 pandemic  providing information on all live births notified by maternity services to NHS Board child health administrative departments.GP data: data from all patients registered in GPs are included in the EAVE II platform.Scottish Morbidity Record (SMR) 01: the SMR01 database includes all general day case and in-patient admissions in Scotland.SMR 02: the SMR02 database includes all day case and in-patient admissions to maternity specialities in Scotland.23Scottish Birth Record (SBR): the SBR records basic demographic data on all births in Scotland and additional clinical information and diagnostic and operational procedure codes on babies admitted to neonatal care.Scottish Intensive Care Society Audit Group records: this is a national database of patients admitted to adult general critical care units in Scotland detailing information on the management of critically ill or injured patients. All general intensive care units and combined ICU/high dependency units (HDUs) collect data and more than 90% of general HDUs and a number of specialist ICU and HDUs also provide records.Electronic Communication of Surveillance in Scotland (ECOSS)ECOSS is a database that holds surveillance data on various microorganisms  and infections reported from NHS diagnostic and reference laboratories.30In substudies, residual sera from routine antenatal booking blood tests and 28-week gestation blood group and red cell antibody screen samples will be tested for SARS-CoV-2 antibodies. Residual sera from other blood tests conducted as part of routine (not COVID-19 related) primary and secondary care, and blood donation, are also being tested for SARS-CoV-2 antibodies as part of the surveillance of the pandemic in Scotland, and any results relating to pregnant women will also be incorporated.18GP consultations, GP out of hours attendances, NHS24 calls, COVID-19 phone assessment hub calls and COVID-19 clinical assessment centre attendances are linked on the EAVE II platform.32Unscheduled Care Datamart: This links data from NHS 24, Scottish Ambulance Service, Out of Hours Primary Care, Emergency Department, Acute and Mental Health admissions and Deaths to show a Continuous Unscheduled Care Pathway. Data are included in the EAVE II platform.33NRS statutory death registrations will be used for identification of any women with COVID-19 recorded as cause of death.34SMR01, SMR02 and NRS stillbirths will be used to identify women with COVID-19 recorded as cause of admission/stillbirth.25 27Prescribing information system includes information on all prescribed medications that are dispensed in the community in Scotland.Scottish Hospital Electronic Prescribing and Medicines Administration systems are currently available within four Scottish hospitals, and data from these are linked in the EAVE II platform36GP consultation records included on the EAVE II platformWe will identify pregnant women and neonates with COVID-19 in existing enhanced surveillance studies using minimal ‘flag’ variables from the BPSU and CO-CIN studiesA pregnancy will be defined by presence of a record pertaining to a pregnancy. As well as identifying completed pregnancies, through a record of any pregnancy outcome, we will be able to identify ongoing pregnancies at population level, through inclusion of records from women booked for antenatal care.The following definitions will be used for pregnancy outcomes. The codes and data sources used to identify relevant records are described in detail in 10.1136/bmjopen-2020-042813.supp1Supplementary dataEctopic pregnancy: this will include any early pregnancy loss where the pregnancy is implanted outwith the uterusSpontaneous pregnancy losses: these will be defined as miscarriage at less than 20 weeks gestation, late fetal losses at 20–23 weeks if there are no signs of life; and stillbirth if birth occurs at 24 weeks’ gestation or more and there are no signs of life. If numbers allow, the miscarriages will be further split into the more clinically meaningful outcome categories of miscarriage at less than 14 weeks gestation and 14 weeks gestation and beyond.Termination of pregnancy: these will be subclassified by the grounds for termination of pregnancy of the Abortion Act 1967.37Live birth: the birth of a baby at any gestation with signs of life. No lower gestational limit will be used although in practice around 22 weeks gestation would be considered the lower limit at which live-born babies may survivePregnancy start date will be taken as the date of conception. In pregnancies that have ended date of conception will be imputed from‘date of conception=pregnancy end date —(the number of weeks of gestation at pregnancy end+2 weeks)’.In ongoing pregnancies that have booked with maternity services and have a documented estimated date of delivery (EDD), date of conception will be imputed from‘date of conception=date of antenatal booking—(gestation at booking+2 week)’.In ongoing pregnancies without a documented EDD, date of conception will be imputed from‘date of conception=date of last menstrual period+2 weeks’.It is standard care for women who book with maternity services in Scotland have a first trimester ultrasound scan  to determine EDD, from which gestation is calculated. Booking takes place around 10 weeks gestation.We will use the following definitions for COVID-19.Confirmed COVID-19 in pregnancy will be defined as positive viral PCR for SARS-CoV-2 on a test.Probable COVID-19 will be defined as COVID-19 recorded on a hospital admission, stillbirth or a maternal death record  10 codes U07.1, U07.2, B34.2, B97.2).Possible COVID-19 