Wall, Chest

PBIDS household surveillance methods have been described previously [10] (link). Briefly, all households in both surveillance sites are offered enrollment. Eligible households are those located within 5 km and 1 km from the designated referral clinics for the project in Asembo and Kibera, respectively. Eligible persons must have resided permanently in these areas for 4 calendar months or be a child born to a woman enrolled in PBIDS. Enrollment was continuous in both sites since the project's beginning. Community interviewers visit enrolled households every two weeks (“fortnightly ” visits.) Participants are asked standardized questions, in local language, about recent illnesses. For certain key symptoms—cough, fever and diarrhea—the exact days of occurrence are recorded. For older children (approximately over 12 years old) and adults, interviews of that person are done. If not at home or unable to answer questions, a proxy who is knowledgeable about the participant's health is interviewed. For children unable to answer for themselves, the mother or other primary caretaker of the child is interviewed. Abbreviated physical exams are carried out on ill persons present during the visit, including axillary temperature, 1 minute respiratory rate, evaluation for lower chest wall indrawing and stridor in ill children, and observation for signs of dehydration. Community interviewers are secondary school graduates, who undergo extensive training on data collection and physical examination led by KEMRI/CDC clinicians, including WHO Integrated Management of Childhood Illness (IMCI) training videos [14] .

We systematically reviewed all literature published from January 1, 1990 through March 31, 2012 to identify studies with data on risk factors for pediatric pneumonia. We searched a variety of databases-Medline (Ovid), Embase, CINAHL and Global Health Library using combinations of key search terms: pneumonia, low birth weight, undernutrition, breast feeding, crowding, smoking, indoor air pollution, immunization, HIV etc. (full search terms are available in Supplementary material). Hand searching of online journals was also performed by examining the reference lists for relevant articles. We did not apply any language or publication restrictions. Relevant full-text articles in foreign language were translated to English using Google translator.
We defined an episode of severe pneumonia in hospital setting as any child hospitalized overnight with an admission diagnosis of pneumonia or bronchiolitis. In community-based studies, the presence of lower chest wall indrawing in a child with cough and difficulty breathing with increased respiratory rate for age was used to define a case, using the same cut off values as in the WHO's case definition (4 ,5 ). We recognized that the eligible studies used varying case definitions for the putative risk factors. We therefore grouped the risk factor definitions into categories and analyzed the association between risk factor and outcome for each of these categories (Table 1). We classified the risk factors into three groups based on the consistency and strength of association with severe ALRI:
(i) those that consistently (ie, across all identified studies) demonstrated an association with severe ALRI, with a significant meta-estimate of the odds ratio, would be classified as “definite”;
(ii) those demonstrating an association in the majority (ie, in more than 50%) of studies, with a meta-estimate of the odds ratio that was not significant, would be classified as “likely;” and
(iii) those that were sporadically (ie, occasionally) reported as being associated with severe ALRI in some contexts were classified as “possible.” This classification is consistent with the one originally used by Rudan et al (2 (link)).
We included studies that reported severe pneumonia in children under five years of age (Table 2). Eligible study designs included randomized control trials (RCTs), observational studies (cohort, case-control, or cross-sectional) that assessed the relationship between severe pneumonia in children and any one of the putative risk factors. Studies were excluded if their sample size was less than 100 detected cases, if their case definitions did not meet our broad range of case definitions, or if the case definitions were not stated clearly and/or not consistently applied (Figure 1). Studies where health care workers went house to house to identify cases of pneumonia were considered as having active community-based case ascertainment. By contrast, studies where children with pneumonia presented to a health facility were considered as having passive hospital-based case ascertainment.
The included studies used either multivariate or univariate analyses to report the association between the putative risk factors and the outcome, ie severe pneumonia. Since the multivariate design takes into account the interaction with other risk factors and potential confounders, we decided to report the results of the meta-analysis of these data separately. We decided that if there was significant heterogeneity in the data, ie, I²>80%, (corresponding to P < 0.005) (6 (link)), then we would report the meta-estimates from the random effects model (7 (link)). Importantly, we hypothesized that the effects of the risk factors were likely to be different in developing countries and industrialized countries. Because of this, we decided to report the results separately for developing (Table 3) and industrialized countries (Table 4). We extracted all relevant information from each retained study (Supplementary Table S2(supplementary Table 2)) and assessed the quality of included studies using a modified GRADE scoring system (Supplementary Tables S1(supplementary Table 1)) (8 (link)). Briefly, we assessed each article against the GRADE criteria and calculated the overall score for each article. We then calculated the cumulative score for each risk factor after accounting for the included studies (Supplementary Table S3(supplementary Table 3)). We used Stata 11.2 (StataCorp, College Station, TX, USA) for the meta-analysis (Figure 2; Supplementary Figure S1(supplementary Figure 1)).