will be defined as meeting one or more of the following criteria:GP consultation or GP out of hours attendance coded as possible COVID-19.NHS24 call coded as possible COVID-19.Patient triaged to NHS24 COVID-19 phone assessment hub or clinical assessment centre.Scottish Ambulance Service call for possible COVID-19.A&E attendance coded as possible COVID-19.Negative SARS-CoV-2 viral PCR test when the test was taken for clinical indications .The above definitions are hierarchical, for example, a positive SARS-CoV-2 nucleic acid test assigns a woman to the confirmed COVID-19 group, regardless of the presence of other records.We will use the indication for SARS-CoV-2 nucleic acid test, which is recorded in ECOSS records, to distinguish between tests taken for clinical indications and routine testing of asymptomatic individuals. If we can not distinguish between these groups, we will exclude women testing negative from both the ‘case’ and ‘control’ groups—and base our definition of possible case on presentation to various healthcare settings with relevant symptoms as described above.SARS-CoV-2 infections during pregnancy will be identified if the event of interest  occurs between 14 days prior to the estimated date of conception  and the end of pregnancy.We will seek to access serological data as these become available. We will report the proportion of women with circulating IgG and/or IgM for SARS-CoV-2 and may incorporate serology results in case definitions and/or use in additional analyses as data mature. The timing of exposure to/infection with SARS-CoV-2 is more difficult to ascertain from serology results than from the other indicators of (possible) infection listed above. Dates of serological testing; start and end of pregnancy and plausible start  of transmission of SARS-CoV-2 in Scotland will be taken into account when identifying women with exposure before, during and after pregnancy. Seroconversion windows will also be considered for women with sequential serology results.We have included hierarchical definitions of COVID-19 to mitigate against potential biases that may result from (1) limitations of diagnostic strategy performance and (2) variation in availability of diagnostic tests. The definition of confirmed COVID-19 (women who test positive on PCR) may potentially bias results away from the null hypothesis . The definition of possible COVID-19 may potentially bias results towards the null hypothesis . We will test our hypotheses in this observational cohort across the range of assumptions allowed by hierarchical definitions. Other diagnostic and exposure categories may be added as the pandemic develops and diagnostic criteria change.The following fetal and neonatal outcomes will be included.Congenital anomaly Preterm birth (<37 weeks) categorised as spontaneous or medically indicated .Small for gestational age .Neonatal mortality (death of a live born baby at <28 days of age).Extended perinatal mortality .We will collect data on the following maternal outcomes:COVID-19 disease requiring any hospital admission (defined as a patient admitted within 14 days of confirmed or probable COVID-19 or with confirmed or probable COVID-19 during admission).Severe COVID-19 disease requiring critical care admission or resulting in death .Any maternal death .A number of maternal and pregnancy characteristics will be collected that could be potential confounders or effect modifiers.Demographics including age band and socioeconomic status determined by the Scottish Index of Multiple Deprivation (SIMD) classification of material deprivation.Clinical at-risk groups of individuals with certain underlying medical conditions thought to increase risk of COVID-related complications. The following clinical at-risk conditions are identified in the EAVE II platformSmoking status in pregnancy will be presented into the following four categories: Current smoker, non-smoker, ex-smoker and not recorded. Smoking status will be taken from booking record and/or GP records.Obstetric characteristics (SMR02) will include previous pregnancies, plurality (number of babies), drug and alcohol use, antenatal steroid administration, mode of birth or management of pregnancy loss.Clustering of outcomes by the 14 different Maternal NHS Board areas of residence.Baseline characteristics of all study participants will be described in relation to presence and absence of confirmed, probable or possible COVID-19 and outcomes of interest. Mean, median and proportions, together with a measure of dispersion, will be provided where appropriate to describe differences between the various groups of interest based on the nature of each variable. Missing data will be provided for each variable. Two-tailed hypothesis tests will be used for all study’s outcomes, with 95% CIs presented to show precision of estimates, and p values will be reported. All analyses will be carried out using the R statistical programming language. We do not propose to make any formal statistical adjustment for the multiple comparisons as the principal aim of the study is to estimate the effect of COVID-19 infection on pregnancy outcomes. The estimated effects and 95% CIs will be reported for the range of outcomes. However, a caveat will be clearly expressed regarding the dangers of overinterpreting these data, given the multiple outcomes used, particularly if it transpires that conflicting results are obtained from the differing outcome measures. The approach to imputing estimated date of conception when gestation is missing on records indicating pregnancy status is detailed in Analyses will be updated monthly, providing results for sequential months, and also information on the cumulative risk of COVID-19 as women progress through their pregnancies. Simple smoothing techniques such as rolling averages will be used to facilitate presentation and interpretation of findings. We will also present our results as proportions of COVID-19 infection, together with CIs based on the Wilson method. We will describe the temporal changes in the proportion using cumulative risk models. Covariates such as the trimester of pregnancy, age of the mother and deprivation will also be included with a view to estimating the potential effects of these variables on the risk of COVID-19 infectionIf/when numbers of cases allow, we will examine incidence of COVID-19, and report outcomes, in subgroups including by maternal age band, SIMD deprivation quintile, maternal NHS Board area of residence and maternal comorbidity status. We may assess whether findings are robust to more stringent or emerging definitions of confirmed and suspected infection, in sensitivity analyses. Other sensitivity and subgroup analyses may be indicated by initial findings. We will clearly state which analyses were prespecified and which were post hoc.We will perform descriptive analysis of the number of cases over the total number of pregnancies, that is, how many pregnant women have had confirmed, probable or possible COVID-19/total number of pregnant women. Where timing of infection is known, we will describe incidence of SARS-CoV-2 infection by trimester of exposure—first trimester (0–13 weeks gestation), second trimester (14–27 weeks gestation), third trimester (≥28 weeks gestation)Initially we will perform a descriptive analysis comparing pregnancy outcomes in women with and without (i) confirmed, (2) probable and (3) possible COVID-19. In order to create appropriate comparison groups, for each woman with COVID-19, we will identify 10 women without COVID-19, with an ongoing pregnancy matched on gestation of diagnosis, and additionally matched on maternal age and maternal deprivation level. We will explore the need to match additional parameters such as NHS Board.Occurrence of the outcomes of interest will be compared in women with and without COVID-19 using simple descriptive statistics  and visualised appropriately.If/when sufficient cases of COVID-19 among pregnant women accrue, and the univariable comparisons described above suggest that outcomes differ between women with and without SARS-2-CoV or COVID-19, formal modelling will be undertaken to quantify the impact of infection on outcomes, adjusting appropriately for confounding. We will use direct acyclical graphs to identify which factors to adjust for to mitigate for confounding. Appropriate methods that accommodate the competing risk and time to event nature of pregnancy outcomes  will be used.We will use summary statistics to describe neonatal SARS-CoV-2  by presentation of COVID-19 in the mother in different time periods .We will use summary statistics to describe the number and proportion of cases included in the external surveillance studies, and any factors associated with inclusion, for example, hospital admission status and NHS Board area of residence.We will use summary statistics to describe the treatments and prophylactic interventions used in pregnancy. We plan future linkage of data within COPS with child health and education data to allow assessment of long-term outcomes.There are approximately 50 000 live births in Scotland per year, 13 000 terminations of pregnancy, 5000 miscarriages managed in hospital and 200 stillbirths. The estimated number of women in the population who are pregnant at any one time is approximately 42 000.We cannot influence the number of women with confirmed, probable or possible COVID-19 available for analysis, hence sample size calculations will not be performed. We will report the precision with which we are able to estimate any association between COVID-19 and the outcomes of interest using CIs as appropriate. An approximate estimate of the expected number of confirmed COVID-19 cases in pregnant women from March to May 2020 is presented in COPS is a substudy of EAVE II, using unconsented data, which is covered by National Research Ethics Service Committee, South East Scotland 02 approval reference REC 12/SS/0201: SA 2 and Public Benefit and Privacy Panel approval reference 2021-0116. PHS and the Chief Medical Officer for Scotland are both (independent) data controllers for the national AAS database of termination of pregnancy notifications, thus the Chief Medical Officer has been informed of the intended use of AAS records for this study.The results of monthly analyses summarising the incidence of COVID-19 in pregnant women, and outcomes seen in women with COVID-19 and pregnant controls, will be reported through the PHS COVID-19-enhanced surveillance cell to the Scottish Government’s Chief Medical Officer’s COVID-19 Advisory Group. Any results of formal modelling of outcomes that is undertaken will be reported through the same route. Results reported through this route may be provided as management information  as appropriate.Results will also be submitted for peer-reviewed academic publication and presented at international conferences. All results put into the public domain will be subjected to statistical disclosure control according to usual PHS processes. Meta-data produced in this study will also become available to Health Data Research UK Gateway. Strengthening the Reporting of Observational Studies in Epidemiology guidance