As previously reported1 (link), all shoulder ROM data were measured by a single certified orthopedic surgeon using a digital protractor (iGaging, CA, USA). We have previously established the intrarater validity and reliability of the goniometer and hand-held dynamometers1 (link)9 (link). The passive ROM of shoulder internal rotation at 90° of abduction and horizontal adduction were determined for the dominant and nondominant shoulders using an examination table, and a digital goniometer with a bubble level was used to measure shoulder ROM1 (link)2 (link)10 (link)11 (link). For the measurements, the pitchers were placed in a supine position with their humerus abducted to 90°. To measure 90° abducted shoulder internal rotation, the humerus was kept parallel to the floor using a small towel roll under the elbow. The examiner used his thenar eminence and thumb to apply a posterior force through the coracoid process to stabilize the scapula before the arm was rotated1 (link)2 (link)10 (link)12 (link), and the humerus was then passively rotated at the end of 90° abducted internal rotation with the force of gravity acting on the arm. To measure horizontal adduction, the pitcher was placed with their elbow flexed to 90° and the scapula was stabilized behind the chest wall. The humerus was then moved passively into horizontal adduction. Shoulder ROM measurements were obtained by the examiner while an assistant provided a stabilizing force to maintain the shoulder position13 (link). Elbow flexion and extension ROM were also passively measured while the participants lay in a supine position. ROM measurements were performed before muscle strength measurements because muscle tonus can vary with the effects of reciprocal inhibition due to muscle contraction.

The respiratory system undergoes various anatomical, physiological and immunological changes with age. Ageing is associated with a progressive decline in respiratory function that accompanies changes in the structure of the chest wall due to loss of supporting tissue, increased air trapping and decreased respiratory muscle strength [28 ]. Respiratory function was measured using the CareFusion Microlab Spirometer with the participant seated. Measurements included forced expiratory volume in one second (FEV1, l), forced vital capacity (FVC, l) and forced expiratory flow (FEF) 25–75%. Measures of lung function (FEV1 and FVC) are associated with all-cause and cardiovascular mortality [29 , 30 ]. Low FEV1 is also recognised as an independent predictor of non-cardiopulmonary comorbidities including diabetes, chronic kidney disease, osteoporosis and dementia [31 –34 ]. For the purposes of this manuscript the highest FEV1 and FVC reading was used. A maximum of five attempts were undertaken to obtain three satisfactory readings. Analyses are only based on participants who obtained at least three satisfactory readings.

All SBRT treatments were performed using a Helical Tomotherapy (HT) Hi-Art Treatment System (Accuray, Madison, WI, USA). The HT-SBRT technique and treatment planning were performed as previously described according to our institutional protocol [16 (link)]. The gross tumor volume (GTV) was delineated as a lesion observed at the lung window level on the enhanced CT and/or FDG-PET. The clinical target volume was equal to gross tumor volume. The internal target volume (ITV) was contoured based on the extension of GTVs at the all phases (5 inspiratory, 5 expiratory, and 1 resting phase) of the respiratory cycle on the four-dimensional CT (4D-CT) (Siemens Somatom Sensation, Siemens Healthineers Corporation, Germany) scanning to include the full movement of the tumor. To compensate for the uncertainty in tumor position and changes in tumor motion caused by breathing, the planning target volume (PTV) was extended by a margin of 0.5 cm from the ITV. Cone beam CT was implemented before each treatment to confirm the position of the target was achieved. The main factors determining the dose/fractionation scheme were tumor location, tumor size, and lung function parameters. In general, a total dose of 50 Gy/5 fractions (biologically effective dose [BED] = 100 Gy) was delivered for patients with peripherally located tumors and 60 Gy/10 fractions (BED = 96 Gy) was delivered for patients with centrally located tumors or tumors with extensive adherence to the chest wall. Dose constraints for the OARs were implemented according to the experience of the Radiation Therapy Oncology Group (RTOG) 0236 guidelines [2 (link)].